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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1102.0113 | Michael B\"orsch | Stefan Ernst, Brandy Verhalen, Nawid Zarrabi, Stephan Wilkens, Michael
Boersch | Drug transport mechanism of P-glycoprotein monitored by single molecule
fluorescence resonance energy transfer | 10 pages, 7 figures | null | 10.1117/12.872989 | null | q-bio.BM physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work we monitor the catalytic mechanism of P-glycoprotein (Pgp) using
single-molecule fluorescence resonance energy transfer (FRET). Pgp, a member of
the ATP binding cassette family of transport proteins, is found in the plasma
membrane of animal cells where it is involved in the ATP hydrolysis driven
export of hydrophobic molecules. When expressed in the plasma membrane of
cancer cells, the transport activity of Pgp can lead to the failure of
chemotherapy by excluding the mostly hydrophobic drugs from the interior of the
cell. Despite ongoing effort, the catalytic mechanism by which Pgp couples
MgATP binding and hydrolysis to translocation of drug molecules across the
lipid bilayer is poorly understood. Using site directed mutagenesis, we have
introduced cysteine residues for fluorescence labeling into different regions
of the nucleotide binding domains (NBDs) of Pgp. Double-labeled single Pgp
molecules showed fluctuating FRET efficiencies during drug stimulated ATP
hydrolysis suggesting that the NBDs undergo significant movements during
catalysis. Duty cycle-optimized alternating laser excitation (DCO-ALEX) is
applied to minimize FRET artifacts and to select the appropriate molecules. The
data show that Pgp is a highly dynamic enzyme that appears to fluctuate between
at least two major conformations during steady state turnover.
| [
{
"created": "Tue, 1 Feb 2011 10:08:57 GMT",
"version": "v1"
}
] | 2015-05-27 | [
[
"Ernst",
"Stefan",
""
],
[
"Verhalen",
"Brandy",
""
],
[
"Zarrabi",
"Nawid",
""
],
[
"Wilkens",
"Stephan",
""
],
[
"Boersch",
"Michael",
""
]
] | In this work we monitor the catalytic mechanism of P-glycoprotein (Pgp) using single-molecule fluorescence resonance energy transfer (FRET). Pgp, a member of the ATP binding cassette family of transport proteins, is found in the plasma membrane of animal cells where it is involved in the ATP hydrolysis driven export of hydrophobic molecules. When expressed in the plasma membrane of cancer cells, the transport activity of Pgp can lead to the failure of chemotherapy by excluding the mostly hydrophobic drugs from the interior of the cell. Despite ongoing effort, the catalytic mechanism by which Pgp couples MgATP binding and hydrolysis to translocation of drug molecules across the lipid bilayer is poorly understood. Using site directed mutagenesis, we have introduced cysteine residues for fluorescence labeling into different regions of the nucleotide binding domains (NBDs) of Pgp. Double-labeled single Pgp molecules showed fluctuating FRET efficiencies during drug stimulated ATP hydrolysis suggesting that the NBDs undergo significant movements during catalysis. Duty cycle-optimized alternating laser excitation (DCO-ALEX) is applied to minimize FRET artifacts and to select the appropriate molecules. The data show that Pgp is a highly dynamic enzyme that appears to fluctuate between at least two major conformations during steady state turnover. |
1108.5746 | Miroslaw Rewekant PhD MD | Slawomir Piekarski and Miroslaw Rewekant | On drug transport after intravenous administration | 5 pages | null | null | null | q-bio.TO q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A mathematical model of a drug transport after rapid injection is given. It
takes into account three processes: - drug plasma protein binding in central
compartment - transport processes between the central compartment and the
peripheral compartment - elimination of a drug from the central compartment. .
| [
{
"created": "Mon, 29 Aug 2011 20:33:45 GMT",
"version": "v1"
}
] | 2012-08-21 | [
[
"Piekarski",
"Slawomir",
""
],
[
"Rewekant",
"Miroslaw",
""
]
] | A mathematical model of a drug transport after rapid injection is given. It takes into account three processes: - drug plasma protein binding in central compartment - transport processes between the central compartment and the peripheral compartment - elimination of a drug from the central compartment. . |
1108.4167 | Jean-Louis Dessalles | Jean-Louis Dessalles (INFRES, LTCI) | Storing events to retell them (Commentary on Suddendorf and Corballis:
'The evolution of foresight') | jld-07051403 | Behavioral and Brain Sciences 30, 3 (2007) 321-322 | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Episodic memory is certainly a unique endowment, but its primary purpose is
something other than to provide raw material for creative synthesis of future
scenarios. Remembered episodes are exactly those which are worth telling. The
function of episodic memory, in our view, is to accumulate stories that are
relevant to recount in conversation.
| [
{
"created": "Sun, 21 Aug 2011 06:54:49 GMT",
"version": "v1"
}
] | 2011-08-23 | [
[
"Dessalles",
"Jean-Louis",
"",
"INFRES, LTCI"
]
] | Episodic memory is certainly a unique endowment, but its primary purpose is something other than to provide raw material for creative synthesis of future scenarios. Remembered episodes are exactly those which are worth telling. The function of episodic memory, in our view, is to accumulate stories that are relevant to recount in conversation. |
1710.04973 | Robert Endres | Li-Wei Yap and Robert G. Endres | A model of cell-wall dynamics during sporulation in Bacillus subtilis | 7 pages, 6 figures | null | null | null | q-bio.SC q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | To survive starvation, Bacillus subtilis forms durable spores. After
asymmetric cell division, the septum grows around the forespore in a process
called engulfment, but the mechanism of force generation is unknown. Here, we
derived a novel biophysical model for the dynamics of cell-wall remodeling
during engulfment based on a balancing of dissipative, active, and mechanical
forces. By plotting phase diagrams, we predict that sporulation is promoted by
a line tension from the attachment of the septum to the outer cell wall, as
well as by an imbalance in turgor pressures in the mother-cell and forespore
compartments. We also predict that significant mother-cell growth hinders
engulfment. Hence, relatively simple physical principles may guide this complex
biological process.
| [
{
"created": "Fri, 13 Oct 2017 15:44:53 GMT",
"version": "v1"
}
] | 2017-10-16 | [
[
"Yap",
"Li-Wei",
""
],
[
"Endres",
"Robert G.",
""
]
] | To survive starvation, Bacillus subtilis forms durable spores. After asymmetric cell division, the septum grows around the forespore in a process called engulfment, but the mechanism of force generation is unknown. Here, we derived a novel biophysical model for the dynamics of cell-wall remodeling during engulfment based on a balancing of dissipative, active, and mechanical forces. By plotting phase diagrams, we predict that sporulation is promoted by a line tension from the attachment of the septum to the outer cell wall, as well as by an imbalance in turgor pressures in the mother-cell and forespore compartments. We also predict that significant mother-cell growth hinders engulfment. Hence, relatively simple physical principles may guide this complex biological process. |
1704.03941 | Henry Tuckwell | Henry C. Tuckwell, Ying Zhou, Nicholas J. Penington | Analysis of pacemaker activity in a two-component model of some
brainstem neurons | arXiv admin note: substantial text overlap with arXiv:1508.05468 | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Serotonergic, noradrenergic and dopaminergic brainstem (including midbrain)
neurons, often exhibit spontaneous and fairly regular spiking with frequencies
of order a few Hz, though dopaminergic and noradrenergic neurons only exhibit
such pacemaker-type activity in vitro or in vivo under special conditions.
A large number of ion channel types contribute to such spiking so that
detailed modeling of spike generation leads to the requirement of solving very
large systems of differential equations. It is useful to have simplified
mathematical models of spiking in such neurons so that, for example, features
of inputs and output spike trains can be incorporated including stochastic
effects for possible use in network models.
In this article we investigate a simple two-component conductance-based model
of the Hodgkin-Huxley type. Solutions are computed numerically and with
suitably chosen parameters mimic features of pacemaker-type spiking in the
above types of neurons. The effects of varying parameters is investigated in
detail, it being found that there is extreme sensitivity to eight of them.
Transitions from non-spiking to spiking are examined for two of these, the
half-activation potential for an activation variable and the added
(depolarizing) current and contrasted with the behavior of the classical
Hodgkin-Huxley system. The plateaux levels between spikes can be adjusted, by
changing a set of voltage parameters, to agree with experimental observations.
Experiment has shown that in, in vivo, dopaminergic and noradrenergic neurons'
pacemaker activity can be induced by the removal of excitatory inputs or the
introduction of inhibitory ones. These properties are confirmed by mimicking
opposite such changes in the model, which resulted in a change from pacemaker
activity to bursting-type phenomena.
| [
{
"created": "Wed, 12 Apr 2017 21:59:55 GMT",
"version": "v1"
},
{
"created": "Sat, 15 Apr 2017 13:38:15 GMT",
"version": "v2"
}
] | 2017-04-18 | [
[
"Tuckwell",
"Henry C.",
""
],
[
"Zhou",
"Ying",
""
],
[
"Penington",
"Nicholas J.",
""
]
] | Serotonergic, noradrenergic and dopaminergic brainstem (including midbrain) neurons, often exhibit spontaneous and fairly regular spiking with frequencies of order a few Hz, though dopaminergic and noradrenergic neurons only exhibit such pacemaker-type activity in vitro or in vivo under special conditions. A large number of ion channel types contribute to such spiking so that detailed modeling of spike generation leads to the requirement of solving very large systems of differential equations. It is useful to have simplified mathematical models of spiking in such neurons so that, for example, features of inputs and output spike trains can be incorporated including stochastic effects for possible use in network models. In this article we investigate a simple two-component conductance-based model of the Hodgkin-Huxley type. Solutions are computed numerically and with suitably chosen parameters mimic features of pacemaker-type spiking in the above types of neurons. The effects of varying parameters is investigated in detail, it being found that there is extreme sensitivity to eight of them. Transitions from non-spiking to spiking are examined for two of these, the half-activation potential for an activation variable and the added (depolarizing) current and contrasted with the behavior of the classical Hodgkin-Huxley system. The plateaux levels between spikes can be adjusted, by changing a set of voltage parameters, to agree with experimental observations. Experiment has shown that in, in vivo, dopaminergic and noradrenergic neurons' pacemaker activity can be induced by the removal of excitatory inputs or the introduction of inhibitory ones. These properties are confirmed by mimicking opposite such changes in the model, which resulted in a change from pacemaker activity to bursting-type phenomena. |
1609.05676 | Michael Margaliot | Yoram Zarai and Michael Margaliot and Tamir Tuller | A Deterministic Mathematical Model for Bidirectional Excluded Flow with
Langmuir Kinetics | null | null | 10.1371/journal.pone.0182178 | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In many important cellular processes, including mRNA translation, gene
transcription, phosphotransfer, and intracellular transport, biological
"particles" move along some kind of "tracks". The motion of these particles can
be modeled as a one-dimensional movement along an ordered sequence of sites.
The biological particles (e.g., ribosomes, RNAPs, phosphate groups, motor
proteins) have volume and cannot surpass one another. In some cases, there is a
preferred direction of movement along the track, but in general the movement
may be two-directional, and furthermore the particles may attach or detach from
various regions along the tracks (e.g. ribosomes may drop off the mRNA molecule
before reaching a stop codon). We derive a new deterministic mathematical model
for such transport phenomena that may be interpreted as the dynamic mean-field
approximation of an important model from mechanical statistics called the
asymmetric simple exclusion process (ASEP) with Langmuir kinetics. Using tools
from the theory of monotone dynamical systems and contraction theory we show
that the model admits a unique globally asymptotically stable equilibrium. This
means that the occupancy in all the sites along the lattice converges to a
steady-state value that depends on the parameters but not on the initial
conditions. We also show that the model entrains (or phase locks) to periodic
excitations in any of its forward, backward, attachment, or detachment rates.
We demonstrate an application of this phenomenological transport model for
analyzing the effect of ribosome drop off in mRNA translation. One may perhaps
expect that drop off from a jammed site may increase the total flow by reducing
congestion. Our results show that this is not true. Drop off has a substantial
effect on the flow, yet always leads to a reduction in the steady-state protein
production rate.
| [
{
"created": "Mon, 19 Sep 2016 11:55:29 GMT",
"version": "v1"
}
] | 2017-11-01 | [
[
"Zarai",
"Yoram",
""
],
[
"Margaliot",
"Michael",
""
],
[
"Tuller",
"Tamir",
""
]
] | In many important cellular processes, including mRNA translation, gene transcription, phosphotransfer, and intracellular transport, biological "particles" move along some kind of "tracks". The motion of these particles can be modeled as a one-dimensional movement along an ordered sequence of sites. The biological particles (e.g., ribosomes, RNAPs, phosphate groups, motor proteins) have volume and cannot surpass one another. In some cases, there is a preferred direction of movement along the track, but in general the movement may be two-directional, and furthermore the particles may attach or detach from various regions along the tracks (e.g. ribosomes may drop off the mRNA molecule before reaching a stop codon). We derive a new deterministic mathematical model for such transport phenomena that may be interpreted as the dynamic mean-field approximation of an important model from mechanical statistics called the asymmetric simple exclusion process (ASEP) with Langmuir kinetics. Using tools from the theory of monotone dynamical systems and contraction theory we show that the model admits a unique globally asymptotically stable equilibrium. This means that the occupancy in all the sites along the lattice converges to a steady-state value that depends on the parameters but not on the initial conditions. We also show that the model entrains (or phase locks) to periodic excitations in any of its forward, backward, attachment, or detachment rates. We demonstrate an application of this phenomenological transport model for analyzing the effect of ribosome drop off in mRNA translation. One may perhaps expect that drop off from a jammed site may increase the total flow by reducing congestion. Our results show that this is not true. Drop off has a substantial effect on the flow, yet always leads to a reduction in the steady-state protein production rate. |
2308.16799 | Vincent Blay | Vincent Blay, Felix Grases | Research directions for kidney stone disease | null | null | null | null | q-bio.TO | http://creativecommons.org/licenses/by/4.0/ | Kidney stone disease poses a major burden to patients and healthcare systems
around the world. The formation of kidney stones may occur over months or
years, but many patients are diagnosed at a late stage, suffer excruciating
pain, and require surgical intervention to physically remove the stones. The
prevalence of kidney stones has increased during recent decades to over 10% in
many developed countries, suggesting a link with environmental and behavioral
factors. Recurrence rates are also high. In terms of their impact and scale,
kidney stones are an ongoing pandemic. The causes and mechanisms of kidney
stone formation are diverse and often unknown, resulting in varied compositions
and different anatomical locations being affected. A better understanding of
these processes could enable earlier diagnoses through more sensitive and
scalable biomarkers, as well as more effective preventives and therapeutics.
| [
{
"created": "Thu, 31 Aug 2023 15:21:42 GMT",
"version": "v1"
}
] | 2023-09-01 | [
[
"Blay",
"Vincent",
""
],
[
"Grases",
"Felix",
""
]
] | Kidney stone disease poses a major burden to patients and healthcare systems around the world. The formation of kidney stones may occur over months or years, but many patients are diagnosed at a late stage, suffer excruciating pain, and require surgical intervention to physically remove the stones. The prevalence of kidney stones has increased during recent decades to over 10% in many developed countries, suggesting a link with environmental and behavioral factors. Recurrence rates are also high. In terms of their impact and scale, kidney stones are an ongoing pandemic. The causes and mechanisms of kidney stone formation are diverse and often unknown, resulting in varied compositions and different anatomical locations being affected. A better understanding of these processes could enable earlier diagnoses through more sensitive and scalable biomarkers, as well as more effective preventives and therapeutics. |
1409.8270 | Sayan Mukherjee Dr. | Sayan Mukherjee, Sanjay Kumar Palit, D. K. Bhattacharya | Approximate discrete dynamics of EMG signal | null | Applied Mathematics and Computation 243 (15 September 2014)
879-888 | 10.1016/j.amc.2014.06.059 | null | q-bio.NC nlin.CD | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Approximation of a continuous dynamics by discrete dynamics in the form of
Poincare map is one of the fascinating mathematical tool, which can describe
the approximate behaviour of the dynamics of the dynamical system in lesser
dimension than the embedding diemnsion. The present article considers a very
rare biomedical signal like Electromyography (EMG) signal. It determines
suitable time delay and reconstruct the attractor of embedding diemnsion three.
By measuring its Lyapunov exponent, the attractor so reconstructed is found to
be chaotic. Naturally the Poincare map obtained by corresponding Poincare
section is to be chaotic too. This may be verified by calculation of Lyapunov
exponent of the map. The main objective of this article is to show that
Poincare map exists in this case as a 2D map for a suitable Poincare section
only. In fact, the article considers two Poincare sections of the attractor for
construction of the Poincare map. It is seen that one such map is chaotic but
the other one is not so, both are verified by calculation of Lyapunov exponent
of the map.
| [
{
"created": "Tue, 23 Sep 2014 20:06:16 GMT",
"version": "v1"
}
] | 2014-09-30 | [
[
"Mukherjee",
"Sayan",
""
],
[
"Palit",
"Sanjay Kumar",
""
],
[
"Bhattacharya",
"D. K.",
""
]
] | Approximation of a continuous dynamics by discrete dynamics in the form of Poincare map is one of the fascinating mathematical tool, which can describe the approximate behaviour of the dynamics of the dynamical system in lesser dimension than the embedding diemnsion. The present article considers a very rare biomedical signal like Electromyography (EMG) signal. It determines suitable time delay and reconstruct the attractor of embedding diemnsion three. By measuring its Lyapunov exponent, the attractor so reconstructed is found to be chaotic. Naturally the Poincare map obtained by corresponding Poincare section is to be chaotic too. This may be verified by calculation of Lyapunov exponent of the map. The main objective of this article is to show that Poincare map exists in this case as a 2D map for a suitable Poincare section only. In fact, the article considers two Poincare sections of the attractor for construction of the Poincare map. It is seen that one such map is chaotic but the other one is not so, both are verified by calculation of Lyapunov exponent of the map. |
1306.3392 | Yue Wang | Li Chen, Peter L. Choyke, Niya Wang, Robert Clarke, Zaver M.
Bhujwalla, Elizabeth M. C. Hillman, Yue Wang | Unsupervised deconvolution of dynamic imaging reveals intratumor
vascular heterogeneity | Content: main manuscript, 31 pages | null | 10.1371/journal.pone.0112143 | null | q-bio.QM stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Intratumor heterogeneity is often manifested by vascular compartments with
distinct pharmacokinetics that cannot be resolved directly by in vivo dynamic
imaging. We developed tissue-specific compartment modeling (TSCM), an
unsupervised computational method of deconvolving dynamic imaging series from
heterogeneous tumors that can improve vascular phenotyping in many biological
contexts. Applying TSCM to dynamic contrast-enhanced MRI of breast cancers
revealed characteristic intratumor vascular heterogeneity and therapeutic
responses that were otherwise undetectable.
| [
{
"created": "Fri, 14 Jun 2013 13:32:07 GMT",
"version": "v1"
},
{
"created": "Wed, 3 Sep 2014 15:35:06 GMT",
"version": "v2"
},
{
"created": "Thu, 4 Sep 2014 18:46:29 GMT",
"version": "v3"
}
] | 2017-02-08 | [
[
"Chen",
"Li",
""
],
[
"Choyke",
"Peter L.",
""
],
[
"Wang",
"Niya",
""
],
[
"Clarke",
"Robert",
""
],
[
"Bhujwalla",
"Zaver M.",
""
],
[
"Hillman",
"Elizabeth M. C.",
""
],
[
"Wang",
"Yue",
""
]
] | Intratumor heterogeneity is often manifested by vascular compartments with distinct pharmacokinetics that cannot be resolved directly by in vivo dynamic imaging. We developed tissue-specific compartment modeling (TSCM), an unsupervised computational method of deconvolving dynamic imaging series from heterogeneous tumors that can improve vascular phenotyping in many biological contexts. Applying TSCM to dynamic contrast-enhanced MRI of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable. |
1106.3386 | Liane Gabora | Liane Gabora and Scott Barry Kaufman | Evolutionary Approaches to Creativity | 28 pages | In J. Kaufman & R. Sternberg (Eds.), The Cambridge handbook of
creativity (pp. 279-300). Cambridge, UK: Cambridge University Press. (2010) | null | null | q-bio.NC q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Many species engage in acts that could be called creative. However, human
creativity is unique in that it has transformed our planet. Given that the
anatomy of the human brain is not so different from that of the great apes,
what enables us to be so creative? Recent collaborations at the frontier of
anthropology, archaeology, psychology, and cognitive science are culminating in
speculative but increasingly sophisticated efforts to answer to this question.
Examining the skeletons of our ancestors gives cues as to anatomical
constraints that hindered or made possible various kinds of creative
expression. Relics of the past have much to tell us about the thoughts,
beliefs, and creative abilities of the people who invented and used them. How
the spectacular creativity of humans came about is the first topic addressed in
this chapter. Studies at the intersection of creativity and evolution are not
limited to investigations into the biological evolution of a highly creative
species. Creative ideas themselves might be said to evolve through culture.
Human creativity is distinctive because of the adaptive and open-ended manner
in which change accumulates. Inventions build on previous ones in ways that
enhance their utility or aesthetic appeal, or make them applicable in different
situations. There is no a priori limit to how a creative idea might unfold. It
is this proclivity to take an idea and make it our own, or 'put our own spin on
it', that makes creative ideas evolve. The next section of this chapter
investigates in what sense creative ideas evolve through culture. Finally, we
address what forces supported the evolution of creativity. Does being creative
help us live longer, or attract mates? Perhaps creative projects can sometimes
interfere with survival and reproductive fitness; are there non-biological
factors that compel us to create? This is a third topic addressed in this
chapter.
| [
{
"created": "Fri, 17 Jun 2011 05:20:47 GMT",
"version": "v1"
},
{
"created": "Sun, 30 Jun 2019 00:33:53 GMT",
"version": "v2"
},
{
"created": "Fri, 5 Jul 2019 22:06:11 GMT",
"version": "v3"
},
{
"created": "Tue, 9 Jul 2019 19:55:10 GMT",
"version": "v4"
}
] | 2019-07-11 | [
[
"Gabora",
"Liane",
""
],
[
"Kaufman",
"Scott Barry",
""
]
] | Many species engage in acts that could be called creative. However, human creativity is unique in that it has transformed our planet. Given that the anatomy of the human brain is not so different from that of the great apes, what enables us to be so creative? Recent collaborations at the frontier of anthropology, archaeology, psychology, and cognitive science are culminating in speculative but increasingly sophisticated efforts to answer to this question. Examining the skeletons of our ancestors gives cues as to anatomical constraints that hindered or made possible various kinds of creative expression. Relics of the past have much to tell us about the thoughts, beliefs, and creative abilities of the people who invented and used them. How the spectacular creativity of humans came about is the first topic addressed in this chapter. Studies at the intersection of creativity and evolution are not limited to investigations into the biological evolution of a highly creative species. Creative ideas themselves might be said to evolve through culture. Human creativity is distinctive because of the adaptive and open-ended manner in which change accumulates. Inventions build on previous ones in ways that enhance their utility or aesthetic appeal, or make them applicable in different situations. There is no a priori limit to how a creative idea might unfold. It is this proclivity to take an idea and make it our own, or 'put our own spin on it', that makes creative ideas evolve. The next section of this chapter investigates in what sense creative ideas evolve through culture. Finally, we address what forces supported the evolution of creativity. Does being creative help us live longer, or attract mates? Perhaps creative projects can sometimes interfere with survival and reproductive fitness; are there non-biological factors that compel us to create? This is a third topic addressed in this chapter. |
2006.03454 | Giorgia Sironi | F. Nicastro, G. Sironi, E. Antonello, A. Bianco, M. Biasin, J. R.
Brucato, I. Ermolli, G. Pareschi, M. Salvati, P. Tozzi, D. Trabattoni, M.
Clerici | Solar UV$-$B$/$A radiation is highly effective in inactivating
SARS$-$CoV$-$2 | 11 pages + 3 pages supplementary information | Scientific reports (2021) | 10.1038/s41598-021-94417-9 | null | q-bio.PE physics.ao-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Solar UV$-$C photons do not reach Earth's surface, but are known to be
endowed with germicidal properties that are also effective on viruses. The
effect of softer UV$-$B and UV$-$A photons, which copiously reach the Earth's
surface, on viruses are instead little studied, particularly on
single$-$stranded RNA viruses. Here we combine our measurements of the action
spectrum of Covid$-$19 in response to UV light, Solar irradiation measurements
on Earth during the SARS$-$CoV$-$2 pandemics, worldwide recorded Covid$-$19
mortality data and our 'Solar$-$Pump' diffusive model of epidemics to show that
(a) UV$-$B$/$A photons have a powerful virucidal effect on the
single$-$stranded RNA virus Covid$-$19 and that (b) the Solar radiation that
reaches temperate regions of the Earth at noon during summers, is sufficient to
inactivate 63\perc of virions in open$-$space concentrations (1.5 x 103
TCID50$/$mL, higher than typical aerosol) in less than 2 min. We conclude that
the characteristic seasonality imprint displayed world$-$wide by the
SARS$-$Cov$-$2 mortality time$-$series throughout the diffusion of the outbreak
(with temperate regions showing clear seasonal trends and equatorial regions
suffering, on average, a systematically lower mortality), might have been
efficiently set by the different intensity of UV$-$B$/$A Solar radiation
hitting different Earth's locations at different times of the year. Our results
suggest that Solar UV$-$B$/$A play an important role in planning strategies of
confinement of the epidemics, which should be worked out and set up during
spring$/$summer months and fully implemented during low$-$solar$-$irradiation
periods.
| [
{
"created": "Wed, 3 Jun 2020 18:51:59 GMT",
"version": "v1"
},
{
"created": "Thu, 30 Jul 2020 07:24:18 GMT",
"version": "v2"
},
{
"created": "Wed, 21 Jul 2021 07:47:41 GMT",
"version": "v3"
}
] | 2021-07-22 | [
[
"Nicastro",
"F.",
""
],
[
"Sironi",
"G.",
""
],
[
"Antonello",
"E.",
""
],
[
"Bianco",
"A.",
""
],
[
"Biasin",
"M.",
""
],
[
"Brucato",
"J. R.",
""
],
[
"Ermolli",
"I.",
""
],
[
"Pareschi",
"G.",
""
],
[
"Salvati",
"M.",
""
],
[
"Tozzi",
"P.",
""
],
[
"Trabattoni",
"D.",
""
],
[
"Clerici",
"M.",
""
]
] | Solar UV$-$C photons do not reach Earth's surface, but are known to be endowed with germicidal properties that are also effective on viruses. The effect of softer UV$-$B and UV$-$A photons, which copiously reach the Earth's surface, on viruses are instead little studied, particularly on single$-$stranded RNA viruses. Here we combine our measurements of the action spectrum of Covid$-$19 in response to UV light, Solar irradiation measurements on Earth during the SARS$-$CoV$-$2 pandemics, worldwide recorded Covid$-$19 mortality data and our 'Solar$-$Pump' diffusive model of epidemics to show that (a) UV$-$B$/$A photons have a powerful virucidal effect on the single$-$stranded RNA virus Covid$-$19 and that (b) the Solar radiation that reaches temperate regions of the Earth at noon during summers, is sufficient to inactivate 63\perc of virions in open$-$space concentrations (1.5 x 103 TCID50$/$mL, higher than typical aerosol) in less than 2 min. We conclude that the characteristic seasonality imprint displayed world$-$wide by the SARS$-$Cov$-$2 mortality time$-$series throughout the diffusion of the outbreak (with temperate regions showing clear seasonal trends and equatorial regions suffering, on average, a systematically lower mortality), might have been efficiently set by the different intensity of UV$-$B$/$A Solar radiation hitting different Earth's locations at different times of the year. Our results suggest that Solar UV$-$B$/$A play an important role in planning strategies of confinement of the epidemics, which should be worked out and set up during spring$/$summer months and fully implemented during low$-$solar$-$irradiation periods. |
0807.4014 | Vladimir Ivancevic | Vladimir G. Ivancevic and Tijana T. Ivancevic | Geometrical Bioelectrodynamics | 38 pages, 7 figures, Latex | null | null | null | q-bio.QM physics.bio-ph q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper proposes rigorous geometrical treatment of bioelectrodynamics,
underpinning two fast-growing biomedical research fields: bioelectromagnetism,
which deals with the ability of life to produce its own electromagnetism, and
bioelectromagnetics, which deals with the effect on life from external
electromagnetism.
Keywords: Bioelectrodynamics, exterior geometrical machinery, Dirac-Feynman
quantum electrodynamics, functional electrical stimulation
| [
{
"created": "Fri, 25 Jul 2008 07:47:45 GMT",
"version": "v1"
},
{
"created": "Mon, 28 Jul 2008 01:55:12 GMT",
"version": "v2"
},
{
"created": "Fri, 26 Sep 2008 02:55:25 GMT",
"version": "v3"
}
] | 2008-09-26 | [
[
"Ivancevic",
"Vladimir G.",
""
],
[
"Ivancevic",
"Tijana T.",
""
]
] | This paper proposes rigorous geometrical treatment of bioelectrodynamics, underpinning two fast-growing biomedical research fields: bioelectromagnetism, which deals with the ability of life to produce its own electromagnetism, and bioelectromagnetics, which deals with the effect on life from external electromagnetism. Keywords: Bioelectrodynamics, exterior geometrical machinery, Dirac-Feynman quantum electrodynamics, functional electrical stimulation |
2310.05297 | Jason Yim | Jason Yim, Andrew Campbell, Andrew Y. K. Foong, Michael Gastegger,
Jos\'e Jim\'enez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S.
Veeling, Regina Barzilay, Tommi Jaakkola, Frank No\'e | Fast protein backbone generation with SE(3) flow matching | Preprint | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present FrameFlow, a method for fast protein backbone generation using
SE(3) flow matching. Specifically, we adapt FrameDiff, a state-of-the-art
diffusion model, to the flow-matching generative modeling paradigm. We show how
flow matching can be applied on SE(3) and propose modifications during training
to effectively learn the vector field. Compared to FrameDiff, FrameFlow
requires five times fewer sampling timesteps while achieving two fold better
designability. The ability to generate high quality protein samples at a
fraction of the cost of previous methods paves the way towards more efficient
generative models in de novo protein design.
| [
{
"created": "Sun, 8 Oct 2023 21:55:00 GMT",
"version": "v1"
},
{
"created": "Tue, 10 Oct 2023 19:01:24 GMT",
"version": "v2"
}
] | 2023-10-12 | [
[
"Yim",
"Jason",
""
],
[
"Campbell",
"Andrew",
""
],
[
"Foong",
"Andrew Y. K.",
""
],
[
"Gastegger",
"Michael",
""
],
[
"Jiménez-Luna",
"José",
""
],
[
"Lewis",
"Sarah",
""
],
[
"Satorras",
"Victor Garcia",
""
],
[
"Veeling",
"Bastiaan S.",
""
],
[
"Barzilay",
"Regina",
""
],
[
"Jaakkola",
"Tommi",
""
],
[
"Noé",
"Frank",
""
]
] | We present FrameFlow, a method for fast protein backbone generation using SE(3) flow matching. Specifically, we adapt FrameDiff, a state-of-the-art diffusion model, to the flow-matching generative modeling paradigm. We show how flow matching can be applied on SE(3) and propose modifications during training to effectively learn the vector field. Compared to FrameDiff, FrameFlow requires five times fewer sampling timesteps while achieving two fold better designability. The ability to generate high quality protein samples at a fraction of the cost of previous methods paves the way towards more efficient generative models in de novo protein design. |
1309.2521 | Daniel Schrider | Daniel R. Schrider and Andrew D. Kern | Inferring selective constraint from population genomic data suggests
recent regulatory turnover in the human brain | null | null | 10.1093/gbe/evv228 | null | q-bio.PE q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The comparative genomics revolution of the past decade has enabled the
discovery of functional elements in the human genome via sequence comparison.
While that is so, an important class of elements, those specific to humans, is
entirely missed by searching for sequence conservation across species. Here we
present an analysis based on variation data among human genomes that utilizes a
supervised machine learning approach for the identification of human specific
purifying selection in the genome. Using only allele frequency information from
the complete low coverage 1000 Genomes Project dataset in conjunction with a
support vector machine trained from known functional and non-functional
portions of the genome, we are able to accurately identify portions of the
genome constrained by purifying selection. Our method identifies previously
known human-specific gains or losses of function and uncovers many novel
candidates. Candidate targets for gain and loss of function along the human
lineage include numerous putative regulatory regions of genes essential for
normal development of the central nervous system, including a significant
enrichment of gain of function events near neurotransmitter receptor genes.
These results are consistent with regulatory turnover being a key mechanism in
the evolution of human-specific characteristics of brain development. Finally,
we show that the majority of the genome is unconstrained by natural selection
currently, in agreement with what has been estimated from phylogenetic methods
but in sharp contrast to estimates based on transcriptomics or other
high-throughput functional methods.
| [
{
"created": "Tue, 10 Sep 2013 14:14:14 GMT",
"version": "v1"
},
{
"created": "Tue, 22 Oct 2013 02:44:23 GMT",
"version": "v2"
},
{
"created": "Fri, 7 Feb 2014 23:22:49 GMT",
"version": "v3"
},
{
"created": "Wed, 21 May 2014 03:23:02 GMT",
"version": "v4"
},
{
"created": "Sun, 22 Nov 2015 03:24:36 GMT",
"version": "v5"
}
] | 2015-11-24 | [
[
"Schrider",
"Daniel R.",
""
],
[
"Kern",
"Andrew D.",
""
]
] | The comparative genomics revolution of the past decade has enabled the discovery of functional elements in the human genome via sequence comparison. While that is so, an important class of elements, those specific to humans, is entirely missed by searching for sequence conservation across species. Here we present an analysis based on variation data among human genomes that utilizes a supervised machine learning approach for the identification of human specific purifying selection in the genome. Using only allele frequency information from the complete low coverage 1000 Genomes Project dataset in conjunction with a support vector machine trained from known functional and non-functional portions of the genome, we are able to accurately identify portions of the genome constrained by purifying selection. Our method identifies previously known human-specific gains or losses of function and uncovers many novel candidates. Candidate targets for gain and loss of function along the human lineage include numerous putative regulatory regions of genes essential for normal development of the central nervous system, including a significant enrichment of gain of function events near neurotransmitter receptor genes. These results are consistent with regulatory turnover being a key mechanism in the evolution of human-specific characteristics of brain development. Finally, we show that the majority of the genome is unconstrained by natural selection currently, in agreement with what has been estimated from phylogenetic methods but in sharp contrast to estimates based on transcriptomics or other high-throughput functional methods. |
2405.10112 | Robert Worden | Robert Worden | Spatial Cognition: a Wave Hypothesis | 15 pages | null | null | null | q-bio.NC q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Animals build Bayesian 3D models of their surroundings, to control their
movements. There is strong selection pressure to make these models as precise
as possible, given their sense data. A previous paper has described how a
precise 3D model of space can be built by object tracking. This only works if
3D locations are stored with high spatial precision. Neural models of 3D
spatial memory have large random errors; too large to support the tracking
model. An alternative is described, in which neurons couple to a wave
excitation in the brain, representing 3-D space. This can give high spatial
precision, fast response, and other benefits. Three lines of evidence support
the wave hypothesis: (1) it has better precision and speed than neural spatial
memory, and is good enough to support object tracking; (2) the central body of
the insect brain, whose form is highly conserved across all insect species, is
well suited to hold a wave; and (3) the thalamus, whose round shape is
conserved across all mammal species, is well suited to hold a wave. These lines
of evidence strongly support the wave hypothesis.
| [
{
"created": "Thu, 16 May 2024 14:04:01 GMT",
"version": "v1"
}
] | 2024-05-17 | [
[
"Worden",
"Robert",
""
]
] | Animals build Bayesian 3D models of their surroundings, to control their movements. There is strong selection pressure to make these models as precise as possible, given their sense data. A previous paper has described how a precise 3D model of space can be built by object tracking. This only works if 3D locations are stored with high spatial precision. Neural models of 3D spatial memory have large random errors; too large to support the tracking model. An alternative is described, in which neurons couple to a wave excitation in the brain, representing 3-D space. This can give high spatial precision, fast response, and other benefits. Three lines of evidence support the wave hypothesis: (1) it has better precision and speed than neural spatial memory, and is good enough to support object tracking; (2) the central body of the insect brain, whose form is highly conserved across all insect species, is well suited to hold a wave; and (3) the thalamus, whose round shape is conserved across all mammal species, is well suited to hold a wave. These lines of evidence strongly support the wave hypothesis. |
1203.0738 | Alain Destexhe | Nima Dehghani, Nicholas G. Hatsopoulos, Zach D. Haga, Rebecca A.
Parker, Bradley Greger, Eric Halgren, Sydney S. Cash and Alain Destexhe | Avalanche analysis from multi-electrode ensemble recordings in cat,
monkey and human cerebral cortex during wakefulness and sleep | In press in: Frontiers in Physiology, 2012, special issue "Critical
Brain Dynamics" (Edited by He BY, Daffertshofer A, Boonstra TW); 33 pages, 13
figures. 3 tables | Frontiers in Physiology 3: 302, 2012 | null | null | q-bio.NC nlin.AO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Self-organized critical states are found in many natural systems, from
earthquakes to forest fires, they have also been observed in neural systems,
particularly, in neuronal cultures. However, the presence of critical states in
the awake brain remains controversial. Here, we compared avalanche analyses
performed on different in vivo preparations during wakefulness, slow-wave sleep
and REM sleep, using high-density electrode arrays in cat motor cortex (96
electrodes), monkey motor cortex and premotor cortex and human temporal cortex
(96 electrodes) in epileptic patients. In neuronal avalanches defined from
units (up to 160 single units), the size of avalanches never clearly scaled as
power-law, but rather scaled exponentially or displayed intermediate scaling.
We also analyzed the dynamics of local field potentials (LFPs) and in
particular LFP negative peaks (nLFPs) among the different electrodes (up to 96
sites in temporal cortex or up to 128 sites in adjacent motor and pre-motor
cortices). In this case, the avalanches defined from nLFPs displayed power-law
scaling in double log representations, as reported previously in monkey.
However, avalanche defined as positive LFP (pLFP) peaks, which are less
directly related to neuronal firing, also displayed apparent power-law scaling.
Closer examination of this scaling using more reliable cumulative distribution
functions (CDF) and other rigorous statistical measures, did not confirm
power-law scaling. The same pattern was seen for cats, monkey and human, as
well as for different brain states of wakefulness and sleep. We also tested
other alternative distributions. Multiple exponential fitting yielded optimal
fits of the avalanche dynamics with bi-exponential distributions. Collectively,
these results show no clear evidence for power-law scaling or self-organized
critical states in the awake and sleeping brain of mammals, from cat to man.
| [
{
"created": "Sun, 4 Mar 2012 13:16:19 GMT",
"version": "v1"
},
{
"created": "Wed, 25 Apr 2012 12:27:31 GMT",
"version": "v2"
},
{
"created": "Fri, 22 Jun 2012 21:24:58 GMT",
"version": "v3"
},
{
"created": "Sun, 15 Jul 2012 12:54:06 GMT",
"version": "v4"
}
] | 2012-08-20 | [
[
"Dehghani",
"Nima",
""
],
[
"Hatsopoulos",
"Nicholas G.",
""
],
[
"Haga",
"Zach D.",
""
],
[
"Parker",
"Rebecca A.",
""
],
[
"Greger",
"Bradley",
""
],
[
"Halgren",
"Eric",
""
],
[
"Cash",
"Sydney S.",
""
],
[
"Destexhe",
"Alain",
""
]
] | Self-organized critical states are found in many natural systems, from earthquakes to forest fires, they have also been observed in neural systems, particularly, in neuronal cultures. However, the presence of critical states in the awake brain remains controversial. Here, we compared avalanche analyses performed on different in vivo preparations during wakefulness, slow-wave sleep and REM sleep, using high-density electrode arrays in cat motor cortex (96 electrodes), monkey motor cortex and premotor cortex and human temporal cortex (96 electrodes) in epileptic patients. In neuronal avalanches defined from units (up to 160 single units), the size of avalanches never clearly scaled as power-law, but rather scaled exponentially or displayed intermediate scaling. We also analyzed the dynamics of local field potentials (LFPs) and in particular LFP negative peaks (nLFPs) among the different electrodes (up to 96 sites in temporal cortex or up to 128 sites in adjacent motor and pre-motor cortices). In this case, the avalanches defined from nLFPs displayed power-law scaling in double log representations, as reported previously in monkey. However, avalanche defined as positive LFP (pLFP) peaks, which are less directly related to neuronal firing, also displayed apparent power-law scaling. Closer examination of this scaling using more reliable cumulative distribution functions (CDF) and other rigorous statistical measures, did not confirm power-law scaling. The same pattern was seen for cats, monkey and human, as well as for different brain states of wakefulness and sleep. We also tested other alternative distributions. Multiple exponential fitting yielded optimal fits of the avalanche dynamics with bi-exponential distributions. Collectively, these results show no clear evidence for power-law scaling or self-organized critical states in the awake and sleeping brain of mammals, from cat to man. |
2305.10466 | Hailan Zhang | Hailan Zhang and Gongjin Song | Solitary pulmonary nodules prediction for lung cancer patients using
nomogram and machine learning | null | null | null | null | q-bio.QM cs.AI eess.IV | http://creativecommons.org/licenses/by/4.0/ | Lung cancer(LC) is a type of malignant neoplasm that originates in the
bronchial mucosa or glands.As a clinically common nodule,solitary pulmonary
nodules(SPNs) have a significantly higher probability of malignancy when they
are larger than 8 mm in diameter.But there is also a risk of lung cancer when
the diameter is less than 8mm,the purpose of this study was to create a
nomogram for estimating the likelihood of lung cancer in patients with SPNs of
8 mm or smaller using computed tomography(CT) scans and biomarker
information.Use CT scans and various biomarkers as input to build predictive
models for the likelihood of lung cancer in patients with SPNs of 8 mm or
less.The age,precursor gastrin-releasing peptide
(ProGRP),gender,Carcinoembryonic Antigen(CEA),and stress corrosion
cracking(SCC) were independent key tumor markers and were entered into the
nomogram.The developed nomogram demonstrated strong accuracy in predicting lung
cancer risk,with an internal validation area under the receiver operating
characteristics curve(ROC) of 0.8474.The calibration curves plotted showed that
the nomogram predicted the probability of lung cancer with good agreement with
the actual probability.In this study,we finally succeeded in constructing a
suitable nomogram that could predict the risk of lung cancer in patients with
SPNs<=8 mm in diameter.The model has a high level of accuracy and is able to
accurately distinguish between different patients,allowing clinicians to
develop personalized treatment plans for individuals with SPNs.
| [
{
"created": "Wed, 17 May 2023 13:12:17 GMT",
"version": "v1"
}
] | 2023-05-19 | [
[
"Zhang",
"Hailan",
""
],
[
"Song",
"Gongjin",
""
]
] | Lung cancer(LC) is a type of malignant neoplasm that originates in the bronchial mucosa or glands.As a clinically common nodule,solitary pulmonary nodules(SPNs) have a significantly higher probability of malignancy when they are larger than 8 mm in diameter.But there is also a risk of lung cancer when the diameter is less than 8mm,the purpose of this study was to create a nomogram for estimating the likelihood of lung cancer in patients with SPNs of 8 mm or smaller using computed tomography(CT) scans and biomarker information.Use CT scans and various biomarkers as input to build predictive models for the likelihood of lung cancer in patients with SPNs of 8 mm or less.The age,precursor gastrin-releasing peptide (ProGRP),gender,Carcinoembryonic Antigen(CEA),and stress corrosion cracking(SCC) were independent key tumor markers and were entered into the nomogram.The developed nomogram demonstrated strong accuracy in predicting lung cancer risk,with an internal validation area under the receiver operating characteristics curve(ROC) of 0.8474.The calibration curves plotted showed that the nomogram predicted the probability of lung cancer with good agreement with the actual probability.In this study,we finally succeeded in constructing a suitable nomogram that could predict the risk of lung cancer in patients with SPNs<=8 mm in diameter.The model has a high level of accuracy and is able to accurately distinguish between different patients,allowing clinicians to develop personalized treatment plans for individuals with SPNs. |
1404.7549 | Ben Lansdell | Benjamin Lansdell and Kevin Ford and J. Nathan Kutz | A reaction-diffusion model of cholinergic retinal waves | 38 pages, 10 figures | null | 10.1371/journal.pcbi.1003953 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Prior to receiving visual stimuli, spontaneous, correlated activity called
retinal waves drives activity-dependent developmental programs. Early-stage
waves mediated by acetylcholine (ACh) manifest as slow, spreading bursts of
action potentials. They are believed to be initiated by the spontaneous firing
of Starburst Amacrine Cells (SACs), whose dense, recurrent connectivity then
propagates this activity laterally. Their extended inter-wave intervals and
shifting wave boundaries are the result of the slow after-hyperpolarization of
the SACs creating an evolving mosaic of recruitable and refractory cells, which
can and cannot participate in waves, respectively. Recent evidence suggests
that cholinergic waves may be modulated by the extracellular concentration of
ACh. Here, we construct a simplified, biophysically consistent,
reaction-diffusion model of cholinergic retinal waves capable of recapitulating
wave dynamics observed in mice retina recordings. The dense, recurrent
connectivity of SACs is modeled through local, excitatory coupling occurring
via the volume release and diffusion of ACh. In contrast with previous,
simulation-based models, we are able to use non-linear wave theory to connect
wave features to underlying physiological parameters, making the model useful
in determining appropriate pharmacological manipulations to experimentally
produce waves of a prescribed spatiotemporal character. The model is used to
determine how ACh mediated connectivity may modulate wave activity, and how the
noise rate and sAHP refractory period contributes to critical wave size
variability.
| [
{
"created": "Tue, 29 Apr 2014 22:26:41 GMT",
"version": "v1"
},
{
"created": "Sat, 11 Oct 2014 19:28:14 GMT",
"version": "v2"
}
] | 2015-06-19 | [
[
"Lansdell",
"Benjamin",
""
],
[
"Ford",
"Kevin",
""
],
[
"Kutz",
"J. Nathan",
""
]
] | Prior to receiving visual stimuli, spontaneous, correlated activity called retinal waves drives activity-dependent developmental programs. Early-stage waves mediated by acetylcholine (ACh) manifest as slow, spreading bursts of action potentials. They are believed to be initiated by the spontaneous firing of Starburst Amacrine Cells (SACs), whose dense, recurrent connectivity then propagates this activity laterally. Their extended inter-wave intervals and shifting wave boundaries are the result of the slow after-hyperpolarization of the SACs creating an evolving mosaic of recruitable and refractory cells, which can and cannot participate in waves, respectively. Recent evidence suggests that cholinergic waves may be modulated by the extracellular concentration of ACh. Here, we construct a simplified, biophysically consistent, reaction-diffusion model of cholinergic retinal waves capable of recapitulating wave dynamics observed in mice retina recordings. The dense, recurrent connectivity of SACs is modeled through local, excitatory coupling occurring via the volume release and diffusion of ACh. In contrast with previous, simulation-based models, we are able to use non-linear wave theory to connect wave features to underlying physiological parameters, making the model useful in determining appropriate pharmacological manipulations to experimentally produce waves of a prescribed spatiotemporal character. The model is used to determine how ACh mediated connectivity may modulate wave activity, and how the noise rate and sAHP refractory period contributes to critical wave size variability. |
1907.13118 | Kristine Heiney | Kristine Heiney, Ola Huse Ramstad, Ioanna Sandvig, Axel Sandvig,
Stefano Nichele | Assessment and manipulation of the computational capacity of in vitro
neuronal networks through criticality in neuronal avalanches | 8 pages, 3 figures, submitted to IEEE SSCI2019 ALIFE Symposium. arXiv
admin note: substantial text overlap with arXiv:1907.02351 | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work, we report the preliminary analysis of the electrophysiological
behavior of in vitro neuronal networks to identify when the networks are in a
critical state based on the size distribution of network-wide avalanches of
activity. The results presented here demonstrate the importance of selecting
appropriate parameters in the evaluation of the size distribution and indicate
that it is possible to perturb networks showing highly synchronized---or
supercritical---behavior into the critical state by increasing the level of
inhibition in the network. The classification of critical versus non-critical
networks is valuable in identifying networks that can be expected to perform
well on computational tasks, as criticality is widely considered to be the
state in which a system is best suited for computation. This type of analysis
is expected to enable the identification of networks that are well-suited for
computation and the classification of networks as perturbed or healthy. This
study is part of a larger research project, the overarching aim of which is to
develop computational models that are able to reproduce target behaviors
observed in in vitro neuronal networks. These models will ultimately be used to
aid in the realization of these behaviors in nanomagnet arrays to be used in
novel computing hardwares.
| [
{
"created": "Mon, 29 Jul 2019 12:33:41 GMT",
"version": "v1"
}
] | 2019-07-31 | [
[
"Heiney",
"Kristine",
""
],
[
"Ramstad",
"Ola Huse",
""
],
[
"Sandvig",
"Ioanna",
""
],
[
"Sandvig",
"Axel",
""
],
[
"Nichele",
"Stefano",
""
]
] | In this work, we report the preliminary analysis of the electrophysiological behavior of in vitro neuronal networks to identify when the networks are in a critical state based on the size distribution of network-wide avalanches of activity. The results presented here demonstrate the importance of selecting appropriate parameters in the evaluation of the size distribution and indicate that it is possible to perturb networks showing highly synchronized---or supercritical---behavior into the critical state by increasing the level of inhibition in the network. The classification of critical versus non-critical networks is valuable in identifying networks that can be expected to perform well on computational tasks, as criticality is widely considered to be the state in which a system is best suited for computation. This type of analysis is expected to enable the identification of networks that are well-suited for computation and the classification of networks as perturbed or healthy. This study is part of a larger research project, the overarching aim of which is to develop computational models that are able to reproduce target behaviors observed in in vitro neuronal networks. These models will ultimately be used to aid in the realization of these behaviors in nanomagnet arrays to be used in novel computing hardwares. |
2009.11549 | Dirk Wittekind Dr. | Dirk Alexander Wittekind, Markus Scholz, J\"urgen Kratzsch, Markus
L\"offler, Katrin Horn, Holger Kirsten, Veronica Witte, Arno Villringer,
Michael Kluge | Genome-wide association and transcriptome analysis reveals serum ghrelin
to be linked with GFRAL | null | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Objective: Ghrelin is an orexigenic peptide hormone involved in the
regulation of energy homeostasis, food intake and glucose metabolism. Serum
levels increase anticipating a meal and fall afterwards. Underlying genetic
mechanisms of the ghrelin secretion are unknown. Methods: Total serum ghrelin
was measured in 1501 subjects selected from the population-based
LIFE-ADULT-sample after an overnight fast. A genome-wide association study
(GWAS) was performed. Gene-based expression association analyses
(transcriptome-wide association study (TWAS)) were done using MetaXcan.
Results: In the GWAS, three loci reached genome-wide significance: the
WW-domain containing the oxidoreductase-gene (WWOX; p=1.80E-10) on chromosome
16q23.3-24.1 (SNP: rs76823993); the Contactin-Associated Protein-Like 2 gene
(CNTNAP2; p=9.0E-9) on chromosome 7q35-q36 (SNP: rs192092592) and the Ghrelin
And Obestatin Prepropeptide gene (GHRL; p=2.72E-8) on chromosome 3p25.3 (SNP:
rs143729751). In the TWAS, serum ghrelin was negatively associated with RNA
expression of the GDNF Family Receptor Alpha Like (GFRAL), receptor of the
anorexigenic Growth Differentiation Factor-15 (GDF15), (z-score=-4.288,
p=1.81E-05). Furthermore, ghrelin was positively associated with Ribosomal
Protein L36 (RPL36; z-score=4.848, p=1.25E-06). Conclusions: Our findings
provide evidence of a functional link between two major players of weight
regulation, the ghrelin system and the GDF15/GFRAL-pathway.
| [
{
"created": "Thu, 24 Sep 2020 08:44:42 GMT",
"version": "v1"
}
] | 2020-09-25 | [
[
"Wittekind",
"Dirk Alexander",
""
],
[
"Scholz",
"Markus",
""
],
[
"Kratzsch",
"Jürgen",
""
],
[
"Löffler",
"Markus",
""
],
[
"Horn",
"Katrin",
""
],
[
"Kirsten",
"Holger",
""
],
[
"Witte",
"Veronica",
""
],
[
"Villringer",
"Arno",
""
],
[
"Kluge",
"Michael",
""
]
] | Objective: Ghrelin is an orexigenic peptide hormone involved in the regulation of energy homeostasis, food intake and glucose metabolism. Serum levels increase anticipating a meal and fall afterwards. Underlying genetic mechanisms of the ghrelin secretion are unknown. Methods: Total serum ghrelin was measured in 1501 subjects selected from the population-based LIFE-ADULT-sample after an overnight fast. A genome-wide association study (GWAS) was performed. Gene-based expression association analyses (transcriptome-wide association study (TWAS)) were done using MetaXcan. Results: In the GWAS, three loci reached genome-wide significance: the WW-domain containing the oxidoreductase-gene (WWOX; p=1.80E-10) on chromosome 16q23.3-24.1 (SNP: rs76823993); the Contactin-Associated Protein-Like 2 gene (CNTNAP2; p=9.0E-9) on chromosome 7q35-q36 (SNP: rs192092592) and the Ghrelin And Obestatin Prepropeptide gene (GHRL; p=2.72E-8) on chromosome 3p25.3 (SNP: rs143729751). In the TWAS, serum ghrelin was negatively associated with RNA expression of the GDNF Family Receptor Alpha Like (GFRAL), receptor of the anorexigenic Growth Differentiation Factor-15 (GDF15), (z-score=-4.288, p=1.81E-05). Furthermore, ghrelin was positively associated with Ribosomal Protein L36 (RPL36; z-score=4.848, p=1.25E-06). Conclusions: Our findings provide evidence of a functional link between two major players of weight regulation, the ghrelin system and the GDF15/GFRAL-pathway. |
1004.2270 | Marcelo Sobottka | Eduardo Garibaldi and Marcelo Sobottka | Average sex ratio and population maintenance cost | 18 pages. A revised new version, where all the text was improved to
become more clear for the reader | SIAM Journal on Applied Mathematics (2011), 71, 1009--1025 | 10.1137/100817310 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The ratio of males to females in a population is a meaningful characteristic
of sexual species. The reason for this biological property to be available to
the observers of nature seems to be a question never asked. Introducing the
notion of historically adapted populations as global minimizers of maintenance
cost functions, we propose a theoretical explanation for the reported stability
of this feature. This mathematical formulation suggests that sex ratio could be
considered as an indirect result shaped by the antagonism between the size of
the population and the finiteness of resources.
| [
{
"created": "Tue, 13 Apr 2010 21:10:58 GMT",
"version": "v1"
},
{
"created": "Sat, 17 Jul 2010 20:14:58 GMT",
"version": "v2"
},
{
"created": "Tue, 14 Feb 2017 17:31:48 GMT",
"version": "v3"
}
] | 2017-02-15 | [
[
"Garibaldi",
"Eduardo",
""
],
[
"Sobottka",
"Marcelo",
""
]
] | The ratio of males to females in a population is a meaningful characteristic of sexual species. The reason for this biological property to be available to the observers of nature seems to be a question never asked. Introducing the notion of historically adapted populations as global minimizers of maintenance cost functions, we propose a theoretical explanation for the reported stability of this feature. This mathematical formulation suggests that sex ratio could be considered as an indirect result shaped by the antagonism between the size of the population and the finiteness of resources. |
1312.3283 | Thomas Van Boeckel Dr | Thomas P. Van Boeckel, Michael J. Tildesley, Catherine Linard, Jos\'e
Halloy, Matt J. Keeling, Marius Gilbert | The Nosoi commute: a spatial perspective on the rise of BSL-4
laboratories in cities | null | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent H5N1 influenza research has revived the debate on the storage and
manipulation of potentially harmful pathogens. In the last two decades, new
high biosafety (BSL-4) laboratories entered into operation, raising strong
concerns from the public. The probability of an accidental release of a
pathogen from a BSL-4 laboratory is extremely low, but the corresponding risk
-- defined as the probability of occurrence multiplied by its impact -- could
be significant depending on the pathogen specificities and the population
potentially affected. A list of BSL-4 laboratories throughout the world, with
their location and date of first activity, was established from publicly
available sources. This database was used to estimate the total population
living within a daily commuting distance of BSL-4 laboratories, and to quantify
how this figure changed over time. We show that from 1990 to present, the
population living within the commuting belt of BSL-4 laboratories increased by
a factor of 4 to reach up to 1.8% of the world population, owing to an increase
in the number of facilities and their installation in cities. Europe is
currently hosting the largest population living in the direct vicinity of BSL-4
laboratories, while the recent building of new facilities in Asia suggests that
an important increase of the population living close to BSL-4 laboratories will
be observed in the next decades. We discuss the potential implications in term
of global risk, and call for better pathogen-specific quantitative assessment
of the risk of outbreaks resulting from the accidental release of potentially
pandemic pathogens
| [
{
"created": "Wed, 11 Dec 2013 19:15:46 GMT",
"version": "v1"
},
{
"created": "Fri, 13 Dec 2013 16:22:06 GMT",
"version": "v2"
}
] | 2013-12-16 | [
[
"Van Boeckel",
"Thomas P.",
""
],
[
"Tildesley",
"Michael J.",
""
],
[
"Linard",
"Catherine",
""
],
[
"Halloy",
"José",
""
],
[
"Keeling",
"Matt J.",
""
],
[
"Gilbert",
"Marius",
""
]
] | Recent H5N1 influenza research has revived the debate on the storage and manipulation of potentially harmful pathogens. In the last two decades, new high biosafety (BSL-4) laboratories entered into operation, raising strong concerns from the public. The probability of an accidental release of a pathogen from a BSL-4 laboratory is extremely low, but the corresponding risk -- defined as the probability of occurrence multiplied by its impact -- could be significant depending on the pathogen specificities and the population potentially affected. A list of BSL-4 laboratories throughout the world, with their location and date of first activity, was established from publicly available sources. This database was used to estimate the total population living within a daily commuting distance of BSL-4 laboratories, and to quantify how this figure changed over time. We show that from 1990 to present, the population living within the commuting belt of BSL-4 laboratories increased by a factor of 4 to reach up to 1.8% of the world population, owing to an increase in the number of facilities and their installation in cities. Europe is currently hosting the largest population living in the direct vicinity of BSL-4 laboratories, while the recent building of new facilities in Asia suggests that an important increase of the population living close to BSL-4 laboratories will be observed in the next decades. We discuss the potential implications in term of global risk, and call for better pathogen-specific quantitative assessment of the risk of outbreaks resulting from the accidental release of potentially pandemic pathogens |
2306.02510 | D\'ebora Princepe | D\'ebora Princepe, Simone Czarnobai, Rodrigo A. Caetano, Flavia M. D.
Marquitti, Marcus A. M. de Aguiar, and Sabrina B. L. Araujo | Intermittent migration can induce pulses of speciation in a two-island
system | 18 pages, 4 figures | null | 10.1093/evolut/qpad210 | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Geographic barriers prevent migration between populations, thereby
facilitating speciation through allopatry. However, these barriers can exhibit
dynamic behavior in nature, promoting cycles of expansion and contraction of
populations. Such oscillations cause temporal variations in migration that do
not necessarily prevent speciation; on the contrary, they have been suggested
as a driving force for diversification. Here we present a study on a two-island
neutral speciation model in scenarios with intermittent migration driven by
sea-level fluctuations. Mating is constrained to genetically compatible
individuals inhabiting the same island, and offspring inherit nuclear genomes
from both parents with recombination. We observe pulses of speciation that
would not occur in strict isolation or continuous migration. According to the
seabed height, which modulates the duration of the isolation and connection
periods, the maximum richness occurs at different times and in an ephemeral
fashion. The expansion-contraction dynamics can accelerate diversification, but
a long time in isolation can reduce the richness to one species per island,
resembling patterns described by the taxon pulse hypothesis of diversification.
Together with other studies, our results support the relevance of research on
the impact of variable migration on diversification, suggested to be related to
regions of high diversity.
| [
{
"created": "Mon, 5 Jun 2023 00:12:48 GMT",
"version": "v1"
}
] | 2024-02-01 | [
[
"Princepe",
"Débora",
""
],
[
"Czarnobai",
"Simone",
""
],
[
"Caetano",
"Rodrigo A.",
""
],
[
"Marquitti",
"Flavia M. D.",
""
],
[
"de Aguiar",
"Marcus A. M.",
""
],
[
"Araujo",
"Sabrina B. L.",
""
]
] | Geographic barriers prevent migration between populations, thereby facilitating speciation through allopatry. However, these barriers can exhibit dynamic behavior in nature, promoting cycles of expansion and contraction of populations. Such oscillations cause temporal variations in migration that do not necessarily prevent speciation; on the contrary, they have been suggested as a driving force for diversification. Here we present a study on a two-island neutral speciation model in scenarios with intermittent migration driven by sea-level fluctuations. Mating is constrained to genetically compatible individuals inhabiting the same island, and offspring inherit nuclear genomes from both parents with recombination. We observe pulses of speciation that would not occur in strict isolation or continuous migration. According to the seabed height, which modulates the duration of the isolation and connection periods, the maximum richness occurs at different times and in an ephemeral fashion. The expansion-contraction dynamics can accelerate diversification, but a long time in isolation can reduce the richness to one species per island, resembling patterns described by the taxon pulse hypothesis of diversification. Together with other studies, our results support the relevance of research on the impact of variable migration on diversification, suggested to be related to regions of high diversity. |
2003.14334 | Georgios D. Barmparis | G. D. Barmparis and G. P. Tsironis | Estimating the infection horizon of COVID-19 in eight countries with a
data-driven approach | null | null | 10.1016/j.chaos.2020.109842 | null | q-bio.PE physics.bio-ph physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The COVID-19 pandemic has affected all countries of the world producing a
substantial number of fatalities accompanied by a major disruption in their
social, financial, and educational organization. The strict disciplinary
measures implemented by China were very effective and thus were subsequently
adopted by most world countries to various degrees. The infection duration and
number of infected persons are of critical importance for the battle against
the pandemic. We use the quantitative landscape of the disease spreading in
China as a benchmark and utilize infection data from eight countries to
estimate the complete evolution of the infection in each of these countries.
The analysis predicts successfully both the expected number of daily infections
per country and, perhaps more importantly, the duration of the epidemic in each
country. Our quantitative approach is based on a Gaussian spreading hypothesis
that is shown to arise as a result of imposed measures in a simple dynamical
infection model. This may have consequences and shed light in the efficiency of
policies once the phenomenon is over.
| [
{
"created": "Tue, 31 Mar 2020 16:18:23 GMT",
"version": "v1"
},
{
"created": "Wed, 1 Apr 2020 16:15:51 GMT",
"version": "v2"
},
{
"created": "Mon, 6 Apr 2020 09:43:52 GMT",
"version": "v3"
},
{
"created": "Wed, 22 Apr 2020 10:57:13 GMT",
"version": "v4"
}
] | 2020-04-28 | [
[
"Barmparis",
"G. D.",
""
],
[
"Tsironis",
"G. P.",
""
]
] | The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial, and educational organization. The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees. The infection duration and number of infected persons are of critical importance for the battle against the pandemic. We use the quantitative landscape of the disease spreading in China as a benchmark and utilize infection data from eight countries to estimate the complete evolution of the infection in each of these countries. The analysis predicts successfully both the expected number of daily infections per country and, perhaps more importantly, the duration of the epidemic in each country. Our quantitative approach is based on a Gaussian spreading hypothesis that is shown to arise as a result of imposed measures in a simple dynamical infection model. This may have consequences and shed light in the efficiency of policies once the phenomenon is over. |
1402.4348 | Matthieu Foll | Matthieu Foll, Oscar E. Gaggiotti, Josephine T. Daub, Alexandra
Vatsiou and Laurent Excoffier | Widespread signals of convergent adaptation to high altitude in Asia and
America | null | null | 10.1016/j.ajhg.2014.09.002 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Living at high-altitude is one of the most difficult challenges that humans
had to cope with during their evolution. Whereas several genomic studies have
revealed some of the genetic bases of adaptations in Tibetan, Andean and
Ethiopian populations, relatively little evidence of convergent evolution to
altitude in different continents has accumulated. This lack of evidence can be
due to truly different evolutionary responses, but it can be also due to the
low power of former studies that have mainly focused on populations from a
single geographical region or performed separate analyses on multiple pairs of
populations to avoid problems linked to shared histories between some
populations. We introduce here a hierarchical Bayesian method to detect local
adaptation that can deal with complex demographic histories. Our method can
identify selection occurring at different scales, as well as convergent
adaptation in different regions. We apply our approach to the analysis of a
large SNP dataset from low- and high-altitude human populations from America
and Asia. The simultaneous analysis of these two geographic areas allows us to
identify several candidate genome regions for altitudinal selection, and we
show that convergent evolution among continents has been quite common. In
addition to identifying several genes and biological processes involved in high
altitude adaptation, we identify two specific biological pathways that could
have evolved in both continents to counter toxic effects induced by hypoxia.
| [
{
"created": "Tue, 18 Feb 2014 14:21:51 GMT",
"version": "v1"
},
{
"created": "Fri, 26 Sep 2014 12:56:53 GMT",
"version": "v2"
}
] | 2014-09-29 | [
[
"Foll",
"Matthieu",
""
],
[
"Gaggiotti",
"Oscar E.",
""
],
[
"Daub",
"Josephine T.",
""
],
[
"Vatsiou",
"Alexandra",
""
],
[
"Excoffier",
"Laurent",
""
]
] | Living at high-altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can be also due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP dataset from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia. |
2407.17420 | Brian Camley | Ifunanya Nwogbaga and Brian A. Camley | Cell shape and orientation control galvanotactic accuracy | null | null | null | null | q-bio.CB cond-mat.soft physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Galvanotaxis is believed to be driven by the redistribution of transmembrane
proteins and other molecules, referred to as "sensors", through electrophoresis
and electroosmosis. Here, we update our previous model of the limits of
galvanotaxis due to stochasticity of sensor movements to account for cell shape
and orientation. Computing the Fisher information, we find that cells in
principle possess more information about the electric field direction when
their long axis is parallel to the field, but that for weak fields
maximum-likelihood estimators of the field direction may actually have lower
variability when the cell's long axis is perpendicular to the field. In an
alternate possibility, we find that if cells instead estimate the field
direction by taking the average of all the sensor locations as its directional
cue ("vector sum"), this introduces a bias towards the short axis, an effect
not present for isotropic cells. We also explore the possibility that cell
elongation arises downstream of sensor redistribution. We argue that if sensors
migrate to the cell's rear, the cell will expand perpendicular the field - as
is more commonly observed - but if sensors migrate to the front, the cell will
elongate parallel to the field.
| [
{
"created": "Wed, 24 Jul 2024 16:57:59 GMT",
"version": "v1"
},
{
"created": "Fri, 26 Jul 2024 17:55:53 GMT",
"version": "v2"
}
] | 2024-07-29 | [
[
"Nwogbaga",
"Ifunanya",
""
],
[
"Camley",
"Brian A.",
""
]
] | Galvanotaxis is believed to be driven by the redistribution of transmembrane proteins and other molecules, referred to as "sensors", through electrophoresis and electroosmosis. Here, we update our previous model of the limits of galvanotaxis due to stochasticity of sensor movements to account for cell shape and orientation. Computing the Fisher information, we find that cells in principle possess more information about the electric field direction when their long axis is parallel to the field, but that for weak fields maximum-likelihood estimators of the field direction may actually have lower variability when the cell's long axis is perpendicular to the field. In an alternate possibility, we find that if cells instead estimate the field direction by taking the average of all the sensor locations as its directional cue ("vector sum"), this introduces a bias towards the short axis, an effect not present for isotropic cells. We also explore the possibility that cell elongation arises downstream of sensor redistribution. We argue that if sensors migrate to the cell's rear, the cell will expand perpendicular the field - as is more commonly observed - but if sensors migrate to the front, the cell will elongate parallel to the field. |
2312.09690 | Jingmeng Cui | Jingmeng Cui, Anna Lichtwarck-Aschoff, Fred Hasselman | Comments on "Climbing Escher's stairs: A way to approximate stability
landscapes in multidimensional systems" | null | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | The article under discussion, titled "Climbing Escher's stairs: A way to
approximate stability landscapes in multidimensional systems" (doi:
10.1371/journal.pcbi.1007788), has captured our attention due to important
methodological limitations that we believe warrant discussion. Our aim in
writing this Formal Comment is to bring to the attention of potential readers
and users the following key points: 1. The construction of the potential
landscape function necessitates the global integrability of the velocity
functions. However, the decomposition method outlined in this article is only
applied to the Jacobian of the velocity functions instead of the velocity
functions themselves, which leads to path-dependent integrals. Such a
characteristic is not desirable for a potential landscape function. 2. In the
article's implementation, integration is conducted along the x- and y-axes.
This approach renders the decomposition method, which primarily affects the
non-diagonal elements in the Jacobian matrix, ineffective. 3. We provide
evidence that removing the core step of the method, the decomposition process,
in the rolldown package (now renamed as waydown), results in identical output.
This finding highlights the ineffectiveness of this crucial implementation
step. 4. In our Comment, we also offer recommendations for potential
alternatives for readers interested in constructing potential landscape
functions.
| [
{
"created": "Fri, 15 Dec 2023 11:04:42 GMT",
"version": "v1"
}
] | 2023-12-18 | [
[
"Cui",
"Jingmeng",
""
],
[
"Lichtwarck-Aschoff",
"Anna",
""
],
[
"Hasselman",
"Fred",
""
]
] | The article under discussion, titled "Climbing Escher's stairs: A way to approximate stability landscapes in multidimensional systems" (doi: 10.1371/journal.pcbi.1007788), has captured our attention due to important methodological limitations that we believe warrant discussion. Our aim in writing this Formal Comment is to bring to the attention of potential readers and users the following key points: 1. The construction of the potential landscape function necessitates the global integrability of the velocity functions. However, the decomposition method outlined in this article is only applied to the Jacobian of the velocity functions instead of the velocity functions themselves, which leads to path-dependent integrals. Such a characteristic is not desirable for a potential landscape function. 2. In the article's implementation, integration is conducted along the x- and y-axes. This approach renders the decomposition method, which primarily affects the non-diagonal elements in the Jacobian matrix, ineffective. 3. We provide evidence that removing the core step of the method, the decomposition process, in the rolldown package (now renamed as waydown), results in identical output. This finding highlights the ineffectiveness of this crucial implementation step. 4. In our Comment, we also offer recommendations for potential alternatives for readers interested in constructing potential landscape functions. |
1011.3674 | Wei Li Dr. | Juergen Jost and Wei Li | Learning, evolution and population dynamics | 26 pages, 13 figures | Advances in Complex Systems 11 (6), 901-926, 2008 | null | null | q-bio.PE cs.GT physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study a complementarity game as a systematic tool for the investigation of
the interplay between individual optimization and population effects and for
the comparison of different strategy and learning schemes. The game randomly
pairs players from opposite populations. The game is symmetric at the
individual level, but has many equilibria that are more or less favorable to
the members of the two populations. Which of these equilibria then is attained
is decided by the dynamics at the population level. Players play repeatedly,
but in each round with a new opponent. They can learn from their previous
encounters and translate this into their actions in the present round on the
basis of strategic schemes. The schemes can be quite simple, or very elaborate.
We can then break the symmetry in the game and give the members of the two
populations access to different strategy spaces. Typically, simpler strategy
types have an advantage because they tend to go more quickly towards a
favorable equilibrium which, once reached, the other population is forced to
accept. Also, populations with bolder individuals that may not fare so well at
the level of individual performance may obtain an advantage towards ones with
more timid players. By checking the effects of parameters such as the
generation length or the mutation rate, we are able to compare the relative
contributions of individual learning and evolutionary adaptations.
| [
{
"created": "Tue, 16 Nov 2010 12:32:32 GMT",
"version": "v1"
}
] | 2010-11-17 | [
[
"Jost",
"Juergen",
""
],
[
"Li",
"Wei",
""
]
] | We study a complementarity game as a systematic tool for the investigation of the interplay between individual optimization and population effects and for the comparison of different strategy and learning schemes. The game randomly pairs players from opposite populations. The game is symmetric at the individual level, but has many equilibria that are more or less favorable to the members of the two populations. Which of these equilibria then is attained is decided by the dynamics at the population level. Players play repeatedly, but in each round with a new opponent. They can learn from their previous encounters and translate this into their actions in the present round on the basis of strategic schemes. The schemes can be quite simple, or very elaborate. We can then break the symmetry in the game and give the members of the two populations access to different strategy spaces. Typically, simpler strategy types have an advantage because they tend to go more quickly towards a favorable equilibrium which, once reached, the other population is forced to accept. Also, populations with bolder individuals that may not fare so well at the level of individual performance may obtain an advantage towards ones with more timid players. By checking the effects of parameters such as the generation length or the mutation rate, we are able to compare the relative contributions of individual learning and evolutionary adaptations. |
0906.1678 | Ellen Baake | Ute von Wangenheim, Ellen Baake, Michael Baake | Single--crossover recombination in discrete time | J. Math. Biol., in press | J. Math. Biol. 60 (2010), 727-760 | null | null | q-bio.PE math.DS q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Modelling the process of recombination leads to a large coupled nonlinear
dynamical system. Here, we consider a particular case of recombination in {\em
discrete} time, allowing only for {\em single crossovers}. While the analogous
dynamics in {\em continuous} time admits a closed solution, this no longer
works for discrete time. A more general model (i.e. without the restriction to
single crossovers) has been studied before and was solved algorithmically by
means of Haldane linearisation. Using the special formalism introduced by Baake
and Baake (2003), we obtain further insight into the single-crossover dynamics
and the particular difficulties that arise in discrete time. We then transform
the equations to a solvable system in a two-step procedure: linearisation
followed by diagonalisation. Still, the coefficients of the second step must be
determined in a recursive manner, but once this is done for a given system,
they allow for an explicit solution valid for all times.
| [
{
"created": "Tue, 9 Jun 2009 09:52:12 GMT",
"version": "v1"
}
] | 2011-01-12 | [
[
"von Wangenheim",
"Ute",
""
],
[
"Baake",
"Ellen",
""
],
[
"Baake",
"Michael",
""
]
] | Modelling the process of recombination leads to a large coupled nonlinear dynamical system. Here, we consider a particular case of recombination in {\em discrete} time, allowing only for {\em single crossovers}. While the analogous dynamics in {\em continuous} time admits a closed solution, this no longer works for discrete time. A more general model (i.e. without the restriction to single crossovers) has been studied before and was solved algorithmically by means of Haldane linearisation. Using the special formalism introduced by Baake and Baake (2003), we obtain further insight into the single-crossover dynamics and the particular difficulties that arise in discrete time. We then transform the equations to a solvable system in a two-step procedure: linearisation followed by diagonalisation. Still, the coefficients of the second step must be determined in a recursive manner, but once this is done for a given system, they allow for an explicit solution valid for all times. |
1111.0201 | Geraldine Celliere | Geraldine Celliere, Georgios Fengos, Marianne Herve and Dagmar Iber | The plasticity of TGF-beta signaling | 43 pages, main text, supplementary figures and supplementary tables | null | null | null | q-bio.MN q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The family of TGFb ligands is large and its members are involved in many
different signaling processes. These signaling processes strongly differ in
type with TGFb ligands eliciting both sustained or transient responses. Members
of the TGFb family can also act as morphogen and cellular responses would then
be expected to provide a direct read-out of the extracellular ligand
concentration. We were interested to define the set of minimal modifications
that are required to change the type of signal processing in the TGFb signaling
network. To define the key aspects for signaling plasticity we focused on the
core of the TGFb signaling network. With the help of a parameter screen we
identified ranges of kinetic parameters and protein concentrations that give
rise to transient, sustained, or oscillatory responses to constant stimuli, as
well as those parameter ranges that enable a proportional response to
time-varying ligand concentrations (as expected in the read-out of morphogens).
A combination of a strong negative feedback and fast shuttling to the nucleus
biases signaling to a transient rather than a sustained response, while
oscillations were obtained if ligand binding to the receptor is weak and the
turn-over of the I-Smad is fast. A proportional read-out required inefficient
receptor activation in addition to a low affinity of receptor-ligand binding.
We find that targeted modification of single parameters suffices to alter the
response type. The architecture of the TGFb pathway enables the observed
signaling plasticity. The observed range of signaling outputs to TGFb ligand in
different cell types and under different conditions can be explained with
differences in cellular protein concentrations and with changes in effective
rate constants due to cross-talk with other signaling pathways.
| [
{
"created": "Tue, 1 Nov 2011 13:34:54 GMT",
"version": "v1"
},
{
"created": "Wed, 2 Nov 2011 14:54:32 GMT",
"version": "v2"
}
] | 2015-03-19 | [
[
"Celliere",
"Geraldine",
""
],
[
"Fengos",
"Georgios",
""
],
[
"Herve",
"Marianne",
""
],
[
"Iber",
"Dagmar",
""
]
] | The family of TGFb ligands is large and its members are involved in many different signaling processes. These signaling processes strongly differ in type with TGFb ligands eliciting both sustained or transient responses. Members of the TGFb family can also act as morphogen and cellular responses would then be expected to provide a direct read-out of the extracellular ligand concentration. We were interested to define the set of minimal modifications that are required to change the type of signal processing in the TGFb signaling network. To define the key aspects for signaling plasticity we focused on the core of the TGFb signaling network. With the help of a parameter screen we identified ranges of kinetic parameters and protein concentrations that give rise to transient, sustained, or oscillatory responses to constant stimuli, as well as those parameter ranges that enable a proportional response to time-varying ligand concentrations (as expected in the read-out of morphogens). A combination of a strong negative feedback and fast shuttling to the nucleus biases signaling to a transient rather than a sustained response, while oscillations were obtained if ligand binding to the receptor is weak and the turn-over of the I-Smad is fast. A proportional read-out required inefficient receptor activation in addition to a low affinity of receptor-ligand binding. We find that targeted modification of single parameters suffices to alter the response type. The architecture of the TGFb pathway enables the observed signaling plasticity. The observed range of signaling outputs to TGFb ligand in different cell types and under different conditions can be explained with differences in cellular protein concentrations and with changes in effective rate constants due to cross-talk with other signaling pathways. |
1710.08384 | Diego Mateos | D.M. Mateos, R.Wennberg, R. Guevara, and J.L. Perez Velazquez | Consciousness as a global property of brain dynamic activity | 13 pages, 5 figures | Phys. Rev. E 96, 062410 (2017) | 10.1103/PhysRevE.96.062410 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We seek general principles of the structure of the cellular collective
activity associated with conscious awareness. Can we obtain evidence for
features of the optimal brain organization that allows for adequate processing
of stimuli and that may guide the emergence of cognition and consciousness?
Analysing brain recordings in conscious and unconscious states, we followed
initially the classic approach in physics when it comes to understanding
collective behaviours of systems composed of a myriad of units: the assessment
of the number of possible configurations (microstates) that the system can
adopt, for which we use a global entropic measure associated with the number of
connected brain regions. Having found maximal entropy in conscious states, we
then inspected the microscopic nature of the configurations of connections
using an adequate complexity measure, and found higher complexity in states
characterised not only by conscious awareness but also by subconscious
cognitive processing, such as sleep stages. Our observations indicate that
conscious awareness is associated with maximal global (macroscopic) entropy and
with the short time scale (microscopic) complexity of the configurations of
connected brain networks in pathological unconscious states (seizures and
coma), but the microscopic view captures the high complexity in physiological
unconscious states (sleep) where there is information processing. As such, our
results support the global nature of conscious awareness, as advocated by
several theories of cognition. We thus hope that our studies represent
preliminary steps to reveal aspects of the structure of cognition that leads to
conscious awareness.
| [
{
"created": "Fri, 13 Oct 2017 14:07:50 GMT",
"version": "v1"
}
] | 2017-12-27 | [
[
"Mateos",
"D. M.",
""
],
[
"Wennberg",
"R.",
""
],
[
"Guevara",
"R.",
""
],
[
"Velazquez",
"J. L. Perez",
""
]
] | We seek general principles of the structure of the cellular collective activity associated with conscious awareness. Can we obtain evidence for features of the optimal brain organization that allows for adequate processing of stimuli and that may guide the emergence of cognition and consciousness? Analysing brain recordings in conscious and unconscious states, we followed initially the classic approach in physics when it comes to understanding collective behaviours of systems composed of a myriad of units: the assessment of the number of possible configurations (microstates) that the system can adopt, for which we use a global entropic measure associated with the number of connected brain regions. Having found maximal entropy in conscious states, we then inspected the microscopic nature of the configurations of connections using an adequate complexity measure, and found higher complexity in states characterised not only by conscious awareness but also by subconscious cognitive processing, such as sleep stages. Our observations indicate that conscious awareness is associated with maximal global (macroscopic) entropy and with the short time scale (microscopic) complexity of the configurations of connected brain networks in pathological unconscious states (seizures and coma), but the microscopic view captures the high complexity in physiological unconscious states (sleep) where there is information processing. As such, our results support the global nature of conscious awareness, as advocated by several theories of cognition. We thus hope that our studies represent preliminary steps to reveal aspects of the structure of cognition that leads to conscious awareness. |
1705.08026 | Alireza Alemi | Alireza Alemi, Christian Machens, Sophie Den\`eve, Jean-Jacques
Slotine | Learning arbitrary dynamics in efficient, balanced spiking networks
using local plasticity rules | minor editorial changes | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Understanding how recurrent neural circuits can learn to implement dynamical
systems is a fundamental challenge in neuroscience. The credit assignment
problem, i.e. determining the local contribution of each synapse to the
network's global output error, is a major obstacle in deriving biologically
plausible local learning rules. Moreover, spiking recurrent networks
implementing such tasks should not be hugely costly in terms of number of
neurons and spikes, as they often are when adapted from rate models. Finally,
these networks should be robust to noise and neural deaths in order to sustain
these representations in the face of such naturally occurring perturbation. We
approach this problem by fusing the theory of efficient, balanced spiking
networks (EBN) with nonlinear adaptive control theory. Local learning rules are
ensured by feeding back into the network its own error, resulting in a synaptic
plasticity rule depending solely on presynaptic inputs and post-synaptic
feedback. The spiking efficiency and robustness of the network are guaranteed
by maintaining a tight excitatory/inhibitory balance, ensuring that each spike
represents a local projection of the global output error and minimizes a loss
function. The resulting networks can learn to implement complex dynamics with
very small numbers of neurons and spikes, exhibit the same spike train
variability as observed experimentally, and are extremely robust to noise and
neuronal loss.
| [
{
"created": "Mon, 22 May 2017 22:18:01 GMT",
"version": "v1"
},
{
"created": "Sat, 5 Aug 2017 00:28:05 GMT",
"version": "v2"
}
] | 2017-08-08 | [
[
"Alemi",
"Alireza",
""
],
[
"Machens",
"Christian",
""
],
[
"Denève",
"Sophie",
""
],
[
"Slotine",
"Jean-Jacques",
""
]
] | Understanding how recurrent neural circuits can learn to implement dynamical systems is a fundamental challenge in neuroscience. The credit assignment problem, i.e. determining the local contribution of each synapse to the network's global output error, is a major obstacle in deriving biologically plausible local learning rules. Moreover, spiking recurrent networks implementing such tasks should not be hugely costly in terms of number of neurons and spikes, as they often are when adapted from rate models. Finally, these networks should be robust to noise and neural deaths in order to sustain these representations in the face of such naturally occurring perturbation. We approach this problem by fusing the theory of efficient, balanced spiking networks (EBN) with nonlinear adaptive control theory. Local learning rules are ensured by feeding back into the network its own error, resulting in a synaptic plasticity rule depending solely on presynaptic inputs and post-synaptic feedback. The spiking efficiency and robustness of the network are guaranteed by maintaining a tight excitatory/inhibitory balance, ensuring that each spike represents a local projection of the global output error and minimizes a loss function. The resulting networks can learn to implement complex dynamics with very small numbers of neurons and spikes, exhibit the same spike train variability as observed experimentally, and are extremely robust to noise and neuronal loss. |
1307.3446 | Ozlem Tastan Bishop | Rowan Hatherley, Gregory L. Blatch and \"Ozlem Tastan Bishop | Plasmodium falciparum Hsp70-x: A Heat Shock Protein at the Host -
Parasite Interface | null | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Plasmodium falciparum 70 kDa heat shock proteins (PfHsp70s) are expressed at
all stages of the pathogenic erythrocytic phase of the malaria parasite
lifecycle. There are six PfHsp70s, all of which have orthologues in other
plasmodial species, except for PfHsp70-x which is unique to P. falciparum. This
paper highlights a number of original results obtained by a detailed
bioinformatics analysis of the protein. Large scale sequence analysis indicated
the presence of an extended transit peptide sequence of PfHsp70-x which
potentially directs it to the endoplasmic reticulum (ER). Further analysis
showed that PfHsp70-x does not have an ER-retention sequence, suggesting that
the protein transits through the ER and is secreted into the parasitophorous
vacuole (PV) or beyond into the erythrocyte cytosol. These results are
consistent with experimental findings. Next, possible interactions between
PfHsp70-x and exported P. falciparum Hsp40s or host erythrocyte DnaJs were
interrogated by modeling and docking. Docking results indicated that
interaction between PfHsp70-x and each of the Hsp40s, regardless of biological
feasibility, seems equally likely. This suggests that J domain might not
provide the specificity in the formation of unique Hsp70-Hsp40 complexes, but
that the specificity might be provided by other domains of Hsp40s. By studying
different structural conformations of PfHsp70-x, it was shown that Hsp40s can
only bind when PfHsp70-x is in a certain conformation. Additionally, this work
highlighted the possible dependence of the substrate binding domain residues on
the orientation of the {\alpha}-helical lid for formation of the substrate
binding pocket.
| [
{
"created": "Fri, 12 Jul 2013 13:04:31 GMT",
"version": "v1"
}
] | 2013-07-15 | [
[
"Hatherley",
"Rowan",
""
],
[
"Blatch",
"Gregory L.",
""
],
[
"Bishop",
"Özlem Tastan",
""
]
] | Plasmodium falciparum 70 kDa heat shock proteins (PfHsp70s) are expressed at all stages of the pathogenic erythrocytic phase of the malaria parasite lifecycle. There are six PfHsp70s, all of which have orthologues in other plasmodial species, except for PfHsp70-x which is unique to P. falciparum. This paper highlights a number of original results obtained by a detailed bioinformatics analysis of the protein. Large scale sequence analysis indicated the presence of an extended transit peptide sequence of PfHsp70-x which potentially directs it to the endoplasmic reticulum (ER). Further analysis showed that PfHsp70-x does not have an ER-retention sequence, suggesting that the protein transits through the ER and is secreted into the parasitophorous vacuole (PV) or beyond into the erythrocyte cytosol. These results are consistent with experimental findings. Next, possible interactions between PfHsp70-x and exported P. falciparum Hsp40s or host erythrocyte DnaJs were interrogated by modeling and docking. Docking results indicated that interaction between PfHsp70-x and each of the Hsp40s, regardless of biological feasibility, seems equally likely. This suggests that J domain might not provide the specificity in the formation of unique Hsp70-Hsp40 complexes, but that the specificity might be provided by other domains of Hsp40s. By studying different structural conformations of PfHsp70-x, it was shown that Hsp40s can only bind when PfHsp70-x is in a certain conformation. Additionally, this work highlighted the possible dependence of the substrate binding domain residues on the orientation of the {\alpha}-helical lid for formation of the substrate binding pocket. |
2006.05194 | Akiva Bruno Melka | Akiva B. Melka and Yoram Louzoun | Evaluation of the number of undiagnosed infected in an outbreak using
source of infection measurements | null | Sci Rep 11, 3601 (2021) | 10.1038/s41598-021-82691-6 | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In times of outbreaks, an essential requirement for better monitoring is the
evaluation of the number of undiagnosed infected individuals. An accurate
estimate of this fraction is crucial for the assessment of the situation and
the establishment of protective measures. In most current studies using
epidemics models, the total number of infected is either approximated by the
number of diagnosed individuals or is dependent on the model parameters and
assumptions, which are often debated. We here study the relationship between
the fraction of diagnosed infected out of all infected, and the fraction of
infected with known contaminator out of all diagnosed infected. We show that
those two are approximately the same in exponential models and across most
models currently used in the study of epidemics, independently of the model
parameters. As an application, we compute an estimate of the effective number
of infected by the SARS-CoV-2 virus in various countries.
| [
{
"created": "Tue, 9 Jun 2020 11:43:13 GMT",
"version": "v1"
},
{
"created": "Sun, 14 Jun 2020 10:00:49 GMT",
"version": "v2"
},
{
"created": "Wed, 2 Sep 2020 09:43:14 GMT",
"version": "v3"
},
{
"created": "Sun, 14 Mar 2021 11:45:07 GMT",
"version": "v4"
},
{
"created": "Tue, 16 Mar 2021 08:26:25 GMT",
"version": "v5"
}
] | 2021-03-17 | [
[
"Melka",
"Akiva B.",
""
],
[
"Louzoun",
"Yoram",
""
]
] | In times of outbreaks, an essential requirement for better monitoring is the evaluation of the number of undiagnosed infected individuals. An accurate estimate of this fraction is crucial for the assessment of the situation and the establishment of protective measures. In most current studies using epidemics models, the total number of infected is either approximated by the number of diagnosed individuals or is dependent on the model parameters and assumptions, which are often debated. We here study the relationship between the fraction of diagnosed infected out of all infected, and the fraction of infected with known contaminator out of all diagnosed infected. We show that those two are approximately the same in exponential models and across most models currently used in the study of epidemics, independently of the model parameters. As an application, we compute an estimate of the effective number of infected by the SARS-CoV-2 virus in various countries. |
2107.12078 | Sergei Grudinin | Dmitrii Zhemchuzhnikov (DAO), Ilia Igashov (DAO), Sergei Grudinin
(DAO) | 6DCNN with roto-translational convolution filters for volumetric data
processing | null | null | null | null | q-bio.QM cs.LG eess.SP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work, we introduce 6D Convolutional Neural Network (6DCNN) designed
to tackle the problem of detecting relative positions and orientations of local
patterns when processing three-dimensional volumetric data. 6DCNN also includes
SE(3)-equivariant message-passing and nonlinear activation operations
constructed in the Fourier space. Working in the Fourier space allows
significantly reducing the computational complexity of our operations. We
demonstrate the properties of the 6D convolution and its efficiency in the
recognition of spatial patterns. We also assess the 6DCNN model on several
datasets from the recent CASP protein structure prediction challenges. Here,
6DCNN improves over the baseline architecture and also outperforms the state of
the art.
| [
{
"created": "Mon, 26 Jul 2021 09:56:55 GMT",
"version": "v1"
},
{
"created": "Fri, 30 Jul 2021 08:04:05 GMT",
"version": "v2"
}
] | 2021-08-02 | [
[
"Zhemchuzhnikov",
"Dmitrii",
"",
"DAO"
],
[
"Igashov",
"Ilia",
"",
"DAO"
],
[
"Grudinin",
"Sergei",
"",
"DAO"
]
] | In this work, we introduce 6D Convolutional Neural Network (6DCNN) designed to tackle the problem of detecting relative positions and orientations of local patterns when processing three-dimensional volumetric data. 6DCNN also includes SE(3)-equivariant message-passing and nonlinear activation operations constructed in the Fourier space. Working in the Fourier space allows significantly reducing the computational complexity of our operations. We demonstrate the properties of the 6D convolution and its efficiency in the recognition of spatial patterns. We also assess the 6DCNN model on several datasets from the recent CASP protein structure prediction challenges. Here, 6DCNN improves over the baseline architecture and also outperforms the state of the art. |
1807.03241 | Na Liu | Na Liu, Tormod Skauge, David Landa-Marban, Beate Hovland, Bente
Thorbjornsen, Florin Adrain Radu, Bartek Florczyk Vik, Thomas Baumann,
Gunhild Bodtker | Microfluidic study of effects of flow velocity and nutrient
concentration on biofilm accumulation and adhesive strength in a microchannel | 14 pages, 5 figures | null | null | null | q-bio.CB physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Biofilm accumulation in the porous media can cause plugging and change many
physical properties of porous media. Targeted bioplugging may have significant
applications for industrial processes. A deeper understanding of the relative
influences of hydrodynamic conditions including flow velocity and nutrient
concentration, on biofilm growth and detachment is necessary to plan and
analyze bioplugging experiments and field trials. The experimental results by
means of microscopic imaging over a T-shape microchannel show that increase in
fluid velocity could facilitate biofilm growth, but that above a velocity
threshold, biofilm detachment and inhibition of biofilm formation due to high
shear stress were observed. High nutrient concentration prompts the biofilm
growth, but was accompanied by a relatively weak adhesive strength. This letter
provides an overview of biofilm development in a hydrodynamic environment for
better predicting and modelling the bioplugging associated with porous system
in petroleum industry, hydrogeology, and water purification.
| [
{
"created": "Mon, 9 Jul 2018 15:40:59 GMT",
"version": "v1"
}
] | 2018-07-10 | [
[
"Liu",
"Na",
""
],
[
"Skauge",
"Tormod",
""
],
[
"Landa-Marban",
"David",
""
],
[
"Hovland",
"Beate",
""
],
[
"Thorbjornsen",
"Bente",
""
],
[
"Radu",
"Florin Adrain",
""
],
[
"Vik",
"Bartek Florczyk",
""
],
[
"Baumann",
"Thomas",
""
],
[
"Bodtker",
"Gunhild",
""
]
] | Biofilm accumulation in the porous media can cause plugging and change many physical properties of porous media. Targeted bioplugging may have significant applications for industrial processes. A deeper understanding of the relative influences of hydrodynamic conditions including flow velocity and nutrient concentration, on biofilm growth and detachment is necessary to plan and analyze bioplugging experiments and field trials. The experimental results by means of microscopic imaging over a T-shape microchannel show that increase in fluid velocity could facilitate biofilm growth, but that above a velocity threshold, biofilm detachment and inhibition of biofilm formation due to high shear stress were observed. High nutrient concentration prompts the biofilm growth, but was accompanied by a relatively weak adhesive strength. This letter provides an overview of biofilm development in a hydrodynamic environment for better predicting and modelling the bioplugging associated with porous system in petroleum industry, hydrogeology, and water purification. |
1812.09566 | BingKan Xue | BingKan Xue, Pablo Sartori, Stanislas Leibler | Geometry of environment-to-phenotype mapping: Unifying adaptation
strategies in varying environments | 12 pages, plus supplemental figures | null | 10.1073/pnas.1903232116 | null | q-bio.PE physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Biological organisms exhibit diverse strategies for adapting to varying
environments. For example, a population of organisms may express the same
phenotype in all environments (`unvarying strategy'), or follow environmental
cues and express alternative phenotypes to match the environment (`tracking
strategy'), or diversify into coexisting phenotypes to cope with environmental
uncertainty (`bet-hedging strategy'). We introduce a general framework for
studying how organisms respond to environmental variations, which models an
adaptation strategy by an abstract mapping from environmental cues to
phenotypic traits. Depending on the accuracy of environmental cues and the
strength of natural selection, we find different adaptation strategies
represented by mappings that maximize the longterm growth rate of a population.
The previously studied strategies emerge as special cases of our model: the
tracking strategy is favorable when environmental cues are accurate, whereas
when cues are noisy, organisms can either use an unvarying strategy or,
remarkably, use the uninformative cue as a source of randomness to bet-hedge.
Our model of the environment-to-phenotype mapping is based on a network with
hidden units; the performance of the strategies is shown to rely on having a
high-dimensional internal representation, which can even be random.
| [
{
"created": "Sat, 22 Dec 2018 17:07:47 GMT",
"version": "v1"
},
{
"created": "Tue, 16 Apr 2019 16:45:08 GMT",
"version": "v2"
}
] | 2022-06-08 | [
[
"Xue",
"BingKan",
""
],
[
"Sartori",
"Pablo",
""
],
[
"Leibler",
"Stanislas",
""
]
] | Biological organisms exhibit diverse strategies for adapting to varying environments. For example, a population of organisms may express the same phenotype in all environments (`unvarying strategy'), or follow environmental cues and express alternative phenotypes to match the environment (`tracking strategy'), or diversify into coexisting phenotypes to cope with environmental uncertainty (`bet-hedging strategy'). We introduce a general framework for studying how organisms respond to environmental variations, which models an adaptation strategy by an abstract mapping from environmental cues to phenotypic traits. Depending on the accuracy of environmental cues and the strength of natural selection, we find different adaptation strategies represented by mappings that maximize the longterm growth rate of a population. The previously studied strategies emerge as special cases of our model: the tracking strategy is favorable when environmental cues are accurate, whereas when cues are noisy, organisms can either use an unvarying strategy or, remarkably, use the uninformative cue as a source of randomness to bet-hedge. Our model of the environment-to-phenotype mapping is based on a network with hidden units; the performance of the strategies is shown to rely on having a high-dimensional internal representation, which can even be random. |
1408.2085 | Tobias Reichenbach | T. Reichenbach, A. J. Hudspeth | The physics of hearing: fluid mechanics and the active process of the
inner ear | 86 pages, 24 figures | Rep. Progr. Phys. 77:7 (2014) | 10.1088/0034-4885/77/7/076601 | null | q-bio.NC nlin.AO physics.bio-ph q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Most sounds of interest consist of complex, time-dependent admixtures of
tones of diverse frequencies and variable amplitudes. To detect and process
these signals, the ear employs a highly nonlinear, adaptive, real-time spectral
analyzer: the cochlea. Sound excites vibration of the eardrum and the three
miniscule bones of the middle ear, the last of which acts as a piston to
initiate oscillatory pressure changes within the liquid-filled chambers of the
cochlea. The basilar membrane, an elastic band spiraling along the cochlea
between two of these chambers, responds to these pressures by conducting a
largely independent traveling wave for each frequency component of the input.
Because the basilar membrane is graded in mass and stiffness along its length,
however, each traveling wave grows in magnitude and decreases in wavelength
until it peaks at a specific, frequency-dependent position: low frequencies
propagate to the cochlear apex, whereas high frequencies culminate at the base.
The oscillations of the basilar membrane deflect hair bundles, the mechanically
sensitive organelles of the ear's sensory receptors, the hair cells. As
mechanically sensitive ion channels open and close, each hair cell responds
with an electrical signal that is chemically transmitted to an afferent nerve
fiber and thence into the brain. In addition to transducing mechanical inputs,
hair cells amplify them [...]
| [
{
"created": "Sat, 9 Aug 2014 12:09:27 GMT",
"version": "v1"
}
] | 2014-08-12 | [
[
"Reichenbach",
"T.",
""
],
[
"Hudspeth",
"A. J.",
""
]
] | Most sounds of interest consist of complex, time-dependent admixtures of tones of diverse frequencies and variable amplitudes. To detect and process these signals, the ear employs a highly nonlinear, adaptive, real-time spectral analyzer: the cochlea. Sound excites vibration of the eardrum and the three miniscule bones of the middle ear, the last of which acts as a piston to initiate oscillatory pressure changes within the liquid-filled chambers of the cochlea. The basilar membrane, an elastic band spiraling along the cochlea between two of these chambers, responds to these pressures by conducting a largely independent traveling wave for each frequency component of the input. Because the basilar membrane is graded in mass and stiffness along its length, however, each traveling wave grows in magnitude and decreases in wavelength until it peaks at a specific, frequency-dependent position: low frequencies propagate to the cochlear apex, whereas high frequencies culminate at the base. The oscillations of the basilar membrane deflect hair bundles, the mechanically sensitive organelles of the ear's sensory receptors, the hair cells. As mechanically sensitive ion channels open and close, each hair cell responds with an electrical signal that is chemically transmitted to an afferent nerve fiber and thence into the brain. In addition to transducing mechanical inputs, hair cells amplify them [...] |
2001.05158 | Pargorn Puttapirat | Pargorn Puttapirat, Haichuan Zhang, Jingyi Deng, Yuxin Dong, Jiangbo
Shi, Hongyu He, Zeyu Gao, Chunbao Wang, Xiangrong Zhang, Chen Li | OpenHI2 -- Open source histopathological image platform | Preprint version accepted to AIPath2019 workshop at BIBM2019. 6
pages, 3 figures, 2 tables | null | null | null | q-bio.QM cs.CV cs.NI eess.IV | http://creativecommons.org/licenses/by/4.0/ | Transition from conventional to digital pathology requires a new category of
biomedical informatic infrastructure which could facilitate delicate
pathological routine. Pathological diagnoses are sensitive to many external
factors and is known to be subjective. Only systems that can meet strict
requirements in pathology would be able to run along pathological routines and
eventually digitized the study area, and the developed platform should comply
with existing pathological routines and international standards. Currently,
there are a number of available software tools which can perform
histopathological tasks including virtual slide viewing, annotating, and basic
image analysis, however, none of them can serve as a digital platform for
pathology. Here we describe OpenHI2, an enhanced version Open Histopathological
Image platform which is capable of supporting all basic pathological tasks and
file formats; ready to be deployed in medical institutions on a standard server
environment or cloud computing infrastructure. In this paper, we also describe
the development decisions for the platform and propose solutions to overcome
technical challenges so that OpenHI2 could be used as a platform for
histopathological images. Further addition can be made to the platform since
each component is modularized and fully documented. OpenHI2 is free,
open-source, and available at https://gitlab.com/BioAI/OpenHI.
| [
{
"created": "Wed, 15 Jan 2020 07:29:29 GMT",
"version": "v1"
}
] | 2020-01-16 | [
[
"Puttapirat",
"Pargorn",
""
],
[
"Zhang",
"Haichuan",
""
],
[
"Deng",
"Jingyi",
""
],
[
"Dong",
"Yuxin",
""
],
[
"Shi",
"Jiangbo",
""
],
[
"He",
"Hongyu",
""
],
[
"Gao",
"Zeyu",
""
],
[
"Wang",
"Chunbao",
""
],
[
"Zhang",
"Xiangrong",
""
],
[
"Li",
"Chen",
""
]
] | Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological diagnoses are sensitive to many external factors and is known to be subjective. Only systems that can meet strict requirements in pathology would be able to run along pathological routines and eventually digitized the study area, and the developed platform should comply with existing pathological routines and international standards. Currently, there are a number of available software tools which can perform histopathological tasks including virtual slide viewing, annotating, and basic image analysis, however, none of them can serve as a digital platform for pathology. Here we describe OpenHI2, an enhanced version Open Histopathological Image platform which is capable of supporting all basic pathological tasks and file formats; ready to be deployed in medical institutions on a standard server environment or cloud computing infrastructure. In this paper, we also describe the development decisions for the platform and propose solutions to overcome technical challenges so that OpenHI2 could be used as a platform for histopathological images. Further addition can be made to the platform since each component is modularized and fully documented. OpenHI2 is free, open-source, and available at https://gitlab.com/BioAI/OpenHI. |
1212.4733 | Alexey Mazur K | Alexey K. Mazur | Comments on "Length scale dependence of DNA mechanical properties" | Revised version to appear in Phys. Rev. Lett | Phys. Rev. Lett. 111, 179801 (2013) [2 pages] | 10.1103/PhysRevLett.111.179801 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent experimental data indicate that the elastic wormlike rod model of DNA
that works well on long length scales may break down on shorter scales relevant
to biology. According to Noy and Golestanian (Phys. Rev. Lett. 109, 228101,
2012) molecular dynamics (MD) simulations predict DNA rigidity close to
experimental data and confirm one scenario of such breakdown, namely, that for
lengths of a few helical turns, DNA dynamics exhibit long-range bending and
stretching correlations. Earlier studies using similar forcefields concluded
that (i) MD systematically overestimate the DNA rigidity, and (ii) no
deviations from the WLR model are detectable. Here it is argued that the data
analysis in the above mentioned paper was incorrect and that the earlier
conclusions are valid.
| [
{
"created": "Wed, 19 Dec 2012 16:49:30 GMT",
"version": "v1"
},
{
"created": "Wed, 18 Sep 2013 08:30:39 GMT",
"version": "v2"
}
] | 2013-11-12 | [
[
"Mazur",
"Alexey K.",
""
]
] | Recent experimental data indicate that the elastic wormlike rod model of DNA that works well on long length scales may break down on shorter scales relevant to biology. According to Noy and Golestanian (Phys. Rev. Lett. 109, 228101, 2012) molecular dynamics (MD) simulations predict DNA rigidity close to experimental data and confirm one scenario of such breakdown, namely, that for lengths of a few helical turns, DNA dynamics exhibit long-range bending and stretching correlations. Earlier studies using similar forcefields concluded that (i) MD systematically overestimate the DNA rigidity, and (ii) no deviations from the WLR model are detectable. Here it is argued that the data analysis in the above mentioned paper was incorrect and that the earlier conclusions are valid. |
2401.17174 | Alex Golts | Alex Golts, Vadim Ratner, Yoel Shoshan, Moshe Raboh, Sagi Polaczek,
Michal Ozery-Flato, Daniel Shats, Liam Hazan, Sivan Ravid, Efrat Hexter | A large dataset curation and benchmark for drug target interaction | null | null | null | null | q-bio.BM cs.LG | http://creativecommons.org/licenses/by-sa/4.0/ | Bioactivity data plays a key role in drug discovery and repurposing. The
resource-demanding nature of \textit{in vitro} and \textit{in vivo}
experiments, as well as the recent advances in data-driven computational
biochemistry research, highlight the importance of \textit{in silico} drug
target interaction (DTI) prediction approaches. While numerous large public
bioactivity data sources exist, research in the field could benefit from better
standardization of existing data resources. At present, different research
works that share similar goals are often difficult to compare properly because
of different choices of data sources and train/validation/test split
strategies. Additionally, many works are based on small data subsets, leading
to results and insights of possible limited validity. In this paper we propose
a way to standardize and represent efficiently a very large dataset curated
from multiple public sources, split the data into train, validation and test
sets based on different meaningful strategies, and provide a concrete
evaluation protocol to accomplish a benchmark. We analyze the proposed data
curation, prove its usefulness and validate the proposed benchmark through
experimental studies based on an existing neural network model.
| [
{
"created": "Tue, 30 Jan 2024 17:06:25 GMT",
"version": "v1"
}
] | 2024-01-31 | [
[
"Golts",
"Alex",
""
],
[
"Ratner",
"Vadim",
""
],
[
"Shoshan",
"Yoel",
""
],
[
"Raboh",
"Moshe",
""
],
[
"Polaczek",
"Sagi",
""
],
[
"Ozery-Flato",
"Michal",
""
],
[
"Shats",
"Daniel",
""
],
[
"Hazan",
"Liam",
""
],
[
"Ravid",
"Sivan",
""
],
[
"Hexter",
"Efrat",
""
]
] | Bioactivity data plays a key role in drug discovery and repurposing. The resource-demanding nature of \textit{in vitro} and \textit{in vivo} experiments, as well as the recent advances in data-driven computational biochemistry research, highlight the importance of \textit{in silico} drug target interaction (DTI) prediction approaches. While numerous large public bioactivity data sources exist, research in the field could benefit from better standardization of existing data resources. At present, different research works that share similar goals are often difficult to compare properly because of different choices of data sources and train/validation/test split strategies. Additionally, many works are based on small data subsets, leading to results and insights of possible limited validity. In this paper we propose a way to standardize and represent efficiently a very large dataset curated from multiple public sources, split the data into train, validation and test sets based on different meaningful strategies, and provide a concrete evaluation protocol to accomplish a benchmark. We analyze the proposed data curation, prove its usefulness and validate the proposed benchmark through experimental studies based on an existing neural network model. |
2211.14718 | Hirokuni Miyamoto | Shunnosuke Okada, Yudai Inabu, Hirokuni Miyamoto, Kenta Suzuki,
Tamotsu Kato, Atsushi Kurotani, Yutaka Taguchi, Ryoichi Fujino, Yuji
Shiotsuka, Tetsuji Etoh, Naoko Tsuji, Makiko Matsuura, Arisa Tsuboi, Akira
Saito, Hiroshi Masuya, Jun Kikuchi, Hiroshi Ohno, Hideyuki Takahashi | Antibiotic-dependent instability of homeostatic plasticity for growth
and environmental load | null | null | 10.1038/s41598-023-33444-0 | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Reducing antibiotic usage in livestock animals has become an urgent issue
worldwide to prevent antimicrobial resistance. Here, abuse of chlortetracycline
(CTC), a versatile antibacterial agent, on the performance, blood components,
fecal microbiota, and organic acid concentration in calves was investigated.
Japanese Black calves were fed milk replacer containing CTC at 10 g/kg (CON) or
0 g/kg (EXP). Growth performance was not affected by CTC administration.
However, CTC administration altered the correlation between fecal organic acids
and bacterial genera. Machine learning methods such as association analysis,
linear discriminant analysis, and energy landscape analysis revealed that CTC
administration affected according to certain rules the population of various
types of fecal bacteria. It is particularly interesting that the population of
several methane-producing bacteria was high in the CON, and that of
Lachnospiraceae, a butyrate-producing bacteria, was high in the EXP at 60 d of
age. Furthermore, statistical causal inference based on machine learning data
estimated that CTC treatment affects the entire intestinal environment,
inhibiting butyrate production for growth and biological defense, which may be
attributed to methanogens in feces. Thus, these observations highlight the
multiple harmful impacts of antibiotics on intestinal health and the potential
production of greenhouse gas in the calves.
| [
{
"created": "Sun, 27 Nov 2022 04:10:47 GMT",
"version": "v1"
},
{
"created": "Thu, 20 Apr 2023 03:40:36 GMT",
"version": "v2"
}
] | 2023-04-21 | [
[
"Okada",
"Shunnosuke",
""
],
[
"Inabu",
"Yudai",
""
],
[
"Miyamoto",
"Hirokuni",
""
],
[
"Suzuki",
"Kenta",
""
],
[
"Kato",
"Tamotsu",
""
],
[
"Kurotani",
"Atsushi",
""
],
[
"Taguchi",
"Yutaka",
""
],
[
"Fujino",
"Ryoichi",
""
],
[
"Shiotsuka",
"Yuji",
""
],
[
"Etoh",
"Tetsuji",
""
],
[
"Tsuji",
"Naoko",
""
],
[
"Matsuura",
"Makiko",
""
],
[
"Tsuboi",
"Arisa",
""
],
[
"Saito",
"Akira",
""
],
[
"Masuya",
"Hiroshi",
""
],
[
"Kikuchi",
"Jun",
""
],
[
"Ohno",
"Hiroshi",
""
],
[
"Takahashi",
"Hideyuki",
""
]
] | Reducing antibiotic usage in livestock animals has become an urgent issue worldwide to prevent antimicrobial resistance. Here, abuse of chlortetracycline (CTC), a versatile antibacterial agent, on the performance, blood components, fecal microbiota, and organic acid concentration in calves was investigated. Japanese Black calves were fed milk replacer containing CTC at 10 g/kg (CON) or 0 g/kg (EXP). Growth performance was not affected by CTC administration. However, CTC administration altered the correlation between fecal organic acids and bacterial genera. Machine learning methods such as association analysis, linear discriminant analysis, and energy landscape analysis revealed that CTC administration affected according to certain rules the population of various types of fecal bacteria. It is particularly interesting that the population of several methane-producing bacteria was high in the CON, and that of Lachnospiraceae, a butyrate-producing bacteria, was high in the EXP at 60 d of age. Furthermore, statistical causal inference based on machine learning data estimated that CTC treatment affects the entire intestinal environment, inhibiting butyrate production for growth and biological defense, which may be attributed to methanogens in feces. Thus, these observations highlight the multiple harmful impacts of antibiotics on intestinal health and the potential production of greenhouse gas in the calves. |
2210.16062 | Patrick Krauss | Paul Stoewer, Achim Schilling, Andreas Maier, Patrick Krauss | Neural Network based Formation of Cognitive Maps of Semantic Spaces and
the Emergence of Abstract Concepts | null | null | null | null | q-bio.NC cs.AI cs.CL | http://creativecommons.org/licenses/by-nc-nd/4.0/ | The hippocampal-entorhinal complex plays a major role in the organization of
memory and thought. The formation of and navigation in cognitive maps of
arbitrary mental spaces via place and grid cells can serve as a representation
of memories and experiences and their relations to each other. The multi-scale
successor representation is proposed to be the mathematical principle
underlying place and grid cell computations. Here, we present a neural network,
which learns a cognitive map of a semantic space based on 32 different animal
species encoded as feature vectors. The neural network successfully learns the
similarities between different animal species, and constructs a cognitive map
of 'animal space' based on the principle of successor representations with an
accuracy of around 30% which is near to the theoretical maximum regarding the
fact that all animal species have more than one possible successor, i.e.
nearest neighbor in feature space. Furthermore, a hierarchical structure, i.e.
different scales of cognitive maps, can be modeled based on multi-scale
successor representations. We find that, in fine-grained cognitive maps, the
animal vectors are evenly distributed in feature space. In contrast, in
coarse-grained maps, animal vectors are highly clustered according to their
biological class, i.e. amphibians, mammals and insects. This could be a
possible mechanism explaining the emergence of new abstract semantic concepts.
Finally, even completely new or incomplete input can be represented by
interpolation of the representations from the cognitive map with remarkable
high accuracy of up to 95%. We conclude that the successor representation can
serve as a weighted pointer to past memories and experiences, and may therefore
be a crucial building block for future machine learning to include prior
knowledge, and to derive context knowledge from novel input.
| [
{
"created": "Fri, 28 Oct 2022 11:16:33 GMT",
"version": "v1"
}
] | 2022-10-31 | [
[
"Stoewer",
"Paul",
""
],
[
"Schilling",
"Achim",
""
],
[
"Maier",
"Andreas",
""
],
[
"Krauss",
"Patrick",
""
]
] | The hippocampal-entorhinal complex plays a major role in the organization of memory and thought. The formation of and navigation in cognitive maps of arbitrary mental spaces via place and grid cells can serve as a representation of memories and experiences and their relations to each other. The multi-scale successor representation is proposed to be the mathematical principle underlying place and grid cell computations. Here, we present a neural network, which learns a cognitive map of a semantic space based on 32 different animal species encoded as feature vectors. The neural network successfully learns the similarities between different animal species, and constructs a cognitive map of 'animal space' based on the principle of successor representations with an accuracy of around 30% which is near to the theoretical maximum regarding the fact that all animal species have more than one possible successor, i.e. nearest neighbor in feature space. Furthermore, a hierarchical structure, i.e. different scales of cognitive maps, can be modeled based on multi-scale successor representations. We find that, in fine-grained cognitive maps, the animal vectors are evenly distributed in feature space. In contrast, in coarse-grained maps, animal vectors are highly clustered according to their biological class, i.e. amphibians, mammals and insects. This could be a possible mechanism explaining the emergence of new abstract semantic concepts. Finally, even completely new or incomplete input can be represented by interpolation of the representations from the cognitive map with remarkable high accuracy of up to 95%. We conclude that the successor representation can serve as a weighted pointer to past memories and experiences, and may therefore be a crucial building block for future machine learning to include prior knowledge, and to derive context knowledge from novel input. |
1402.5332 | Danko Nikolic | Danko Nikoli\'c | Practopoiesis: Or how life fosters a mind | Revised version in response to reviewer comments | (2015) Journal of Theoretical Biology Volume 373, 21 May 2015,
Pages 40-61 | 10.1016/j.jtbi.2015.03.003 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The mind is a biological phenomenon. Thus, biological principles of
organization should also be the principles underlying mental operations.
Practopoiesis states that the key for achieving intelligence through adaptation
is an arrangement in which mechanisms laying a lower level of organization, by
their operations and interaction with the environment, enable creation of
mechanisms lying at a higher level of organization. When such an organizational
advance of a system occurs, it is called a traverse. A case of traverse is when
plasticity mechanisms (at a lower level of organization), by their operations,
create a neural network anatomy (at a higher level of organization). Another
case is the actual production of behavior by that network, whereby the
mechanisms of neuronal activity operate to create motor actions. Practopoietic
theory explains why the adaptability of a system increases with each increase
in the number of traverses. With a larger number of traverses, a system can be
relatively small and yet, produce a higher degree of adaptive/intelligent
behavior than a system with a lower number of traverses. The present analyses
indicate that the two well-known traverses-neural plasticity and neural
activity-are not sufficient to explain human mental capabilities. At least one
additional traverse is needed, which is named anapoiesis for its contribution
in reconstructing knowledge e.g., from long-term memory into working memory.
The conclusions bear implications for brain theory, the mind-body explanatory
gap, and developments of artificial intelligence technologies.
| [
{
"created": "Thu, 20 Feb 2014 09:17:32 GMT",
"version": "v1"
},
{
"created": "Mon, 24 Feb 2014 18:45:27 GMT",
"version": "v2"
},
{
"created": "Wed, 26 Feb 2014 21:20:58 GMT",
"version": "v3"
},
{
"created": "Fri, 4 Apr 2014 18:22:35 GMT",
"version": "v4"
},
{
"created": "Wed, 17 Dec 2014 18:21:51 GMT",
"version": "v5"
}
] | 2015-05-11 | [
[
"Nikolić",
"Danko",
""
]
] | The mind is a biological phenomenon. Thus, biological principles of organization should also be the principles underlying mental operations. Practopoiesis states that the key for achieving intelligence through adaptation is an arrangement in which mechanisms laying a lower level of organization, by their operations and interaction with the environment, enable creation of mechanisms lying at a higher level of organization. When such an organizational advance of a system occurs, it is called a traverse. A case of traverse is when plasticity mechanisms (at a lower level of organization), by their operations, create a neural network anatomy (at a higher level of organization). Another case is the actual production of behavior by that network, whereby the mechanisms of neuronal activity operate to create motor actions. Practopoietic theory explains why the adaptability of a system increases with each increase in the number of traverses. With a larger number of traverses, a system can be relatively small and yet, produce a higher degree of adaptive/intelligent behavior than a system with a lower number of traverses. The present analyses indicate that the two well-known traverses-neural plasticity and neural activity-are not sufficient to explain human mental capabilities. At least one additional traverse is needed, which is named anapoiesis for its contribution in reconstructing knowledge e.g., from long-term memory into working memory. The conclusions bear implications for brain theory, the mind-body explanatory gap, and developments of artificial intelligence technologies. |
1702.02873 | Xavier Navarro-Sune | X. Navarro, F. Por\'ee, M. Kuchenbuch, M. Chavez, A. Beuch\'ee, G.
Carrault | Multi-feature classifiers for burst detection in single EEG channels
from preterm infants | 11 pages, 5 figures. Table 1 in the last page | null | 10.1088/1741-2552/aa714a | null | q-bio.NC cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The study of electroencephalographic (EEG) bursts in preterm infants provides
valuable information about maturation or prognostication after perinatal
asphyxia. Over the last two decades, a number of works proposed algorithms to
automatically detect EEG bursts in preterm infants, but they were designed for
populations under 35 weeks of post menstrual age (PMA). However, as the brain
activity evolves rapidly during postnatal life, these solutions might be
under-performing with increasing PMA. In this work we focused on preterm
infants reaching term ages (PMA $\geq$ 36 weeks) using multi-feature
classification on a single EEG channel. Five EEG burst detectors relying on
different machine learning approaches were compared: Logistic regression (LR),
linear discriminant analysis (LDA), k-nearest neighbors (kNN), support vector
machines (SVM) and thresholding (Th). Classifiers were trained by visually
labeled EEG recordings from 14 very preterm infants (born after 28 weeks of
gestation) with 36 - 41 weeks PMA. The most performing classifiers reached
about 95\% accuracy (kNN, SVM and LR) whereas Th obtained 84\%. Compared to
human-automatic agreements, LR provided the highest scores (Cohen's kappa =
0.71) and the best computational efficiency using only three EEG features.
Applying this classifier in a test database of 21 infants $\geq$ 36 weeks PMA,
we show that long EEG bursts and short inter-bust periods are characteristic of
infants with the highest PMA and weights. In view of these results, LR-based
burst detection could be a suitable tool to study maturation in monitoring or
portable devices using a single EEG channel.
| [
{
"created": "Wed, 8 Feb 2017 09:58:49 GMT",
"version": "v1"
}
] | 2017-06-02 | [
[
"Navarro",
"X.",
""
],
[
"Porée",
"F.",
""
],
[
"Kuchenbuch",
"M.",
""
],
[
"Chavez",
"M.",
""
],
[
"Beuchée",
"A.",
""
],
[
"Carrault",
"G.",
""
]
] | The study of electroencephalographic (EEG) bursts in preterm infants provides valuable information about maturation or prognostication after perinatal asphyxia. Over the last two decades, a number of works proposed algorithms to automatically detect EEG bursts in preterm infants, but they were designed for populations under 35 weeks of post menstrual age (PMA). However, as the brain activity evolves rapidly during postnatal life, these solutions might be under-performing with increasing PMA. In this work we focused on preterm infants reaching term ages (PMA $\geq$ 36 weeks) using multi-feature classification on a single EEG channel. Five EEG burst detectors relying on different machine learning approaches were compared: Logistic regression (LR), linear discriminant analysis (LDA), k-nearest neighbors (kNN), support vector machines (SVM) and thresholding (Th). Classifiers were trained by visually labeled EEG recordings from 14 very preterm infants (born after 28 weeks of gestation) with 36 - 41 weeks PMA. The most performing classifiers reached about 95\% accuracy (kNN, SVM and LR) whereas Th obtained 84\%. Compared to human-automatic agreements, LR provided the highest scores (Cohen's kappa = 0.71) and the best computational efficiency using only three EEG features. Applying this classifier in a test database of 21 infants $\geq$ 36 weeks PMA, we show that long EEG bursts and short inter-bust periods are characteristic of infants with the highest PMA and weights. In view of these results, LR-based burst detection could be a suitable tool to study maturation in monitoring or portable devices using a single EEG channel. |
2202.11930 | Dhaker Kroumi | Dhaker Kroumi and Sabin Lessard | Average abundancy of cooperation in multi-player games with random
payoffs | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-nd/4.0/ | We consider interactions between players in groups of size $d\geq2$ with
payoffs that not only depend on the strategies used in the group but also
fluctuate at random over time. An individual can adopt either cooperation or
defection as strategy and the population is updated from one-time step to the
next by a birth-death event according to a Moran model. Assuming recurrent
symmetric mutation and payoffs with expected values, variances, and covariances
of the same small order, we derive a first-order approximation of the average
abundance of cooperation in the selection-mutation equilibrium. We show that
increasing the variance of any payoff for defection or decreasing the variance
of any payoff for cooperation increases the average abundance of cooperation.
As for the effect of the covariance between any payoff for cooperation and any
payoff for defection, we show that it depends on the number of cooperators in
the group associated with these payoffs. We study in particular the public
goods game, the stag hunt game, and the snowdrift game, all social dilemmas
based on random benefit $b$ and cost $c$ for cooperation. We show that a
decrease in the scaled variance of $b$ or $c$, or an increase in their scaled
covariance, makes it easier for weak selection to favor the abundance of
cooperation in the stag hunt game and the snowdrift game. The same conclusion
holds for the public goods game except that the covariance of $b$ has no effect
on the average abundance of $C$. On the other hand, increasing the scaled
mutation rate or the group size can enhance or lessen the condition for weak
selection to favor the abundance of $C$.
| [
{
"created": "Thu, 24 Feb 2022 07:03:12 GMT",
"version": "v1"
}
] | 2022-02-25 | [
[
"Kroumi",
"Dhaker",
""
],
[
"Lessard",
"Sabin",
""
]
] | We consider interactions between players in groups of size $d\geq2$ with payoffs that not only depend on the strategies used in the group but also fluctuate at random over time. An individual can adopt either cooperation or defection as strategy and the population is updated from one-time step to the next by a birth-death event according to a Moran model. Assuming recurrent symmetric mutation and payoffs with expected values, variances, and covariances of the same small order, we derive a first-order approximation of the average abundance of cooperation in the selection-mutation equilibrium. We show that increasing the variance of any payoff for defection or decreasing the variance of any payoff for cooperation increases the average abundance of cooperation. As for the effect of the covariance between any payoff for cooperation and any payoff for defection, we show that it depends on the number of cooperators in the group associated with these payoffs. We study in particular the public goods game, the stag hunt game, and the snowdrift game, all social dilemmas based on random benefit $b$ and cost $c$ for cooperation. We show that a decrease in the scaled variance of $b$ or $c$, or an increase in their scaled covariance, makes it easier for weak selection to favor the abundance of cooperation in the stag hunt game and the snowdrift game. The same conclusion holds for the public goods game except that the covariance of $b$ has no effect on the average abundance of $C$. On the other hand, increasing the scaled mutation rate or the group size can enhance or lessen the condition for weak selection to favor the abundance of $C$. |
1703.10929 | Katrin B\"ottger | Katrin Talkenberger, Elisabetta Ada Cavalcanti-Adamda, Andreas
Deutsch, Anja Voss-B\"ohme | Amoeboid-mesenchymal migration plasticity promotes invasion only in
complex heterogeneous microenvironments | null | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | During tissue invasion individual tumor cells exhibit two interconvertible
migration modes, namely mesenchymal and amoeboid migration. The cellular
microenvironment triggers the switch between both modes, thereby allowing
adaptation to dynamic conditions. It is, however, unclear if this
amoeboid-mesenchymal migration plasticity contributes to a more effective tumor
invasion. We address this question with a mathematical model, where the
amoeboid-mesenchymal migration plasticity is regulated in response to local
extracellular matrix resistance. Our numerical analysis reveals that
extracellular matrix structure and presence of a chemotactic gradient are key
determinants of the model behavior. Only in complex microenvironments, if the
extracellular matrix is highly heterogeneous and a chemotactic gradient directs
migration, the amoeboid-mesenchymal migration plasticity allows a more
widespread invasion compared to the non-switching amoeboid and mesenchymal
modes. Importantly, these specific conditions are characteristic for in vivo
tumor invasion. Thus, our study suggests that \emph{in vitro} systems aiming at
unraveling the underlying molecular mechanisms of tumor invasion should take
into account the complexity of the microenvironment by considering the combined
effects of structural heterogeneities and chemical gradients on cell migration.
| [
{
"created": "Fri, 31 Mar 2017 15:03:52 GMT",
"version": "v1"
}
] | 2017-04-03 | [
[
"Talkenberger",
"Katrin",
""
],
[
"Cavalcanti-Adamda",
"Elisabetta Ada",
""
],
[
"Deutsch",
"Andreas",
""
],
[
"Voss-Böhme",
"Anja",
""
]
] | During tissue invasion individual tumor cells exhibit two interconvertible migration modes, namely mesenchymal and amoeboid migration. The cellular microenvironment triggers the switch between both modes, thereby allowing adaptation to dynamic conditions. It is, however, unclear if this amoeboid-mesenchymal migration plasticity contributes to a more effective tumor invasion. We address this question with a mathematical model, where the amoeboid-mesenchymal migration plasticity is regulated in response to local extracellular matrix resistance. Our numerical analysis reveals that extracellular matrix structure and presence of a chemotactic gradient are key determinants of the model behavior. Only in complex microenvironments, if the extracellular matrix is highly heterogeneous and a chemotactic gradient directs migration, the amoeboid-mesenchymal migration plasticity allows a more widespread invasion compared to the non-switching amoeboid and mesenchymal modes. Importantly, these specific conditions are characteristic for in vivo tumor invasion. Thus, our study suggests that \emph{in vitro} systems aiming at unraveling the underlying molecular mechanisms of tumor invasion should take into account the complexity of the microenvironment by considering the combined effects of structural heterogeneities and chemical gradients on cell migration. |
2407.15735 | Alexandre Matov | Alexandre Matov | A Real-Time Suite of Biological Cell Image Analysis Software for
Computers, Smartphones, and Smart Glasses, Suitable for Resource-Constrained
Computing | null | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Methods for personalizing medical treatment are the focal point of
contemporary clinical research. In cancer care, for instance, we can analyze
the effects of therapies at the level of individual cells. Complete
characterization of treatment efficacy and evaluation of why some individuals
respond to specific regimens, whereas others do not, requires additional
approaches to genetic sequencing at single time points. Methods for the
continuous analysis of changes in phenotype, such as morphology and motion
tracking of cellular proteins and organelles over time frames spanning the
minute-hour scales, can provide important insight to patient treatment options.
The integration of measurements of intracellular dynamics and the contribution
of multiple genetic pathways in degenerative diseases is vital for the
development of biomarkers for the early detection of pathogenesis and therapy
efficacy. We have developed a software suite (DataSet Tracker) for real-time
analysis designed to run on computers, smartphones, and smart glasses hardware
and suitable for resource-constrained, on-the-fly computing in microscopes
without internet connectivity; a demo is available for viewing at
datasetanalysis.com. Our objective is to present the community with an
integrated, easy to use by all, tool for resolving the complex dynamics of the
cytoskeletal meshworks, intracytoplasmic membranous networks, and vesicle
trafficking. It is our goal to have this integrated tool approved for use in
the clinical practice.
| [
{
"created": "Mon, 22 Jul 2024 15:39:58 GMT",
"version": "v1"
},
{
"created": "Tue, 23 Jul 2024 05:53:03 GMT",
"version": "v2"
}
] | 2024-07-24 | [
[
"Matov",
"Alexandre",
""
]
] | Methods for personalizing medical treatment are the focal point of contemporary clinical research. In cancer care, for instance, we can analyze the effects of therapies at the level of individual cells. Complete characterization of treatment efficacy and evaluation of why some individuals respond to specific regimens, whereas others do not, requires additional approaches to genetic sequencing at single time points. Methods for the continuous analysis of changes in phenotype, such as morphology and motion tracking of cellular proteins and organelles over time frames spanning the minute-hour scales, can provide important insight to patient treatment options. The integration of measurements of intracellular dynamics and the contribution of multiple genetic pathways in degenerative diseases is vital for the development of biomarkers for the early detection of pathogenesis and therapy efficacy. We have developed a software suite (DataSet Tracker) for real-time analysis designed to run on computers, smartphones, and smart glasses hardware and suitable for resource-constrained, on-the-fly computing in microscopes without internet connectivity; a demo is available for viewing at datasetanalysis.com. Our objective is to present the community with an integrated, easy to use by all, tool for resolving the complex dynamics of the cytoskeletal meshworks, intracytoplasmic membranous networks, and vesicle trafficking. It is our goal to have this integrated tool approved for use in the clinical practice. |
1810.07576 | Qi Su | Qi Su and Lei Zhou and Long Wang | Evolutionary multiplayer games on graphs with edge diversity | 50 pages, 7 figures | null | 10.1371/journal.pcbi.1006947 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Evolutionary game dynamics in structured populations has been extensively
explored in past decades. However, most previous studies assume that payoffs of
individuals are fully determined by the strategic behaviors of interacting
parties and social ties between them only serve as the indicator of the
existence of interactions. This assumption neglects important information
carried by inter-personal social ties such as genetic similarity, geographic
proximity, and social closeness, which may crucially affect the outcome of
interactions. To model these situations, we present a framework of evolutionary
multiplayer games on graphs with edge diversity, where different types of edges
describe diverse social ties. Strategic behaviors together with social ties
determine the resulting payoffs of interactants. Under weak selection, we
provide a general formula to predict the success of one behavior over the
other. We apply this formula to various examples which cannot be dealt with
using previous models, including the division of labor and relationship- or
edge-dependent games. We find that labor division facilitates collective
cooperation by decomposing a many-player game into several games of smaller
sizes. The evolutionary process based on relationship-dependent games can be
approximated by interactions under a transformed and unified game. Our work
stresses the importance of social ties and provides effective methods to reduce
the calculating complexity in analyzing the evolution of realistic systems.
| [
{
"created": "Wed, 17 Oct 2018 14:29:32 GMT",
"version": "v1"
}
] | 2019-06-19 | [
[
"Su",
"Qi",
""
],
[
"Zhou",
"Lei",
""
],
[
"Wang",
"Long",
""
]
] | Evolutionary game dynamics in structured populations has been extensively explored in past decades. However, most previous studies assume that payoffs of individuals are fully determined by the strategic behaviors of interacting parties and social ties between them only serve as the indicator of the existence of interactions. This assumption neglects important information carried by inter-personal social ties such as genetic similarity, geographic proximity, and social closeness, which may crucially affect the outcome of interactions. To model these situations, we present a framework of evolutionary multiplayer games on graphs with edge diversity, where different types of edges describe diverse social ties. Strategic behaviors together with social ties determine the resulting payoffs of interactants. Under weak selection, we provide a general formula to predict the success of one behavior over the other. We apply this formula to various examples which cannot be dealt with using previous models, including the division of labor and relationship- or edge-dependent games. We find that labor division facilitates collective cooperation by decomposing a many-player game into several games of smaller sizes. The evolutionary process based on relationship-dependent games can be approximated by interactions under a transformed and unified game. Our work stresses the importance of social ties and provides effective methods to reduce the calculating complexity in analyzing the evolution of realistic systems. |
q-bio/0311037 | Alexander Kraskov | Alexander Kraskov, Harald Stoegbauer, Ralph G. Andrzejak, Peter
Grassberger | Hierarchical Clustering Using Mutual Information | 4 pages, 4 figures | null | null | null | q-bio.QM cs.CC physics.data-an | null | We present a method for hierarchical clustering of data called {\it mutual
information clustering} (MIC) algorithm. It uses mutual information (MI) as a
similarity measure and exploits its grouping property: The MI between three
objects $X, Y,$ and $Z$ is equal to the sum of the MI between $X$ and $Y$, plus
the MI between $Z$ and the combined object $(XY)$. We use this both in the
Shannon (probabilistic) version of information theory and in the Kolmogorov
(algorithmic) version. We apply our method to the construction of phylogenetic
trees from mitochondrial DNA sequences and to the output of independent
components analysis (ICA) as illustrated with the ECG of a pregnant woman.
| [
{
"created": "Thu, 27 Nov 2003 07:58:52 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Kraskov",
"Alexander",
""
],
[
"Stoegbauer",
"Harald",
""
],
[
"Andrzejak",
"Ralph G.",
""
],
[
"Grassberger",
"Peter",
""
]
] | We present a method for hierarchical clustering of data called {\it mutual information clustering} (MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects $X, Y,$ and $Z$ is equal to the sum of the MI between $X$ and $Y$, plus the MI between $Z$ and the combined object $(XY)$. We use this both in the Shannon (probabilistic) version of information theory and in the Kolmogorov (algorithmic) version. We apply our method to the construction of phylogenetic trees from mitochondrial DNA sequences and to the output of independent components analysis (ICA) as illustrated with the ECG of a pregnant woman. |
0908.1199 | Sumedha | Sumedha, Michael F Hagan, Bulbul Chakraborty | Prolonging assembly through dissociation:A self assembly paradigm in
microtubules | accepted for publication in Physical Review E | Phys. Rev. E 83, 051904 (2011) | 10.1103/PhysRevE.83.051904 | null | q-bio.BM cond-mat.stat-mech q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study a one-dimensional model of microtubule assembly/disassembly in which
GTP bound to tubulins within the microtubule undergoes stochastic hydrolysis.
In contrast to models that only consider a cap of GTP-bound tubulin, stochastic
hydrolysis allows GTP-bound tubulin remnants to exist within the microtubule.
We find that these buried GTP remnants enable an alternative mechanism of
recovery from shrinkage, and enhances fluctuations of filament lengths. Under
conditions for which this alternative mechanism dominates, an increasing
depolymerization rate leads to a decrease in dissociation rate and thus a net
increase in assembly.
| [
{
"created": "Sun, 9 Aug 2009 01:10:49 GMT",
"version": "v1"
},
{
"created": "Wed, 13 Apr 2011 08:23:59 GMT",
"version": "v2"
}
] | 2015-05-13 | [
[
"Sumedha",
"",
""
],
[
"Hagan",
"Michael F",
""
],
[
"Chakraborty",
"Bulbul",
""
]
] | We study a one-dimensional model of microtubule assembly/disassembly in which GTP bound to tubulins within the microtubule undergoes stochastic hydrolysis. In contrast to models that only consider a cap of GTP-bound tubulin, stochastic hydrolysis allows GTP-bound tubulin remnants to exist within the microtubule. We find that these buried GTP remnants enable an alternative mechanism of recovery from shrinkage, and enhances fluctuations of filament lengths. Under conditions for which this alternative mechanism dominates, an increasing depolymerization rate leads to a decrease in dissociation rate and thus a net increase in assembly. |
1511.00139 | Christophe Guyeux | Jacques M. Bahi and Nathalie M.-L. Cote, and Christophe Guyeux | Chaos of Protein Folding | null | null | 10.1109/IJCNN.2011.6033463 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | As protein folding is a NP-complete problem, artificial intelligence tools
like neural networks and genetic algorithms are used to attempt to predict the
3D shape of an amino acids sequence. Underlying these attempts, it is supposed
that this folding process is predictable. However, to the best of our
knowledge, this important assumption has been neither proven, nor studied. In
this paper the topological dynamic of protein folding is evaluated. It is
mathematically established that protein folding in 2D hydrophobic-hydrophilic
(HP) square lattice model is chaotic as defined by Devaney. Consequences for
both structure prediction and biology are then outlined.
| [
{
"created": "Sat, 31 Oct 2015 15:26:57 GMT",
"version": "v1"
}
] | 2015-11-03 | [
[
"Bahi",
"Jacques M.",
""
],
[
"Cote",
"Nathalie M. -L.",
""
],
[
"Guyeux",
"Christophe",
""
]
] | As protein folding is a NP-complete problem, artificial intelligence tools like neural networks and genetic algorithms are used to attempt to predict the 3D shape of an amino acids sequence. Underlying these attempts, it is supposed that this folding process is predictable. However, to the best of our knowledge, this important assumption has been neither proven, nor studied. In this paper the topological dynamic of protein folding is evaluated. It is mathematically established that protein folding in 2D hydrophobic-hydrophilic (HP) square lattice model is chaotic as defined by Devaney. Consequences for both structure prediction and biology are then outlined. |
2005.14286 | Guo-Wei Wei | Kaifu Gao, Duc D Nguyen, Meihua Tu, and Guo-Wei Wei | Generative network complex for the automated generation of druglike
molecules | 27 pages, 2 tables and 19 figures | null | null | null | q-bio.BM q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Current drug discovery is expensive and time-consuming. It remains a
challenging task to create a wide variety of novel compounds with desirable
pharmacological properties and cheaply available to low-income people. In this
work, we develop a generative network complex (GNC) to generate new drug-like
molecules based on the multi-property optimization via the gradient descent in
the latent space of an autoencoder. In our GNC, both multiple chemical
properties and similarity scores are optimized to generate and predict
drug-like molecules with desired chemical properties. To further validate the
reliability of the predictions, these molecules are reevaluated and screened by
independent 2D fingerprint-based predictors to come up with a few hundreds of
new drug candidates. As a demonstration, we apply our GNC to generate a large
number of new BACE1 inhibitors, as well as thousands of novel alternative drug
candidates for eight existing market drugs, including Ceritinib, Ribociclib,
Acalabrutinib, Idelalisib, Dabrafenib, Macimorelin, Enzalutamide, and
Panobinostat.
| [
{
"created": "Thu, 28 May 2020 20:42:16 GMT",
"version": "v1"
}
] | 2020-06-01 | [
[
"Gao",
"Kaifu",
""
],
[
"Nguyen",
"Duc D",
""
],
[
"Tu",
"Meihua",
""
],
[
"Wei",
"Guo-Wei",
""
]
] | Current drug discovery is expensive and time-consuming. It remains a challenging task to create a wide variety of novel compounds with desirable pharmacological properties and cheaply available to low-income people. In this work, we develop a generative network complex (GNC) to generate new drug-like molecules based on the multi-property optimization via the gradient descent in the latent space of an autoencoder. In our GNC, both multiple chemical properties and similarity scores are optimized to generate and predict drug-like molecules with desired chemical properties. To further validate the reliability of the predictions, these molecules are reevaluated and screened by independent 2D fingerprint-based predictors to come up with a few hundreds of new drug candidates. As a demonstration, we apply our GNC to generate a large number of new BACE1 inhibitors, as well as thousands of novel alternative drug candidates for eight existing market drugs, including Ceritinib, Ribociclib, Acalabrutinib, Idelalisib, Dabrafenib, Macimorelin, Enzalutamide, and Panobinostat. |
1911.03710 | Hendrik Richter | Hendrik Richter | Evolution of Cooperation for Multiple Mutant Configurations on All
Regular Graphs with $N \leq 14$ players | null | null | null | null | q-bio.PE cs.NE math.CO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the emergence of cooperation in structured populations with any
arrangement of cooperators and defectors on the evolutionary graph. Using
structure coefficients defined for configurations describing such arrangements
of any number of mutants, we provide results for weak selection to favor
cooperation over defection on any regular graph with $N \leq 14$ vertices.
Furthermore, the properties of graphs that particularly promote cooperation are
analyzed. It is shown that the number of graph cycles of certain length is a
good predictor for the values of the structure coefficient, and thus a tendency
to favor cooperation. Another property of particularly cooperation-promoting
regular graphs with a low degree is that they are structured to have blocks
with clusters of mutants that are connected by cut vertices and/or hinge
vertices.
| [
{
"created": "Sat, 9 Nov 2019 15:07:22 GMT",
"version": "v1"
}
] | 2019-11-12 | [
[
"Richter",
"Hendrik",
""
]
] | We study the emergence of cooperation in structured populations with any arrangement of cooperators and defectors on the evolutionary graph. Using structure coefficients defined for configurations describing such arrangements of any number of mutants, we provide results for weak selection to favor cooperation over defection on any regular graph with $N \leq 14$ vertices. Furthermore, the properties of graphs that particularly promote cooperation are analyzed. It is shown that the number of graph cycles of certain length is a good predictor for the values of the structure coefficient, and thus a tendency to favor cooperation. Another property of particularly cooperation-promoting regular graphs with a low degree is that they are structured to have blocks with clusters of mutants that are connected by cut vertices and/or hinge vertices. |
2305.11982 | Mufeng Tang | Mufeng Tang, Helen Barron and Rafal Bogacz | Sequential Memory with Temporal Predictive Coding | 37th Conference on Neural Information Processing Systems (NeurIPS
2023) | null | null | null | q-bio.NC cs.LG stat.ML | http://creativecommons.org/licenses/by/4.0/ | Forming accurate memory of sequential stimuli is a fundamental function of
biological agents. However, the computational mechanism underlying sequential
memory in the brain remains unclear. Inspired by neuroscience theories and
recent successes in applying predictive coding (PC) to \emph{static} memory
tasks, in this work we propose a novel PC-based model for \emph{sequential}
memory, called \emph{temporal predictive coding} (tPC). We show that our tPC
models can memorize and retrieve sequential inputs accurately with a
biologically plausible neural implementation. Importantly, our analytical study
reveals that tPC can be viewed as a classical Asymmetric Hopfield Network (AHN)
with an implicit statistical whitening process, which leads to more stable
performance in sequential memory tasks of structured inputs. Moreover, we find
that tPC exhibits properties consistent with behavioral observations and
theories in neuroscience, thereby strengthening its biological relevance. Our
work establishes a possible computational mechanism underlying sequential
memory in the brain that can also be theoretically interpreted using existing
memory model frameworks.
| [
{
"created": "Fri, 19 May 2023 20:03:31 GMT",
"version": "v1"
},
{
"created": "Thu, 26 Oct 2023 15:39:02 GMT",
"version": "v2"
}
] | 2023-10-27 | [
[
"Tang",
"Mufeng",
""
],
[
"Barron",
"Helen",
""
],
[
"Bogacz",
"Rafal",
""
]
] | Forming accurate memory of sequential stimuli is a fundamental function of biological agents. However, the computational mechanism underlying sequential memory in the brain remains unclear. Inspired by neuroscience theories and recent successes in applying predictive coding (PC) to \emph{static} memory tasks, in this work we propose a novel PC-based model for \emph{sequential} memory, called \emph{temporal predictive coding} (tPC). We show that our tPC models can memorize and retrieve sequential inputs accurately with a biologically plausible neural implementation. Importantly, our analytical study reveals that tPC can be viewed as a classical Asymmetric Hopfield Network (AHN) with an implicit statistical whitening process, which leads to more stable performance in sequential memory tasks of structured inputs. Moreover, we find that tPC exhibits properties consistent with behavioral observations and theories in neuroscience, thereby strengthening its biological relevance. Our work establishes a possible computational mechanism underlying sequential memory in the brain that can also be theoretically interpreted using existing memory model frameworks. |
2302.03590 | Nasim Abdollahi Ph.D. | Nasim Abdollahi, Seyed Ali Madani Tonekaboni, Jay Huang, Bo Wang,
Stephen MacKinnon | NodeCoder: a graph-based machine learning platform to predict active
sites of modeled protein structures | including supplementary materials 22 pages, 6 figures, 4 tables,
presented at NeurIPS 2021 and ACS 2022 | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | While accurate protein structure predictions are now available for nearly
every observed protein sequence, predicted structures lack much of the
functional context offered by experimental structure determination. We address
this gap with NodeCoder, a task-independent platform that maps residue-based
datasets onto 3D protein structures, embeds the resulting structural feature
into a contact network, and models residue classification tasks with a Graph
Convolutional Network (GCN). We demonstrate the versatility of this strategy by
modeling six separate tasks, with some labels derived from other experimental
structure studies (ligand, peptide, ion, and nucleic acid binding sites) and
other labels derived from annotation databases (post-translational modification
and transmembrane regions). Moreover, A NodeCoder model trained to identify
ligand binding site residues was able to outperform P2Rank, a widely-used
software developed specifically for ligand binding site detection. NodeCoder is
available as an open-source python package at
https://pypi.org/project/NodeCoder/.
| [
{
"created": "Tue, 7 Feb 2023 16:58:24 GMT",
"version": "v1"
}
] | 2023-02-08 | [
[
"Abdollahi",
"Nasim",
""
],
[
"Tonekaboni",
"Seyed Ali Madani",
""
],
[
"Huang",
"Jay",
""
],
[
"Wang",
"Bo",
""
],
[
"MacKinnon",
"Stephen",
""
]
] | While accurate protein structure predictions are now available for nearly every observed protein sequence, predicted structures lack much of the functional context offered by experimental structure determination. We address this gap with NodeCoder, a task-independent platform that maps residue-based datasets onto 3D protein structures, embeds the resulting structural feature into a contact network, and models residue classification tasks with a Graph Convolutional Network (GCN). We demonstrate the versatility of this strategy by modeling six separate tasks, with some labels derived from other experimental structure studies (ligand, peptide, ion, and nucleic acid binding sites) and other labels derived from annotation databases (post-translational modification and transmembrane regions). Moreover, A NodeCoder model trained to identify ligand binding site residues was able to outperform P2Rank, a widely-used software developed specifically for ligand binding site detection. NodeCoder is available as an open-source python package at https://pypi.org/project/NodeCoder/. |
2110.13910 | Francoise Argoul | A. Guillet, A. Arneodo, P. Argoul, F. Argoul | Quantifying the rationality of rhythmic signals | 27 pages, 11 figures | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Rhythms and vibrations represent the quintessence of life, they are
ubiquitous (systemic) in all living systems. Recognising, unfolding these
rhythms is paramount in medicine, for example in the physiology of the heart,
lung, hearing, speech, brain, the cellular and molecular processes involved in
biological clocks. The importance of the commensurability of the frequencies in
different rhythms has been thoroughly studied in music. We define a
log-frequency correlation measure on spectral densities that gives the temporal
evolution of the distribution of frequency ratios (rational or irrational) in
between two signals, using analytic wavelets. We illustrate these concepts on
numerical signals (sums of sine functions) and voice recordings from the
Voice-Icar-Federico II database. Finally, with a second correlation operation
from two of these ratio distributions (a reference one, the other from the
voices) we introduce another quantity that we call \emph{sonance}, measuring
the ``harmony'' (rationality) of two voices sung together as a function of a
pitch transposition.
| [
{
"created": "Mon, 25 Oct 2021 10:24:21 GMT",
"version": "v1"
}
] | 2021-10-28 | [
[
"Guillet",
"A.",
""
],
[
"Arneodo",
"A.",
""
],
[
"Argoul",
"P.",
""
],
[
"Argoul",
"F.",
""
]
] | Rhythms and vibrations represent the quintessence of life, they are ubiquitous (systemic) in all living systems. Recognising, unfolding these rhythms is paramount in medicine, for example in the physiology of the heart, lung, hearing, speech, brain, the cellular and molecular processes involved in biological clocks. The importance of the commensurability of the frequencies in different rhythms has been thoroughly studied in music. We define a log-frequency correlation measure on spectral densities that gives the temporal evolution of the distribution of frequency ratios (rational or irrational) in between two signals, using analytic wavelets. We illustrate these concepts on numerical signals (sums of sine functions) and voice recordings from the Voice-Icar-Federico II database. Finally, with a second correlation operation from two of these ratio distributions (a reference one, the other from the voices) we introduce another quantity that we call \emph{sonance}, measuring the ``harmony'' (rationality) of two voices sung together as a function of a pitch transposition. |
2008.06023 | Matthew Johnston | Matthew D. Johnston and Bruce Pell | A Dynamical Framework for Modeling Fear of Infection and Frustration
with Social Distancing in COVID-19 Spread | 10 figures | null | null | null | q-bio.PE math.DS physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we introduce a novel modeling framework for incorporating fear
of infection and frustration with social distancing into disease dynamics. We
show that the resulting SEIR behavior-perception model has three principal
modes of qualitative behavior---no outbreak, controlled outbreak, and
uncontrolled outbreak. We also demonstrate that the model can produce transient
and sustained waves of infection consistent with secondary outbreaks. We fit
the model to cumulative COVID-19 case and mortality data from several regions.
Our analysis suggests that regions which experience a significant decline after
the first wave of infection, such as Canada and Israel, are more likely to
contain secondary waves of infection, whereas regions which only achieve
moderate success in mitigating the disease's spread initially, such as the
United States, are likely to experience substantial secondary waves or
uncontrolled outbreaks.
| [
{
"created": "Thu, 13 Aug 2020 17:23:21 GMT",
"version": "v1"
}
] | 2020-08-14 | [
[
"Johnston",
"Matthew D.",
""
],
[
"Pell",
"Bruce",
""
]
] | In this paper, we introduce a novel modeling framework for incorporating fear of infection and frustration with social distancing into disease dynamics. We show that the resulting SEIR behavior-perception model has three principal modes of qualitative behavior---no outbreak, controlled outbreak, and uncontrolled outbreak. We also demonstrate that the model can produce transient and sustained waves of infection consistent with secondary outbreaks. We fit the model to cumulative COVID-19 case and mortality data from several regions. Our analysis suggests that regions which experience a significant decline after the first wave of infection, such as Canada and Israel, are more likely to contain secondary waves of infection, whereas regions which only achieve moderate success in mitigating the disease's spread initially, such as the United States, are likely to experience substantial secondary waves or uncontrolled outbreaks. |
1705.01135 | Eben Kenah | Yushuf Sharker and Eben Kenah | Estimating and interpreting secondary attack risk: Binomial considered
harmful | 25 pages, 8 figures | PLoS Computational Biology 17(1): e1008601, January 2021 | 10.1371/journal.pcbi.1008601 | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The household secondary attack risk (SAR), often called the secondary attack
rate or secondary infection risk, is the probability of infectious contact from
an infectious household member A to a given household member B, where we define
infectious contact to be a contact sufficient to infect B if he or she is
susceptible. Estimation of the SAR is an important part of understanding and
controlling the transmission of infectious diseases. In practice, it is most
often estimated using binomial models such as logistic regression, which
implicitly attribute all secondary infections in a household to the primary
case. In the simplest case, the number of secondary infections in a household
with m susceptibles and a single primary case is modeled as a binomial(m, p)
random variable where p is the SAR. Although it has long been understood that
transmission within households is not binomial, it is thought that multiple
generations of transmission can be safely neglected when p is small. We use
probability generating functions and simulations to show that this is a
mistake. The proportion of susceptible household members infected can be
substantially larger than the SAR even when p is small. As a result, binomial
estimates of the SAR are biased upward and their confidence intervals have poor
coverage probabilities even if adjusted for clustering. Accurate point and
interval estimates of the SAR can be obtained using longitudinal chain binomial
models or pairwise survival analysis, which account for multiple generations of
transmission within households, the ongoing risk of infection from outside the
household, and incomplete follow-up. We illustrate the practical implications
of these results in an analysis of household surveillance data collected by the
Los Angeles County Department of Public Health during the 2009 influenza A
(H1N1) pandemic.
| [
{
"created": "Tue, 2 May 2017 18:37:44 GMT",
"version": "v1"
},
{
"created": "Fri, 17 Jul 2020 05:15:31 GMT",
"version": "v2"
}
] | 2023-10-24 | [
[
"Sharker",
"Yushuf",
""
],
[
"Kenah",
"Eben",
""
]
] | The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household member A to a given household member B, where we define infectious contact to be a contact sufficient to infect B if he or she is susceptible. Estimation of the SAR is an important part of understanding and controlling the transmission of infectious diseases. In practice, it is most often estimated using binomial models such as logistic regression, which implicitly attribute all secondary infections in a household to the primary case. In the simplest case, the number of secondary infections in a household with m susceptibles and a single primary case is modeled as a binomial(m, p) random variable where p is the SAR. Although it has long been understood that transmission within households is not binomial, it is thought that multiple generations of transmission can be safely neglected when p is small. We use probability generating functions and simulations to show that this is a mistake. The proportion of susceptible household members infected can be substantially larger than the SAR even when p is small. As a result, binomial estimates of the SAR are biased upward and their confidence intervals have poor coverage probabilities even if adjusted for clustering. Accurate point and interval estimates of the SAR can be obtained using longitudinal chain binomial models or pairwise survival analysis, which account for multiple generations of transmission within households, the ongoing risk of infection from outside the household, and incomplete follow-up. We illustrate the practical implications of these results in an analysis of household surveillance data collected by the Los Angeles County Department of Public Health during the 2009 influenza A (H1N1) pandemic. |
1206.1108 | Marko Puljic | Robert Kozma, Marko Puljic, and Walter J. Freeman | Thermodynamic Model of Criticality in the Cortex Based On EEG/ECOG Data | Criticality in Neural Systems, 2012 (book chapter) | null | null | null | q-bio.NC cond-mat.dis-nn | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Criticality in the cortex emerges from the seemingly random interaction of
microscopic components and produces higher cognitive functions at mesoscopic
and macroscopic scales. Random graphs and percolation theory provide natural
means to de- scribe critical regions in the behavior of the cortex and they are
proposed here as novel mathematical tools helping us deciphering the language
of the brain.
| [
{
"created": "Wed, 6 Jun 2012 02:30:44 GMT",
"version": "v1"
}
] | 2012-06-07 | [
[
"Kozma",
"Robert",
""
],
[
"Puljic",
"Marko",
""
],
[
"Freeman",
"Walter J.",
""
]
] | Criticality in the cortex emerges from the seemingly random interaction of microscopic components and produces higher cognitive functions at mesoscopic and macroscopic scales. Random graphs and percolation theory provide natural means to de- scribe critical regions in the behavior of the cortex and they are proposed here as novel mathematical tools helping us deciphering the language of the brain. |
2112.15379 | Louxin Zhang | Louxin Zhang | The Sackin Index of Simplex Networks | 19 pages, 2 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A phylogenetic network is a simplex (or 1-component tree-child) network if
the child of every reticulation node is a network leaf. Simplex networks are a
superclass of phylogenetic trees and a subclass of tree-child networks.
Generalizing the Sackin index to phylogenetic networks, we prove that the
expected Sackin index of a random simplex network is asymptotically
$\Omega(n^{7/4})$ in the uniform model.
| [
{
"created": "Fri, 31 Dec 2021 10:45:54 GMT",
"version": "v1"
}
] | 2022-01-03 | [
[
"Zhang",
"Louxin",
""
]
] | A phylogenetic network is a simplex (or 1-component tree-child) network if the child of every reticulation node is a network leaf. Simplex networks are a superclass of phylogenetic trees and a subclass of tree-child networks. Generalizing the Sackin index to phylogenetic networks, we prove that the expected Sackin index of a random simplex network is asymptotically $\Omega(n^{7/4})$ in the uniform model. |
1605.07053 | Jacques P\'ecr\'eaux | Jacques Pecreaux, Stefanie Redemann, Zahraa Alayan, Benjamin Mercat,
Sylvain Pastezeur, Carlos Garzon-Coral, Anthony A. Hyman, Jonathon Howard | The mitotic spindle in the one-cell C. elegans embryo is positioned with
high precision and stability | Accepted in Biophysical Journal (2016) | null | 10.1016/j.bpj.2016.09.007 | null | q-bio.SC q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Precise positioning of the mitotic spindle is important for specifying the
plane of cell division, which in turn determines how the cytoplasmic contents
are partitioned into the daughter cells, and how the daughters are positioned
within the tissue. During metaphase in the early C. elegans embryo, the spindle
is aligned and centered on the anterior-posterior axis by a
microtubule-dependent machinery that exerts restoring forces when the spindle
is displaced from the center. To investigate the accuracy and stability of
centering, we tracked the position and orientation of the mitotic spindle
during the first cell division with high temporal and spatial resolution. We
found that the precision is remarkably high: the cell-to-cell variation in the
transverse position of the center of the spindle during metaphase, as measured
by the standard deviation, was only 1.5% of the length of the short axis of the
cell. Spindle position is also very stable: the standard deviation of the
fluctuations in transverse spindle position during metaphase was only 0.5% of
the short axis of the cell. Assuming that stability is limited by fluctuations
in the number of independent motor elements such as microtubules or dyneins
underlying the centering machinery, we infer that the number is on the order of
one thousand, consistent with the several thousand of astral microtubules in
these cells. Astral microtubules grow out from the two spindle poles, make
contact with the cell cortex, and then shrink back shortly thereafter. The high
stability of centering can be accounted for quantitatively if, while making
contact with the cortex, the astral microtubules buckle as they exert
compressive, pushing forces. We thus propose that the large number of
microtubules in the asters provides a highly precise mechanism for positioning
the spindle during metaphase while assembly is completed prior to the onset of
anaphase.
| [
{
"created": "Mon, 23 May 2016 15:14:23 GMT",
"version": "v1"
},
{
"created": "Tue, 13 Sep 2016 06:36:05 GMT",
"version": "v2"
}
] | 2016-11-23 | [
[
"Pecreaux",
"Jacques",
""
],
[
"Redemann",
"Stefanie",
""
],
[
"Alayan",
"Zahraa",
""
],
[
"Mercat",
"Benjamin",
""
],
[
"Pastezeur",
"Sylvain",
""
],
[
"Garzon-Coral",
"Carlos",
""
],
[
"Hyman",
"Anthony A.",
""
],
[
"Howard",
"Jonathon",
""
]
] | Precise positioning of the mitotic spindle is important for specifying the plane of cell division, which in turn determines how the cytoplasmic contents are partitioned into the daughter cells, and how the daughters are positioned within the tissue. During metaphase in the early C. elegans embryo, the spindle is aligned and centered on the anterior-posterior axis by a microtubule-dependent machinery that exerts restoring forces when the spindle is displaced from the center. To investigate the accuracy and stability of centering, we tracked the position and orientation of the mitotic spindle during the first cell division with high temporal and spatial resolution. We found that the precision is remarkably high: the cell-to-cell variation in the transverse position of the center of the spindle during metaphase, as measured by the standard deviation, was only 1.5% of the length of the short axis of the cell. Spindle position is also very stable: the standard deviation of the fluctuations in transverse spindle position during metaphase was only 0.5% of the short axis of the cell. Assuming that stability is limited by fluctuations in the number of independent motor elements such as microtubules or dyneins underlying the centering machinery, we infer that the number is on the order of one thousand, consistent with the several thousand of astral microtubules in these cells. Astral microtubules grow out from the two spindle poles, make contact with the cell cortex, and then shrink back shortly thereafter. The high stability of centering can be accounted for quantitatively if, while making contact with the cortex, the astral microtubules buckle as they exert compressive, pushing forces. We thus propose that the large number of microtubules in the asters provides a highly precise mechanism for positioning the spindle during metaphase while assembly is completed prior to the onset of anaphase. |
1806.05177 | Subba Reddy Oota | Subba Reddy Oota, Naresh Manwani, and Bapi Raju S | fMRI Semantic Category Decoding using Linguistic Encoding of Word
Embeddings | 12 pages, 7 Figures | null | null | null | q-bio.NC cs.CL cs.CV | http://creativecommons.org/licenses/by/4.0/ | The dispute of how the human brain represents conceptual knowledge has been
argued in many scientific fields. Brain imaging studies have shown that the
spatial patterns of neural activation in the brain are correlated with thinking
about different semantic categories of words (for example, tools, animals, and
buildings) or when viewing the related pictures. In this paper, we present a
computational model that learns to predict the neural activation captured in
functional magnetic resonance imaging (fMRI) data of test words. Unlike the
models with hand-crafted features that have been used in the literature, in
this paper we propose a novel approach wherein decoding models are built with
features extracted from popular linguistic encodings of Word2Vec, GloVe,
Meta-Embeddings in conjunction with the empirical fMRI data associated with
viewing several dozen concrete nouns. We compared these models with several
other models that use word features extracted from FastText, Randomly-generated
features, Mitchell's 25 features [1]. The experimental results show that the
predicted fMRI images using Meta-Embeddings meet the state-of-the-art
performance. Although models with features from GloVe and Word2Vec predict fMRI
images similar to the state-of-the-art model, model with features from
Meta-Embeddings predicts significantly better. The proposed scheme that uses
popular linguistic encoding offers a simple and easy approach for semantic
decoding from fMRI experiments.
| [
{
"created": "Wed, 13 Jun 2018 10:59:33 GMT",
"version": "v1"
}
] | 2018-06-15 | [
[
"Oota",
"Subba Reddy",
""
],
[
"Manwani",
"Naresh",
""
],
[
"S",
"Bapi Raju",
""
]
] | The dispute of how the human brain represents conceptual knowledge has been argued in many scientific fields. Brain imaging studies have shown that the spatial patterns of neural activation in the brain are correlated with thinking about different semantic categories of words (for example, tools, animals, and buildings) or when viewing the related pictures. In this paper, we present a computational model that learns to predict the neural activation captured in functional magnetic resonance imaging (fMRI) data of test words. Unlike the models with hand-crafted features that have been used in the literature, in this paper we propose a novel approach wherein decoding models are built with features extracted from popular linguistic encodings of Word2Vec, GloVe, Meta-Embeddings in conjunction with the empirical fMRI data associated with viewing several dozen concrete nouns. We compared these models with several other models that use word features extracted from FastText, Randomly-generated features, Mitchell's 25 features [1]. The experimental results show that the predicted fMRI images using Meta-Embeddings meet the state-of-the-art performance. Although models with features from GloVe and Word2Vec predict fMRI images similar to the state-of-the-art model, model with features from Meta-Embeddings predicts significantly better. The proposed scheme that uses popular linguistic encoding offers a simple and easy approach for semantic decoding from fMRI experiments. |
1211.0060 | Philipp Messer | Philipp W. Messer, Dmitri A. Petrov | The McDonald-Kreitman Test and its Extensions under Frequent Adaptation:
Problems and Solutions | null | null | 10.1073/pnas.1220835110 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Population genomic studies have shown that genetic draft and background
selection can profoundly affect the genome-wide patterns of molecular
variation. We performed forward simulations under realistic gene-structure and
selection scenarios to investigate whether such linkage effects impinge on the
ability of the McDonald-Kreitman (MK) test to infer the rate of positive
selection (\alpha) from polymorphism and divergence data. We find that in the
presence of slightly deleterious mutations, MK estimates of \alpha\ severely
underestimate the true rate of adaptation even if all polymorphisms with
population frequencies under 50% are excluded. Furthermore, already under
intermediate rates of adaptation, genetic draft substantially distorts the site
frequency spectra at neutral and functional sites from the expectations under
mutation-selection-drift balance. MK-type approaches that first infer
demography from synonymous sites and then use the inferred demography to
correct the estimation of \alpha\ obtain almost the correct \alpha\ in our
simulations. However, these approaches typically infer a severe past population
expansion although there was no such expansion in the simulations, casting
doubt on the accuracy of methods that infer demography from synonymous
polymorphism data. We suggest a simple asymptotic extension of the MK test that
should yield accurate estimates of \alpha\ even in the presence of linkage
effects.
| [
{
"created": "Thu, 1 Nov 2012 00:07:41 GMT",
"version": "v1"
}
] | 2013-05-08 | [
[
"Messer",
"Philipp W.",
""
],
[
"Petrov",
"Dmitri A.",
""
]
] | Population genomic studies have shown that genetic draft and background selection can profoundly affect the genome-wide patterns of molecular variation. We performed forward simulations under realistic gene-structure and selection scenarios to investigate whether such linkage effects impinge on the ability of the McDonald-Kreitman (MK) test to infer the rate of positive selection (\alpha) from polymorphism and divergence data. We find that in the presence of slightly deleterious mutations, MK estimates of \alpha\ severely underestimate the true rate of adaptation even if all polymorphisms with population frequencies under 50% are excluded. Furthermore, already under intermediate rates of adaptation, genetic draft substantially distorts the site frequency spectra at neutral and functional sites from the expectations under mutation-selection-drift balance. MK-type approaches that first infer demography from synonymous sites and then use the inferred demography to correct the estimation of \alpha\ obtain almost the correct \alpha\ in our simulations. However, these approaches typically infer a severe past population expansion although there was no such expansion in the simulations, casting doubt on the accuracy of methods that infer demography from synonymous polymorphism data. We suggest a simple asymptotic extension of the MK test that should yield accurate estimates of \alpha\ even in the presence of linkage effects. |
1402.5348 | Jian-Jun Shu | Jian-Jun Shu and Kian Yan Yong | Identifying DNA motifs based on match and mismatch alignment information | null | Journal of Mathematical Chemistry, Vol. 51, No. 7, pp. 1720-1728,
2013 | 10.1007/s10910-013-0175-2 | null | q-bio.QM q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The conventional way of identifying DNA motifs, solely based on match
alignment information, is susceptible to a high number of spurious sites. A
novel scoring system has been introduced by taking both match and mismatch
alignment information into account. The mismatch alignment information is
useful to remove spurious sites encountered in DNA motif searching. As an
example, a correct TATA box site in Homo sapiens H4/g gene has successfully
been identified based on match and mismatch alignment information.
| [
{
"created": "Fri, 21 Feb 2014 16:46:42 GMT",
"version": "v1"
},
{
"created": "Fri, 28 Feb 2014 14:32:14 GMT",
"version": "v2"
}
] | 2014-03-03 | [
[
"Shu",
"Jian-Jun",
""
],
[
"Yong",
"Kian Yan",
""
]
] | The conventional way of identifying DNA motifs, solely based on match alignment information, is susceptible to a high number of spurious sites. A novel scoring system has been introduced by taking both match and mismatch alignment information into account. The mismatch alignment information is useful to remove spurious sites encountered in DNA motif searching. As an example, a correct TATA box site in Homo sapiens H4/g gene has successfully been identified based on match and mismatch alignment information. |
1604.01826 | Nathan Baker | Igor S. Tolokh, Aleksander Drozdetski, Lois Pollack, Nathan A. Baker,
Alexey V. Onufriev | Multi-shell model of ion-induced nucleic acid condensation | null | J. Chem. Phys. 144, 155101 (2016) | 10.1063/1.4945382 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present a semi-quantitative model of condensation of short nucleic acid
(NA) duplexes induced by tri-valent cobalt(III) hexammine (CoHex) ions. The
model is based on partitioning of bound counterion distribution around singleNA
duplex into "external" and "internal" ion binding shells distinguished by the
proximity to duplex helical axis. In the aggregated phase the shells overlap,
which leads to significantly increased attraction of CoHex ions in these
overlaps with the neighboring duplexes. The duplex aggregation free energy is
decomposed into attractive and repulsive components in such a way that they can
be represented by simple analytical expressions with parameters derived from
molecular dynamic (MD) simulations and numerical solutions of Poisson equation.
The short-range interactions described by the attractive term depend on the
fractions of bound ions in the overlapping shells and affinity of CoHex to the
"external" shell of nearly neutralized duplex. The repulsive components of the
free energy are duplex configurational entropy loss upon the aggregation and
the electrostatic repulsion of the duplexes that remains after neutralization
by bound CoHex ions. The estimates of the aggregation free energy are
consistent with the experimental range of NA duplex condensation propensities,
including the unusually poor condensation of RNA structures and subtle sequence
effects upon DNA condensation. The model predicts that, in contrast to DNA, RNA
duplexes may condense into tighter packed aggregates with a higher degree of
duplex neutralization. The model also predicts that longer NA fragments will
condense more readily than shorter ones. The ability of this model to explain
experimentally observed trends in NA condensation, lends support to proposed NA
condensation picture based on the multivalent "ion binding shells".
| [
{
"created": "Wed, 6 Apr 2016 22:55:47 GMT",
"version": "v1"
}
] | 2016-05-17 | [
[
"Tolokh",
"Igor S.",
""
],
[
"Drozdetski",
"Aleksander",
""
],
[
"Pollack",
"Lois",
""
],
[
"Baker",
"Nathan A.",
""
],
[
"Onufriev",
"Alexey V.",
""
]
] | We present a semi-quantitative model of condensation of short nucleic acid (NA) duplexes induced by tri-valent cobalt(III) hexammine (CoHex) ions. The model is based on partitioning of bound counterion distribution around singleNA duplex into "external" and "internal" ion binding shells distinguished by the proximity to duplex helical axis. In the aggregated phase the shells overlap, which leads to significantly increased attraction of CoHex ions in these overlaps with the neighboring duplexes. The duplex aggregation free energy is decomposed into attractive and repulsive components in such a way that they can be represented by simple analytical expressions with parameters derived from molecular dynamic (MD) simulations and numerical solutions of Poisson equation. The short-range interactions described by the attractive term depend on the fractions of bound ions in the overlapping shells and affinity of CoHex to the "external" shell of nearly neutralized duplex. The repulsive components of the free energy are duplex configurational entropy loss upon the aggregation and the electrostatic repulsion of the duplexes that remains after neutralization by bound CoHex ions. The estimates of the aggregation free energy are consistent with the experimental range of NA duplex condensation propensities, including the unusually poor condensation of RNA structures and subtle sequence effects upon DNA condensation. The model predicts that, in contrast to DNA, RNA duplexes may condense into tighter packed aggregates with a higher degree of duplex neutralization. The model also predicts that longer NA fragments will condense more readily than shorter ones. The ability of this model to explain experimentally observed trends in NA condensation, lends support to proposed NA condensation picture based on the multivalent "ion binding shells". |
2405.15968 | Emmet Francis | Emmet A. Francis, Justin G. Laughlin, J{\o}rgen S. Dokken, Henrik N.T.
Finsberg, Christopher T. Lee, Marie E. Rognes, and Padmini Rangamani | Spatial modeling algorithms for reactions and transport (SMART) in
biological cells | null | null | null | null | q-bio.QM q-bio.MN | http://creativecommons.org/licenses/by/4.0/ | Biological cells rely on precise spatiotemporal coordination of biochemical
reactions to control their many functions. Such cell signaling networks have
been a common focus for mathematical models, but they remain challenging to
simulate, particularly in realistic cell geometries. Herein, we present our
software, Spatial Modeling Algorithms for Reactions and Transport (SMART), a
package that takes in high-level user specifications about cell signaling
networks and molecular transport, and then assembles and solves the associated
mathematical and computational systems. SMART uses state-of-the-art finite
element analysis, via the FEniCS Project software, to efficiently and
accurately resolve cell signaling events over discretized cellular and
subcellular geometries. We demonstrate its application to several different
biological systems, including YAP/TAZ mechanotransduction, calcium signaling in
neurons and cardiomyocytes, and ATP generation in mitochondria. Throughout, we
utilize experimentally-derived realistic cellular geometries represented by
well-conditioned tetrahedral meshes. These scenarios demonstrate the
applicability, flexibility, accuracy and efficiency of SMART across a range of
temporal and spatial scales.
| [
{
"created": "Fri, 24 May 2024 22:40:07 GMT",
"version": "v1"
}
] | 2024-05-28 | [
[
"Francis",
"Emmet A.",
""
],
[
"Laughlin",
"Justin G.",
""
],
[
"Dokken",
"Jørgen S.",
""
],
[
"Finsberg",
"Henrik N. T.",
""
],
[
"Lee",
"Christopher T.",
""
],
[
"Rognes",
"Marie E.",
""
],
[
"Rangamani",
"Padmini",
""
]
] | Biological cells rely on precise spatiotemporal coordination of biochemical reactions to control their many functions. Such cell signaling networks have been a common focus for mathematical models, but they remain challenging to simulate, particularly in realistic cell geometries. Herein, we present our software, Spatial Modeling Algorithms for Reactions and Transport (SMART), a package that takes in high-level user specifications about cell signaling networks and molecular transport, and then assembles and solves the associated mathematical and computational systems. SMART uses state-of-the-art finite element analysis, via the FEniCS Project software, to efficiently and accurately resolve cell signaling events over discretized cellular and subcellular geometries. We demonstrate its application to several different biological systems, including YAP/TAZ mechanotransduction, calcium signaling in neurons and cardiomyocytes, and ATP generation in mitochondria. Throughout, we utilize experimentally-derived realistic cellular geometries represented by well-conditioned tetrahedral meshes. These scenarios demonstrate the applicability, flexibility, accuracy and efficiency of SMART across a range of temporal and spatial scales. |
2201.00622 | Jessie Huang | Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk,
Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita
Krishnaswamy | Learning shared neural manifolds from multi-subject FMRI data | null | null | null | null | q-bio.NC cs.LG eess.SP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Functional magnetic resonance imaging (fMRI) is a notoriously noisy
measurement of brain activity because of the large variations between
individuals, signals marred by environmental differences during collection, and
spatiotemporal averaging required by the measurement resolution. In addition,
the data is extremely high dimensional, with the space of the activity
typically having much lower intrinsic dimension. In order to understand the
connection between stimuli of interest and brain activity, and analyze
differences and commonalities between subjects, it becomes important to learn a
meaningful embedding of the data that denoises, and reveals its intrinsic
structure. Specifically, we assume that while noise varies significantly
between individuals, true responses to stimuli will share common,
low-dimensional features between subjects which are jointly discoverable.
Similar approaches have been exploited previously but they have mainly used
linear methods such as PCA and shared response modeling (SRM). In contrast, we
propose a neural network called MRMD-AE (manifold-regularized multiple decoder,
autoencoder), that learns a common embedding from multiple subjects in an
experiment while retaining the ability to decode to individual raw fMRI
signals. We show that our learned common space represents an extensible
manifold (where new points not seen during training can be mapped), improves
the classification accuracy of stimulus features of unseen timepoints, as well
as improves cross-subject translation of fMRI signals. We believe this
framework can be used for many downstream applications such as guided
brain-computer interface (BCI) training in the future.
| [
{
"created": "Wed, 22 Dec 2021 23:08:39 GMT",
"version": "v1"
}
] | 2022-01-04 | [
[
"Huang",
"Jessie",
""
],
[
"Busch",
"Erica L.",
""
],
[
"Wallenstein",
"Tom",
""
],
[
"Gerasimiuk",
"Michal",
""
],
[
"Benz",
"Andrew",
""
],
[
"Lajoie",
"Guillaume",
""
],
[
"Wolf",
"Guy",
""
],
[
"Turk-Browne",
"Nicholas B.",
""
],
[
"Krishnaswamy",
"Smita",
""
]
] | Functional magnetic resonance imaging (fMRI) is a notoriously noisy measurement of brain activity because of the large variations between individuals, signals marred by environmental differences during collection, and spatiotemporal averaging required by the measurement resolution. In addition, the data is extremely high dimensional, with the space of the activity typically having much lower intrinsic dimension. In order to understand the connection between stimuli of interest and brain activity, and analyze differences and commonalities between subjects, it becomes important to learn a meaningful embedding of the data that denoises, and reveals its intrinsic structure. Specifically, we assume that while noise varies significantly between individuals, true responses to stimuli will share common, low-dimensional features between subjects which are jointly discoverable. Similar approaches have been exploited previously but they have mainly used linear methods such as PCA and shared response modeling (SRM). In contrast, we propose a neural network called MRMD-AE (manifold-regularized multiple decoder, autoencoder), that learns a common embedding from multiple subjects in an experiment while retaining the ability to decode to individual raw fMRI signals. We show that our learned common space represents an extensible manifold (where new points not seen during training can be mapped), improves the classification accuracy of stimulus features of unseen timepoints, as well as improves cross-subject translation of fMRI signals. We believe this framework can be used for many downstream applications such as guided brain-computer interface (BCI) training in the future. |
1410.2942 | Daril Vilhena | Daril A. Vilhena and Alexandre Antonelli | Beyond similarity: A network approach for identifying and delimiting
biogeographical regions | 5 figures and 1 supporting figure | null | 10.1038/ncomms7848 | null | q-bio.QM q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Biogeographical regions (geographically distinct assemblages of species and
communities) constitute a cornerstone for ecology, biogeography, evolution and
conservation biology. Species turnover measures are often used to quantify
biodiversity patterns, but algorithms based on similarity and clustering are
highly sensitive to common biases and intricacies of species distribution data.
Here we apply a community detection approach from network theory that
incorporates complex, higher order presence-absence patterns. We demonstrate
the performance of the method by applying it to all amphibian species in the
world (c. 6,100 species), all vascular plant species of the USA (c. 17,600),
and a hypothetical dataset containing a zone of biotic transition. In
comparison with current methods, our approach tackles the challenges posed by
transition zones and succeeds in identifying a larger number of commonly
recognised biogeographical regions. This method constitutes an important
advance towards objective, data derived identification and delimitation of the
world's biogeographical regions.
| [
{
"created": "Sat, 11 Oct 2014 03:40:31 GMT",
"version": "v1"
}
] | 2015-08-19 | [
[
"Vilhena",
"Daril A.",
""
],
[
"Antonelli",
"Alexandre",
""
]
] | Biogeographical regions (geographically distinct assemblages of species and communities) constitute a cornerstone for ecology, biogeography, evolution and conservation biology. Species turnover measures are often used to quantify biodiversity patterns, but algorithms based on similarity and clustering are highly sensitive to common biases and intricacies of species distribution data. Here we apply a community detection approach from network theory that incorporates complex, higher order presence-absence patterns. We demonstrate the performance of the method by applying it to all amphibian species in the world (c. 6,100 species), all vascular plant species of the USA (c. 17,600), and a hypothetical dataset containing a zone of biotic transition. In comparison with current methods, our approach tackles the challenges posed by transition zones and succeeds in identifying a larger number of commonly recognised biogeographical regions. This method constitutes an important advance towards objective, data derived identification and delimitation of the world's biogeographical regions. |
2304.07805 | Sonja Aits | Rafsan Ahmed, Petter Berntsson, Alexander Skafte, Salma Kazemi Rashed,
Marcus Klang, Adam Barvesten, Ola Olde, William Lindholm, Antton Lamarca
Arrizabalaga, Pierre Nugues, Sonja Aits | EasyNER: A Customizable Easy-to-Use Pipeline for Deep Learning- and
Dictionary-based Named Entity Recognition from Medical Text | null | null | null | null | q-bio.QM cs.CL | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Background Medical research generates millions of publications and it is a
great challenge for researchers to utilize this information in full since its
scale and complexity greatly surpasses human reading capabilities. Automated
text mining can help extract and connect information spread across this large
body of literature but this technology is not easily accessible to life
scientists. Results Here, we developed an easy-to-use end-to-end pipeline for
deep learning- and dictionary-based named entity recognition (NER) of typical
entities found in medical research articles, including diseases, cells,
chemicals, genes/proteins, and species. The pipeline can access and process
large medical research article collections (PubMed, CORD-19) or raw text and
incorporates a series of deep learning models fine-tuned on the HUNER corpora
collection. In addition, the pipeline can perform dictionary-based NER related
to COVID-19 and other medical topics. Users can also load their own NER models
and dictionaries to include additional entities. The output consists of
publication-ready ranked lists and graphs of detected entities and files
containing the annotated texts. An associated script allows rapid inspection of
the results for specific entities of interest. As model use cases, the pipeline
was deployed on two collections of autophagy-related abstracts from PubMed and
on the CORD19 dataset, a collection of 764 398 research article abstracts
related to COVID-19. Conclusions The NER pipeline we present is applicable in a
variety of medical research settings and makes customizable text mining
accessible to life scientists.
| [
{
"created": "Sun, 16 Apr 2023 15:17:56 GMT",
"version": "v1"
},
{
"created": "Thu, 7 Mar 2024 11:52:11 GMT",
"version": "v2"
}
] | 2024-03-08 | [
[
"Ahmed",
"Rafsan",
""
],
[
"Berntsson",
"Petter",
""
],
[
"Skafte",
"Alexander",
""
],
[
"Rashed",
"Salma Kazemi",
""
],
[
"Klang",
"Marcus",
""
],
[
"Barvesten",
"Adam",
""
],
[
"Olde",
"Ola",
""
],
[
"Lindholm",
"William",
""
],
[
"Arrizabalaga",
"Antton Lamarca",
""
],
[
"Nugues",
"Pierre",
""
],
[
"Aits",
"Sonja",
""
]
] | Background Medical research generates millions of publications and it is a great challenge for researchers to utilize this information in full since its scale and complexity greatly surpasses human reading capabilities. Automated text mining can help extract and connect information spread across this large body of literature but this technology is not easily accessible to life scientists. Results Here, we developed an easy-to-use end-to-end pipeline for deep learning- and dictionary-based named entity recognition (NER) of typical entities found in medical research articles, including diseases, cells, chemicals, genes/proteins, and species. The pipeline can access and process large medical research article collections (PubMed, CORD-19) or raw text and incorporates a series of deep learning models fine-tuned on the HUNER corpora collection. In addition, the pipeline can perform dictionary-based NER related to COVID-19 and other medical topics. Users can also load their own NER models and dictionaries to include additional entities. The output consists of publication-ready ranked lists and graphs of detected entities and files containing the annotated texts. An associated script allows rapid inspection of the results for specific entities of interest. As model use cases, the pipeline was deployed on two collections of autophagy-related abstracts from PubMed and on the CORD19 dataset, a collection of 764 398 research article abstracts related to COVID-19. Conclusions The NER pipeline we present is applicable in a variety of medical research settings and makes customizable text mining accessible to life scientists. |
q-bio/0701021 | Chris Wiggins PhD | Manuel Middendorf, Anshul Kundaje, Mihir Shah, Yoav Freund, Chris H.
Wiggins, and Christina Leslie | Motif Discovery through Predictive Modeling of Gene Regulation | RECOMB 2005 | Research in Computational Molecular Biology 2005 | 10.1007/11415770_41 | null | q-bio.GN | null | We present MEDUSA, an integrative method for learning motif models of
transcription factor binding sites by incorporating promoter sequence and gene
expression data. We use a modern large-margin machine learning approach, based
on boosting, to enable feature selection from the high-dimensional search space
of candidate binding sequences while avoiding overfitting. At each iteration of
the algorithm, MEDUSA builds a motif model whose presence in the promoter
region of a gene, coupled with activity of a regulator in an experiment, is
predictive of differential expression. In this way, we learn motifs that are
functional and predictive of regulatory response rather than motifs that are
simply overrepresented in promoter sequences. Moreover, MEDUSA produces a model
of the transcriptional control logic that can predict the expression of any
gene in the organism, given the sequence of the promoter region of the target
gene and the expression state of a set of known or putative transcription
factors and signaling molecules. Each motif model is either a $k$-length
sequence, a dimer, or a PSSM that is built by agglomerative probabilistic
clustering of sequences with similar boosting loss. By applying MEDUSA to a set
of environmental stress response expression data in yeast, we learn motifs
whose ability to predict differential expression of target genes outperforms
motifs from the TRANSFAC dataset and from a previously published candidate set
of PSSMs. We also show that MEDUSA retrieves many experimentally confirmed
binding sites associated with environmental stress response from the
literature.
| [
{
"created": "Mon, 15 Jan 2007 03:51:56 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Middendorf",
"Manuel",
""
],
[
"Kundaje",
"Anshul",
""
],
[
"Shah",
"Mihir",
""
],
[
"Freund",
"Yoav",
""
],
[
"Wiggins",
"Chris H.",
""
],
[
"Leslie",
"Christina",
""
]
] | We present MEDUSA, an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data. We use a modern large-margin machine learning approach, based on boosting, to enable feature selection from the high-dimensional search space of candidate binding sequences while avoiding overfitting. At each iteration of the algorithm, MEDUSA builds a motif model whose presence in the promoter region of a gene, coupled with activity of a regulator in an experiment, is predictive of differential expression. In this way, we learn motifs that are functional and predictive of regulatory response rather than motifs that are simply overrepresented in promoter sequences. Moreover, MEDUSA produces a model of the transcriptional control logic that can predict the expression of any gene in the organism, given the sequence of the promoter region of the target gene and the expression state of a set of known or putative transcription factors and signaling molecules. Each motif model is either a $k$-length sequence, a dimer, or a PSSM that is built by agglomerative probabilistic clustering of sequences with similar boosting loss. By applying MEDUSA to a set of environmental stress response expression data in yeast, we learn motifs whose ability to predict differential expression of target genes outperforms motifs from the TRANSFAC dataset and from a previously published candidate set of PSSMs. We also show that MEDUSA retrieves many experimentally confirmed binding sites associated with environmental stress response from the literature. |
1503.04072 | Sol Lim | Sol Lim, Marcus Kaiser | Developmental time windows for axon growth influence neuronal network
topology | Biol Cybern. 2015 Jan 30. [Epub ahead of print] | null | 10.1007/s00422-014-0641-3 | null | q-bio.NC physics.bio-ph physics.soc-ph | http://creativecommons.org/licenses/by/3.0/ | Early brain connectivity development consists of multiple stages: birth of
neurons, their migration and the subsequent growth of axons and dendrites. Each
stage occurs within a certain period of time depending on types of neurons and
cortical layers. Forming synapses between neurons either by growing axons
starting at similar times for all neurons (much-overlapped time windows) or at
different time points (less-overlapped) may affect the topological and spatial
properties of neuronal networks. Here, we explore the extreme cases of axon
formation especially concerning short-distance connectivity during early
development, either starting at the same time for all neurons (parallel, i.e.
maximally-overlapped time windows) or occurring for each neuron separately one
neuron after another (serial, i.e. no overlaps in time windows). For both
cases, the number of potential and established synapses remained comparable.
Topological and spatial properties, however, differed: neurons that started
axon growth early on in serial growth achieved higher out-degrees, higher local
efficiency, and longer axon lengths while neurons demonstrated more homogeneous
connectivity patterns for parallel growth. Second, connection probability
decreased more rapidly with distance between neurons for parallel growth than
for serial growth. Third, bidirectional connections were more numerous for
parallel growth. Finally, we tested our predictions with C. elegans data.
Together, this indicates that time windows for axon growth influence the
topological and spatial properties of neuronal networks opening the possibility
to a posteriori estimate developmental mechanisms based on network properties
of a developed network.
| [
{
"created": "Fri, 13 Mar 2015 14:07:23 GMT",
"version": "v1"
}
] | 2015-03-16 | [
[
"Lim",
"Sol",
""
],
[
"Kaiser",
"Marcus",
""
]
] | Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation especially concerning short-distance connectivity during early development, either starting at the same time for all neurons (parallel, i.e. maximally-overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e. no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency, and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network. |
2004.09849 | James Grist | James T. Grist, Stephanie Withey, Christopher Bennett, Heather E. L.
Rose, Lesley MacPherson, Adam Oates, Stephen Powell, Jan Novak, Laurence
Abernethy, Barry Pizer, Simon Bailey, Steven C. Clifford, Dipayan Mitra,
Theodoros N. Arvanitis, Dorothee P. Auer, Shivaram Avula, Richard Grundy,
Andrew C Peet | Combining multi-site Magnetic Resonance Imaging with machine learning
predicts survival in paediatric brain tumours | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Background Brain tumours represent the highest cause of mortality in the
paediatric oncological population. Diagnosis is commonly performed with
magnetic resonance imaging and spectroscopy. Survival biomarkers are
challenging to identify due to the relatively low numbers of individual tumour
types, especially for rare tumour types such as atypical rhabdoid tumours.
Methods 69 children with biopsy-confirmed brain tumours were recruited into
this study. All participants had both perfusion and diffusion weighted imaging
performed at diagnosis. Data were processed using conventional methods, and a
Bayesian survival analysis performed. Unsupervised and supervised machine
learning were performed with the survival features, to determine novel
sub-groups related to survival. Sub-group analysis was undertaken to understand
differences in imaging features, which pertain to survival.
Findings Survival analysis showed that a combination of diffusion and
perfusion imaging were able to determine two novel sub-groups of brain tumours
with different survival characteristics (p <0.01), which were subsequently
classified with high accuracy (98%) by a neural network. Further analysis of
high-grade tumours showed a marked difference in survival (p=0.029) between the
two clusters with high risk and low risk imaging features.
Interpretation This study has developed a novel model of survival for
paediatric brain tumours, with an implementation ready for integration into
clinical practice. Results show that tumour perfusion plays a key role in
determining survival in brain tumours and should be considered as a high
priority for future imaging protocols.
| [
{
"created": "Tue, 21 Apr 2020 09:24:46 GMT",
"version": "v1"
}
] | 2020-04-22 | [
[
"Grist",
"James T.",
""
],
[
"Withey",
"Stephanie",
""
],
[
"Bennett",
"Christopher",
""
],
[
"Rose",
"Heather E. L.",
""
],
[
"MacPherson",
"Lesley",
""
],
[
"Oates",
"Adam",
""
],
[
"Powell",
"Stephen",
""
],
[
"Novak",
"Jan",
""
],
[
"Abernethy",
"Laurence",
""
],
[
"Pizer",
"Barry",
""
],
[
"Bailey",
"Simon",
""
],
[
"Clifford",
"Steven C.",
""
],
[
"Mitra",
"Dipayan",
""
],
[
"Arvanitis",
"Theodoros N.",
""
],
[
"Auer",
"Dorothee P.",
""
],
[
"Avula",
"Shivaram",
""
],
[
"Grundy",
"Richard",
""
],
[
"Peet",
"Andrew C",
""
]
] | Background Brain tumours represent the highest cause of mortality in the paediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging and spectroscopy. Survival biomarkers are challenging to identify due to the relatively low numbers of individual tumour types, especially for rare tumour types such as atypical rhabdoid tumours. Methods 69 children with biopsy-confirmed brain tumours were recruited into this study. All participants had both perfusion and diffusion weighted imaging performed at diagnosis. Data were processed using conventional methods, and a Bayesian survival analysis performed. Unsupervised and supervised machine learning were performed with the survival features, to determine novel sub-groups related to survival. Sub-group analysis was undertaken to understand differences in imaging features, which pertain to survival. Findings Survival analysis showed that a combination of diffusion and perfusion imaging were able to determine two novel sub-groups of brain tumours with different survival characteristics (p <0.01), which were subsequently classified with high accuracy (98%) by a neural network. Further analysis of high-grade tumours showed a marked difference in survival (p=0.029) between the two clusters with high risk and low risk imaging features. Interpretation This study has developed a novel model of survival for paediatric brain tumours, with an implementation ready for integration into clinical practice. Results show that tumour perfusion plays a key role in determining survival in brain tumours and should be considered as a high priority for future imaging protocols. |
2210.08171 | Tianxiao Li | Tianxiao Li, Hongyu Guo, Filippo Grazioli, Mark Gerstein, Martin
Renqiang Min | Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering | null | null | null | null | q-bio.BM | http://creativecommons.org/licenses/by-nc-sa/4.0/ | In protein biophysics, the separation between the functionally important
residues (forming the active site or binding surface) and those that create the
overall structure (the fold) is a well-established and fundamental concept.
Identifying and modifying those functional sites is critical for protein
engineering but computationally non-trivial, and requires significant domain
knowledge. To automate this process from a data-driven perspective, we propose
a disentangled Wasserstein autoencoder with an auxiliary classifier, which
isolates the function-related patterns from the rest with theoretical
guarantees. This enables one-pass protein sequence editing and improves the
understanding of the resulting sequences and editing actions involved. To
demonstrate its effectiveness, we apply it to T-cell receptors (TCRs), a
well-studied structure-function case. We show that our method can be used to
alter the function of TCRs without changing the structural backbone,
outperforming several competing methods in generation quality and efficiency,
and requiring only 10% of the running time needed by baseline models. To our
knowledge, this is the first approach that utilizes disentangled
representations for TCR engineering.
| [
{
"created": "Sat, 15 Oct 2022 02:59:05 GMT",
"version": "v1"
},
{
"created": "Mon, 16 Oct 2023 17:05:38 GMT",
"version": "v2"
}
] | 2023-10-17 | [
[
"Li",
"Tianxiao",
""
],
[
"Guo",
"Hongyu",
""
],
[
"Grazioli",
"Filippo",
""
],
[
"Gerstein",
"Mark",
""
],
[
"Min",
"Martin Renqiang",
""
]
] | In protein biophysics, the separation between the functionally important residues (forming the active site or binding surface) and those that create the overall structure (the fold) is a well-established and fundamental concept. Identifying and modifying those functional sites is critical for protein engineering but computationally non-trivial, and requires significant domain knowledge. To automate this process from a data-driven perspective, we propose a disentangled Wasserstein autoencoder with an auxiliary classifier, which isolates the function-related patterns from the rest with theoretical guarantees. This enables one-pass protein sequence editing and improves the understanding of the resulting sequences and editing actions involved. To demonstrate its effectiveness, we apply it to T-cell receptors (TCRs), a well-studied structure-function case. We show that our method can be used to alter the function of TCRs without changing the structural backbone, outperforming several competing methods in generation quality and efficiency, and requiring only 10% of the running time needed by baseline models. To our knowledge, this is the first approach that utilizes disentangled representations for TCR engineering. |
0710.4481 | Florian Markowetz | Achim Tresch and Florian Markowetz | Structure Learning in Nested Effects Models | null | Stat Appl in Gen and Mol Bio (SAGMB): Vol. 7: Iss. 1, Article 9,
2008 | 10.2202/1544-6115.1332 | null | q-bio.QM q-bio.MN | null | Nested Effects Models (NEMs) are a class of graphical models introduced to
analyze the results of gene perturbation screens. NEMs explore noisy subset
relations between the high-dimensional outputs of phenotyping studies, e.g. the
effects showing in gene expression profiles or as morphological features of the
perturbed cell.
In this paper we expand the statistical basis of NEMs in four directions:
First, we derive a new formula for the likelihood function of a NEM, which
generalizes previous results for binary data. Second, we prove model
identifiability under mild assumptions. Third, we show that the new formulation
of the likelihood allows to efficiently traverse model space. Fourth, we
incorporate prior knowledge and an automated variable selection criterion to
decrease the influence of noise in the data.
| [
{
"created": "Wed, 24 Oct 2007 14:19:32 GMT",
"version": "v1"
},
{
"created": "Sun, 20 Jan 2008 23:08:38 GMT",
"version": "v2"
}
] | 2010-10-08 | [
[
"Tresch",
"Achim",
""
],
[
"Markowetz",
"Florian",
""
]
] | Nested Effects Models (NEMs) are a class of graphical models introduced to analyze the results of gene perturbation screens. NEMs explore noisy subset relations between the high-dimensional outputs of phenotyping studies, e.g. the effects showing in gene expression profiles or as morphological features of the perturbed cell. In this paper we expand the statistical basis of NEMs in four directions: First, we derive a new formula for the likelihood function of a NEM, which generalizes previous results for binary data. Second, we prove model identifiability under mild assumptions. Third, we show that the new formulation of the likelihood allows to efficiently traverse model space. Fourth, we incorporate prior knowledge and an automated variable selection criterion to decrease the influence of noise in the data. |
1305.6320 | Rostislav Serota | Tao Ma, John G. Holden and R.A. Serota | Distribution of Human Response Times | 11 pages, 19 figures. arXiv admin note: substantial text overlap with
arXiv:1305.4173 | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We demonstrate that distributions of human response times have power-law
tails and, among closed-form distributions, are best fit by the generalized
inverse gamma distribution. We speculate that the task difficulty tracks the
half-width of the distribution and show that it is related to the exponent of
the power-law tail.
| [
{
"created": "Mon, 27 May 2013 20:06:02 GMT",
"version": "v1"
}
] | 2013-05-29 | [
[
"Ma",
"Tao",
""
],
[
"Holden",
"John G.",
""
],
[
"Serota",
"R. A.",
""
]
] | We demonstrate that distributions of human response times have power-law tails and, among closed-form distributions, are best fit by the generalized inverse gamma distribution. We speculate that the task difficulty tracks the half-width of the distribution and show that it is related to the exponent of the power-law tail. |
1708.06844 | Jeferson J. Arenzon | Gabriel A. Canova and J. J. Arenzon | Risk and interaction aversion: screening mechanisms in the Prisoner's
Dilemma game | 8 pages | null | 10.1007/s10955-017-1873-0 | null | q-bio.PE physics.bio-ph physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | When the interactions between cooperators (C) and defectors (D) can be
partially avoided within a population, there may be an overall enhancement of
cooperation. One example of such screening mechanism occurs in the presence of
risk-averse agents (loners, L) that are neutral towards others, i.e., both L
and its opponent, whatever its strategy, receive the same payoff. Their
presence in the Prisoner's Dilemma (PD) game sustains the coexistence of
cooperators and defectors far beyond the level attained in their absence.
Another screening mechanism is a heterogeneous landscape obtained, for example,
by site diluting the lattice. In this case, cooperation is enhanced with some
fraction of such inactive, interaction-averse sites. By considering the
interplay of both mechanisms, we show that there is an explosive increase in
the range of densities, just above the percolation threshold, where neutrality
is prevented and loners become extinct, the behavior reverting to the pure PD
game. Interestingly, this occurs despite defectors being usually abundant in
that region. This has to be compared with the corresponding loner-free region
in the undiluted case that, besides being very small, is dominatedby
cooperators.
| [
{
"created": "Tue, 22 Aug 2017 22:45:32 GMT",
"version": "v1"
}
] | 2017-09-20 | [
[
"Canova",
"Gabriel A.",
""
],
[
"Arenzon",
"J. J.",
""
]
] | When the interactions between cooperators (C) and defectors (D) can be partially avoided within a population, there may be an overall enhancement of cooperation. One example of such screening mechanism occurs in the presence of risk-averse agents (loners, L) that are neutral towards others, i.e., both L and its opponent, whatever its strategy, receive the same payoff. Their presence in the Prisoner's Dilemma (PD) game sustains the coexistence of cooperators and defectors far beyond the level attained in their absence. Another screening mechanism is a heterogeneous landscape obtained, for example, by site diluting the lattice. In this case, cooperation is enhanced with some fraction of such inactive, interaction-averse sites. By considering the interplay of both mechanisms, we show that there is an explosive increase in the range of densities, just above the percolation threshold, where neutrality is prevented and loners become extinct, the behavior reverting to the pure PD game. Interestingly, this occurs despite defectors being usually abundant in that region. This has to be compared with the corresponding loner-free region in the undiluted case that, besides being very small, is dominatedby cooperators. |
1701.05278 | Woo Seong Jo | Woo Seong Jo, Hwang-Yong Kim and Beom Jun Kim | Climate change alters diffusion of forest pest: A model study | 8 pages, 3 figures | Journal of the Korean Physical Society 70, 108-115 (2017) | 10.3938/jkps.70.108 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Population dynamics with spatial information is applied to understand the
spread of pests. We introduce a model describing how pests spread in discrete
space. The number of pest descendants at each site is controlled by local
information such as temperature, precipitation, and the density of pine trees.
Our simulation leads to a pest spreading pattern comparable to the real data
for pine needle gall midge in the past. We also simulate the model in two
different climate conditions based on two different representative
concentration pathways scenarios for the future. We observe that after an
initial stage of a slow spread of pests, a sudden change in the spreading speed
occurs, which is soon followed by a large-scale outbreak. We found that a
future climate change causes the outbreak point to occur earlier and that the
detailed spatio-temporal pattern of the spread depends on the source position
from which the initial pest infection starts.
| [
{
"created": "Thu, 19 Jan 2017 01:59:15 GMT",
"version": "v1"
}
] | 2017-01-20 | [
[
"Jo",
"Woo Seong",
""
],
[
"Kim",
"Hwang-Yong",
""
],
[
"Kim",
"Beom Jun",
""
]
] | Population dynamics with spatial information is applied to understand the spread of pests. We introduce a model describing how pests spread in discrete space. The number of pest descendants at each site is controlled by local information such as temperature, precipitation, and the density of pine trees. Our simulation leads to a pest spreading pattern comparable to the real data for pine needle gall midge in the past. We also simulate the model in two different climate conditions based on two different representative concentration pathways scenarios for the future. We observe that after an initial stage of a slow spread of pests, a sudden change in the spreading speed occurs, which is soon followed by a large-scale outbreak. We found that a future climate change causes the outbreak point to occur earlier and that the detailed spatio-temporal pattern of the spread depends on the source position from which the initial pest infection starts. |
0804.1080 | Ginestra Bianconi | Ginestra Bianconi | Flux distribution in metabolic networks close to optimal biomass
production | (4 pages,2 figures) | Phys. Rev. E 78, 035101 (2008). | 10.1103/PhysRevE.78.035101 | null | q-bio.MN cond-mat.stat-mech | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study a statistical model describing the steady state distribution of the
fluxes in a metabolic network. The resulting model on continuous variables can
be solved by the cavity method. In particular analytical tractability is
possible solving the cavity equation over an ensemble of networks with the same
degree distribution of the real metabolic network. The flux distribution that
optimizes production of biomass has a fat tail with a power-law exponent
independent on the structural properties of the underling network. These
results are in complete agreement with the Flux-Balance-Analysis outcome of the
same system and in qualitative agreement with the experimental results.
| [
{
"created": "Mon, 7 Apr 2008 17:00:23 GMT",
"version": "v1"
},
{
"created": "Tue, 8 Apr 2008 09:38:47 GMT",
"version": "v2"
}
] | 2009-11-13 | [
[
"Bianconi",
"Ginestra",
""
]
] | We study a statistical model describing the steady state distribution of the fluxes in a metabolic network. The resulting model on continuous variables can be solved by the cavity method. In particular analytical tractability is possible solving the cavity equation over an ensemble of networks with the same degree distribution of the real metabolic network. The flux distribution that optimizes production of biomass has a fat tail with a power-law exponent independent on the structural properties of the underling network. These results are in complete agreement with the Flux-Balance-Analysis outcome of the same system and in qualitative agreement with the experimental results. |
2308.07136 | Umberto Lupo | Umberto Lupo, Damiano Sgarbossa, Anne-Florence Bitbol | Pairing interacting protein sequences using masked language modeling | 33 pages, 14 figures, 2 tables | null | null | null | q-bio.BM cs.LG | http://creativecommons.org/licenses/by/4.0/ | Predicting which proteins interact together from amino-acid sequences is an
important task. We develop a method to pair interacting protein sequences which
leverages the power of protein language models trained on multiple sequence
alignments, such as MSA Transformer and the EvoFormer module of AlphaFold. We
formulate the problem of pairing interacting partners among the paralogs of two
protein families in a differentiable way. We introduce a method called DiffPALM
that solves it by exploiting the ability of MSA Transformer to fill in masked
amino acids in multiple sequence alignments using the surrounding context. MSA
Transformer encodes coevolution between functionally or structurally coupled
amino acids. We show that it captures inter-chain coevolution, while it was
trained on single-chain data, which means that it can be used
out-of-distribution. Relying on MSA Transformer without fine-tuning, DiffPALM
outperforms existing coevolution-based pairing methods on difficult benchmarks
of shallow multiple sequence alignments extracted from ubiquitous prokaryotic
protein datasets. It also outperforms an alternative method based on a
state-of-the-art protein language model trained on single sequences. Paired
alignments of interacting protein sequences are a crucial ingredient of
supervised deep learning methods to predict the three-dimensional structure of
protein complexes. DiffPALM substantially improves the structure prediction of
some eukaryotic protein complexes by AlphaFold-Multimer, without significantly
deteriorating any of those we tested. It also achieves competitive performance
with using orthology-based pairing.
| [
{
"created": "Mon, 14 Aug 2023 13:42:09 GMT",
"version": "v1"
}
] | 2023-08-15 | [
[
"Lupo",
"Umberto",
""
],
[
"Sgarbossa",
"Damiano",
""
],
[
"Bitbol",
"Anne-Florence",
""
]
] | Predicting which proteins interact together from amino-acid sequences is an important task. We develop a method to pair interacting protein sequences which leverages the power of protein language models trained on multiple sequence alignments, such as MSA Transformer and the EvoFormer module of AlphaFold. We formulate the problem of pairing interacting partners among the paralogs of two protein families in a differentiable way. We introduce a method called DiffPALM that solves it by exploiting the ability of MSA Transformer to fill in masked amino acids in multiple sequence alignments using the surrounding context. MSA Transformer encodes coevolution between functionally or structurally coupled amino acids. We show that it captures inter-chain coevolution, while it was trained on single-chain data, which means that it can be used out-of-distribution. Relying on MSA Transformer without fine-tuning, DiffPALM outperforms existing coevolution-based pairing methods on difficult benchmarks of shallow multiple sequence alignments extracted from ubiquitous prokaryotic protein datasets. It also outperforms an alternative method based on a state-of-the-art protein language model trained on single sequences. Paired alignments of interacting protein sequences are a crucial ingredient of supervised deep learning methods to predict the three-dimensional structure of protein complexes. DiffPALM substantially improves the structure prediction of some eukaryotic protein complexes by AlphaFold-Multimer, without significantly deteriorating any of those we tested. It also achieves competitive performance with using orthology-based pairing. |
2103.08023 | Rui Wang | Rui Wang, Jiahui Chen, Kaifu Gao, and Guo-Wei Wei | Vaccine-escape and fast-growing mutations in the United Kingdom, the
United States, Singapore, Spain, South Africa, and other COVID-19-devastated
countries | 20 pages, 13 figures | null | null | null | q-bio.PE q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recently, the SARS-CoV-2 variants from the United Kingdom (UK), South Africa,
and Brazil have received much attention for their increased infectivity,
potentially high virulence, and possible threats to existing vaccines and
antibody therapies. The question remains if there are other more infectious
variants transmitted around the world. We carry out a large-scale study of
252,874 SARS-CoV-2 genome isolates from patients to identify many other rapidly
growing mutations on the spike (S) protein receptor-binding domain (RDB). We
reveal that 88 out of 95 significant mutations that were observed more than 10
times strengthen the binding between the RBD and the host
angiotensin-converting enzyme 2 (ACE2), indicating the virus evolves toward
more infectious variants. In particular, we discover new fast-growing RBD
mutations N439K, L452R, S477N, S477R, and N501T that also enhance the RBD and
ACE2 binding. We further unveil that mutation N501Y involved in United Kingdom
(UK), South Africa, and Brazil variants may moderately weaken the binding
between the RBD and many known antibodies, while mutations E484K and K417N
found in South Africa and Brazilian variants can potentially disrupt the
binding between the RDB and many known antibodies. Among three newly identified
fast-growing RBD mutations, L452R, which is now known as part of the California
variant B.1.427, and N501T are able to effectively weaken the binding of many
known antibodies with the RBD. Finally, we hypothesize that RBD mutations that
can simultaneously make SARS-CoV-2 more infectious and disrupt the existing
antibodies, called vaccine escape mutations, will pose an imminent threat to
the current crop of vaccines. A list of most likely vaccine escape mutations is
given, including N501Y, L452R, E484K, N501T, S494P, and K417N.
| [
{
"created": "Sun, 14 Mar 2021 20:13:50 GMT",
"version": "v1"
},
{
"created": "Sun, 21 Mar 2021 19:17:42 GMT",
"version": "v2"
}
] | 2021-03-23 | [
[
"Wang",
"Rui",
""
],
[
"Chen",
"Jiahui",
""
],
[
"Gao",
"Kaifu",
""
],
[
"Wei",
"Guo-Wei",
""
]
] | Recently, the SARS-CoV-2 variants from the United Kingdom (UK), South Africa, and Brazil have received much attention for their increased infectivity, potentially high virulence, and possible threats to existing vaccines and antibody therapies. The question remains if there are other more infectious variants transmitted around the world. We carry out a large-scale study of 252,874 SARS-CoV-2 genome isolates from patients to identify many other rapidly growing mutations on the spike (S) protein receptor-binding domain (RDB). We reveal that 88 out of 95 significant mutations that were observed more than 10 times strengthen the binding between the RBD and the host angiotensin-converting enzyme 2 (ACE2), indicating the virus evolves toward more infectious variants. In particular, we discover new fast-growing RBD mutations N439K, L452R, S477N, S477R, and N501T that also enhance the RBD and ACE2 binding. We further unveil that mutation N501Y involved in United Kingdom (UK), South Africa, and Brazil variants may moderately weaken the binding between the RBD and many known antibodies, while mutations E484K and K417N found in South Africa and Brazilian variants can potentially disrupt the binding between the RDB and many known antibodies. Among three newly identified fast-growing RBD mutations, L452R, which is now known as part of the California variant B.1.427, and N501T are able to effectively weaken the binding of many known antibodies with the RBD. Finally, we hypothesize that RBD mutations that can simultaneously make SARS-CoV-2 more infectious and disrupt the existing antibodies, called vaccine escape mutations, will pose an imminent threat to the current crop of vaccines. A list of most likely vaccine escape mutations is given, including N501Y, L452R, E484K, N501T, S494P, and K417N. |
1801.04919 | Hyobin Kim | Hyobin Kim and Hiroki Sayama | How Criticality of Gene Regulatory Networks Affects the Resulting
Morphogenesis under Genetic Perturbations | 34 pages, 17 figures, 1 table | null | null | null | q-bio.MN nlin.AO nlin.PS physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Whereas the relationship between criticality of gene regulatory networks
(GRNs) and dynamics of GRNs at a single cell level has been vigorously studied,
the relationship between the criticality of GRNs and system properties at a
higher level has remained unexplored. Here we aim at revealing a potential role
of criticality of GRNs at a multicellular level which are hard to uncover
through the single-cell-level studies, especially from an evolutionary
viewpoint. Our model simulated the growth of a cell population from a single
seed cell. All the cells were assumed to have identical GRNs. We induced
genetic perturbations to the GRN of the seed cell by adding, deleting, or
switching a regulatory link between a pair of genes. From numerical
simulations, we found that the criticality of GRNs facilitated the formation of
nontrivial morphologies when the GRNs were critical in the presence of the
evolutionary perturbations. Moreover, the criticality of GRNs produced
topologically homogenous cell clusters by adjusting the spatial arrangements of
cells, which led to the formation of nontrivial morphogenetic patterns. Our
findings corresponded to an epigenetic viewpoint that heterogeneous and complex
features emerge from homogeneous and less complex components through the
interactions among them. Thus, our results imply that highly structured tissues
or organs in morphogenesis of multicellular organisms might stem from the
criticality of GRNs.
| [
{
"created": "Sat, 13 Jan 2018 02:22:03 GMT",
"version": "v1"
},
{
"created": "Fri, 26 Jan 2018 04:46:17 GMT",
"version": "v2"
}
] | 2018-01-29 | [
[
"Kim",
"Hyobin",
""
],
[
"Sayama",
"Hiroki",
""
]
] | Whereas the relationship between criticality of gene regulatory networks (GRNs) and dynamics of GRNs at a single cell level has been vigorously studied, the relationship between the criticality of GRNs and system properties at a higher level has remained unexplored. Here we aim at revealing a potential role of criticality of GRNs at a multicellular level which are hard to uncover through the single-cell-level studies, especially from an evolutionary viewpoint. Our model simulated the growth of a cell population from a single seed cell. All the cells were assumed to have identical GRNs. We induced genetic perturbations to the GRN of the seed cell by adding, deleting, or switching a regulatory link between a pair of genes. From numerical simulations, we found that the criticality of GRNs facilitated the formation of nontrivial morphologies when the GRNs were critical in the presence of the evolutionary perturbations. Moreover, the criticality of GRNs produced topologically homogenous cell clusters by adjusting the spatial arrangements of cells, which led to the formation of nontrivial morphogenetic patterns. Our findings corresponded to an epigenetic viewpoint that heterogeneous and complex features emerge from homogeneous and less complex components through the interactions among them. Thus, our results imply that highly structured tissues or organs in morphogenesis of multicellular organisms might stem from the criticality of GRNs. |
q-bio/0509034 | Alexander Kulminski | A. Kulminski, A. Yashin, S. Ukraintseva, I. Akushevich, K. Arbeev, K.
Land and K. Manton | Age-Associated Disorders As A Proxy Measure Of Biological Age: Findings
From the NLTCS Data | 14 pages, 3 figures, and 5 tables | null | null | null | q-bio.PE | null | Background: The relative contribution of different aging-associated processes
to the age phenotype may differ among individuals, creating variability in
aging manifestations among age-peers. Capturing this variability can
significantly advance understanding the aging and mortality. An index of
age-associated health disorders (deficits), called a "frailty index" (FI),
appears to be a promising characteristic of such processes. In this study we
address the connections of the FI with age focusing on disabled individuals who
might be at excessive risk of frailty. Methods: The National Long Term Care
Survey (NLTCS) assessed health and functioning of the U.S. elderly in 1982,
1984, 1989, 1994, and 1999. Detailed information for our sample was assessed
from about 26,700 interviews. The individual FI is defined as a proportion of
deficits for a given person. We perform cross-sectional empirical analysis of
the FI age-patterns. Results: FI in the NLTCS exhibits accelerated (quadratic)
increase with age. Deficits might accumulate faster among the elderly who, at
younger ages, had a low mean FI ("healthy" group) than a high FI ("disabled"
group). Age-patterns for "healthy" and "disabled" groups converge at advanced
ages. The rate of deficit accumulation is sex-sensitive. Convergence of the
(sex-specific) FI for "healthy" and "disabled" groups in later ages determines
biological age limits, associated with given levels of health-maintenance in
the society, which correspond to 109.4 years for females and 92.5 years for
males. Conclusions: The FI can be employed as a measure of biological age and
population heterogeneity for modeling aging processes and mortality in elderly
individuals.
| [
{
"created": "Sun, 25 Sep 2005 15:52:39 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Kulminski",
"A.",
""
],
[
"Yashin",
"A.",
""
],
[
"Ukraintseva",
"S.",
""
],
[
"Akushevich",
"I.",
""
],
[
"Arbeev",
"K.",
""
],
[
"Land",
"K.",
""
],
[
"Manton",
"K.",
""
]
] | Background: The relative contribution of different aging-associated processes to the age phenotype may differ among individuals, creating variability in aging manifestations among age-peers. Capturing this variability can significantly advance understanding the aging and mortality. An index of age-associated health disorders (deficits), called a "frailty index" (FI), appears to be a promising characteristic of such processes. In this study we address the connections of the FI with age focusing on disabled individuals who might be at excessive risk of frailty. Methods: The National Long Term Care Survey (NLTCS) assessed health and functioning of the U.S. elderly in 1982, 1984, 1989, 1994, and 1999. Detailed information for our sample was assessed from about 26,700 interviews. The individual FI is defined as a proportion of deficits for a given person. We perform cross-sectional empirical analysis of the FI age-patterns. Results: FI in the NLTCS exhibits accelerated (quadratic) increase with age. Deficits might accumulate faster among the elderly who, at younger ages, had a low mean FI ("healthy" group) than a high FI ("disabled" group). Age-patterns for "healthy" and "disabled" groups converge at advanced ages. The rate of deficit accumulation is sex-sensitive. Convergence of the (sex-specific) FI for "healthy" and "disabled" groups in later ages determines biological age limits, associated with given levels of health-maintenance in the society, which correspond to 109.4 years for females and 92.5 years for males. Conclusions: The FI can be employed as a measure of biological age and population heterogeneity for modeling aging processes and mortality in elderly individuals. |
1506.02208 | Susan Wardle | Susan G. Wardle, Nikolaus Kriegeskorte, Tijl Grootswagers, Seyed-Mahdi
Khaligh-Razavi and Thomas A. Carlson | Perceptual similarity of visual patterns predicts the similarity of
their dynamic neural activation patterns measured with MEG | 34 pages, 6 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Perceptual similarity is a cognitive judgment that represents the end-stage
of a complex cascade of hierarchical processing throughout visual cortex.
Previous studies have shown a correspondence between the similarity of
coarse-scale fMRI activation patterns and the perceived similarity of visual
stimuli, suggesting that visual objects that appear similar also share similar
underlying patterns of neural activation. Here we explore the temporal
relationship between the human brain's time-varying representation of visual
patterns and behavioral judgments of perceptual similarity. The visual stimuli
were abstract patterns constructed from identical perceptual units (oriented
Gabor patches) so that each pattern had a unique global form or perceptual
'Gestalt'. The visual stimuli were decodable from evoked neural activation
patterns measured with magnetoencephalography (MEG), however, stimuli differed
in the similarity of their neural representation as estimated by differences in
decodability. Early after stimulus onset (from 50ms), a model based on
retinotopic organization predicted the representational similarity of the
visual stimuli. Following the peak correlation between the retinotopic model
and neural data at 80ms, the neural representations quickly evolved so that
retinotopy no longer provided a sufficient account of the brain's time-varying
representation of the stimuli. Overall the strongest predictor of the brain's
representation was a model based on human judgments of perceptual similarity,
which reached the limits of the maximum correlation with the neural data
defined by the 'noise ceiling'. Our results show that large-scale brain
activation patterns contain a neural signature for the perceptual Gestalt of
composite visual features, and demonstrate a strong correspondence between
perception and complex patterns of brain activity.
| [
{
"created": "Sun, 7 Jun 2015 01:56:50 GMT",
"version": "v1"
},
{
"created": "Wed, 10 Feb 2016 04:13:59 GMT",
"version": "v2"
}
] | 2016-02-11 | [
[
"Wardle",
"Susan G.",
""
],
[
"Kriegeskorte",
"Nikolaus",
""
],
[
"Grootswagers",
"Tijl",
""
],
[
"Khaligh-Razavi",
"Seyed-Mahdi",
""
],
[
"Carlson",
"Thomas A.",
""
]
] | Perceptual similarity is a cognitive judgment that represents the end-stage of a complex cascade of hierarchical processing throughout visual cortex. Previous studies have shown a correspondence between the similarity of coarse-scale fMRI activation patterns and the perceived similarity of visual stimuli, suggesting that visual objects that appear similar also share similar underlying patterns of neural activation. Here we explore the temporal relationship between the human brain's time-varying representation of visual patterns and behavioral judgments of perceptual similarity. The visual stimuli were abstract patterns constructed from identical perceptual units (oriented Gabor patches) so that each pattern had a unique global form or perceptual 'Gestalt'. The visual stimuli were decodable from evoked neural activation patterns measured with magnetoencephalography (MEG), however, stimuli differed in the similarity of their neural representation as estimated by differences in decodability. Early after stimulus onset (from 50ms), a model based on retinotopic organization predicted the representational similarity of the visual stimuli. Following the peak correlation between the retinotopic model and neural data at 80ms, the neural representations quickly evolved so that retinotopy no longer provided a sufficient account of the brain's time-varying representation of the stimuli. Overall the strongest predictor of the brain's representation was a model based on human judgments of perceptual similarity, which reached the limits of the maximum correlation with the neural data defined by the 'noise ceiling'. Our results show that large-scale brain activation patterns contain a neural signature for the perceptual Gestalt of composite visual features, and demonstrate a strong correspondence between perception and complex patterns of brain activity. |
2401.15133 | Mar\'ia Teresa Moreno-Flores | N Plaza, D Sim\'on, J Sierra, MT Moreno-Flores | Transduction of an immortalized olfactory ensheathing glia cell line
with the green fluorescent protein (GFP) gene: evaluation of its
neuroregenerative capacity as a proof of concept | 22 pages, 3 Figures | Neurosci Lett. 2016. 612:25-31 | 10.1016/j.neulet.2015.12.001 | null | q-bio.CB | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Olfactory ensheathing glia (OEG) cells are known to foster axonal
regeneration of central nervous system (CNS) neurons. Several lines of
reversibly immortalized human OEG (ihOEG) have been previously established that
enabled to develop models for their validation in vitro and in vivo. In this
work, a constitutively GFP-expressing ihOEG cell line was obtained, and named
Ts14-GFP. Ts14-GFP neuroregenerative ability was similar to that found for the
parental line Ts14 and it can be assayed using in vivo transplantation
experimental paradigms, after spinal cord or optic nerve damage. Additionally,
we have engineered a low-regenerative ihOEG line, hTL2, using lentiviral
transduction of the large T antigen from SV40 virus, denominated from now on
Ts12. Ts12 can be used as a low regeneration control in these experiments.
| [
{
"created": "Fri, 26 Jan 2024 16:55:15 GMT",
"version": "v1"
}
] | 2024-01-30 | [
[
"Plaza",
"N",
""
],
[
"Simón",
"D",
""
],
[
"Sierra",
"J",
""
],
[
"Moreno-Flores",
"MT",
""
]
] | Olfactory ensheathing glia (OEG) cells are known to foster axonal regeneration of central nervous system (CNS) neurons. Several lines of reversibly immortalized human OEG (ihOEG) have been previously established that enabled to develop models for their validation in vitro and in vivo. In this work, a constitutively GFP-expressing ihOEG cell line was obtained, and named Ts14-GFP. Ts14-GFP neuroregenerative ability was similar to that found for the parental line Ts14 and it can be assayed using in vivo transplantation experimental paradigms, after spinal cord or optic nerve damage. Additionally, we have engineered a low-regenerative ihOEG line, hTL2, using lentiviral transduction of the large T antigen from SV40 virus, denominated from now on Ts12. Ts12 can be used as a low regeneration control in these experiments. |
1109.2644 | Gyorgy Korniss | Andrew Allstadt, Thomas Caraco, F. Molnar Jr., and G. Korniss | Interference competition and invasion: spatial structure, novel weapons
and resistance zones | null | Journal of Theoretical Biology 306, 46-60 (2012) | 10.1016/j.jtbi.2012.04.017 | null | q-bio.PE cond-mat.stat-mech | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Certain invasive plants may rely on interference mechanisms (allelopathy,
e.g.) to gain competitive superiority over native species. But expending
resources on interference presumably exacts a cost in another life-history
trait, so that the significance of interference competition for invasion
ecology remains uncertain. We model ecological invasion when combined effects
of preemptive and interference competition govern interactions at the
neighborhood scale. We consider three cases. Under "novel weapons," only the
initially rare invader exercises interference. For "resistance zones" only the
resident species interferes, and finally we take both species as interference
competitors. Interference increases the other species' mortality, opening space
for colonization. However, a species exercising greater interference has
reduced propagation, which can hinder its colonization of open sites.
Interference never enhances a rare invader's growth in the homogeneously mixing
approximation to our model. But interference can significantly increase an
invader's competitiveness, and its growth when rare, if interactions are
structured spatially. That is, interference can increase an invader's success
when colonization of open sites depends on local, rather than global, species
densities. In contrast, interference enhances the common, resident species'
resistance to invasion independently of spatial structure, unless the
propagation-cost is too great. Increases in background mortality (i.e.,
mortality not due to interference) always reduce the effectiveness of
interference competition.
| [
{
"created": "Mon, 12 Sep 2011 22:52:03 GMT",
"version": "v1"
}
] | 2012-06-08 | [
[
"Allstadt",
"Andrew",
""
],
[
"Caraco",
"Thomas",
""
],
[
"Molnar",
"F.",
"Jr."
],
[
"Korniss",
"G.",
""
]
] | Certain invasive plants may rely on interference mechanisms (allelopathy, e.g.) to gain competitive superiority over native species. But expending resources on interference presumably exacts a cost in another life-history trait, so that the significance of interference competition for invasion ecology remains uncertain. We model ecological invasion when combined effects of preemptive and interference competition govern interactions at the neighborhood scale. We consider three cases. Under "novel weapons," only the initially rare invader exercises interference. For "resistance zones" only the resident species interferes, and finally we take both species as interference competitors. Interference increases the other species' mortality, opening space for colonization. However, a species exercising greater interference has reduced propagation, which can hinder its colonization of open sites. Interference never enhances a rare invader's growth in the homogeneously mixing approximation to our model. But interference can significantly increase an invader's competitiveness, and its growth when rare, if interactions are structured spatially. That is, interference can increase an invader's success when colonization of open sites depends on local, rather than global, species densities. In contrast, interference enhances the common, resident species' resistance to invasion independently of spatial structure, unless the propagation-cost is too great. Increases in background mortality (i.e., mortality not due to interference) always reduce the effectiveness of interference competition. |
2106.09639 | Denis Turcu | Denis Turcu and Christos Papadimitriou | Implementing Permutations in the Brain and SVO Frequencies of Languages | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | The subject-verb-object (SVO) word order prevalent in English is shared by
about $42\%$ of world languages. Another $45\%$ of all languages follow the SOV
order, $9\%$ the VSO order, and fewer languages use the three remaining
permutations. None of the many extant explanations of this phenomenon take into
account the difficulty of implementing these permutations in the brain. We
propose a plausible model of sentence generation inspired by the recently
proposed Assembly Calculus framework of brain function. Our model results in a
natural explanation of the uneven frequencies. Estimating the parameters of
this model yields predictions of the relative difficulty of dis-inhibiting one
brain area from another. Our model is based on the standard syntax tree, a
simple binary tree with three leaves. Each leaf corresponds to one of the three
parts of a basic sentence. The leaves can be activated through lock and unlock
operations and the sequence of activation of the leaves implements a specific
word order. More generally, we also formulate and algorithmically solve the
problems of implementing a permutation of the leaves of any binary tree, and of
selecting the permutation that is easiest to implement on a given binary tree.
| [
{
"created": "Thu, 17 Jun 2021 16:36:37 GMT",
"version": "v1"
}
] | 2021-06-18 | [
[
"Turcu",
"Denis",
""
],
[
"Papadimitriou",
"Christos",
""
]
] | The subject-verb-object (SVO) word order prevalent in English is shared by about $42\%$ of world languages. Another $45\%$ of all languages follow the SOV order, $9\%$ the VSO order, and fewer languages use the three remaining permutations. None of the many extant explanations of this phenomenon take into account the difficulty of implementing these permutations in the brain. We propose a plausible model of sentence generation inspired by the recently proposed Assembly Calculus framework of brain function. Our model results in a natural explanation of the uneven frequencies. Estimating the parameters of this model yields predictions of the relative difficulty of dis-inhibiting one brain area from another. Our model is based on the standard syntax tree, a simple binary tree with three leaves. Each leaf corresponds to one of the three parts of a basic sentence. The leaves can be activated through lock and unlock operations and the sequence of activation of the leaves implements a specific word order. More generally, we also formulate and algorithmically solve the problems of implementing a permutation of the leaves of any binary tree, and of selecting the permutation that is easiest to implement on a given binary tree. |
q-bio/0403012 | Michael Hornquist | Mika Gustafsson, Michael Hornquist and Anna Lombardi | Large-scale reverse engineering by the Lasso | 4 pages, submitted for publication | null | null | null | q-bio.MN | null | We perform a reverse engineering from the ``extended Spellman data'',
consisting of 6178 mRNA levels measured by microarrays at 73 instances in four
time series during the cell cycle of the yeast Saccharomyces cerevisae. By
assuming a linear model of the genetic regulatory network, and imposing an
extra constraint (the Lasso), we obtain a unique inference of coupling
parameters. These parameters are transfered into an adjacent matrix, which is
analyzed with respect to topological properties and biological relevance. We
find a very broad distribution of outdegrees in the network, compatible with
earlier findings for biological systems and totally incompatible with a random
graph, and also indications of modules in the network. Finally, we show there
is an excess of genes coding for transcription factors among the genes of
highest outdegrees, a fact which indicates that our approach has biological
relevance.
| [
{
"created": "Thu, 11 Mar 2004 09:58:06 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Gustafsson",
"Mika",
""
],
[
"Hornquist",
"Michael",
""
],
[
"Lombardi",
"Anna",
""
]
] | We perform a reverse engineering from the ``extended Spellman data'', consisting of 6178 mRNA levels measured by microarrays at 73 instances in four time series during the cell cycle of the yeast Saccharomyces cerevisae. By assuming a linear model of the genetic regulatory network, and imposing an extra constraint (the Lasso), we obtain a unique inference of coupling parameters. These parameters are transfered into an adjacent matrix, which is analyzed with respect to topological properties and biological relevance. We find a very broad distribution of outdegrees in the network, compatible with earlier findings for biological systems and totally incompatible with a random graph, and also indications of modules in the network. Finally, we show there is an excess of genes coding for transcription factors among the genes of highest outdegrees, a fact which indicates that our approach has biological relevance. |
1905.03909 | Kuan-Hao Chao | Kuan-Hao Chao, Yi-Wen Hsiao, Yi-Fang Lee, Chien-Yueh Lee, Liang-Chuan
Lai, Mong-Hsun Tsai, Tzu-Pin Lu, Eric Y. Chuang | RNASeqR: an R package for automated two-group RNA-Seq analysis workflow | 10 pages, 5 figures | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | RNA-Seq analysis has revolutionized researchers' understanding of the
transcriptome in biological research. Assessing the differences in
transcriptomic profiles between tissue samples or patient groups enables
researchers to explore the underlying biological impact of transcription.
RNA-Seq analysis requires multiple processing steps and huge computational
capabilities. There are many well-developed R packages for individual steps;
however, there are few R/Bioconductor packages that integrate existing software
tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end
results in pure R environment so that researchers can quickly and easily get
fundamental information in big sequencing data. To address this need, we have
developed the open source R/Bioconductor package, RNASeqR. It allows users to
run an automated RNA-Seq analysis with only six steps, producing essential
tabular and graphical results for further biological interpretation. The
features of RNASeqR include: six-step analysis, comprehensive visualization,
background execution version, and the integration of both R and command-line
software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis
pipeline in pure R environment. It allows users to efficiently utilize popular
software tools, including both R/Bioconductor and command-line tools, without
predefining the resources or environments. RNASeqR is freely available for
Linux and macOS operating systems from Bioconductor
(https://bioconductor.org/packages/release/bioc/html/RNASeqR.html).
| [
{
"created": "Fri, 10 May 2019 01:44:47 GMT",
"version": "v1"
}
] | 2019-05-13 | [
[
"Chao",
"Kuan-Hao",
""
],
[
"Hsiao",
"Yi-Wen",
""
],
[
"Lee",
"Yi-Fang",
""
],
[
"Lee",
"Chien-Yueh",
""
],
[
"Lai",
"Liang-Chuan",
""
],
[
"Tsai",
"Mong-Hsun",
""
],
[
"Lu",
"Tzu-Pin",
""
],
[
"Chuang",
"Eric Y.",
""
]
] | RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the underlying biological impact of transcription. RNA-Seq analysis requires multiple processing steps and huge computational capabilities. There are many well-developed R packages for individual steps; however, there are few R/Bioconductor packages that integrate existing software tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end results in pure R environment so that researchers can quickly and easily get fundamental information in big sequencing data. To address this need, we have developed the open source R/Bioconductor package, RNASeqR. It allows users to run an automated RNA-Seq analysis with only six steps, producing essential tabular and graphical results for further biological interpretation. The features of RNASeqR include: six-step analysis, comprehensive visualization, background execution version, and the integration of both R and command-line software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis pipeline in pure R environment. It allows users to efficiently utilize popular software tools, including both R/Bioconductor and command-line tools, without predefining the resources or environments. RNASeqR is freely available for Linux and macOS operating systems from Bioconductor (https://bioconductor.org/packages/release/bioc/html/RNASeqR.html). |
2402.08777 | Zhihan Zhou | Zhihan Zhou, Weimin Wu, Harrison Ho, Jiayi Wang, Lizhen Shi, Ramana V
Davuluri, Zhong Wang, Han Liu | DNABERT-S: Learning Species-Aware DNA Embedding with Genome Foundation
Models | null | null | null | null | q-bio.GN cs.AI cs.CE cs.CL | http://creativecommons.org/licenses/by/4.0/ | Effective DNA embedding remains crucial in genomic analysis, particularly in
scenarios lacking labeled data for model fine-tuning, despite the significant
advancements in genome foundation models. A prime example is metagenomics
binning, a critical process in microbiome research that aims to group DNA
sequences by their species from a complex mixture of DNA sequences derived from
potentially thousands of distinct, often uncharacterized species. To fill the
lack of effective DNA embedding models, we introduce DNABERT-S, a genome
foundation model that specializes in creating species-aware DNA embeddings. To
encourage effective embeddings to error-prone long-read DNA sequences, we
introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes
the hidden representations of DNA sequences at randomly selected layers and
trains the model to recognize and differentiate these mixed proportions at the
output layer. We further enhance it with the proposed Curriculum Contrastive
Learning (C$^2$LR) strategy. Empirical results on 18 diverse datasets showed
DNABERT-S's remarkable performance. It outperforms the top baseline's
performance in 10-shot species classification with just a 2-shot training while
doubling the Adjusted Rand Index (ARI) in species clustering and substantially
increasing the number of correctly identified species in metagenomics binning.
The code, data, and pre-trained model are publicly available at
https://github.com/Zhihan1996/DNABERT_S.
| [
{
"created": "Tue, 13 Feb 2024 20:21:29 GMT",
"version": "v1"
},
{
"created": "Thu, 15 Feb 2024 04:55:23 GMT",
"version": "v2"
}
] | 2024-02-16 | [
[
"Zhou",
"Zhihan",
""
],
[
"Wu",
"Weimin",
""
],
[
"Ho",
"Harrison",
""
],
[
"Wang",
"Jiayi",
""
],
[
"Shi",
"Lizhen",
""
],
[
"Davuluri",
"Ramana V",
""
],
[
"Wang",
"Zhong",
""
],
[
"Liu",
"Han",
""
]
] | Effective DNA embedding remains crucial in genomic analysis, particularly in scenarios lacking labeled data for model fine-tuning, despite the significant advancements in genome foundation models. A prime example is metagenomics binning, a critical process in microbiome research that aims to group DNA sequences by their species from a complex mixture of DNA sequences derived from potentially thousands of distinct, often uncharacterized species. To fill the lack of effective DNA embedding models, we introduce DNABERT-S, a genome foundation model that specializes in creating species-aware DNA embeddings. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C$^2$LR) strategy. Empirical results on 18 diverse datasets showed DNABERT-S's remarkable performance. It outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training while doubling the Adjusted Rand Index (ARI) in species clustering and substantially increasing the number of correctly identified species in metagenomics binning. The code, data, and pre-trained model are publicly available at https://github.com/Zhihan1996/DNABERT_S. |
q-bio/0404027 | James Gillooly | James F. Gillooly, Andrew P. Allen, Geoffrey B. West, and James H.
Brown | Metabolic Rate Calibrates the Molecular Clock: Reconciling Molecular and
Fossil Estimates of Evolutionary Divergence | null | null | null | null | q-bio.PE q-bio.GN | null | Observations that rates of molecular evolution vary widely within and among
lineages have cast doubts upon the existence of a single molecular clock.
Differences in the timing of evolutionary events estimated from genetic and
fossil evidence have raised further questions about the existence of molecular
clocks and their use. Here we present a model of nucleotide substitution that
combines new theory on metabolic rate with the now classic neutral theory of
molecular evolution. The model quantitatively predicts rate heterogeneity, and
reconciles differences in molecular- and fossil-estimated dates of evolutionary
events. Model predictions are supported by extensive data from mitochondrial
and nuclear genomes. By accounting for the effects of body size and temperature
on metabolic rate, a single molecular clock explains heterogeneity in rates of
nucleotide substitution in different genes, taxa, and thermal environments.
This model suggests that there is indeed a general molecular clock, as
originally proposed by Zuckerkandl and Pauling, but that it ticks at a constant
substitution rate per unit mass-specific metabolic energy rather than per unit
time. More generally, the model suggests that body size and temperature combine
to control the overall rate of evolution through their effects on metabolism.
| [
{
"created": "Thu, 22 Apr 2004 19:47:19 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Gillooly",
"James F.",
""
],
[
"Allen",
"Andrew P.",
""
],
[
"West",
"Geoffrey B.",
""
],
[
"Brown",
"James H.",
""
]
] | Observations that rates of molecular evolution vary widely within and among lineages have cast doubts upon the existence of a single molecular clock. Differences in the timing of evolutionary events estimated from genetic and fossil evidence have raised further questions about the existence of molecular clocks and their use. Here we present a model of nucleotide substitution that combines new theory on metabolic rate with the now classic neutral theory of molecular evolution. The model quantitatively predicts rate heterogeneity, and reconciles differences in molecular- and fossil-estimated dates of evolutionary events. Model predictions are supported by extensive data from mitochondrial and nuclear genomes. By accounting for the effects of body size and temperature on metabolic rate, a single molecular clock explains heterogeneity in rates of nucleotide substitution in different genes, taxa, and thermal environments. This model suggests that there is indeed a general molecular clock, as originally proposed by Zuckerkandl and Pauling, but that it ticks at a constant substitution rate per unit mass-specific metabolic energy rather than per unit time. More generally, the model suggests that body size and temperature combine to control the overall rate of evolution through their effects on metabolism. |
2009.02241 | Vojtech Spiwok | Dalibor Trapl, Vojt\v{e}ch Spiwok | Analysis of the Results of Metadynamics Simulations by metadynminer and
metadynminer3d | 11 pages, 9 figures | R Journal, 2022, 14(3) 46-58 | 10.32614/RJ-2022-057 | null | q-bio.BM physics.chem-ph physics.comp-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The molecular simulations solve the equation of motion of molecular systems,
making 3D shapes of molecules four-dimensional by adding the time coordinate.
These methods have a great potential in drug discovery because they can
realistically model the structures of protein molecules targeted by drugs as
well as the process of binding of a potential drug to its molecular target.
However, routine application of biomolecular simulations is hampered by the
very high computational costs of this method. Several methods have been
developed to address this problem. One of them, metadynamics, disfavors states
of the simulated system that have been already visited and thus forces the
system to explore new and new states. Here we present the package metadynminer
and metadynminer3d to analyze and visualize results from metadynamics, in
particular those produced by a popular metadynamics package Plumed.
| [
{
"created": "Sat, 22 Aug 2020 16:05:30 GMT",
"version": "v1"
}
] | 2023-01-19 | [
[
"Trapl",
"Dalibor",
""
],
[
"Spiwok",
"Vojtěch",
""
]
] | The molecular simulations solve the equation of motion of molecular systems, making 3D shapes of molecules four-dimensional by adding the time coordinate. These methods have a great potential in drug discovery because they can realistically model the structures of protein molecules targeted by drugs as well as the process of binding of a potential drug to its molecular target. However, routine application of biomolecular simulations is hampered by the very high computational costs of this method. Several methods have been developed to address this problem. One of them, metadynamics, disfavors states of the simulated system that have been already visited and thus forces the system to explore new and new states. Here we present the package metadynminer and metadynminer3d to analyze and visualize results from metadynamics, in particular those produced by a popular metadynamics package Plumed. |
1409.4628 | Brian Williams Dr | Brian G Williams | Managing HIV/AIDS in Malawi | 7 pages. arXiv admin note: substantial text overlap with
arXiv:1401.6430, arXiv:1311.1815 | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The epidemic of HIV in Malawi started early and at its peak 15% of all adults
were infected with HIV. Malawi is a low-income country and the cost of putting
all HIV-positive people in Malawi onto ART, expressed as a percentage of the
gross domestic product, is the highest in the world. Nevertheless, Malawi has
made great progress and the greatly reduced cost of potent anti-retroviral
therapy (ART) makes it possible to contemplate ending the epidemic of HIV/AIDS.
Here we consider what would have happened without ART, the No ART
counterfactual, the impact if the current level of roll-out of ART is
maintained, the Current Programme, and the likely impact if treatment is made
available to everyone who is eligible under the 2013 guidelines of the World
Health Organization reaching full coverage by 2020, the Expanded Programme.
The Current Programme has substantially reduced the epidemic of HIV and the
number of people dying of AIDS. The Expanded Programme has the potential to
avert more infections, save more lives and end the epidemic. The annual cost of
managing HIV will increase from about US$132 million in 2014 to about US$155
million in 2020 but will fall after that. If the Expanded Programme is
implemented several key areas must be addressed. Testing services will need to
be expanded and supported by mass testing campaigns, so as to diagnose people
with HIV and enrol them in treatment and care as early as possible. A regular
and uninterrupted supply of drugs will have to be assured. The quantity and
quality of existing health staff will need to be strengthened. Community health
workers will need to be mobilized and trained to encourage people to be tested
and accept treatment, to monitor progress and to support people on treatment;
this in turn will help to reduce stigma and discrimination, loss to follow up
of people diagnosed with HIV, and improve adherence for those on treatment.
| [
{
"created": "Mon, 15 Sep 2014 14:17:45 GMT",
"version": "v1"
}
] | 2014-09-17 | [
[
"Williams",
"Brian G",
""
]
] | The epidemic of HIV in Malawi started early and at its peak 15% of all adults were infected with HIV. Malawi is a low-income country and the cost of putting all HIV-positive people in Malawi onto ART, expressed as a percentage of the gross domestic product, is the highest in the world. Nevertheless, Malawi has made great progress and the greatly reduced cost of potent anti-retroviral therapy (ART) makes it possible to contemplate ending the epidemic of HIV/AIDS. Here we consider what would have happened without ART, the No ART counterfactual, the impact if the current level of roll-out of ART is maintained, the Current Programme, and the likely impact if treatment is made available to everyone who is eligible under the 2013 guidelines of the World Health Organization reaching full coverage by 2020, the Expanded Programme. The Current Programme has substantially reduced the epidemic of HIV and the number of people dying of AIDS. The Expanded Programme has the potential to avert more infections, save more lives and end the epidemic. The annual cost of managing HIV will increase from about US$132 million in 2014 to about US$155 million in 2020 but will fall after that. If the Expanded Programme is implemented several key areas must be addressed. Testing services will need to be expanded and supported by mass testing campaigns, so as to diagnose people with HIV and enrol them in treatment and care as early as possible. A regular and uninterrupted supply of drugs will have to be assured. The quantity and quality of existing health staff will need to be strengthened. Community health workers will need to be mobilized and trained to encourage people to be tested and accept treatment, to monitor progress and to support people on treatment; this in turn will help to reduce stigma and discrimination, loss to follow up of people diagnosed with HIV, and improve adherence for those on treatment. |
1504.00414 | Alexey Onufriev | Abhishek Mukhopadhyay, Igor S. Tolokh, Alexey V. Onufriev | Accurate Evaluation of Charge Asymmetry in Aqueous Solvation | null | null | 10.1021/acs.jpcb.5b00602 | null | q-bio.BM physics.chem-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Charge hydration asymmetry (CHA)--a characteristic dependence of hydration
free energy on the sign of the solute charge--quantifies the asymmetric
response of water to electric field at microscopic level. Accurate estimates of
CHA are critical for understanding hydration effects ubiquitous in chemistry
and biology. However, measuring hydration energies of charged species is
fraught with significant difficulties, which lead to unacceptably large (up to
300%) variation in the available estimates of the CHA effect. We circumvent
these difficulties by developing a framework which allows us to extract and
accurately estimate the intrinsic propensity of water to exhibit CHA from
accurate experimental hydration free energies of neutral polar molecules.
Specifically, from a set of 504 small molecules we identify two pairs that are
analogous, with respect to CHA, to the K+/F- pair--a classical probe for the
effect. We use these "CHA-conjugate" molecule pairs to quantify the intrinsic
charge-asymmetric response of water to the microscopic charge perturbations:
the asymmetry of the response is strong, ~50% of the average hydration free
energy of these molecules. The ability of widely used classical water models to
predict hydration energies of small molecules correlates with their ability to
predict CHA.
| [
{
"created": "Wed, 1 Apr 2015 23:20:23 GMT",
"version": "v1"
},
{
"created": "Mon, 11 May 2015 15:11:05 GMT",
"version": "v2"
}
] | 2015-05-12 | [
[
"Mukhopadhyay",
"Abhishek",
""
],
[
"Tolokh",
"Igor S.",
""
],
[
"Onufriev",
"Alexey V.",
""
]
] | Charge hydration asymmetry (CHA)--a characteristic dependence of hydration free energy on the sign of the solute charge--quantifies the asymmetric response of water to electric field at microscopic level. Accurate estimates of CHA are critical for understanding hydration effects ubiquitous in chemistry and biology. However, measuring hydration energies of charged species is fraught with significant difficulties, which lead to unacceptably large (up to 300%) variation in the available estimates of the CHA effect. We circumvent these difficulties by developing a framework which allows us to extract and accurately estimate the intrinsic propensity of water to exhibit CHA from accurate experimental hydration free energies of neutral polar molecules. Specifically, from a set of 504 small molecules we identify two pairs that are analogous, with respect to CHA, to the K+/F- pair--a classical probe for the effect. We use these "CHA-conjugate" molecule pairs to quantify the intrinsic charge-asymmetric response of water to the microscopic charge perturbations: the asymmetry of the response is strong, ~50% of the average hydration free energy of these molecules. The ability of widely used classical water models to predict hydration energies of small molecules correlates with their ability to predict CHA. |
2104.10456 | Muktish Acharyya | Agniva Datta and Muktish Acharyya | Modelling the Spread of an Epidemic in Presence of Vaccination using
Cellular Automata | Int. J. Mod. Phys. C (2022) (in press) | Int. J. Mod. Phys. C, 33 (2022) 2250094 | 10.1142/S0129183122500942 | PU-Physics-4-12-2021 | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The results of Kermack-McKendrick SIR model are planned to be reproduced by
cellular automata (CA) lattice model. The CA algorithms are proposed to study
the model of epidemic, systematically. The basic goal is to capture the effects
of spreading of infection over a scale of length. This CA model can provide the
rate of growth of the infection over the space which was lacking in the
mean-field like SIR model. The motion of the circular front of an infected
cluster shows a linear behaviour in time. The correlation of a particular site
to be infected, with respect to the central site is also studied. The outcomes
of CA model are in good agreement with that obtained from SIR model. The
results of vaccination have been also incorporated in the CA algorithm with a
satisfactory degree of success. The advantage of the present model is that it
can shed considerable amount of light to the physical properties of the spread
of a typical epidemic in a simple, yet robust way.
| [
{
"created": "Wed, 21 Apr 2021 10:56:49 GMT",
"version": "v1"
},
{
"created": "Mon, 23 Aug 2021 11:15:15 GMT",
"version": "v2"
},
{
"created": "Wed, 25 Aug 2021 05:34:37 GMT",
"version": "v3"
},
{
"created": "Mon, 6 Dec 2021 02:50:15 GMT",
"version": "v4"
}
] | 2022-08-30 | [
[
"Datta",
"Agniva",
""
],
[
"Acharyya",
"Muktish",
""
]
] | The results of Kermack-McKendrick SIR model are planned to be reproduced by cellular automata (CA) lattice model. The CA algorithms are proposed to study the model of epidemic, systematically. The basic goal is to capture the effects of spreading of infection over a scale of length. This CA model can provide the rate of growth of the infection over the space which was lacking in the mean-field like SIR model. The motion of the circular front of an infected cluster shows a linear behaviour in time. The correlation of a particular site to be infected, with respect to the central site is also studied. The outcomes of CA model are in good agreement with that obtained from SIR model. The results of vaccination have been also incorporated in the CA algorithm with a satisfactory degree of success. The advantage of the present model is that it can shed considerable amount of light to the physical properties of the spread of a typical epidemic in a simple, yet robust way. |
1612.05747 | Wonseok Hwang | Wonseok Hwang, Changbong Hyeon | Quantifying the Heat Dissipation from a Molecular Motor's Transport
Properties in Nonequilibrium Steady States | null | J. Phys. Chem. Lett. (2017) vol. 8, 250-256 | 10.1016/j.bpj.2016.11.2291 | null | q-bio.SC cond-mat.stat-mech physics.bio-ph q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Theoretical analysis, which maps single molecule time trajectories of a
molecular motor onto unicyclic Markov processes, allows us to evaluate the heat
dissipated from the motor and to elucidate its dependence on the mean velocity
and diffusivity. Unlike passive Brownian particles in equilibrium, the velocity
and diffusion constant of molecular motors are closely inter-related to each
other. In particular, our study makes it clear that the increase of diffusivity
with the heat production is a natural outcome of active particles, which is
reminiscent of the recent experimental premise that the diffusion of an
exothermic enzyme is enhanced by the heat released from its own catalytic
turnover. Compared with freely diffusing exothermic enzymes, kinesin-1 whose
dynamics is confined on one-dimensional tracks is highly efficient in
transforming conformational fluctuations into a locally directed motion, thus
displaying a significantly higher enhancement in diffusivity with its turnover
rate. Putting molecular motors and freely diffusing enzymes on an equal
footing, our study offers thermodynamic basis to understand the heat enhanced
self-diffusion of exothermic enzymes.
| [
{
"created": "Sat, 17 Dec 2016 12:53:36 GMT",
"version": "v1"
},
{
"created": "Wed, 28 Dec 2016 09:01:10 GMT",
"version": "v2"
}
] | 2017-04-05 | [
[
"Hwang",
"Wonseok",
""
],
[
"Hyeon",
"Changbong",
""
]
] | Theoretical analysis, which maps single molecule time trajectories of a molecular motor onto unicyclic Markov processes, allows us to evaluate the heat dissipated from the motor and to elucidate its dependence on the mean velocity and diffusivity. Unlike passive Brownian particles in equilibrium, the velocity and diffusion constant of molecular motors are closely inter-related to each other. In particular, our study makes it clear that the increase of diffusivity with the heat production is a natural outcome of active particles, which is reminiscent of the recent experimental premise that the diffusion of an exothermic enzyme is enhanced by the heat released from its own catalytic turnover. Compared with freely diffusing exothermic enzymes, kinesin-1 whose dynamics is confined on one-dimensional tracks is highly efficient in transforming conformational fluctuations into a locally directed motion, thus displaying a significantly higher enhancement in diffusivity with its turnover rate. Putting molecular motors and freely diffusing enzymes on an equal footing, our study offers thermodynamic basis to understand the heat enhanced self-diffusion of exothermic enzymes. |
2109.00518 | Ze Wang | Ze Wang | Cross-time functional connectivity analysis | arXiv admin note: text overlap with arXiv:2109.00146 | null | null | null | q-bio.NC q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | A large body of literature has shown the substantial inter-regional
functional connectivity in the mammal brain. One important property remaining
un-studied is the cross-time interareal connection. This paper serves to
provide a tool to characterize the cross-time functional connectivity. The
method is extended from the temporal embedding based brain temporal coherence
analysis. Both synthetic data and in-vivo data were used to evaluate the
various properties of the cross-time functional connectivity matrix, which is
also called the cross-regional temporal coherence matrix.
| [
{
"created": "Wed, 1 Sep 2021 01:50:16 GMT",
"version": "v1"
}
] | 2021-09-06 | [
[
"Wang",
"Ze",
""
]
] | A large body of literature has shown the substantial inter-regional functional connectivity in the mammal brain. One important property remaining un-studied is the cross-time interareal connection. This paper serves to provide a tool to characterize the cross-time functional connectivity. The method is extended from the temporal embedding based brain temporal coherence analysis. Both synthetic data and in-vivo data were used to evaluate the various properties of the cross-time functional connectivity matrix, which is also called the cross-regional temporal coherence matrix. |
2407.13779 | Saisubramaniam Gopalakrishnan | Siddartha Reddy N, Sai Prakash MV, Varun V, Vishal Vaddina,
Saisubramaniam Gopalakrishnan | Leveraging Latent Evolutionary Optimization for Targeted Molecule
Generation | null | null | null | null | q-bio.BM cs.LG cs.NE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Lead optimization is a pivotal task in the drug design phase within the drug
discovery lifecycle. The primary objective is to refine the lead compound to
meet specific molecular properties for progression to the subsequent phase of
development. In this work, we present an innovative approach, Latent
Evolutionary Optimization for Molecule Generation (LEOMol), a generative
modeling framework for the efficient generation of optimized molecules. LEOMol
leverages Evolutionary Algorithms, such as Genetic Algorithm and Differential
Evolution, to search the latent space of a Variational AutoEncoder (VAE). This
search facilitates the identification of the target molecule distribution
within the latent space. Our approach consistently demonstrates superior
performance compared to previous state-of-the-art models across a range of
constrained molecule generation tasks, outperforming existing models in all
four sub-tasks related to property targeting. Additionally, we suggest the
importance of including toxicity in the evaluation of generative models.
Furthermore, an ablation study underscores the improvements that our approach
provides over gradient-based latent space optimization methods. This
underscores the effectiveness and superiority of LEOMol in addressing the
inherent challenges in constrained molecule generation while emphasizing its
potential to propel advancements in drug discovery.
| [
{
"created": "Tue, 2 Jul 2024 13:42:21 GMT",
"version": "v1"
}
] | 2024-07-22 | [
[
"N",
"Siddartha Reddy",
""
],
[
"MV",
"Sai Prakash",
""
],
[
"V",
"Varun",
""
],
[
"Vaddina",
"Vishal",
""
],
[
"Gopalakrishnan",
"Saisubramaniam",
""
]
] | Lead optimization is a pivotal task in the drug design phase within the drug discovery lifecycle. The primary objective is to refine the lead compound to meet specific molecular properties for progression to the subsequent phase of development. In this work, we present an innovative approach, Latent Evolutionary Optimization for Molecule Generation (LEOMol), a generative modeling framework for the efficient generation of optimized molecules. LEOMol leverages Evolutionary Algorithms, such as Genetic Algorithm and Differential Evolution, to search the latent space of a Variational AutoEncoder (VAE). This search facilitates the identification of the target molecule distribution within the latent space. Our approach consistently demonstrates superior performance compared to previous state-of-the-art models across a range of constrained molecule generation tasks, outperforming existing models in all four sub-tasks related to property targeting. Additionally, we suggest the importance of including toxicity in the evaluation of generative models. Furthermore, an ablation study underscores the improvements that our approach provides over gradient-based latent space optimization methods. This underscores the effectiveness and superiority of LEOMol in addressing the inherent challenges in constrained molecule generation while emphasizing its potential to propel advancements in drug discovery. |
2209.00627 | Umang Goenka | Umang Goenka, Param Patil, Kush Gosalia, Aaryan Jagetia | Classification of Electroencephalograms during Mathematical Calculations
Using Deep Learning | Paper presented in IEEE 23rd International Conference on Information
Reuse and Integration for Data Science | null | null | null | q-bio.NC cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Classifying Electroencephalogram(EEG) signals helps in understanding
Brain-Computer Interface (BCI). EEG signals are vital in studying how the human
mind functions. In this paper, we have used an Arithmetic Calculation dataset
consisting of Before Calculation Signals (BCS) and During Calculation Signals
(DCS). The dataset consisted of 36 participants. In order to understand the
functioning of neurons in the brain, we classified BCS vs DCS. For this
classification, we extracted various features such as Mutual Information (MI),
Phase Locking Value (PLV), and Entropy namely Permutation entropy, Spectral
entropy, Singular value decomposition entropy, Approximate entropy, Sample
entropy. The classification of these features was done using RNN-based
classifiers such as LSTM, BLSTM, ConvLSTM, and CNN-LSTM. The model achieved an
accuracy of 99.72% when entropy was used as a feature and ConvLSTM as a
classifier.
| [
{
"created": "Wed, 31 Aug 2022 10:15:24 GMT",
"version": "v1"
}
] | 2022-09-02 | [
[
"Goenka",
"Umang",
""
],
[
"Patil",
"Param",
""
],
[
"Gosalia",
"Kush",
""
],
[
"Jagetia",
"Aaryan",
""
]
] | Classifying Electroencephalogram(EEG) signals helps in understanding Brain-Computer Interface (BCI). EEG signals are vital in studying how the human mind functions. In this paper, we have used an Arithmetic Calculation dataset consisting of Before Calculation Signals (BCS) and During Calculation Signals (DCS). The dataset consisted of 36 participants. In order to understand the functioning of neurons in the brain, we classified BCS vs DCS. For this classification, we extracted various features such as Mutual Information (MI), Phase Locking Value (PLV), and Entropy namely Permutation entropy, Spectral entropy, Singular value decomposition entropy, Approximate entropy, Sample entropy. The classification of these features was done using RNN-based classifiers such as LSTM, BLSTM, ConvLSTM, and CNN-LSTM. The model achieved an accuracy of 99.72% when entropy was used as a feature and ConvLSTM as a classifier. |
2003.03626 | Jacob George | David M. Page, Suzanne M. Wendelken, Tyler S. Davis, David T. Kluger,
Douglas T. Hutchinson, Jacob A. George and Gregory A. Clark | Discrimination Among Multiple Cutaneous and Proprioceptive Hand Percepts
Evoked by Nerve Stimulation with Utah Slanted Electrode Arrays in Human
Amputees | 19 pages | null | null | null | q-bio.NC cs.RO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Objective: This paper aims to demonstrate functional discriminability among
restored hand sensations with different locations, qualities, and intensities
that are evoked by microelectrode stimulation of residual afferent fibers in
human amputees. Methods: We implanted a Utah Slanted Electrode Array (USEA) in
the median and ulnar residual arm nerves of three transradial amputees and
delivered stimulation via different electrodes and at different frequencies to
produce various locations, qualities, and intensities of sensation on the
missing hand. Blind discrimination trials were performed to determine how well
subjects could discriminate among these restored sensations. Results: Subjects
discriminated among restored sensory percepts with varying cutaneous and
proprioceptive locations, qualities, and intensities in blind trials, including
discrimination among up to 10 different location-intensity combinations (15/30
successes, p < 0.0005). Variations in the site of stimulation within the nerve,
via electrode selection, enabled discrimination among up to 5 locations and
qualities (35/35 successes, p < 0.0001). Variations in the stimulation
frequency enabled discrimination among 4 different intensities at the same
location (13/20 successes, p < 0.005). One subject discriminated among
simultaneous, alternating, and isolated stimulation of two different USEA
electrodes, as may be desired during multi-sensor closed-loop prosthesis use
(20/25 successes, p < 0.001). Conclusion: USEA stimulation enables encoding of
a diversity of functionally discriminable sensations with different locations,
qualities, and intensities. Significance: These percepts provide a potentially
rich source of sensory feedback that may enhance performance and embodiment
during multi-sensor, closed-loop prosthesis use.
| [
{
"created": "Sat, 7 Mar 2020 18:17:03 GMT",
"version": "v1"
}
] | 2020-03-10 | [
[
"Page",
"David M.",
""
],
[
"Wendelken",
"Suzanne M.",
""
],
[
"Davis",
"Tyler S.",
""
],
[
"Kluger",
"David T.",
""
],
[
"Hutchinson",
"Douglas T.",
""
],
[
"George",
"Jacob A.",
""
],
[
"Clark",
"Gregory A.",
""
]
] | Objective: This paper aims to demonstrate functional discriminability among restored hand sensations with different locations, qualities, and intensities that are evoked by microelectrode stimulation of residual afferent fibers in human amputees. Methods: We implanted a Utah Slanted Electrode Array (USEA) in the median and ulnar residual arm nerves of three transradial amputees and delivered stimulation via different electrodes and at different frequencies to produce various locations, qualities, and intensities of sensation on the missing hand. Blind discrimination trials were performed to determine how well subjects could discriminate among these restored sensations. Results: Subjects discriminated among restored sensory percepts with varying cutaneous and proprioceptive locations, qualities, and intensities in blind trials, including discrimination among up to 10 different location-intensity combinations (15/30 successes, p < 0.0005). Variations in the site of stimulation within the nerve, via electrode selection, enabled discrimination among up to 5 locations and qualities (35/35 successes, p < 0.0001). Variations in the stimulation frequency enabled discrimination among 4 different intensities at the same location (13/20 successes, p < 0.005). One subject discriminated among simultaneous, alternating, and isolated stimulation of two different USEA electrodes, as may be desired during multi-sensor closed-loop prosthesis use (20/25 successes, p < 0.001). Conclusion: USEA stimulation enables encoding of a diversity of functionally discriminable sensations with different locations, qualities, and intensities. Significance: These percepts provide a potentially rich source of sensory feedback that may enhance performance and embodiment during multi-sensor, closed-loop prosthesis use. |
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