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recruits. The group of old friends decide to create a new team together called X-Factor. With Cyclops gone and occupied, Sinister sends his newly formed Marauders to attack the now vulnerable Summers house in Alaska. The Marauders attack Maddie and leave her for dead, then take Nathan Summers to the State Home for Foundlings. Meanwhile, Sinister erases all records of Maddie and arranges for the furniture from the house in Anchorage to be removed. Unbeknownst to Sinister, Maddie is taken to a hospital and survives, though she slips into a coma. === "Mutant Massacre" and "Inferno" === Returning to New York, the Marauders are finally sent after the Morlocks. Using his stealth and tracking skills, Gambit leads the group to the Morlock community but abandons the group when he learns they intend murder. The Marauders dismiss Gambit and begin their slaughter, causing the "Mutant Massacre" event, a series of battles that include the X-Men, the new X-Factor team, and other heroes such as Thor. Some of the Marauders are killed in action. Scanning the mind of Sabretooth, the X-Man called Psylocke learns the massacre was ordered by someone called "Sinister", alerting the X-Men to his presence for the first time. Soon afterward, Cyclops returns to Alaska to make amends with Maddie and be a father. Discovering the house is completely empty, he concludes Maddie left with Nathan, deliberately leaving no trace of where she might be. He is then confronted by Master Mold, the robot whose primary task is to create mutant-hunting Sentinels. During the battle, Master Mold refers to Cyclops as one of "the Twelve" who must be destroyed. Later on, Master Mold explains the Twelve are "The dozen mutant humans who will one day rise up and lead all of mutantkind in war against Homo sapiens in the
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twilight of Earth." Months after Nathan's kidnapping, Maddie awakes from her coma, amnesiac. After regaining her memory, she contacts and reunites with the X-Men. Now bitter and increasingly desperate regarding her missing child, Maddie believes Scott completely abandoned them and never cared enough to contact her or look for her. She later joins forces with the demons S'ym and N'Astirh who take advantage of her state of mind and corrupt her, turning her into the Goblyn Queen and leading into the Inferno storyline. During this storyline, the mutant precog Irene Adler (now calling herself Destiny) sends the X-Factor team to Sinister's lab where they discover and rescue Nathan along with other children. The Goblyn Queen then arrives and retrieves Nathan and several other babies to use as sacrifices for a demonic ritual. Sinister reforms his Marauders, even resurrecting the fallen ones through his now perfected cloning technology. He then confronts Madelyne and reveals her true origins. At the end of Inferno, Maddie dies and her life-force and memories merge with Jean Grey's. As the X-Factor and X-Men teams fight Sinister, the villain reveals his many manipulations of Scott Summers over the years, how he mentally influenced Scott to abandon his family, and his quest to create offspring from his and Jean's DNA. After realizing the villainous scientist may be vulnerable to his power, Cyclops releases a high-intensity blast that seems to atomize Mr. Sinister, leaving only charred bones. The battle over, Scott and Jean decide to raise the baby Nathan together. In truth, Mr. Sinister is alive, having decided to fake his death so he can retreat rather than continue to battle both X-Factor and the X-Men single-handedly. Later on, Nathan is fatally infected by a techno-organic virus. Rather than watch his son die, Cyclops sends him into the future
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where treatment exists. Soon afterward, Gambit joins the X-Men team after having befriended the X-Man called Storm. His connection to Sinister and the Mutant Massacre is not revealed for some time. Many months after Nathan Summers is sent into the future, the X-Men learn he grew up to become Cable, a powerful mutant time traveler and one of Apocalypse's most persistent enemies. This also makes the mutant terrorist Stryfe a son of Cyclops in his own way, as he is a clone of Cable. === 1990s === Sinister recruits a new team of agents called the Nasty Boys and allies with Stryfe, now leader of the terrorist Mutant Liberation Front. During this time, he establishes a new cover identity of "Mike Milbury", a neighbor to Scott Summers' grandparents. During the storyline "X-Cutioner's Song", Stryfe gives Sinister a canister he claims contains a sample of his own genetic material, in exchange for a service. When Sinister opens the container, he is angered to find it seemingly empty. He later realizes that he unknowingly unleashed the Legacy Virus, a pathogen engineered by Stryfe that targets mutants. Not long afterward, Scott Summers meets Mike Milbury, who then reveals himself to be Mr. Sinister, still alive. Sinister warns of the Legacy Virus and also hints that there is a third Summers brother unknown to either Scott or Alex. When the villainous Dark Riders arrive to attack Cyclops, Sinister declares the mutant hero under his own protection. Not long afterward, Scott and Jean Grey marry while Sinister monitors from afar, interested in the possible offspring that may result. Some time later, he recruits a new agent named Threnody, a mutant who can sense the dying and draw energy from them. Not long after Scott and Jean's wedding, the X-Men learn that due to an alteration
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to history, their reality is about to be replaced by another. Believing they are about to die, the X-Man Rogue kisses her teammate Gambit, something she had not done before due to the risk that her energy absorbing abilities could harm him. During the kiss, she sees his memories and learns of his past relationship with Mr. Sinister. The alteration to the timeline is due to Xavier's powerful mutant son Legion traveling back in time to kill Magneto before the X-Men have even formed, but accidentally killing Charles Xavier instead. This creates a new "Age of Apocalypse" reality where Apocalypse conquers much of the Western hemisphere and Magneto forms his own team of X-Men rebels, naming them in honor of his fallen friend Charles. In this reality, Sinister helps Apocalypse rule, adopts both Alex and Scott Summers as his personal soldiers, and recruits Henry McCoy (Dark Beast) as his lab assistant. Believing Apocalypse will ultimately destroy the Earth in his quest to eliminate the weak, Sinister still works to create a living weapon against him using DNA from Scott Summers and Jean Grey. The result is a powerful teenage mutant named Nate Grey. Later on, the timeline is restored. Rogue is disturbed by Gambit's connection to Sinister, which is later revealed to the rest of the X-Men. This drives a wedge between them and Gambit for some time. The Age of Apocalypse reality is seemingly erased but some of its inhabitants are transported to the original timeline. Dark Beast is transported to the past and experiments on several Morlocks. Nate Grey winds up in the modern day Marvel Universe, appearing on Earth only days after the X-Men thought their world would wink out of existence. Learning of Nate Grey and his similarity to Cable, Sinister assigns Threnody to earn the
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young man's trust. When Threnody develops genuine friendship with Nate and decides to leave Sinister's employ, the Marauders are sent after her. Nate Grey intervenes, killing the entire team except for Prism (though Sinister later clones the fallen again). === 2000s === Apocalypse gathers the Twelve, now revealed to be twelve powerful mutants he can use to ascend to a god-like state of power, with Nate Grey acting as a new host. After this plan fails, Sinister takes on the appearance of an elderly man, "Dr. Essex", and visits the High Evolutionary. He influences the powerful geneticist to use his advanced space station to remove the powers of all mutants on Earth, causing widespread injury and several deaths, including most of the community of evolved mutants known as the Neo. Sinister then reveals his true nature and takes over the High Evolutionary's satellite, intending to use it to alter the genetics of people at his discretion, making Earth a giant lab where he could create the ultimate race of superhumans. Sinister's plan is then stopped by the X-Men, who restore mutant powers to all of those with the X-gene. The surviving Neo then hunt Sinister to avenge their fallen members, killing 17 clone doppelgangers. Sinister later resurfaces as Dr. Robert Windsor, experimenting on mutants again, with Scalphunter acting as his bodyguard. Later on, an encounter with Colossus and the hero's brother Mikhail Rasputin reveals that Sinister's powers are weakening and he is becoming desperate to find a way to restore them. Due to the event known as M-Day, most mutants lose their powers overnight and it seems there are no new mutant births occurring on Earth. Later on, a mutant named Joe Buggs is murdered by a mysterious mutant hunter. His friend Ed seeks the X-Men for help, claiming the
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killer is Kraven the Hunter (believed dead at the time). The X-Men consult with Spider-Man, Kraven's greatest enemy, and the heroes discover the true killer is Sinister's later creation, Xraven, a telepathic hunter. Realizing Xraven believes he is Sinister's "favorite son," Cyclops invites the hunter to read his own mind. Seeing Cyclops' memories of Sinister's obsession with him and learning the scientists treats all of his soldiers and creations like pawns, Xraven flees but takes DNA samples of the X-Men Shadowcat, Colossus, Nightcrawler, and Wolverine. Later, Mister Sinister tells Xraven he plans to create a new generation of mutants through cloning. Realizing Sinister will enslave these mutants, Xraven destroys the samples and causes the destruction of Sinister's lab and hideout. Sinister survives, but Xraven's fate is unknown. During the storyline Blinded by the Light, Sinister sends the Marauders and Acolytes to murder all those who have knowledge of the future. Some time later, the first new mutant since M-Day is born. Sinister sends agents to kidnap the child in the storyline "X-Men: Messiah Complex." Later, Sinister (whose powers are still weakened) is confronted by Mystique, who presses the villain's face against an unconscious Rogue. Rogue's energy absorption abilities are amplified at the time, causing her skin-to-skin contact with Sinister to kill the villain almost instantaneously. ==== Miss Sinister ==== Thanks to using the Cronus Device decades earlier to implant his own genetic information into the Marko, Ryking, Shaw, and Xavier family lines, Sinister's consciousness is able to inhabit Charles Xavier's body following his death at Mystique's hands. Sebastian Shaw and Gambit destroy the machine, enabling Xavier to drive out Sinister's consciousness. A fail-safe plan allows Sinister's consciousness to then activate within former test subject Claudine Renko, whose body then transforms to mimic Sinister's powers and genetics but with female sex
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characteristics. Although she gains some of Sinister's memories and his knowledge of science, Renko's personality remains intact and resists Sinister's personality. Seeing herself as a different person rather than a host or a clone, Renko takes the name Miss Sinister. Gambit and Laura Kinney, a young woman known as X-23, who was cloned from Wolverine's DNA, encounter a girl named Alice, who introduces them to her owner/adoptive mother, Miss Sinister. Renko explains Alice is also a clone, the fourth of a series created by Essex as one of several experiments involving children held in a desert lab. Renko explains Sinister's mind is like a virus attempting to overtake her. She hopes to maintain her own mind by switching bodies with X-23. The plan backfires when Essex's mind telepathically takes control of X-23 and uses her to mortally wound Renko. Laura overcomes Essex's presence, then escapes the lab with Alice and Gambit, freeing the other children test subjects in the process. In the wreckage left behind, Claudine Renko lives, looked over by a fifth Alice clone who now contains Mr. Sinister's consciousness in her mind. Miss Sinister is next seen in the company of the reality displaced X-Men of a now-dead universe. One member of this team, Jimmy Hudson, has a genetic anomaly that could enable Renko to create and control spontaneous mutation. Over the following months, Renko further researches this anomaly, calling it Mothervine, for the purpose of controlling mutant childbirths, causing further evolution in natural-born mutants, and triggering mutation in non-mutants. Though she realizes the secondary and primary mutations caused by such tampering are debilitating to the point of being lethal, Renko works with Bastion, Emma Frost, and Havok to unleash Mothervine on a global scale. Mothervine bombs containing the catalyst are launched into a dozen major American cities
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resulting in the emergence of primary mutations in people that didn't possess the X-Gene, as well as the appearance of secondary and tertiary enhancements in mutants. The time-displaced X-Men attack but are quickly defeated and captured. Seeing the damage done by Mothervine and realizing all mutants may become enslaved to Miss Sinister, Emma Frost telepathically forces the New Marauders to fight Renko. Miss Sinister activates genetic implants in the New Marauders, killing them instantly. Emma Frost frees Jimmy Hudson from his metal restraints, and he seemingly slays Miss Sinister. The effects of Mothervine are then contained and reversed by Magneto and Elixir. === 2010s === Mister Sinister is eventually able to fully possess the fifth clone of Alice, returning in The Uncanny X-Men #544. Now dressed in Victorian-era garb and using knowledge gained from Apocalypse, he merges with the alien giant known as the Dreaming Celestial, gaining great power. Sinister turns San Francisco's residents into doppelgangers of himself and attempts to create a society resembling 19th century England, which he claims to now see as a perfect culture. His true plan is to gain the attention of the alien Celestials so they might deem humanity too chaotic and then eradicate the species, leaving him to rebuild the planet with a better version of humanity. The X-Men restore San Francisco and defeat Sinister, who loses his enhanced power. Foreseeing the Phoenix Force will one day return to Earth, Sinister tells the young mutant Hope Summers about its existence, knowing she will be its choice for a new host. In truth, he intends to steal the Phoenix energy by using a group of Madelyne Pryor clones. When the Phoenix Force arrives on Earth during the "Avengers vs. X-Men" storyline, its power is divided between five people, including Cyclops. The Phoenix Five track
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down Mister Sinister, learning he has built his own city (based on Victorian-era London) within Subterranea that is inhabited by clones of himself, several of his agents, and some acquaintances. Sinister orders his clones to war against the Phoenix Five. After help arrives, the Phoenix Five kill each and every clone of Sinister present. In the aftermath of "Avengers vs. X-Men," Sinister visits Cyclops and explains that some time ago he killed the X-Men public relations manager Katie Kildare, placing his own personality in the woman's mind while a secondary Sinister clone was left in charge of the city. While his clones and resources are gone, he still lives and will strike again. Sinister, now again in a cloned body of his old form, then infiltrates the X-Men's original mansion home, recently renamed the Jean Grey School, through its student Ernst. Ernst provides Sinister access to DNA samples from the mutants within the school in exchange for providing her friend Martha Johannesen with a new body. His efforts are ultimately foiled by the students and Spider-Man, who was asked by Wolverine to help locate the school's mole. Sinister escapes but his new DNA samples are destroyed. === All New, All Different === When the Inhuman city of Attilan is under attack, its leader Black Bolt releases Terrigen Mist across Earth, the same mutagenic agent derived from Terrigen crystals that unlock an Inhuman's superhuman potential. This causes many humans with latent Inhuman genes (due to an ancestor) to discover new powers. It also proves deadly to mutants after sustained exposure. Mister Sinister experiments on unwilling subjects to see if Inhuman and mutant DNA together can create a genetically superior species. His tests prove such a species would be unstable. After witnessing the death of a test subject that is a copy
|
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of Cyclops, Sinister is defeated by the X-Men and taken to the authorities. During the "Hunt for Wolverine" storyline, Mister Sinister's cell samples of Logan are stolen by a thief who attempts to auction them off. Sinister attacks the thief but is then fought by X-23, who forces him to retreat. The auction attendees are evacuated to South Korea's National Intelligence Service Helicarrier as Iron Man, Jessica Jones, Luke Cage, Spider-Man, and X-23 interrogate the seller Declan Fay. He directs them to the Kerguelen Islands where Mister Sinister has collected the genetic make-up of every person on Earth. Sinister reveals a kill team recently stole his work. The heroes then destroy his database before leaving. Soon after this, Sinister becomes highly interested in Iceman's increased power and control. === The Quiet Council === In the 2019 Powers of X series, it is revealed that at some point in the past, Sinister created his first clone community on an island in the South Pacific, calling it Bar Sinister. While here, he is approached by Professor Xavier and Magneto regarding his collection of DNA samples. Xavier asks Sinister to prioritize cataloging mutant DNA to create a comprehensive database that would be safe, secure, and redundant. In exchange, he offers to provide samples Sinister would have trouble getting on his own. The lead Mister Sinister clone is not interested in the deal but is suddenly killed by another Sinister clone who has a functional X-gene, making him a mutant too. This Sinister clone becomes leader of the community and agrees to have his memories of this deal and encounter telepathically repressed until the day Xavier and Magneto tell him to remember. It is apparently this version of Sinister, or another X-gene clone with his memories, who survived the slaughter of the Phoenix Five.
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This meeting between the mutant Sinister clone, Magneto, and Xavier may have taken place soon before the first X-Men team was formed (in which case, the mutant Sinister has been the primary version the X-Men have fought over the years), or during the early 1980s era of X-Men stories (during which time Magneto and Xavier sometimes acted as allies again and before Xavier regained the ability to walk from 1983 to 1991), or during the early or late 1990s era of stories (indicated by Xavier using a Shi'ar hover chair he started using in 1991, Moira MagTaggert's journal claiming the meeting happened before her apparent death in 2001, and Magneto operating openly as he did from 1990 to 1991 and from 1997 to 2001, whereas he was believed dead from 1992 to 1993, was catatonic from 1993 to 1995, and was operating in secret as Erik the Red from 1995 to 1997). The existence of this mutant version of Sinister helps explain why the villain is classified as an "Alpha-level mutant" in X-Men (vol. 2) #94 (1999) despite previous stories establishing Nathaniel Essex was born a human without an X-gene and was granted powers by Apocalypse using alien technology. Sometime later, along with other mutants, the X-gene Sinister is welcomed to the new mutant community existing on the island Krakoa. At the invitation of Xavier, Magneto and Apocalypse, he joins the Quiet Council that governs Krakoa, agreeing to not continue his schemes to harvest the DNA of mutants. In Marvel's 2019 relaunch of its X-Men franchise, Dawn of X, Sinister finds himself already bored with his new status on Krakoa, and decides to resume his schemes by utilizing a loophole in the Quiet Council rules. To begin, he starts a file concerning Franklin Richards, the mutant son of Mr. Fantastic
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and the Invisible Woman. === The Moira Engine === ==== Essex genetic templates ==== Immortal X-Men #8 (January 2023), which opens in 1895 London, shows that the powers that Apocalypse gave Essex were slowly deteriorating and killing him, and to survive he needed to feast upon the flesh of innocent people who he killed, prompting two long-lived mutants, Mystique (Sherlock Holmes/Raven DarkhΓΆlme) and Destiny (Irene Adler) to confront and imprison him. Essex told the two women that Apocalypse did grant him the power to see the future, including major developments in the 20th and 21st centuries such as the escalation of the scale of war and the rise of the machines as the dominant beings on the planet. After Mystique secretly kills Essex in his cell, covering up her crime in her Holmes form, Destiny finds in a basement level, four human-sized tanks, each one marked with one of the four suits found on playing cards, smashed open and empty. === Fall of X and the Enigma Dominion === While Sinister was trapped within the Pit, the genetic code he had implanted into the assassinated council members was nullified by Forge, with one key exception; Professor X, whom Sinister had experimented on as a child. As Krakoa was destroyed by Orchis, with mutantkind scattered, the part of Sinister within Xavier began looking for ways to overcome its host, and began piloting his body while he slept, simultaneously working on a way to fight the Sinister Dominion. After Xavier discovered the truth, Sinister revealed himself to him. He opened his mind to Xavier and managed to convince him not to kill himself and to work together with Sinister to stop the Dominion. Xavier and Sinister eventually discover the truth behind the four Nathaniel Essex Sinister clones; they were all created to
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absorb data, leading to the birth of a 5th "child" of Nathaniel Essex: an "apex AI" called Enigma, the same force revealed that stands above all creation, and is coming to end Eternity, the personification of the Multiverse. In truth, years ago, Essex decided the only way to defeat the coming machine supremacy was to join them, creating his own all-powerful artificial intelligence, which is where Enigma comes in. Enigma - using a Crown symbol similar to a card deck's King - is the 5th "child" of Essex, an AI that was able to reach Dominion outside time and space after all four clones attempted to reach said status, got incredibly close, and then failed to ascend. == Powers and abilities == As a result of undergoing genetic engineering at the hands of Apocalypse, the original Mister Sinister gained, as revealed in Immortal X-Men #8, precognitive powers that granted him the power to see the future, including major developments in the 20th century such as the escalation of the scale of war. However these powers were slowly killing him. By the late twentieth century, Sinister's mind had been copied into the bodies of others, as well as clones of his own creation. Since no clone is completely perfect on a cellular level, some differences emerged in their biology and personality. At least one clone of Mr. Sinister developed the X-gene in his DNA. This mutant version of Mr. Sinister became the leader of the many versions of the clone community in the 2019 Powers of X miniseries, and has been the primary Sinister to encounter the X-Men since. Mister Sinister has the ability to shape-shift from a humanoid form to an amorphous one. Sinister is an expert at genetic manipulation and a skilled surgeon. On rare occasions, Mister Sinister has
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exhibited the ability to teleport, but it was indicated that this was not an inherent power and was accomplished through the technology of his tesseract headquarters. == Clones of Mister Sinister == Nathaniel Essex cloned himself, and members of his original family, many times. In addition to countless Mister Sinister variations are several unique clones. === Doctor Stasis === Doctor Stasis is a clone of Mister Sinister with a suit of clubs on his forehead, who dedicated his life to unlocking the full potential of humans rather than mutants. Flashbacks reveal that he was involved in experiments leading to the origins of Captain America, Hulk and Spider-Man, among others. Like Sinister, Stasis heavily employs clones, using animal chimeras as servants and having dinners with disposable clones of his late wife and sons. In the present day, he became the director of the Orchis Petal of Human Resources. As a precaution to protect himself from psychic attacks, Doctor Stasis wears a full mask over his head. === Orbis Stellaris === Orbis Stellaris is a clone of Mister Sinister with a suit of spades on his forehead who became an intergalactic arms dealer and used alien technology to prolong his life. He took over the World Farm and later clashed with S.W.O.R.D. === Enigma === First mentioned as a force that stands above all creation and a serious threat to the Marvel Universe which forced the Beyonders to orchestrate the destruction of the Seventh Cosmos through the Molecule Man and the Incursions. A glimpse of the Enigma was first seen by Loki after he survived the destruction of the Seven Cosmos, and before he landed in Taaia's Sixth Cosmos. The God of Stories describes it as " the Crown Above All Things," a menace from beyond the threshold of time, beyond the
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Multiverse itself. Enigma is actually Nathanial Essex's 5th "child", an "apex AI" which used the other four Nathaniel Essex clones to achieve Dominion. === Mother Righteous === Unlike the previously mentioned entities, Mother Righteous is not a clone of Essex himself, but of his deceased wife Rebecca. She is a supremely skilled magic-user and collector of magical artefacts, and a vicious dealer for sorcerous favors with persons like Margali Szardos and Selene. == Reception == In 2017, WhatCulture ranked Mister Sinister 4th in their "10 Most Evil X-Men Villains" list. In 2018, CBR.com ranked Mister Sinister 4th in their "20 Most Powerful Mutants From The '80s" list. == Other versions == === Age of Apocalypse === In the alternate timeline of the 1995β96 "Age of Apocalypse" storyline, Nathaniel Essex is one of Apocalypse's Four Horsemen, making him one of the ruling council that oversees the villain's dominion. He calls himself simply "Sinister" rather than "Mr. Sinister." In this world where Earth's general population became aware of the power and abundance of mutants over a decade earlier than they would have otherwise, Sinister does not bother with manipulating Alex and Scott Summers from the shadows via his orphanage. Instead, he adopts them directly after they are orphaned, becoming their foster father, encouraging their training as warriors and teaching them that their mutant genes place them above the non-mutant "flat scans" who inhabit the Earth. Scott becomes Sinister's obvious favorite son, creating great resentment and animosity in Alex. Later on, Sinister recruits the amoral scientist Hank McCoy, the Dark Beast, as his lab assistant. Though impressed with Dark Beast's abilities, Sinister is disturbed and at times angry with McCoy's habit of enhancing and altering mutations just for the enjoyment of seeing the results, rather than having a true purpose or benefit for
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his research. As the years go on, Cyclops comes to doubt the path of Apocalypse. Though publicly he enforces Sinister's will, fighting criminals and rebels such as that timeline's X-Men, in secret he aids humans and others who need to escape Apocalypse's territory or Sinister's holding pens. Unknown to Cyclops, his "father" Sinister is disillusioned with Apocalypse's empire, convinced the mutant conqueror's actions will simply cause the destruction of Earth eventually, leaving no possibility for a master race to live. Wishing a living weapon he can use against Apocalypse, Sinister clones a powerful mutant from the combined genetic codes of Scott Summers and the X-Man rebel named Jean Grey. Sinister names the genetically engineered boy "Nathan Grey", deciding that while Jean Grey was the boy's mother, he himself was the father. Sinister accelerates Nathan's aging and the boy quickly becomes a teenager, his mutant X-gene granting him incredible telekinetic and telepathic power. Realizing the boy's raw power could easily burn out his life and body prematurely, Sinister becomes desperate to gain full control of Nathan's mind and abilities to use him as a weapon. One night, not knowing the boy's intended purpose or their connection to each other, Cyclops finds and frees Nathan Grey from Sinister's secret lab in the Blightlands. Before Cyclops can lead him to safety, the impulsive teenager immediately unleashes his power and leaves on his own, eventually meeting a group of traveling entertainers called the Outcasts, led by the mutant inventor Forge. The Outcasts accept "Nate" into their ranks. Realizing his creation has fled, Sinister abandons his labs to quickly recapture Nate before he is discovered and killed, knowing Apocalypse will consider his sudden departure a sign of betrayal regardless. Changing his appearance and calling himself simply "Essex," Sinister joins the Outcasts and is present when
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they are attacked by Apocalypse's assassin Domino. When Forge realizes that Essex has a dark plan for Nate, Sinister kills him and reveals himself. Sinister explains Nate's origin and purpose to be the destroyer of Apocalypse. Nate defeats and dismisses Sinister, choosing to be an individual rather than a weapon. He then leaves to face Apocalypse on his own which then leads to Nate Grey being transported into the original timeline of the mainstream Marvel Universe. In the Age of Apocalypse 10th anniversary limited series, Sinister collected the seemingly dead Jean Grey after discovering that it was her connection to the Phoenix Force that saved the world from annihilation. When Magneto was credited with saving the planet, Sinister confronted him and revealed the truth. With Magneto now the head of the Department of Mutant Affairs, Sinister blackmailed him to keep his X-Men away even though Sinister was wanted for war crimes. The X-Men still attempted to hunt down Sinister, unaware that their leader was secretly avoiding this outcome. The truth came out when Paige Guthrie, an X-Man abandoned by her mentors during a mission, attempted to get her revenge on them. Her dying words exposed Magneto's duplicity. After explaining the situation to his X-Men, Magneto and the others found Sinister hidden on Liberty Island. He faced the X-Men with his minions the Sinister Six, which included Cloak and Dagger, Sonique, Sauron, Blob and Jean Grey herself. In the final battle, Jean broke free from Sinister's control and bombarded him with the Phoenix energy, heavily charing his body. Sinister was impaled by both Weapon X and Kirika, slaying him. === Mutant X === In the alternate universe of the series Mutant X, Mr. Sinister is responsible for Christopher Summers and his wife Katherine Anne Summers meeting, ensuring that the powerful mutants
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Cyclops and Havok would be born. Sinister joins forces with a villainous Xavier and clashes with this reality's version of Apocalypse, who becomes allies with Jean Grey and Magneto. Sinister and Xavier create the clone Madelyne Pryor, guiding her to meet and fall in love with Havok, leading to a son named Scotty. Sinister also creates another Summers clone called X-Man (a version of Nate Grey). He and Xavier hope to control the evolution of humanity, but Sinister turns on Xavier when he realizes the telepath has his own agenda. Xavier kills Sinister but his plans are then stopped by that reality's heroes and the Havok of the mainstream Marvel timeline. === X-Men: The End === A trilogy of mini-series under the banner X-Men: The End was published from 2004 to 2006, taking place in a possible future timeline, roughly "fifteen years" forward from where the X-Men stories were in 2004. Sinister is featured in the first mini-series, and then in the second mini-series he blackmails Gambit into bringing him the children of Scott Summers and Emma Frost as well as his own children that he conceived with Rogue. Sinister reveals Gambit is not a natural-born mutant but actually a clone of himself with some of Cyclops's DNA imprinted into his code. The purpose had been to create a "son" with Cyclops's abilities. Knowing Sinister's plan to transplant his own mind into this potentially powerful mutant form, Apocalypse arranged for the boy to be kidnapped and then sent to be raised by the Thieves Guild in New Orleans. Growing up, Gambit only developed a variation of Scott's powers, giving him red eyes and the ability to charge things with explosive force instead of releasing great kinetic force from his body. Taking on Gambit's appearance, Sinister kills Rogue when she arrives
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to rescue the children. In the end, Rogue's adopted mother Mystique murders Sinister in vengeance. === Earth X === In Paradise X, an alternate universe first introduced in the 1999 miniseries Earth X, an older Colossus reveals that he was Mister Sinister all along. After years with the X-Men, he fell in love with Jean Grey and then traveled back in time to learn how to preserve her as a clone, leading to his transformation into the psychopathic geneticist Mr. Sinister who then fought the X-Men, including his younger self. === Ultimate Marvel === In the Ultimate X-Men series, taking place in the Ultimate Marvel Universe, Nathaniel Essex is reimagined as a heavily tattooed street thug nicknamed "Sinister" due to his tattoo. He is a former OsCorp scientist who experiments on himself after failing to perfect his formula on stealth and mind-altering drugs to create a super-soldier who could evade any form of detection and hypnotically persuade others. He seemingly suffers from hallucinations of a being called "Lord Apocalypse" who orders him to kill a number of mutants to complete his transformation. After committing suicide in the Triskelion, Sinister returns to life and transforms into the Ultimate Marvel version of Apocalypse himself, battling an armored Cable and Professor X in his Onslaught form. However, the Phoenix Force appears and destroys his form. After the "Ultimatum Wave", he reforms his body and gets a job at Roxxon as part of their "brain trust". He then allies with Layla Miller and the two embark on a mission to find four specific mutants, at least one of whom is Alex Summers. Their mission and full agenda never come into fruition, as the entire Ultimate Universe soon ends due to a universal incursion depicted in the 2015 Secret Wars event. === X-Men Forever ===
|
{
"page_id": 528214,
"source": null,
"title": "Mister Sinister"
}
|
The 2009 series X-Men Forever (vol. 2) featured stories and canon Chris Claremont would have established had he continued working on the X-Men comics after 1991. In the 2010 sequel series X-Men Forever 2, Nathaniel Essex is a mutant who is over a century old but stuck in the body of a ten-year-old child. Reasoning that no one would be intimidated by his true appearance, Essex uses creates the robot Mr. Sinister, using it as an avatar to command the Marauders. In this timeline, mutants do not live long lives (with rare exceptions) because their mutant abilities cause "burn-out" in their bodies, leading to death later on (which happens earlier if more power is used as they approach middle age). Essex's genetic research and interest in the X-Men is because he believes they may be a key to finding a cure for X-gene burn-out. Sinister's Mauraders attack Cyclops's family in Alaska, including his son Nate. In this reality, Sabretooth joins the X-Men after Wolverine is killed, but Sinister then clones both of them to create Marauder versions loyal to him. After the Marauders are defeated, Cyclops and Nate befriend a new neighbor named Robyn, who is actually one of Sinister's agents. The series ends before resolving this storyline. === 1602 === In the 1602 reality, Lord Nathaniel Essex is a former advisor to King James II, revealed to be a witchbreed murderer of women. He was caught by witch hunters Angela and Lady Serah. == In other media == === Television === Nathaniel Essex / Mister Sinister appears in X-Men: The Animated Series, voiced by Christopher Britton. This version mutated himself amidst his research to save his ailing wife, culminating in his obsession with Cyclops and Jean Grey. Mister Sinister appears in X-Men '97, voiced again by Christopher Britton. Mister
|
{
"page_id": 528214,
"source": null,
"title": "Mister Sinister"
}
|
Sinister appears in Wolverine and the X-Men, voiced by Clancy Brown. This version was born a mutant, is obsessed with creating and weaponizing the "ultimate mutant", and leads the Marauders in collecting mutant DNA. Mister Sinister appears in the M.O.D.O.K. episode "If Saturday Be... For the Boys!", voiced by Kevin Michael Richardson. === Video games === Mister Sinister appears in X2: Wolverine's Revenge, voiced by Christopher Corey Smith. Mister Sinister appears as a boss in X-Men Legends II: Rise of Apocalypse, voiced by Daniel Riordan. This version experiments on Genoshan prisoners on Apocalypse's behalf. Mister Sinister appears as a boss in Marvel Heroes, voiced by Steve Blum. Mister Sinister appears as the final boss of Deadpool, voiced by Keith Ferguson. Mister Sinister appears as a boss in Marvel Avengers Alliance. Mister Sinister appears as a playable character in Marvel Contest of Champions. Mister Sinister appears as a playable character in Marvel: Future Fight. Mister Sinister appears as a playable character in Marvel Puzzle Quest. Mister Sinister appears as a playable character in Marvel Strike Force. This version is a member of the Marauders. == Notes == == References == == External links == Mister Sinister at Marvel.com Sinister Observations at UncannyXmen.Net Citadel Mister Sinister on Marvel Database, a Marvel Comics wiki. Archived 2009-10-21 at the Wayback Machine
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{
"page_id": 528214,
"source": null,
"title": "Mister Sinister"
}
|
FreeFem++ is a programming language and a software focused on solving partial differential equations using the finite element method. FreeFem++ is written in C++ and developed and maintained by UniversitΓ© Pierre et Marie Curie and Laboratoire Jacques-Louis Lions. It runs on Linux, Solaris, macOS and Microsoft Windows systems. FreeFem++ is free software (LGPL). FreeFem++ language is inspired by C++. There is an IDE called FreeFem++-cs. == History == The first version was created in 1987 by Olivier Pironneau and was named MacFem (it only worked on Macintosh); PCFem appeared some time later. Both were written in Pascal. In 1992 it was re-written in C++ and named FreeFem. Later versions, FreeFem+ (1996) and FreeFem++ (1998), used that programming language too. == Other versions == FreeFem++ includes versions for console mode and MPI FreeFem3D Deprecated versions: FreeFem+ FreeFem == See also == List of finite element software packages == References == == External links == Official website
|
{
"page_id": 32313179,
"source": null,
"title": "FreeFem++"
}
|
The molecular formula C10H11NO3 (molar mass: 193.20 g/mol, exact mass: 193.0739 u) may refer to: Actarit Betamipron Methylenedioxycathinone Methylhippuric acid
|
{
"page_id": 24711006,
"source": null,
"title": "C10H11NO3"
}
|
The IEEE Heinrich Hertz Medal was a science award presented by the IEEE for outstanding achievements in the field of electromagnetic waves. The medal was named in honour of German physicist Heinrich Hertz, and was first proposed in 1986 by IEEE Region 8 (Germany) as a centennial recognition of Hertz's work on electromagnetic radiation theory from 1886 to 1891. The medal was first awarded in 1988, and was presented annually until 2001. It was officially discontinued in November 2009. == Recipients == 1988: Hans-Georg Unger (Technical University at Brunswick, Germany) for outstanding merits in radio-frequency science, particularly the theory of dielectric wave guides and their application in modern wide-band communication. 1989: Nathan Marcuvitz (Polytechnic University of New York, United States) for fundamental theoretical and experimental contributions to the engineering formulation of electromagnetic field theory. 1990: John D. Kraus (Ohio State University, United States) for pioneering work in radio astronomy and the development of the helical antenna and the corner reflector antenna. 1991: Leopold B. Felsen (Polytechnic University of New York, United States) for highly original and significant developments in the theories of propagation, diffraction and dispersion of electromagnetic waves. 1992: James R. Wait (University of Arizona, United States) for fundamental contributions to electromagnetic theory, to the study of propagation of Hertzian waves through the atmosphere, ionosphere and the Earth, and to their applications in communications, navigation and geophysical exploration. 1993: Kenneth Budden (Cavendish Laboratory, University of Cambridge, United Kingdom) for major original contributions to the theory of electromagnetic waves in ionized media with applications to terrestrial and space communications. 1994: Ronald N. Bracewell (Stanford University, United States) for pioneering work in antenna aperture synthesis and image reconstruction as applied to radioastronomy and to computer-assisted tomography. 1995: Jean van Bladel (Ghent University, Belgium) for major contributions in fundamental electromagnetic theory and
|
{
"page_id": 14028639,
"source": null,
"title": "IEEE Heinrich Hertz Medal"
}
|
its application to electrical engineering. 1996: Martin A. Uman (University of Florida, United States) for outstanding contributions to the understanding of lightning electromagnetics and its application to lightning detection and protection. 1997: Owen Storey (Stanford University, United States) for discovering the field-aligned paths of Hertzian-wave whistlers generated by lightning, thus discovering the Earth's magnetosphere. 1998: Chen To Tai (University of Michigan, United States) for outstanding contributions to electromagnetic and antenna theory and the development and application of Green's dyadics. 1999: Akira Ishimaru (University of Washington, United States) or fundamental contributions to the theories and applications of wave propagation and scattering in random media and backscattering enhancement. 2000: Arthur A. Oliner (Polytechnic University of New York, United States) for contributions to the theory of guided waves and antennas. 2001: Adrianus de Hoop (Delft University of Technology, Netherlands) for fundamental contributions to the theory of reciprocity and to the understanding of electromagnetic wave propagation layered in media. == See also == List of physics awards == References == == External links == IEEE Heinrich Hertz Medal
|
{
"page_id": 14028639,
"source": null,
"title": "IEEE Heinrich Hertz Medal"
}
|
The molecular formula C19H23ClN2 (molar mass: 314.85 g/mol, exact mass: 314.1550 u) may refer to: Clomipramine Homochlorcyclizine
|
{
"page_id": 37687136,
"source": null,
"title": "C19H23ClN2"
}
|
David Dexter Perkins (May 2, 1919 β January 2, 2007) was an American geneticist, a member of the faculty of the Department of Biology at Stanford University for more than 58 years, from 1948 until his death in 2007. He received his PhD in Zoology in 1949 from Columbia University. A member of the National Academy of Sciences, he served as president of the Genetics Society of America in 1977. In a scientific career that spanned more than six decades, Perkins collaborated on more than 300 papers. His associates included many graduate students and postdoctoral fellows who went on to scientific careers throughout the world. == Scientific career == Upon his arrival at Stanford, he began a collaboration with Edward Tatum, who had been working with Neurospora crassa since 1941 in collaboration with George Beadle. In this way, he was connected to the very earliest research with Neurospora. Throughout his career, he continued to work with Neurospora crassa, which he often championed as a model organism. At the time that he died in 2007, a substantial percentage of all researchers in the world who were working with Neurospora crassa had either trained with or collaborated with Perkins or one of his students or associates. Perkins is best known for his research into the control and regulation of cell division and sexual reproduction in fungi. One of the advantages to Neurospora as a model organism is that it undergoes both sexual and asexual reproduction. Working with associates, Perkins identified many of the genes that control meiotic cell division in Neurospora crassa. In the process, he made fundamental discoveries about the cellular regulation and control of meosis. Building on his discoveries about meiosis, Perkins carried out investigations into ascospore genesis. Ascospore genesis, a form of sexual reproduction common to many fungi, has
|
{
"page_id": 8851297,
"source": null,
"title": "David Perkins (geneticist)"
}
|
parallels with oogenesis and spermatogenesis in mammals and other chordates. Many of his papers in this area were concerned with genetic recombination, with the rearrangement of genes on paired chromosomes that occurs during reproduction, a phenomenon known as crossing over. Perkins developed techniques for mapping genes and centromeres on chromosomes based on the occasional errors, such as duplications and translocations, that occur in recombination. He trained many scientists to work with Neurospora crassa, and wrote several papers on working with, caring for, and maintaining Neurospora under laboratory conditions. He was instrumental in establishing and supporting the Fungal Genetics Stock Center. In 1968, he began a project to obtain wild type Neurospora at tropical and subtropical sites throughout the world. Perkins and his associates surveyed and collected more than 5,000 specimens of Neurospora and other fungi growing in the wild. Later, he initiated work on what would eventually become a worldwide resource for geneticists, The Neurospora Compendium: Chromosomal Loci. Published most recently in 2001, it serves as a reference for mutations and their loci in the Neurospora genome. == References == Perkins, D; Davis, R (Dec 2000), "Evidence for Safety of Neurospora Species for Academic and Commercial Uses", Applied and Environmental Microbiology, vol. 66, no. 12, pp. 5107β9, Bibcode:2000ApEnM..66.5107P, doi:10.1128/aem.66.12.5107-5109.2000, PMC 92429, PMID 11097875 The Perkins Lab β Neurospora genetics and biology Archived 2012-10-09 at the Wayback Machine David D. Perkins, Alan Radford, Matthew S. Sachs. The Neurospora Compendium: Chromosomal Loci. Academic Press: 1st edition (January 15, 2001). ISBN 0-12-550751-8. Rowland H. Davis: Neurospora. Contributions of a Model Organism. Oxford University Press, Oxford, 2000. ISBN 0-19-512236-4. == External links == David Perkins (geneticist) β Biographical Memoirs of the National Academy of Sciences
|
{
"page_id": 8851297,
"source": null,
"title": "David Perkins (geneticist)"
}
|
Labes is also the German name of Εobez, Poland. As well as an extinct mammal. Labes (plural: labes) is a Latin word used by exogeologists to refer to chaotic regions, featuring ridges and steep valleys, in the Valles Marineris region of Mars. Labes are named after the nearest classical albedo feature. == List of labes == This is a list of all named labes. Planetocentric coordinates are given as planetocentric latitude with east longitude. == References ==
|
{
"page_id": 12324707,
"source": null,
"title": "List of Labes on Mars"
}
|
FutureGen was a project to demonstrate capture and sequestration of waste carbon dioxide from a coal-fired electrical generating station. The project (renamed FutureGen 2.0) was retrofitting a shuttered coal-fired power plant in Meredosia, Illinois, with oxy-combustion generators. The waste CO2 would be piped approximately 30 miles (48 km) to be sequestered in underground saline formations. FutureGen was a partnership between the United States government and an alliance of primarily coal-related corporations. Costs were estimated at US$1.65 billion, with $1.0 billion provided by the Federal Government. First announced by President George W. Bush in 2003, construction started in 2014 after restructuring, canceling, relocating, and restarting. Citing an inability to commit and spend the funds by deadlines in 2015, the Department of Energy withdrew funds and suspended FutureGen 2.0 in February, 2015. The government also cited the Alliance's inability to raise the requisite amount of private funding. The Meredosia power plant that had been planned for retrofit was demolished around 2021. FutureGen 2.0 would have been the most comprehensive Department of Energy Carbon Capture and Storage demonstration project, involving all phases from combustion to sequestration. FutureGen's initial plan involved integrated gasification combined cycle technology to produce both electricity and hydrogen. Early in the project it was to be sited in Mattoon, IL. == Original project == The original incarnation of FutureGen was as a public-private partnership to build the world's first near zero-emissions coal-fueled power plant. The 275-megawatt plant would be intended to prove the feasibility of producing electricity and hydrogen from coal while capturing and permanently storing carbon dioxide underground. The Alliance intended to build the plant in Mattoon Township, Coles County, Illinois northwest of Mattoon, Illinois, subject to necessary approvals (issuing a βRecord of Decisionβ) by the Department of Energy (DOE) as part of the National Environmental Policy Act (NEPA)
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
}
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process. FutureGen was to be designed, developed and operated by the FutureGen Industrial Alliance, a non-profit consortium of coal mining and electric utility companies formed to partner with the DOE on the FutureGen project. The project was still in the development stage when its funding was cancelled in January 2008. The Alliance decision of the location of the host site, subject to DOE's completing NEPA environmental reviews, was announced in December 2007 after a two-year bidding and review process. Construction was scheduled to begin in 2009, with full-scale plant operations to begin in 2012. The estimated gross project cost, including construction and operations, and excluding offsetting revenue, was $1.65 billion. The project was governed by a legally binding cooperative agreement between DOE and the Alliance. Under the agreement, DOE was to provide 74% of the projectβs cost, with private industry contributing the other 26%. The DOE also planned to solicit the financial support and participation of international governments in the FutureGen project, since by 2020 more than 60% of man-made greenhouse gas emissions are expected to come from developing countries. Foreign financial support was to offset a portion of DOEβs cost-share. As of January 2008, the foreign governments of China, India, Australia, South Korea, and Japan had expressed interest in participating and sharing the cost of the project. FutureGen was to sequester carbon dioxide emissions at a rate of one million metric tons per year for four years, which is the scale a Massachusetts Institute of Technology (MIT) report cites as appropriate for proving sequestration. The MIT report also states that βthe priority objective with respect to coal should be the successful large-scale demonstration of the technical, economic, and environmental performance of the technologies that make up all of the major components of a large-scale integrated CCS system β capture,
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
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transportation and storage.β An injection field test similar to this was done in Norway. In March 2009 Washington Post reported that U.S. Secretary of Energy Steven Chu expressed support for continuing the project using stimulus funds (after some changes that have not yet been specified) and making it a part of a larger portfolio of research plants developed in collaboration with other countries. Following the successful completion of the first phase, in February 2013, the Energy Department announced the beginning of Phase II of the project development with a new cooperative agreement between the FutureGen Industrial Alliance and the Department of Energy. This means that the FutureGen project has government support as it moves into its third phase, deployment of the project. === Site selection === Site selection for the FutureGen facility was based on a competitive process which began in May 2006. Seven states responded to the Site Request for Proposals with a total of 12 proposals. Proposals were reviewed against a set of environmental, technical, regulatory, and financial criteria with input from external technical advisors on power plant design and carbon sequestration. In July 2006, four candidate sites were selected for further review, including an environmental impact analysis as required by NEPA. DOE issued its Final Environmental impact statement (EIS) on November 8, 2007, which concluded that all four sites were acceptable from an environmental impact standpoint and all would move forward in the site evaluation process. EPA published a Notice of Availability (NOA) for the EIS in the Federal Register on November 16, 2007. The DOE is required by federal law to wait at least 30 days after the NOA release before issuing its final Record of Decision (ROD). The waiting period legally closed on December 17, 2007. DOE chose not to issue the ROD and advised
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
}
|
the FutureGen Alliance to delay the final site selection announcement, which was scheduled to occur at the end of the 30-day waiting period. The Alliance chose to move ahead with the announcement, citing time, money, and a commitment to proposers to select the final site by year-end. "Every month of delay can add $10 million to the project's cost, solely due to inflation," said Michael Mudd, the Alliance's chief executive. The Michael Mudd, the CEO of the FutureGen Alliance, announced the selection of Mattoon, Illinois as the host site on December 18, 2007. According to the EIS, Mattoon, IL the site is located about 3.5 miles (5.6 km) northwest of downtown Mattoon in the eastern part of Mattoon township section 8 on 1.8 km2 (440 acres) of former farm land. The carbon sequestration area is about 8,000 feet (2.4 km) below the ground. In July 2007, Illinois Public Act 095-0018 became law giving the state of Illinois ownership of and liability for the sequestered gases. === Technology === Original FutureGen project was intended to combine and test several new technologies in a single location, including coal gasification, emissions controls, hydrogen production, electricity generation, and carbon dioxide capture and storage (CCS). Integrated Gasification Combined Cycle (IGCC) was the core technology behind FutureGen. IGCC power plants use two turbines β a gas and a steam turbine β to produce electric power more efficiently than pulverized coal plants. IGCC plants also make it easier to capture carbon dioxide for carbon sequestration. FutureGen was to capture carbon dioxide produced during the gasification process and pump it into deep rock formations thousands of feet under ground. FutureGen specifically targeted rock formations containing saline water, as these are one of the most abundant types of geologic formations that can be used to store carbon dioxide worldwide.
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
}
|
A study by the Global Energy Technology Strategy Program estimates the storage capacity of these saline rock formations in the U.S. to be 2,970 gigatons of carbon dioxide, compared to a capacity of 77 gigatons of carbon dioxide for all other types of reservoirs, such as depleted gas fields. Focusing on rock formations with saline water was intended to help ensure that the lessons learned from the project are broadly transferable throughout the U.S. and around the world. === Challenges === Maintaining the project schedule and keeping costs down were two major challenges with which the DOE and the FutureGen Alliance grappled. The project had remained on schedule with the announcement of the host site before the end of 2007; however, a desire by DOE to restructure the projectβs financial arrangement has brought the project to a halt. In December 2007, the DOE Acting Deputy Assistant Secretary for Fossil Energy James Slutz stated that projected cost overruns for the project "require a reassessment of FutureGen's design." And that "This will require restructuring FutureGen to maximize the role of private-sector innovation, facilitate the most productive public-private partnership, and prevent further cost escalation." The FutureGen Alliance wrote a letter to the Department of Energyβs Under Secretary C.H. βBudβ Albright Jr. stating that overall inflation and the rising cost of raw materials and engineering services are driving costs up on energy projects around the world. According to James L. Connaughton, chairman of the White House Council on Environmental Quality, the market for steel, concrete and power plant components has βjust gone through the roof globallyβ, and much of the reason is the construction of hundreds of new conventional coal plants. On January 11, 2008, the FutureGen Alliance sent a letter to the DOE offering to lower the government's portion of the project's costs.
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
}
|
The initial plans had called for DOE to pay based on a percentage of the total cost, and their portion had risen from about $620 million to about $1.33 billion. The letter indicated that DOE's portion would now be $800 million. Risk management was a significant portion of the cost of the first FutureGen experimental implementation. FutureGen involved many complex never-before-solved technology problems. The risks also included significant health risks, if the untested-technology systems failed to work correctly. === Funding cancellation === On January 29, 2008, the U.S. Department of Energy announced that it would pull its funding for the project, mostly due to higher than expected costs. The move is likely to delay the project as other members seek the additional funds that the DOE was to provide. The sudden concern over cost after an Illinois site was chosen over those in Texas raised questions about the motives for the cancellation. Local and state officials in Illinois, including then Governor Rod Blagojevich, expressed frustration at the move, especially in light of the money and resources that the state had spent to attract the project. Democratic Senator Dick Durbin of Illinois accused Energy Secretary Samuel Bodman of "cruel deception" of Illinoisans by "creating false hope in a FutureGen project which he has no intention of funding or supporting." Durbin claimed that "when the city of Mattoon, Illinois, was chosen over possible locations in Texas, the secretary of energy set out to kill FutureGen." Mattoon mayor David Cline said "one could question the motivation of the Department of Energy which was ready to move forward with the project until a site other than Texas was chosen." In March 2009, Congressional auditors determined that the DOE had miscalculated the government portion of the project's cost, overstating the amount by a half billion
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
}
|
dollars. As a result, the Bush administration cited the project as having nearly doubled in cost when, in reality, it had increased by 39% Secretary Bodman stated that with restructuring the FutureGen project, DOE plans "to equip multiple new clean-coal power plants with advanced CCS technology, instead of one demonstration plant. That will provide more electricity from multiple clean-coal plants, sequestering at least twice as much CO2 and providing for wider use and more rapid commercialization." == Revised plan FutureGen 2.0 == === Plans for continuing FutureGen === Despite the cancellation of funding by the DOE, the FutureGen Alliance continued to move forward with the project, opening an office in Mattoon and planning to buy the land for the plant in August 2008, in partnership with a local group. During the 2008 U.S. presidential campaigns, Sen. Barack Obama pledged his support to clean coal technologies, with plans to develop five commercial-scale coal plants equipped with CCS technology. In November 2008, Fred Palmer, senior vice president at Peabody Energy shared his outlook on FutureGen with the American Coalition for Clean Coal Electricity (ACCCE), saying that the FutureGen Alliance would "Make a concerted effort in the Obama administration to reinstate the project and get this built as originally planned." On June 12, 2009, the DOE announced a restart of design work for the FutureGen project. "Following the completion of the detailed cost estimate and fundraising activities," the press release states, "the Department of Energy and the FutureGen Alliance will make a decision either to move forward or to discontinue the project early in 2010." === Revised project: FutureGen 2.0 === On August 5, 2010, the DOE announced a retooling of the FutureGen project, dubbed FutureGen 2.0. The revised plan includes retrofitting a shuttered coal-fired power plant in Meredosia, Illinois to demonstrate advanced
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
}
|
oxy-combustion technology, and piping the carbon dioxide 175 miles to Mattoon for underground storage. Due to these changes, leaders in Mattoon decided to drop out of the FutureGen project. The Illinois sites vying for the underground storage portion of the project were in Christian, Douglas, Fayette, and Morgan counties, after sites in Adams and Pike counties were cut in December 2010. In February 2011, Morgan County was chosen for the sequestration site. In Sept, 2014 FutureGen received the first-ever EPA permits for four class VI carbon dioxide sequestration wells in Morgan County, with plans to store 1.1 million metric tons per year for 20 years. Also in 2014 FutureGen survived a lawsuit from Illinois Electric utility ComEd, which challenged the state's ability to impose a surcharge on all customers to pay for FutureGen electricity. According to critics, including the Illinois Policy Institute, the plan presents major environmental and fiscal pitfalls. === FutureGen 2.0 funding cancellation === The Department of Energy ordered suspension of FutureGen 2.0 in February, 2015. The funds, appropriated by the American Recovery and Reinvestment Act of 2009, needed to be committed by July 1 and spent by Sept 30, 2015. The government also cited the Alliance's inability to raise the requisite amount of private funding. Energy Secretary Ernest Moniz explained at a press conference βIf you look between now and July 1, without them having closed their financing, and try as we might, we just donβt see how it gets over the finish line.β At the time of suspension the power plant part of the project had spent $116.5 million and the sequestration part had spent $86 million. == Alliance members == The FutureGen Industrial Alliance is a consortium of 10 power producers and electric utilities from around the globe. === Former members === Four companies initially
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
}
|
a part of the FutureGen Industrial Alliance have since dropped out of the project. == See also == Coal pollution mitigation Carbon capture and storage Combined cycle Gasification Asia-Pacific Partnership for Clean Development and Climate North American Carbon Program == References == == External links == FutureGen Industrial Alliance, Inc (down since 2016) Marshall University Studies related to the Clean Coal Initiative Clean Coal Push Concerns Environmental Activists. October 16, 2005.
|
{
"page_id": 1249127,
"source": null,
"title": "FutureGen"
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|
At least four types of the enzyme phosphodiesterase 4 (PDE4) are known: PDE4A PDE4B PDE4C PDE4D == See also == 3',5'-cyclic-AMP phosphodiesterase Phosphodiesterase (PDE) PDE4 inhibitor
|
{
"page_id": 27791209,
"source": null,
"title": "Phosphodiesterase 4"
}
|
The Lichenologist is a bimonthly peer-reviewed scientific journal specialising in lichenology, including taxonomy, systematics, ecology, biogeography, and conservation. It is published by Cambridge University Press on behalf of the British Lichen Society and the editors-in-chief are Christopher J. Ellis (Royal Botanic Garden Edinburgh) and Leena Myllys (Finnish Museum of Natural History). == History == The journal was established in November 1958. It followed the founding of the British Lichen Society on 1 February 1958. The journal was founded as a publication of the British Lichen Society, with Peter Wilfred James as editor-in-chief. In its early years, the journal was modest in scope, comprising approximately fifty pages annually. The first two volumes were cyclostyled with text typed by Swinscow's secretary. In its first editorial, the primary objectives of the journal were outlined, which focussed on both the enhancement of lichenological study and the importance of nature conservation. The journal sought to address the scarcity of contemporary literature on British lichen taxonomy by providing detailed articles to assist botanists in identifying local species. Additionally, it aimed to foster contributions on the distribution and ecology of lichens in Britain, areas that were then under-explored. Emphasising the balance between research and the ecological impact of specimen collection, the journal advocated for careful, responsible study practices to avoid harming these slow-growing organisms. In its early years, the journal experimented with different cover designs before settling on a mint green cover in 1959, which remained in use until 2000. The journal also transitioned from irregularly published volumes to annual volumes, with volume 6 in 1974 marking the start of consecutively numbered volumes synchronised with calendar years. Despite being founded in 1958, the journal reached its fiftieth volume only in 2018, as the early volumes spanned multiple years each. Over the decades, the journal grew in size,
|
{
"page_id": 70848363,
"source": null,
"title": "The Lichenologist"
}
|
scope, and international significance. For a considerable period, it was the only scientific journal in the world dedicated entirely to lichens, making it an essential publication for research in the field. As it expanded, it became increasingly respected internationally while remaining the flagship publication of the British Lichen Society. During Crittenden's tenure as senior editor from 2000 to 2019, the journal underwent several significant changes that modernised and enhanced the journal's impact. In 2001, Crittenden initiated a comprehensive overhaul of the journal's layout and printing, introducing a larger page size and a new cover design that departed from the long-standing mint green cover used since 1959. This visual refresh coincided with efforts to broaden the journal's content and appeal. Crittenden also introduced thematic issues focusing on specific topics within lichenology, which helped to consolidate research in particular areas and increase reader engagement. He also encouraged the submission of longer, more comprehensive papers, allowing for more in-depth treatments of complex subjects. This shift towards more substantial contributions was reflected in an increase in the average number of pages per paper over the years. Under Crittenden's leadership, the journal also adapted to changes in academic publishing practices and implemented effective electronic publication. In response to evolving nomenclatural requirements, the obligate registration of new fungal names was introduced, ensuring that taxonomic contributions met the latest standards in the field. Perhaps one of the most notable changes came in 2016 when Crittenden implemented a policy to reject "single naked species descriptions". This decision encouraged authors to contextualise new species descriptions within broader taxonomic or ecological frameworks, thereby increasing the overall impact and usefulness of such contributions. Despite initial concerns, this policy change did not decrease the number of new species described in the journal; instead, it led to more comprehensive taxonomic papers. == Editors-in-chief
|
{
"page_id": 70848363,
"source": null,
"title": "The Lichenologist"
}
|
== The following persons are or have been editors-in-chief: Peter W. James (1958β1977) David L. Hawksworth (1978β1988) Dennis H. Brown (1989β2000) Peter Crittenden (2000β2019) Christopher J. Ellis and Leena Myllys (2020βpresent) == Abstracting and indexing == The journal is abstracted and indexed in: According to the Journal Citation Reports, the journal has a 2023 impact factor of 1.6. == References == === Cited literature === LΓΌcking, Robert (2021). "Peter D. Crittenden: meta-analysis of an exceptional two-decade tenure as senior editor of The Lichenologist, the flagship journal of lichenology". The Lichenologist. 53 (1): 3β19. doi:10.1017/S0024282920000560.
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"title": "The Lichenologist"
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Jerome S. "J.S." Spevack was an American scientist, inventor, and engineer who developed the "dual temperature exchange sulphide process" (known as the Girdler sulfide process) in 1943 while working on the Manhattan Project. This is regarded as the most cost-effective process for producing heavy water. A parallel development of this process was also achieved in 1943 by German physical chemist Karl-Hermann Geib. == Post-war period == After World War II, Spevack became president of Deuterium of Canada Limited (DCL) and, in 1974, won a lawsuit against the United States government and its Atomic Energy Commission receiving protection, and compensation of US$1.5 million, over their use of the Girdler sulfide process without his consent. == References ==
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{
"page_id": 49745772,
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"title": "Jerome S. Spevack"
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Biochemistry, or biological chemistry, is the study of chemical processes within and relating to living organisms. A sub-discipline of both chemistry and biology, biochemistry may be divided into three fields: structural biology, enzymology, and metabolism. Over the last decades of the 20th century, biochemistry has become successful at explaining living processes through these three disciplines. Almost all areas of the life sciences are being uncovered and developed through biochemical methodology and research. Biochemistry focuses on understanding the chemical basis that allows biological molecules to give rise to the processes that occur within living cells and between cells, in turn relating greatly to the understanding of tissues and organs as well as organism structure and function. Biochemistry is closely related to molecular biology, the study of the molecular mechanisms of biological phenomena. Much of biochemistry deals with the structures, functions, and interactions of biological macromolecules such as proteins, nucleic acids, carbohydrates, and lipids. They provide the structure of cells and perform many of the functions associated with life. The chemistry of the cell also depends upon the reactions of small molecules and ions. These can be inorganic (for example, water and metal ions) or organic (for example, the amino acids, which are used to synthesize proteins). The mechanisms used by cells to harness energy from their environment via chemical reactions are known as metabolism. The findings of biochemistry are applied primarily in medicine, nutrition, and agriculture. In medicine, biochemists investigate the causes and cures of diseases. Nutrition studies how to maintain health and wellness and also the effects of nutritional deficiencies. In agriculture, biochemists investigate soil and fertilizers with the goal of improving crop cultivation, crop storage, and pest control. In recent decades, biochemical principles and methods have been combined with problem-solving approaches from engineering to manipulate living systems in order
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to produce useful tools for research, industrial processes, and diagnosis and control of diseaseβthe discipline of biotechnology. == History == At its most comprehensive definition, biochemistry can be seen as a study of the components and composition of living things and how they come together to become life. In this sense, the history of biochemistry may therefore go back as far as the ancient Greeks. However, biochemistry as a specific scientific discipline began sometime in the 19th century, or a little earlier, depending on which aspect of biochemistry is being focused on. Some argued that the beginning of biochemistry may have been the discovery of the first enzyme, diastase (now called amylase), in 1833 by Anselme Payen, while others considered Eduard Buchner's first demonstration of a complex biochemical process alcoholic fermentation in cell-free extracts in 1897 to be the birth of biochemistry. Some might also point as its beginning to the influential 1842 work by Justus von Liebig, Animal chemistry, or, Organic chemistry in its applications to physiology and pathology, which presented a chemical theory of metabolism, or even earlier to the 18th century studies on fermentation and respiration by Antoine Lavoisier. Many other pioneers in the field who helped to uncover the layers of complexity of biochemistry have been proclaimed founders of modern biochemistry. Emil Fischer, who studied the chemistry of proteins, and F. Gowland Hopkins, who studied enzymes and the dynamic nature of biochemistry, represent two examples of early biochemists. The term "biochemistry" was first used when Vinzenz Kletzinsky (1826β1882) had his "Compendium der Biochemie" printed in Vienna in 1858; it derived from a combination of biology and chemistry. In 1877, Felix Hoppe-Seyler used the term (biochemie in German) as a synonym for physiological chemistry in the foreword to the first issue of Zeitschrift fΓΌr Physiologische Chemie (Journal
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{
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"title": "Biochemistry"
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of Physiological Chemistry) where he argued for the setting up of institutes dedicated to this field of study. The German chemist Carl Neuberg however is often cited to have coined the word in 1903, while some credited it to Franz Hofmeister. It was once generally believed that life and its materials had some essential property or substance (often referred to as the "vital principle") distinct from any found in non-living matter, and it was thought that only living beings could produce the molecules of life. In 1828, Friedrich WΓΆhler published a paper on his serendipitous urea synthesis from potassium cyanate and ammonium sulfate; some regarded that as a direct overthrow of vitalism and the establishment of organic chemistry. However, the WΓΆhler synthesis has sparked controversy as some reject the death of vitalism at his hands. Since then, biochemistry has advanced, especially since the mid-20th century, with the development of new techniques such as chromatography, X-ray diffraction, dual polarisation interferometry, NMR spectroscopy, radioisotopic labeling, electron microscopy and molecular dynamics simulations. These techniques allowed for the discovery and detailed analysis of many molecules and metabolic pathways of the cell, such as glycolysis and the Krebs cycle (citric acid cycle), and led to an understanding of biochemistry on a molecular level. Another significant historic event in biochemistry is the discovery of the gene, and its role in the transfer of information in the cell. In the 1950s, James D. Watson, Francis Crick, Rosalind Franklin and Maurice Wilkins were instrumental in solving DNA structure and suggesting its relationship with the genetic transfer of information. In 1958, George Beadle and Edward Tatum received the Nobel Prize for work in fungi showing that one gene produces one enzyme. In 1988, Colin Pitchfork was the first person convicted of murder with DNA evidence, which led to the
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growth of forensic science. More recently, Andrew Z. Fire and Craig C. Mello received the 2006 Nobel Prize for discovering the role of RNA interference (RNAi) in the silencing of gene expression. == Starting materials: the chemical elements of life == Around two dozen chemical elements are essential to various kinds of biological life. Most rare elements on Earth are not needed by life (exceptions being selenium and iodine), while a few common ones (aluminium and titanium) are not used. Most organisms share element needs, but there are a few differences between plants and animals. For example, ocean algae use bromine, but land plants and animals do not seem to need any. All animals require sodium, but is not an essential element for plants. Plants need boron and silicon, but animals may not (or may need ultra-small amounts). Just six elementsβcarbon, hydrogen, nitrogen, oxygen, calcium and phosphorusβmake up almost 99% of the mass of living cells, including those in the human body (see composition of the human body for a complete list). In addition to the six major elements that compose most of the human body, humans require smaller amounts of possibly 18 more. == Biomolecules == The 4 main classes of molecules in biochemistry (often called biomolecules) are carbohydrates, lipids, proteins, and nucleic acids. Many biological molecules are polymers: in this terminology, monomers are relatively small macromolecules that are linked together to create large macromolecules known as polymers. When monomers are linked together to synthesize a biological polymer, they undergo a process called dehydration synthesis. Different macromolecules can assemble in larger complexes, often needed for biological activity. === Carbohydrates === Two of the main functions of carbohydrates are energy storage and providing structure. One of the common sugars known as glucose is a carbohydrate, but not all carbohydrates are
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sugars. There are more carbohydrates on Earth than any other known type of biomolecule; they are used to store energy and genetic information, as well as play important roles in cell to cell interactions and communications. The simplest type of carbohydrate is a monosaccharide, which among other properties contains carbon, hydrogen, and oxygen, mostly in a ratio of 1:2:1 (generalized formula CnH2nOn, where n is at least 3). Glucose (C6H12O6) is one of the most important carbohydrates; others include fructose (C6H12O6), the sugar commonly associated with the sweet taste of fruits, and deoxyribose (C5H10O4), a component of DNA. A monosaccharide can switch between acyclic (open-chain) form and a cyclic form. The open-chain form can be turned into a ring of carbon atoms bridged by an oxygen atom created from the carbonyl group of one end and the hydroxyl group of another. The cyclic molecule has a hemiacetal or hemiketal group, depending on whether the linear form was an aldose or a ketose. In these cyclic forms, the ring usually has 5 or 6 atoms. These forms are called furanoses and pyranoses, respectivelyβby analogy with furan and pyran, the simplest compounds with the same carbon-oxygen ring (although they lack the carbon-carbon double bonds of these two molecules). For example, the aldohexose glucose may form a hemiacetal linkage between the hydroxyl on carbon 1 and the oxygen on carbon 4, yielding a molecule with a 5-membered ring, called glucofuranose. The same reaction can take place between carbons 1 and 5 to form a molecule with a 6-membered ring, called glucopyranose. Cyclic forms with a 7-atom ring called heptoses are rare. Two monosaccharides can be joined by a glycosidic or ester bond into a disaccharide through a dehydration reaction during which a molecule of water is released. The reverse reaction in which the
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glycosidic bond of a disaccharide is broken into two monosaccharides is termed hydrolysis. The best-known disaccharide is sucrose or ordinary sugar, which consists of a glucose molecule and a fructose molecule joined. Another important disaccharide is lactose found in milk, consisting of a glucose molecule and a galactose molecule. Lactose may be hydrolysed by lactase, and deficiency in this enzyme results in lactose intolerance. When a few (around three to six) monosaccharides are joined, it is called an oligosaccharide (oligo- meaning "few"). These molecules tend to be used as markers and signals, as well as having some other uses. Many monosaccharides joined form a polysaccharide. They can be joined in one long linear chain, or they may be branched. Two of the most common polysaccharides are cellulose and glycogen, both consisting of repeating glucose monomers. Cellulose is an important structural component of plant's cell walls and glycogen is used as a form of energy storage in animals. Sugar can be characterized by having reducing or non-reducing ends. A reducing end of a carbohydrate is a carbon atom that can be in equilibrium with the open-chain aldehyde (aldose) or keto form (ketose). If the joining of monomers takes place at such a carbon atom, the free hydroxy group of the pyranose or furanose form is exchanged with an OH-side-chain of another sugar, yielding a full acetal. This prevents opening of the chain to the aldehyde or keto form and renders the modified residue non-reducing. Lactose contains a reducing end at its glucose moiety, whereas the galactose moiety forms a full acetal with the C4-OH group of glucose. Saccharose does not have a reducing end because of full acetal formation between the aldehyde carbon of glucose (C1) and the keto carbon of fructose (C2). === Lipids === Lipids comprise a diverse range
|
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of molecules and to some extent is a catchall for relatively water-insoluble or nonpolar compounds of biological origin, including waxes, fatty acids, fatty-acid derived phospholipids, sphingolipids, glycolipids, and terpenoids (e.g., retinoids and steroids). Some lipids are linear, open-chain aliphatic molecules, while others have ring structures. Some are aromatic (with a cyclic [ring] and planar [flat] structure) while others are not. Some are flexible, while others are rigid. Lipids are usually made from one molecule of glycerol combined with other molecules. In triglycerides, the main group of bulk lipids, there is one molecule of glycerol and three fatty acids. Fatty acids are considered the monomer in that case, and may be saturated (no double bonds in the carbon chain) or unsaturated (one or more double bonds in the carbon chain). Most lipids have some polar character and are largely nonpolar. In general, the bulk of their structure is nonpolar or hydrophobic ("water-fearing"), meaning that it does not interact well with polar solvents like water. Another part of their structure is polar or hydrophilic ("water-loving") and will tend to associate with polar solvents like water. This makes them amphiphilic molecules (having both hydrophobic and hydrophilic portions). In the case of cholesterol, the polar group is a mere βOH (hydroxyl or alcohol). In the case of phospholipids, the polar groups are considerably larger and more polar, as described below. Lipids are an integral part of our daily diet. Most oils and milk products that we use for cooking and eating like butter, cheese, ghee etc. are composed of fats. Vegetable oils are rich in various polyunsaturated fatty acids (PUFA). Lipid-containing foods undergo digestion within the body and are broken into fatty acids and glycerol, the final degradation products of fats and lipids. Lipids, especially phospholipids, are also used in various pharmaceutical products, either
|
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as co-solubilizers (e.g. in parenteral infusions) or else as drug carrier components (e.g. in a liposome or transfersome). === Proteins === Proteins are very large moleculesβmacro-biopolymersβmade from monomers called amino acids. An amino acid consists of an alpha carbon atom attached to an amino group, βNH2, a carboxylic acid group, βCOOH (although these exist as βNH3+ and βCOOβ under physiologic conditions), a simple hydrogen atom, and a side chain commonly denoted as "βR". The side chain "R" is different for each amino acid of which there are 20 standard ones. It is this "R" group that makes each amino acid different, and the properties of the side chains greatly influence the overall three-dimensional conformation of a protein. Some amino acids have functions by themselves or in a modified form; for instance, glutamate functions as an important neurotransmitter. Amino acids can be joined via a peptide bond. In this dehydration synthesis, a water molecule is removed and the peptide bond connects the nitrogen of one amino acid's amino group to the carbon of the other's carboxylic acid group. The resulting molecule is called a dipeptide, and short stretches of amino acids (usually, fewer than thirty) are called peptides or polypeptides. Longer stretches merit the title proteins. As an example, the important blood serum protein albumin contains 585 amino acid residues. Proteins can have structural and/or functional roles. For instance, movements of the proteins actin and myosin ultimately are responsible for the contraction of skeletal muscle. One property many proteins have is that they specifically bind to a certain molecule or class of moleculesβthey may be extremely selective in what they bind. Antibodies are an example of proteins that attach to one specific type of molecule. Antibodies are composed of heavy and light chains. Two heavy chains would be linked to two
|
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light chains through disulfide linkages between their amino acids. Antibodies are specific through variation based on differences in the N-terminal domain. The enzyme-linked immunosorbent assay (ELISA), which uses antibodies, is one of the most sensitive tests modern medicine uses to detect various biomolecules. Probably the most important proteins, however, are the enzymes. Virtually every reaction in a living cell requires an enzyme to lower the activation energy of the reaction. These molecules recognize specific reactant molecules called substrates; they then catalyze the reaction between them. By lowering the activation energy, the enzyme speeds up that reaction by a rate of 1011 or more; a reaction that would normally take over 3,000 years to complete spontaneously might take less than a second with an enzyme. The enzyme itself is not used up in the process and is free to catalyze the same reaction with a new set of substrates. Using various modifiers, the activity of the enzyme can be regulated, enabling control of the biochemistry of the cell as a whole. The structure of proteins is traditionally described in a hierarchy of four levels. The primary structure of a protein consists of its linear sequence of amino acids; for instance, "alanine-glycine-tryptophan-serine-glutamate-asparagine-glycine-lysine-...". Secondary structure is concerned with local morphology (morphology being the study of structure). Some combinations of amino acids will tend to curl up in a coil called an Ξ±-helix or into a sheet called a Ξ²-sheet; some Ξ±-helixes can be seen in the hemoglobin schematic above. Tertiary structure is the entire three-dimensional shape of the protein. This shape is determined by the sequence of amino acids. In fact, a single change can change the entire structure. The alpha chain of hemoglobin contains 146 amino acid residues; substitution of the glutamate residue at position 6 with a valine residue changes the
|
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behavior of hemoglobin so much that it results in sickle-cell disease. Finally, quaternary structure is concerned with the structure of a protein with multiple peptide subunits, like hemoglobin with its four subunits. Not all proteins have more than one subunit. Ingested proteins are usually broken up into single amino acids or dipeptides in the small intestine and then absorbed. They can then be joined to form new proteins. Intermediate products of glycolysis, the citric acid cycle, and the pentose phosphate pathway can be used to form all twenty amino acids, and most bacteria and plants possess all the necessary enzymes to synthesize them. Humans and other mammals, however, can synthesize only half of them. They cannot synthesize isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, and valine. Because they must be ingested, these are the essential amino acids. Mammals do possess the enzymes to synthesize alanine, asparagine, aspartate, cysteine, glutamate, glutamine, glycine, proline, serine, and tyrosine, the nonessential amino acids. While they can synthesize arginine and histidine, they cannot produce it in sufficient amounts for young, growing animals, and so these are often considered essential amino acids. If the amino group is removed from an amino acid, it leaves behind a carbon skeleton called an Ξ±-keto acid. Enzymes called transaminases can easily transfer the amino group from one amino acid (making it an Ξ±-keto acid) to another Ξ±-keto acid (making it an amino acid). This is important in the biosynthesis of amino acids, as for many of the pathways, intermediates from other biochemical pathways are converted to the Ξ±-keto acid skeleton, and then an amino group is added, often via transamination. The amino acids may then be linked together to form a protein. A similar process is used to break down proteins. It is first hydrolyzed into its component amino acids.
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Free ammonia (NH3), existing as the ammonium ion (NH4+) in blood, is toxic to life forms. A suitable method for excreting it must therefore exist. Different tactics have evolved in different animals, depending on the animals' needs. Unicellular organisms release the ammonia into the environment. Likewise, bony fish can release ammonia into the water where it is quickly diluted. In general, mammals convert ammonia into urea, via the urea cycle. In order to determine whether two proteins are related, or in other words to decide whether they are homologous or not, scientists use sequence-comparison methods. Methods like sequence alignments and structural alignments are powerful tools that help scientists identify homologies between related molecules. The relevance of finding homologies among proteins goes beyond forming an evolutionary pattern of protein families. By finding how similar two protein sequences are, we acquire knowledge about their structure and therefore their function. === Nucleic acids === Nucleic acids, so-called because of their prevalence in cellular nuclei, is the generic name of the family of biopolymers. They are complex, high-molecular-weight biochemical macromolecules that can convey genetic information in all living cells and viruses. The monomers are called nucleotides, and each consists of three components: a nitrogenous heterocyclic base (either a purine or a pyrimidine), a pentose sugar, and a phosphate group. The most common nucleic acids are deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). The phosphate group and the sugar of each nucleotide bond with each other to form the backbone of the nucleic acid, while the sequence of nitrogenous bases stores the information. The most common nitrogenous bases are adenine, cytosine, guanine, thymine, and uracil. The nitrogenous bases of each strand of a nucleic acid will form hydrogen bonds with certain other nitrogenous bases in a complementary strand of nucleic acid. Adenine binds with thymine
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and uracil, thymine binds only with adenine, and cytosine and guanine can bind only with one another. Adenine, thymine, and uracil contain two hydrogen bonds, while hydrogen bonds formed between cytosine and guanine are three. Aside from the genetic material of the cell, nucleic acids often play a role as second messengers, as well as forming the base molecule for adenosine triphosphate (ATP), the primary energy-carrier molecule found in all living organisms. Also, the nitrogenous bases possible in the two nucleic acids are different: adenine, cytosine, and guanine occur in both RNA and DNA, while thymine occurs only in DNA and uracil occurs in RNA. == Metabolism == === Carbohydrates as energy source === Glucose is an energy source in most life forms. For instance, polysaccharides are broken down into their monomers by enzymes (glycogen phosphorylase removes glucose residues from glycogen, a polysaccharide). Disaccharides like lactose or sucrose are cleaved into their two component monosaccharides. ==== Glycolysis (anaerobic) ==== Glucose is mainly metabolized by a very important ten-step pathway called glycolysis, the net result of which is to break down one molecule of glucose into two molecules of pyruvate. This also produces a net two molecules of ATP, the energy currency of cells, along with two reducing equivalents of converting NAD+ (nicotinamide adenine dinucleotide: oxidized form) to NADH (nicotinamide adenine dinucleotide: reduced form). This does not require oxygen; if no oxygen is available (or the cell cannot use oxygen), the NAD is restored by converting the pyruvate to lactate (lactic acid) (e.g. in humans) or to ethanol plus carbon dioxide (e.g. in yeast). Other monosaccharides like galactose and fructose can be converted into intermediates of the glycolytic pathway. ==== Aerobic ==== In aerobic cells with sufficient oxygen, as in most human cells, the pyruvate is further metabolized. It is irreversibly
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converted to acetyl-CoA, giving off one carbon atom as the waste product carbon dioxide, generating another reducing equivalent as NADH. The two molecules acetyl-CoA (from one molecule of glucose) then enter the citric acid cycle, producing two molecules of ATP, six more NADH molecules and two reduced (ubi)quinones (via FADH2 as enzyme-bound cofactor), and releasing the remaining carbon atoms as carbon dioxide. The produced NADH and quinol molecules then feed into the enzyme complexes of the respiratory chain, an electron transport system transferring the electrons ultimately to oxygen and conserving the released energy in the form of a proton gradient over a membrane (inner mitochondrial membrane in eukaryotes). Thus, oxygen is reduced to water and the original electron acceptors NAD+ and quinone are regenerated. This is why humans breathe in oxygen and breathe out carbon dioxide. The energy released from transferring the electrons from high-energy states in NADH and quinol is conserved first as proton gradient and converted to ATP via ATP synthase. This generates an additional 28 molecules of ATP (24 from the 8 NADH + 4 from the 2 quinols), totaling to 32 molecules of ATP conserved per degraded glucose (two from glycolysis + two from the citrate cycle). It is clear that using oxygen to completely oxidize glucose provides an organism with far more energy than any oxygen-independent metabolic feature, and this is thought to be the reason why complex life appeared only after Earth's atmosphere accumulated large amounts of oxygen. ==== Gluconeogenesis ==== In vertebrates, vigorously contracting skeletal muscles (during weightlifting or sprinting, for example) do not receive enough oxygen to meet the energy demand, and so they shift to anaerobic metabolism, converting glucose to lactate. The combination of glucose from noncarbohydrates origin, such as fat and proteins. This only happens when glycogen supplies in the
|
{
"page_id": 3954,
"source": null,
"title": "Biochemistry"
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liver are worn out. The pathway is a crucial reversal of glycolysis from pyruvate to glucose and can use many sources like amino acids, glycerol and Krebs Cycle. Large scale protein and fat catabolism usually occur when those suffer from starvation or certain endocrine disorders. The liver regenerates the glucose, using a process called gluconeogenesis. This process is not quite the opposite of glycolysis, and actually requires three times the amount of energy gained from glycolysis (six molecules of ATP are used, compared to the two gained in glycolysis). Analogous to the above reactions, the glucose produced can then undergo glycolysis in tissues that need energy, be stored as glycogen (or starch in plants), or be converted to other monosaccharides or joined into di- or oligosaccharides. The combined pathways of glycolysis during exercise, lactate's crossing via the bloodstream to the liver, subsequent gluconeogenesis and release of glucose into the bloodstream is called the Cori cycle. == Relationship to other "molecular-scale" biological sciences == Researchers in biochemistry use specific techniques native to biochemistry, but increasingly combine these with techniques and ideas developed in the fields of genetics, molecular biology, and biophysics. There is not a defined line between these disciplines. Biochemistry studies the chemistry required for biological activity of molecules, molecular biology studies their biological activity, genetics studies their heredity, which happens to be carried by their genome. This is shown in the following schematic that depicts one possible view of the relationships between the fields: Biochemistry is the study of the chemical substances and vital processes occurring in live organisms. Biochemists focus heavily on the role, function, and structure of biomolecules. The study of the chemistry behind biological processes and the synthesis of biologically active molecules are applications of biochemistry. Biochemistry studies life at the atomic and molecular level. Genetics
|
{
"page_id": 3954,
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is the study of the effect of genetic differences in organisms. This can often be inferred by the absence of a normal component (e.g. one gene). The study of "mutants" β organisms that lack one or more functional components with respect to the so-called "wild type" or normal phenotype. Genetic interactions (epistasis) can often confound simple interpretations of such "knockout" studies. Molecular biology is the study of molecular underpinnings of the biological phenomena, focusing on molecular synthesis, modification, mechanisms and interactions. The central dogma of molecular biology, where genetic material is transcribed into RNA and then translated into protein, despite being oversimplified, still provides a good starting point for understanding the field. This concept has been revised in light of emerging novel roles for RNA. Chemical biology seeks to develop new tools based on small molecules that allow minimal perturbation of biological systems while providing detailed information about their function. Further, chemical biology employs biological systems to create non-natural hybrids between biomolecules and synthetic devices (for example emptied viral capsids that can deliver gene therapy or drug molecules). == See also == === Lists === === See also === == Notes == == References == === Cited literature === == Further reading == == External links == "Biochemical Society". The Virtual Library of Biochemistry, Molecular Biology and Cell Biology Biochemistry, 5th ed. Full text of Berg, Tymoczko, and Stryer, courtesy of NCBI. SystemsX.ch β The Swiss Initiative in Systems Biology Full text of Biochemistry by Kevin and Indira, an introductory biochemistry textbook.
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Water conditioners are formulations designed to be added to tap water before its use in an aquarium. If the tap water is chlorinated then a simple conditioner containing a dechlorinator may be used. These products contain sodium thiosulfate which reduces chlorine to chloride which is less harmful to fish. However, chloramine is now often used in water disinfection and simple dechlorinators only deal with the chlorine portion, releasing free ammonia that is very harmful to fish. More complex products employ sulfonates that are able to deal with both chlorine and ammonia. The most sophisticated products also contain chelators such as ethylenediaminetetraacetic acid to bind and remove heavy metals. Some water conditioners also contain slime coat protectors such as polyvinylpyrrolidones or Aloe vera extracts, which can reduce stress behaviour of fish. == References ==
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"page_id": 25694074,
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"title": "Water conditioner"
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A pressure tank or pressurizer is a type of hydraulic accumulator used in a piping system to maintain a desired pressure. Applications include buffering water pressure in homes. == A simple well water control system == Referring to the figure on the left, a submersible water pump is installed in a well. The pressure switch turns the water pump on when it senses a pressure that is less than Plo and turns it off when it senses a pressure greater than Phi. While the pump is on, the pressure tank fills up. The pressure tank is then depleted as it supplies water in the specified pressure range to prevent "short-cycling", in which the pump tries to establish the proper pressure by rapidly cycling between Plo and Phi. A simple pressure tank would be just a tank which held water with an air space above the water which would compress as more water entered the tank. Modern systems isolate the water from the pressurized air using a flexible rubber or plastic diaphragm or bladder, because otherwise the air will dissolve in the water and be removed from the tank by usage. Eventually there will be little or no air and the tank will become "waterlogged" causing short-cycling, and will need to be drained to restore operation. The diaphragm or bladder may itself exert a pressure on the water, but it is usually small and will be neglected in the following discussion. Referring to the diagram on the right, a pressure tank is generally pressurized when empty with a "charging pressure" Pc, which is usually about 2 psi below the turn-on pressure Plo (Case 1). The total volume of the tank is Vt. When in use, the air in the tank will be compressed to pressure P and there will be a
|
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"source": null,
"title": "Pressure tank"
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volume V of water in the tank (Case 2). In the following development, all pressures are gauge pressures, which are the pressures above atmospheric pressure (Pa, which is altitude dependent). The ideal gas law may be written for both cases, and the amount of air in each case is equal: ( P c + P a ) V t = N k T Case 1 {\displaystyle (P_{\text{c}}+P_{\text{a}})V_{\text{t}}=NkT\qquad {\text{Case 1}}} ( P + P a ) ( V t β V ) = N k T C a s e 2 {\displaystyle (P+P_{\text{a}})(V_{\text{t}}-V)=NkT\qquad \mathrm {Case2} } where N is the number of molecules of gas (equal in both cases), k is the Boltzmann constant and T is the temperature. Assuming that the temperature is equal for both cases, the above equations can be solved for the water pressure/volume relationship in the tank: V ( P ) = V t P β P c P + P a {\displaystyle V(P)=V_{\text{t}}{\frac {P-P_{\text{c}}}{P+P_{\text{a}}}}} P ( V ) = P a V + P c V t V t β V {\displaystyle P(V)={\frac {P_{\text{a}}V+P_{\text{c}}V_{\text{t}}}{V_{\text{t}}-V}}} Tanks are generally specified by their total volume Vt and the "drawdown" (ΞV), which is the amount of water the tank will eject as the tank pressure goes from Phi to Plo, which are established by the pressure switch: Ξ V = V ( P hi ) β V ( P lo ) = V t ( P a + P c ) ( P hi β P lo ) ( P hi + P a ) ( P lo + P a ) {\displaystyle \Delta V=V(P_{\text{hi}})-V(P_{\text{lo}})=V_{\text{t}}{\frac {(P_{\text{a}}+P_{\text{c}})(P_{\text{hi}}-P_{\text{lo}})}{(P_{\text{hi}}+P_{\text{a}})(P_{\text{lo}}+P_{\text{a}})}}} The reason for the charging pressure can now be seen: The larger the charging pressure, the larger the drawdown. However, a charging pressure above Plo will not allow the pump to turn on
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}
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when the water pressure is below Plo, so it is kept a bit below Plo. Another important parameter is the drawdown factor (fΞV), which is the ratio of the drawdown to the total tank volume: f Ξ V = ( P a + P c ) ( P hi β P lo ) ( P hi + P a ) ( P lo + P a ) {\displaystyle f_{\Delta V}={\frac {(P_{\text{a}}+P_{\text{c}})(P_{\text{hi}}-P_{\text{lo}})}{(P_{\text{hi}}+P_{\text{a}})(P_{\text{lo}}+P_{\text{a}})}}} This factor is independent of the tank size so that the drawdown can be calculated for any tank, given its total volume, atmospheric pressure, charging pressure, and the limiting pressures established by the pressure switch. == See also == Pressurizer (nuclear power) == References == == Bibliography == Calder, N. (2005). Boatowner's Mechanical and Electrical Manual: How to Maintain, Repair, and Improve Your Boat's Essential Systems. McGraw-Hill Education. ISBN 978-0-07-178406-1. Retrieved 2022-09-30. == External links == Direct, Tanks. "Submersible Water Pumps - Sump Pumps". Tanks Direct. Retrieved 2022-09-30.
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{
"page_id": 1249147,
"source": null,
"title": "Pressure tank"
}
|
Jennifer Holmgren (born 1962) is a Colombian chemist whose research area is on chemical technologies and fuel. She is currently the CEO of LanzaTech, a company dedicated to sustainability by using gas fermentation products to create materials that are necessary for everyday life. == Early life == Holmgren, the eldest of three children, was born in Colombia and migrated to the United States with her family when her father, an aircraft mechanic, got a new job with Avianca, a Colombian airline. Her mother, a homemaker, worked odd jobs when and where she could. Both of Holmgren's parents were proponents of education. While still a child in Colombia, Holmgren had a fascination with the universe and dreams of space travel. Upon her family's move to the United States, Holmgren attended a high school in Los Angeles and developed interests in chemistry and STEM. With the encouragement of her teachers, Holmgren continued her endeavors in STEM and created a space for herself in the male-dominated field. Her father's work as an aircraft mechanic inspired her to contribute to the field of aviation at Universal Oil Products. She claims that aviation is her first love. An aptitude for academics and support from family and educators aided in her success. == Education == Holmgren graduated from Harvey Mudd College with a Bachelor of Science degree. She also holds an MBA from the University of Chicago and a PhD from the University of Illinois Urbana-Champaign. == Career == Holmgren has worked to promote and expand the field of chemical technologies and fuel. She was the former Vice President and General Manager, Renewable Energy and Chemicals at Universal Oil Products (UOP). During her time at UOP she led renewable technology that was useful in fuel production for use in the field of aviation. Holmgren is currently
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{
"page_id": 73404284,
"source": null,
"title": "Jennifer Holmgren"
}
|
the chief Executive Officer at LanzaTech and sits on the board for Bio Energy Research. LanzaTech is a carbon recycling company that uses bacteria to transform carbon into ethanol. Compared to traditional petroleum methods, LanzaTechβs waste gas-to-ethanol process (biomass gasification) reduces life-cycle greenhouse gas emissions by 67-98%. Since working at LanzaTech, Holmgren has arranged for repurpose facilities to be built across the world to create chemicals and fuel from carbon sequestration. Her work in both organizations has contributed to the popularization of new biofuel mechanization. Under Holmgrenβs guidance, LanzaTech ceased making jet fuel and formed, LanzaJet, a profit-driven production plant located in Soperton, Georgia, which will begin operating in 2023. == Awards and achievements == Since her time at LanzaTech, Holmgren, along with her crew has received the United States Environmental Protection Agency Presidential Green Chemistry Award in 2015. She also received an Outstanding Leadership Award in Corporate Social Innovation from the YMCA Metropolitan Chicago and the BIO Rosalind Franklin Award for Leadership in Industrial Biotechnology in 2015. In 2017, Holmgren was titled the most influential leader in the Bioeconomy sector and acquired an award in leadership from Global Bioenergy in 2018. Holmgren has been the author and co-author of 20 scientific publications and has also been a part of 50 patents and publications. In 2022, Holmgren received an honorary doctorate degree from Delft University of Technology and was classified as a Top 40 Power Player by the Independent Commodity Intelligence Service. In 2022, LanzaTech entered the Earthshot competition for their carbon recycling technology. LanzaTech is one of 15 finalist, the only finalist from the United States. The competition had the support of Prince William who established the prize. == References ==
|
{
"page_id": 73404284,
"source": null,
"title": "Jennifer Holmgren"
}
|
Bandwidth is the difference between the upper and lower frequencies in a continuous band of frequencies. It is typically measured in unit of hertz (symbol Hz). It may refer more specifically to two subcategories: Passband bandwidth is the difference between the upper and lower cutoff frequencies of, for example, a band-pass filter, a communication channel, or a signal spectrum. Baseband bandwidth is equal to the upper cutoff frequency of a low-pass filter or baseband signal, which includes a zero frequency. Bandwidth in hertz is a central concept in many fields, including electronics, information theory, digital communications, radio communications, signal processing, and spectroscopy and is one of the determinants of the capacity of a given communication channel. A key characteristic of bandwidth is that any band of a given width can carry the same amount of information, regardless of where that band is located in the frequency spectrum. For example, a 3 kHz band can carry a telephone conversation whether that band is at baseband (as in a POTS telephone line) or modulated to some higher frequency. However, wide bandwidths are easier to obtain and process at higher frequencies because the Β§ Fractional bandwidth is smaller. == Overview == Bandwidth is a key concept in many telecommunications applications. In radio communications, for example, bandwidth is the frequency range occupied by a modulated carrier signal. An FM radio receiver's tuner spans a limited range of frequencies. A government agency (such as the Federal Communications Commission in the United States) may apportion the regionally available bandwidth to broadcast license holders so that their signals do not mutually interfere. In this context, bandwidth is also known as channel spacing. For other applications, there are other definitions. One definition of bandwidth, for a system, could be the range of frequencies over which the system produces
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{
"page_id": 3967,
"source": null,
"title": "Bandwidth (signal processing)"
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a specified level of performance. A less strict and more practically useful definition will refer to the frequencies beyond which performance is degraded. In the case of frequency response, degradation could, for example, mean more than 3 dB below the maximum value or it could mean below a certain absolute value. As with any definition of the width of a function, many definitions are suitable for different purposes. In the context of, for example, the sampling theorem and Nyquist sampling rate, bandwidth typically refers to baseband bandwidth. In the context of Nyquist symbol rate or Shannon-Hartley channel capacity for communication systems it refers to passband bandwidth. The Rayleigh bandwidth of a simple radar pulse is defined as the inverse of its duration. For example, a one-microsecond pulse has a Rayleigh bandwidth of one megahertz. The essential bandwidth is defined as the portion of a signal spectrum in the frequency domain which contains most of the energy of the signal. == x dB bandwidth == In some contexts, the signal bandwidth in hertz refers to the frequency range in which the signal's spectral density (in W/Hz or V2/Hz) is nonzero or above a small threshold value. The threshold value is often defined relative to the maximum value, and is most commonly the 3 dB point, that is the point where the spectral density is half its maximum value (or the spectral amplitude, in V {\displaystyle \mathrm {V} } or V / H z {\displaystyle \mathrm {V/{\sqrt {Hz}}} } , is 70.7% of its maximum). This figure, with a lower threshold value, can be used in calculations of the lowest sampling rate that will satisfy the sampling theorem. The bandwidth is also used to denote system bandwidth, for example in filter or communication channel systems. To say that a system has a
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{
"page_id": 3967,
"source": null,
"title": "Bandwidth (signal processing)"
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certain bandwidth means that the system can process signals with that range of frequencies, or that the system reduces the bandwidth of a white noise input to that bandwidth. The 3 dB bandwidth of an electronic filter or communication channel is the part of the system's frequency response that lies within 3 dB of the response at its peak, which, in the passband filter case, is typically at or near its center frequency, and in the low-pass filter is at or near its cutoff frequency. If the maximum gain is 0 dB, the 3 dB bandwidth is the frequency range where attenuation is less than 3 dB. 3 dB attenuation is also where power is half its maximum. This same half-power gain convention is also used in spectral width, and more generally for the extent of functions as full width at half maximum (FWHM). In electronic filter design, a filter specification may require that within the filter passband, the gain is nominally 0 dB with a small variation, for example within the Β±1 dB interval. In the stopband(s), the required attenuation in decibels is above a certain level, for example >100 dB. In a transition band the gain is not specified. In this case, the filter bandwidth corresponds to the passband width, which in this example is the 1 dB-bandwidth. If the filter shows amplitude ripple within the passband, the x dB point refers to the point where the gain is x dB below the nominal passband gain rather than x dB below the maximum gain. In signal processing and control theory the bandwidth is the frequency at which the closed-loop system gain drops 3 dB below peak. In communication systems, in calculations of the ShannonβHartley channel capacity, bandwidth refers to the 3 dB-bandwidth. In calculations of the maximum symbol
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{
"page_id": 3967,
"source": null,
"title": "Bandwidth (signal processing)"
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rate, the Nyquist sampling rate, and maximum bit rate according to the Hartley's law, the bandwidth refers to the frequency range within which the gain is non-zero. The fact that in equivalent baseband models of communication systems, the signal spectrum consists of both negative and positive frequencies, can lead to confusion about bandwidth since they are sometimes referred to only by the positive half, and one will occasionally see expressions such as B = 2 W {\displaystyle B=2W} , where B {\displaystyle B} is the total bandwidth (i.e. the maximum passband bandwidth of the carrier-modulated RF signal and the minimum passband bandwidth of the physical passband channel), and W {\displaystyle W} is the positive bandwidth (the baseband bandwidth of the equivalent channel model). For instance, the baseband model of the signal would require a low-pass filter with cutoff frequency of at least W {\displaystyle W} to stay intact, and the physical passband channel would require a passband filter of at least B {\displaystyle B} to stay intact. == Relative bandwidth == The absolute bandwidth is not always the most appropriate or useful measure of bandwidth. For instance, in the field of antennas the difficulty of constructing an antenna to meet a specified absolute bandwidth is easier at a higher frequency than at a lower frequency. For this reason, bandwidth is often quoted relative to the frequency of operation which gives a better indication of the structure and sophistication needed for the circuit or device under consideration. There are two different measures of relative bandwidth in common use: fractional bandwidth ( B F {\displaystyle B_{\mathrm {F} }} ) and ratio bandwidth ( B R {\displaystyle B_{\mathrm {R} }} ). In the following, the absolute bandwidth is defined as follows, B = Ξ f = f H β f L {\displaystyle B=\Delta
|
{
"page_id": 3967,
"source": null,
"title": "Bandwidth (signal processing)"
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f=f_{\mathrm {H} }-f_{\mathrm {L} }} where f H {\displaystyle f_{\mathrm {H} }} and f L {\displaystyle f_{\mathrm {L} }} are the upper and lower frequency limits respectively of the band in question. === Fractional bandwidth === Fractional bandwidth is defined as the absolute bandwidth divided by the center frequency ( f C {\displaystyle f_{\mathrm {C} }} ), B F = Ξ f f C . {\displaystyle B_{\mathrm {F} }={\frac {\Delta f}{f_{\mathrm {C} }}}\,.} The center frequency is usually defined as the arithmetic mean of the upper and lower frequencies so that, f C = f H + f L 2 {\displaystyle f_{\mathrm {C} }={\frac {f_{\mathrm {H} }+f_{\mathrm {L} }}{2}}\ } and B F = 2 ( f H β f L ) f H + f L . {\displaystyle B_{\mathrm {F} }={\frac {2(f_{\mathrm {H} }-f_{\mathrm {L} })}{f_{\mathrm {H} }+f_{\mathrm {L} }}}\,.} However, the center frequency is sometimes defined as the geometric mean of the upper and lower frequencies, f C = f H f L {\displaystyle f_{\mathrm {C} }={\sqrt {f_{\mathrm {H} }f_{\mathrm {L} }}}} and B F = f H β f L f H f L . {\displaystyle B_{\mathrm {F} }={\frac {f_{\mathrm {H} }-f_{\mathrm {L} }}{\sqrt {f_{\mathrm {H} }f_{\mathrm {L} }}}}\,.} While the geometric mean is more rarely used than the arithmetic mean (and the latter can be assumed if not stated explicitly) the former is considered more mathematically rigorous. It more properly reflects the logarithmic relationship of fractional bandwidth with increasing frequency. For narrowband applications, there is only marginal difference between the two definitions. The geometric mean version is inconsequentially larger. For wideband applications they diverge substantially with the arithmetic mean version approaching 2 in the limit and the geometric mean version approaching infinity. Fractional bandwidth is sometimes expressed as a percentage of the center frequency (percent bandwidth,
|
{
"page_id": 3967,
"source": null,
"title": "Bandwidth (signal processing)"
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|
% B {\displaystyle \%B} ), % B F = 100 Ξ f f C . {\displaystyle \%B_{\mathrm {F} }=100{\frac {\Delta f}{f_{\mathrm {C} }}}\,.} === Ratio bandwidth === Ratio bandwidth is defined as the ratio of the upper and lower limits of the band, B R = f H f L . {\displaystyle B_{\mathrm {R} }={\frac {f_{\mathrm {H} }}{f_{\mathrm {L} }}}\,.} Ratio bandwidth may be notated as B R : 1 {\displaystyle B_{\mathrm {R} }:1} . The relationship between ratio bandwidth and fractional bandwidth is given by, B F = 2 B R β 1 B R + 1 {\displaystyle B_{\mathrm {F} }=2{\frac {B_{\mathrm {R} }-1}{B_{\mathrm {R} }+1}}} and B R = 2 + B F 2 β B F . {\displaystyle B_{\mathrm {R} }={\frac {2+B_{\mathrm {F} }}{2-B_{\mathrm {F} }}}\,.} Percent bandwidth is a less meaningful measure in wideband applications. A percent bandwidth of 100% corresponds to a ratio bandwidth of 3:1. All higher ratios up to infinity are compressed into the range 100β200%. Ratio bandwidth is often expressed in octaves (i.e., as a frequency level) for wideband applications. An octave is a frequency ratio of 2:1 leading to this expression for the number of octaves, log 2 β‘ ( B R ) . {\displaystyle \log _{2}\left(B_{\mathrm {R} }\right).} == Noise equivalent bandwidth == The noise equivalent bandwidth (or equivalent noise bandwidth (enbw)) of a system of frequency response H ( f ) {\displaystyle H(f)} is the bandwidth of an ideal filter with rectangular frequency response centered on the system's central frequency that produces the same average power outgoing H ( f ) {\displaystyle H(f)} when both systems are excited with a white noise source. The value of the noise equivalent bandwidth depends on the ideal filter reference gain used. Typically, this gain equals | H ( f ) | {\displaystyle
|
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"page_id": 3967,
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|
|H(f)|} at its center frequency, but it can also equal the peak value of | H ( f ) | {\displaystyle |H(f)|} . The noise equivalent bandwidth B n {\displaystyle B_{n}} can be calculated in the frequency domain using H ( f ) {\displaystyle H(f)} or in the time domain by exploiting the Parseval's theorem with the system impulse response h ( t ) {\displaystyle h(t)} . If H ( f ) {\displaystyle H(f)} is a lowpass system with zero central frequency and the filter reference gain is referred to this frequency, then: B n = β« β β β | H ( f ) | 2 d f 2 | H ( 0 ) | 2 = β« β β β | h ( t ) | 2 d t 2 | β« β β β h ( t ) d t | 2 . {\displaystyle B_{n}={\frac {\int _{-\infty }^{\infty }|H(f)|^{2}df}{2|H(0)|^{2}}}={\frac {\int _{-\infty }^{\infty }|h(t)|^{2}dt}{2\left|\int _{-\infty }^{\infty }h(t)dt\right|^{2}}}\,.} The same expression can be applied to bandpass systems by substituting the equivalent baseband frequency response for H ( f ) {\displaystyle H(f)} . The noise equivalent bandwidth is widely used to simplify the analysis of telecommunication systems in the presence of noise. == Photonics == In photonics, the term bandwidth carries a variety of meanings: the bandwidth of the output of some light source, e.g., an ASE source or a laser; the bandwidth of ultrashort optical pulses can be particularly large the width of the frequency range that can be transmitted by some element, e.g. an optical fiber the gain bandwidth of an optical amplifier the width of the range of some other phenomenon, e.g., a reflection, the phase matching of a nonlinear process, or some resonance the maximum modulation frequency (or range of modulation frequencies) of an optical modulator
|
{
"page_id": 3967,
"source": null,
"title": "Bandwidth (signal processing)"
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|
the range of frequencies in which some measurement apparatus (e.g., a power meter) can operate the data rate (e.g., in Gbit/s) achieved in an optical communication system; see bandwidth (computing). A related concept is the spectral linewidth of the radiation emitted by excited atoms. == See also == Bandwidth extension Broadband Noise bandwidth Rise time Spectral efficiency Spectral width == Notes == == References ==
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{
"page_id": 3967,
"source": null,
"title": "Bandwidth (signal processing)"
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Almond meal, almond flour or ground almond is made from ground sweet almonds. Almond flour is usually made with blanched almonds (no skin), whereas almond meal can be made with whole or blanched almonds. The consistency is more like corn meal than wheat flour. It is used in pastry and confectionery β in the manufacture of almond macarons and macaroons and other sweet pastries, in cake and pie filling, such as Austrian Sachertorte β and is one of the two main ingredients of marzipan and almond paste. In France, almond meal is an important ingredient in frangipane, the filling of traditional galette des Rois cake. Almond meal has recently become important in baking items for those on low-carbohydrate diets. It adds moistness and a rich nutty taste to baked goods. Items baked with almond meal tend to be calorie-dense. Almonds have high levels of polyunsaturated fats. Typically, the omega 6 fatty acids in almonds are protected from oxidation by the surface skin and vitamin E. When almonds are ground, this protective skin is broken and exposed surface area increases dramatically, greatly enhancing the nut's tendency to oxidize. == See also == Almond butter List of almond dishes == References == This article incorporates text from a publication now in the public domain: Ward, Artemas (1911). "Almond meal, almond paste". The Grocer's Encyclopedia. p. 20.
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{
"page_id": 3215233,
"source": null,
"title": "Almond meal"
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The Strep-tag system is a method which allows the purification and detection of proteins by affinity chromatography. The Strep-tag II is a synthetic peptide consisting of eight amino acids (Trp-Ser-His-Pro-Gln-Phe-Glu-Lys). This peptide sequence exhibits intrinsic affinity towards Strep-Tactin, a specifically engineered streptavidin, and can be N- or C- terminally fused to recombinant proteins. By exploiting the highly specific interaction, Strep-tagged proteins can be isolated in one step from crude cell lysates. Because the Strep-tag elutes under gentle, physiological conditions, it is especially suited for the generation of functional proteins. Strep-tag, Twin-Strep-tag and Strep-Tactin are registered trademarks of IBA Lifesciences GmbH. == Development and biochemistry of the Strep-tag == Streptavidin is a tetrameric protein expressed in Streptomyces avidinii. Because of Streptavidin's high affinity for vitamin H (biotin), Streptavidin is commonly used in the fields of molecular biology and biotechnology. The Strep-tag was originally selected from a genetic library to specifically bind to a proteolytically truncated "core" version of streptavidin. Over the years, the Strep-tag was systemically optimized, to permit a greater flexibility in the choice of attachment site. Further, its interaction partner, Streptavidin, was also optimized to increase peptide-binding capacity, which resulted in the development of Strep-Tactin. The binding affinity of Strep-tag to Strep-Tactin is nearly 100 times higher than from Strep-tag to Streptavidin. The so-called Strep-tag system, consisting of Strep-tag and Strep-Tactin, has proven particularly useful for the functional isolation and analysis of protein complexes in proteome research. == The Strep-tag principle == Just like other short-affinity tags (His-tag, FLAG-tag), the Strep-tag can be easily fused to recombinant proteins during subcloning of its cDNA or gene. For its expression, various vectors for various host organisms (E. coli, yeast, insect, and mammalian cells) are available. A particular benefit of the Strep-tag is its rather small size and the fact that it
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{
"page_id": 22810498,
"source": null,
"title": "Strep-tag"
}
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is biochemically almost inert. Therefore, protein folding or secretion is not influenced and usually it does not interfere with protein function. Strep-tag is especially suited for analysis of functional proteins, because the purification procedure can be kept under physiological conditions. This not only allows the isolation of sensitive proteins in a native state, but it is also possible to purify intact protein complexes, even if just one subunit carries the tag. In the first step of the Strep-tag purification cycle, the cell lysate containing Strep-tag fusion protein is applied to a column with immobilized Strep-Tactin (step 1). After the tagged protein has specifically bound to Strep-Tactin, a short washing step with a physiological buffer (e.g. phosphate buffered saline, PBS) removes all other host proteins (step 2). This is due to Strep-Tactin's low tendency to bind proteins non specifically. Then, the purified Strep-tag fusion protein is gently eluted with a low concentration of desthiobiotin, which specifically competes for the biotin binding pocket (step 3). To regenerate the column, desthiobiotin is removed by application of a HABA containing solution (a yellow azo dye). The removal of desthiobiotin is indicated by a color change from yellow-orange to red (step 4+5). Finally, the HABA solution is washed out with a small volume of running buffer, thus making the column ready to use for the next purification run. == Strep-tag applications == The Strep-tag system offers a selective tool to purify proteins under physiological conditions. The proteins obtained are bioactive and display a very high purity (above 95%). Also, the Strep-tag system can be used for protein detection in various assays. Depending on the experimental circumstances, Strep-tag antibodies or Strep-Tactin, with an enzymatic (e.g.horseradish peroxidase (HRP), alkaline phosphatase (AP)) or fluorescence (e.g. green fluorescent protein (GFP)) marker. If high purity is required, the lysate can
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{
"page_id": 22810498,
"source": null,
"title": "Strep-tag"
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be purified by first using Strep-Tactin and then perform a second run using antibodies against Strep-tag. This reduces the contamination with unspecific bound proteins, which might occur in some rare scenarios. Following assays can be conducted using the Strep-tag detection system: one-step affinity purification Protein:protein interaction studies Colony blot, dot blot, Western blot and ELISA Screening for positive expression clones Immunocytochemistry and Immunohistochemistry Protein localization and targeting studies Because the Strep-tag is capable of isolating protein complexes, strategies for the study of protein-protein interactions can also be conducted. Another option is the immobilization of Strep-tag proteins with a specific high affinity antibody on microplates or biochips. Strep-Tag/StrepTactin system is also used in single-molecule optical tweezers and atomic force microscope experiments, showing high mechanical stability comparable to the strongest non-covalent linkages currently available. == See also == Streptamer Protein tag SpyTag == References == == External links == The Strep Tag
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{
"page_id": 22810498,
"source": null,
"title": "Strep-tag"
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A loading control is a protein used as a control in a Western blotting experiment. Typically, loading controls are proteins with high and ubiquitous expression, such as beta-actin or GADPH. They are used to make sure that the protein has been loaded equally across all wells. == References ==
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{
"page_id": 52432771,
"source": null,
"title": "Loading control"
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Large deformation diffeomorphic metric mapping (LDDMM) is a specific suite of algorithms used for diffeomorphic mapping and manipulating dense imagery based on diffeomorphic metric mapping within the academic discipline of computational anatomy, to be distinguished from its precursor based on diffeomorphic mapping. The distinction between the two is that diffeomorphic metric maps satisfy the property that the length associated to their flow away from the identity induces a metric on the group of diffeomorphisms, which in turn induces a metric on the orbit of shapes and forms within the field of computational anatomy. The study of shapes and forms with the metric of diffeomorphic metric mapping is called diffeomorphometry. A diffeomorphic mapping system is a system designed to map, manipulate, and transfer information which is stored in many types of spatially distributed medical imagery. Diffeomorphic mapping is the underlying technology for mapping and analyzing information measured in human anatomical coordinate systems which have been measured via Medical imaging. Diffeomorphic mapping is a broad term that actually refers to a number of different algorithms, processes, and methods. It is attached to many operations and has many applications for analysis and visualization. Diffeomorphic mapping can be used to relate various sources of information which are indexed as a function of spatial position as the key index variable. Diffeomorphisms are by their Latin root structure preserving transformations, which are in turn differentiable and therefore smooth, allowing for the calculation of metric based quantities such as arc length and surface areas. Spatial location and extents in human anatomical coordinate systems can be recorded via a variety of Medical imaging modalities, generally termed multi-modal medical imagery, providing either scalar and or vector quantities at each spatial location. Examples are scalar T1 or T2 magnetic resonance imagery, or as 3x3 diffusion tensor matrices diffusion MRI and
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{
"page_id": 49418115,
"source": null,
"title": "Large deformation diffeomorphic metric mapping"
}
|
diffusion-weighted imaging, to scalar densities associated to computed tomography (CT), or functional imagery such as temporal data of functional magnetic resonance imaging and scalar densities such as Positron emission tomography (PET). Computational anatomy is a subdiscipline within the broader field of neuroinformatics within bioinformatics and medical imaging. The first algorithm for dense image mapping via diffeomorphic metric mapping was Beg's LDDMM for volumes and Joshi's landmark matching for point sets with correspondence, with LDDMM algorithms now available for computing diffeomorphic metric maps between non-corresponding landmarks and landmark matching intrinsic to spherical manifolds, curves, currents and surfaces, tensors, varifolds, and time-series. The term LDDMM was first established as part of the National Institutes of Health supported Biomedical Informatics Research Network. In a more general sense, diffeomorphic mapping is any solution that registers or builds correspondences between dense coordinate systems in medical imaging by ensuring the solutions are diffeomorphic. There are now many codes organized around diffeomorphic registration including ANTS, DARTEL, DEMONS, StationaryLDDMM, FastLDDMM, as examples of actively used computational codes for constructing correspondences between coordinate systems based on dense images. The distinction between diffeomorphic metric mapping forming the basis for LDDMM and the earliest methods of diffeomorphic mapping is the introduction of a Hamilton principle of least-action in which large deformations are selected of shortest length corresponding to geodesic flows. This important distinction arises from the original formulation of the Riemannian metric corresponding to the right-invariance. The lengths of these geodesics give the metric in the metric space structure of human anatomy. Non-geodesic formulations of diffeomorphic mapping in general does not correspond to any metric formulation. == History of development == Diffeomorphic mapping 3-dimensional information across coordinate systems is central to high-resolution Medical imaging and the area of Neuroinformatics within the newly emerging field of bioinformatics. Diffeomorphic mapping 3-dimensional coordinate systems
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{
"page_id": 49418115,
"source": null,
"title": "Large deformation diffeomorphic metric mapping"
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|
as measured via high resolution dense imagery has a long history in 3-D beginning with Computed Axial Tomography (CAT scanning) in the early 80's by the University of Pennsylvania group led by Ruzena Bajcsy, and subsequently the Ulf Grenander school at Brown University with the HAND experiments. In the 90's there were several solutions for image registration which were associated to linearizations of small deformation and non-linear elasticity. The central focus of the sub-field of Computational anatomy (CA) within medical imaging is mapping information across anatomical coordinate systems at the 1 millimeter morphome scale. In CA mapping of dense information measured within Magnetic resonance image (MRI) based coordinate systems such as in the brain has been solved via inexact matching of 3D MR images one onto the other. The earliest introduction of the use of diffeomorphic mapping via large deformation flows of diffeomorphisms for transformation of coordinate systems in image analysis and medical imaging was by Christensen, Rabbitt and Miller and TrouvΓ©. The introduction of flows, which are akin to the equations of motion used in fluid dynamics, exploit the notion that dense coordinates in image analysis follow the Lagrangian and Eulerian equations of motion. This model becomes more appropriate for cross-sectional studies in which brains and or hearts are not necessarily deformations of one to the other. Methods based on linear or non-linear elasticity energetics which grows with distance from the identity mapping of the template, is not appropriate for cross-sectional study. Rather, in models based on Lagrangian and Eulerian flows of diffeomorphisms, the constraint is associated to topological properties, such as open sets being preserved, coordinates not crossing implying uniqueness and existence of the inverse mapping, and connected sets remaining connected. The use of diffeomorphic methods grew quickly to dominate the field of mapping methods post Christensen's original
|
{
"page_id": 49418115,
"source": null,
"title": "Large deformation diffeomorphic metric mapping"
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paper, with fast and symmetric methods becoming available. Such methods are powerful in that they introduce notions of regularity of the solutions so that they can be differentiated and local inverses can be calculated. The disadvantages of these methods is that there was no associated global least-action property which could score the flows of minimum energy. This contrasts the geodesic motions which are central to the study of Rigid body kinematics and the many problems solved in Physics via Hamilton's principle of least action. In 1998, Dupuis, Grenander and Miller established the conditions for guaranteeing the existence of solutions for dense image matching in the space of flows of diffeomorphisms. These conditions require an action penalizing kinetic energy measured via the Sobolev norm on spatial derivatives of the flow of vector fields. The large deformation diffeomorphic metric mapping (LDDMM) code that Faisal Beg derived and implemented for his PhD at Johns Hopkins University developed the earliest algorithmic code which solved for flows with fixed points satisfying the necessary conditions for the dense image matching problem subject to least-action. Computational anatomy now has many existing codes organized around diffeomorphic registration including ANTS, DARTEL, DEMONS, LDDMM, StationaryLDDMM as examples of actively used computational codes for constructing correspondences between coordinate systems based on dense images. These large deformation methods have been extended to landmarks without registration via measure matching, curves, surfaces, dense vector and tensor imagery, and varifolds removing orientation. == The diffeomorphism orbit model in computational anatomy == Deformable shape in computational anatomy (CA)is studied via the use of diffeomorphic mapping for establishing correspondences between anatomical coordinates in Medical Imaging. In this setting, three dimensional medical images are modelled as a random deformation of some exemplar, termed the template I t e m p {\displaystyle I_{temp}} , with the set of observed
|
{
"page_id": 49418115,
"source": null,
"title": "Large deformation diffeomorphic metric mapping"
}
|
images element in the random orbit model of CA for images I β I β { I = I temp β Ο , Ο β Diff V } {\displaystyle I\in {\mathcal {I}}\doteq \{I=I_{\text{temp}}\circ \varphi ,\varphi \in \operatorname {Diff} _{V}\}} . The template is mapped onto the target by defining a variational problem in which the template is transformed via the diffeomorphism used as a change of coordinate to minimize a squared-error matching condition between the transformed template and the target. The diffeomorphisms are generated via smooth flows Ο t , t β [ 0 , 1 ] {\displaystyle \varphi _{t},t\in [0,1]} , with Ο β Ο 1 {\displaystyle \varphi \doteq \varphi _{1}} , satisfying the Lagrangian and Eulerian specification of the flow field associated to the ordinary differential equation, d d t Ο t = v t β Ο t , Ο 0 = i d , {\displaystyle {\frac {d}{dt}}\varphi _{t}=v_{t}\circ \varphi _{t},\ \varphi _{0}={\rm {id}},} with v t , t β [ 0 , 1 ] {\displaystyle v_{t},t\in [0,1]} the Eulerian vector fields determining the flow. The vector fields are guaranteed to be 1-time continuously differentiable v t β C 1 {\displaystyle v_{t}\in C^{1}} by modelling them to be in a smooth Hilbert space v β V {\displaystyle v\in V} supporting 1-continuous derivative. The inverse Ο t β 1 , t β [ 0 , 1 ] {\displaystyle \varphi _{t}^{-1},t\in [0,1]} is defined by the Eulerian vector-field with flow given by To ensure smooth flows of diffeomorphisms with inverse, the vector fields with components in R 3 {\displaystyle {\mathbb {R} }^{3}} must be at least 1-time continuously differentiable in space which are modelled as elements of the Hilbert space ( V , β β
β V ) {\displaystyle (V,\|\cdot \|_{V})} using the Sobolev embedding theorems so that each element
|
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v i β H 0 3 , i = 1 , 2 , 3 , {\displaystyle v_{i}\in H_{0}^{3},i=1,2,3,} has 3-times square-integrable weak-derivatives. Thus ( V , β β
β V ) {\displaystyle (V,\|\cdot \|_{V})} embeds smoothly in 1-time continuously differentiable functions. The diffeomorphism group are flows with vector fields absolutely integrable in Sobolev norm == The variational problem of dense image matching and sparse landmark matching == === LDDMM algorithm for dense image matching === In CA the space of vector fields ( V , β β
β V ) {\displaystyle (V,\|\cdot \|_{V})} are modelled as a reproducing Kernel Hilbert space (RKHS) defined by a 1-1, differential operator A : V β V β {\displaystyle A:V\rightarrow V^{*}} determining the norm β v β V 2 β β« R 3 A v β
v d x , v β V , {\displaystyle \|v\|_{V}^{2}\doteq \int _{R^{3}}Av\cdot v\,dx,\ v\in V\ ,} where the integral is calculated by integration by parts when A v {\displaystyle Av} is a generalized function in the dual space V β {\displaystyle V^{*}} . The differential operator is selected so that the Green's kernel, the inverse of the operator, is continuously differentiable in each variable implying that the vector fields support 1-continuous derivative; see for the necessary conditions on the norm for existence of solutions. The original large deformation diffeomorphic metric mapping (LDDMM) algorithms of Beg, Miller, Trouve, Younes was derived taking variations with respect to the vector field parameterization of the group, since v = Ο Λ β Ο β 1 {\displaystyle v={\dot {\phi }}\circ \phi ^{-1}} are in a vector spaces. Beg solved the dense image matching minimizing the action integral of kinetic energy of diffeomorphic flow while minimizing endpoint matching term according to Beg's Iterative Algorithm for Dense Image Matching Update until convergence, Ο t o
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l d β Ο t n e w {\displaystyle \phi _{t}^{old}\leftarrow \phi _{t}^{new}} each iteration, with Ο t 1 β Ο 1 β Ο t β 1 {\displaystyle \phi _{t1}\doteq \phi _{1}\circ \phi _{t}^{-1}} : This implies that the fixed point at t = 0 {\displaystyle t=0} satisfies ΞΌ 0 β = A v 0 β = ( I β J β Ο 1 β ) β I | D Ο 1 β | {\displaystyle \mu _{0}^{*}=Av_{0}^{*}=(I-J\circ \phi _{1}^{*})\nabla I|D\phi _{1}^{*}|} , which in turn implies it satisfies the Conservation equation given by the Endpoint Matching Condition according to A v t β = ( D Ο t β β 1 ) T A v 0 β β Ο t β β 1 | D Ο t β β 1 | {\displaystyle Av_{t}^{*}=(D\phi _{t}^{*-1})^{T}Av_{0}^{*}\circ \phi _{t}^{*-1}|D\phi _{t}^{*-1}|} === LDDMM registered landmark matching === The landmark matching problem has a pointwise correspondence defining the endpoint condition with geodesics given by the following minimum: min v : Ο Λ t = v t β Ο t C ( v ) β 1 2 β« 0 1 β« R 3 A v t β
v t d x d t + 1 2 β i ( Ο 1 ( x i ) β y i ) β
( Ο 1 ( x i ) β y i ) {\displaystyle \min _{v:{\dot {\phi }}_{t}=v_{t}\circ \phi _{t}}C(v)\doteq {\frac {1}{2}}\int _{0}^{1}\int _{R^{3}}Av_{t}\cdot v_{t}dxdt+{\frac {1}{2}}\sum _{i}(\phi _{1}(x_{i})-y_{i})\cdot (\phi _{1}(x_{i})-y_{i})} ; Iterative Algorithm for Landmark Matching Joshi originally defined the registered landmark matching probleme,. Update until convergence, Ο t o l d β Ο t n e w {\displaystyle \phi _{t}^{old}\leftarrow \phi _{t}^{new}} each iteration, with Ο t 1 β Ο 1 β Ο t β 1 {\displaystyle \phi _{t1}\doteq \phi _{1}\circ \phi _{t}^{-1}} : This implies that
|
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"page_id": 49418115,
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the fixed point satisfy A v 0 = β β i ( D Ο 1 ) ( x i ) T ( y i β Ο 1 ( x i ) ) Ξ΄ x i {\displaystyle Av_{0}=-\sum _{i}(D\phi _{1})(x_{i})^{T}(y_{i}-\phi _{1}(x_{i}))\delta _{x_{i}}} with A v t = β β i ( D Ο t 1 ) T | Ο t ( x i ) ( y i β Ο 1 ( x i ) ) Ξ΄ Ο t ( x i ) {\displaystyle Av_{t}=-\sum _{i}(D\phi _{t1})^{T}|_{\phi _{t}(x_{i})}(y_{i}-\phi _{1}(x_{i}))\delta _{\phi _{t}(x_{i})}} . === Variations for LDDMM dense image and landmark matching === The Calculus of variations was used in Beg[49] to derive the iterative algorithm as a solution which when it converges satisfies the necessary maximizer conditions given by the necessary conditions for a first order variation requiring the variation of the endpoint with respect to a first order variation of the vector field. The directional derivative calculates the Gateaux derivative as calculated in Beg's original paper[49] and. == LDDMM Diffusion Tensor Image Matching == LDDMM matching based on the principal eigenvector of the diffusion tensor matrix takes the image I ( x ) , x β R 3 {\displaystyle I(x),x\in {\mathbb {R} }^{3}} as a unit vector field defined by the first eigenvector. The group action becomes Ο β
I = { D Ο β 1 Ο I β Ο β 1 β I β Ο β 1 β β D Ο β 1 Ο I β Ο β 1 β I β Ο β 0 , 0 otherwise. {\displaystyle \varphi \cdot I={\begin{cases}{\frac {D_{\varphi ^{-1}}\varphi I\circ \varphi ^{-1}\|I\circ \varphi ^{-1}\|}{\|D_{\varphi ^{-1}}\varphi I\circ \varphi ^{-1}\|}}&I\circ \varphi \neq 0,\\0&{\text{otherwise.}}\end{cases}}} where β β
β {\displaystyle \|\cdot \|} that denotes image squared-error norm. LDDMM matching based on the entire tensor matrix has group action Ο
|
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"page_id": 49418115,
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β
M = ( Ξ» 1 e ^ 1 e ^ 1 T + Ξ» 2 e ^ 2 e ^ 2 T + Ξ» 3 e ^ 3 e ^ 3 T ) β Ο β 1 , {\displaystyle \varphi \cdot M=(\lambda _{1}{\hat {e}}_{1}{\hat {e}}_{1}^{T}+\lambda _{2}{\hat {e}}_{2}{\hat {e}}_{2}^{T}+\lambda _{3}{\hat {e}}_{3}{\hat {e}}_{3}^{T})\circ \varphi ^{-1},} transformed eigenvectors e ^ 1 = D Ο e 1 β D Ο e 1 β , e ^ 2 = D Ο e 2 β β¨ e ^ 1 , D Ο e 2 β© e ^ 1 β D Ο e 2 β 2 β β¨ e ^ 1 , D Ο e 2 β© 2 , e ^ 3 = e ^ 1 Γ e ^ 2 {\displaystyle {\begin{aligned}{\hat {e}}_{1}&={\frac {D\varphi e_{1}}{\|D\varphi e_{1}\|}}\ ,\ \ \ {\hat {e}}_{2}={\frac {D\varphi e_{2}-\langle {\hat {e}}_{1},D\varphi e_{2}\rangle {\hat {e}}_{1}}{\sqrt {\|D\varphi e_{2}\|^{2}-\langle {\hat {e}}_{1},D\varphi e_{2}\rangle ^{2}}}}\ ,\ \ \ {\hat {e}}_{3}={\hat {e}}_{1}\times {\hat {e}}_{2}\end{aligned}}} . === Dense matching problem onto principle eigenvector of DTI === The variational problem matching onto vector image I β² ( x ) , x β R 3 {\displaystyle I^{\prime }(x),x\in {\mathbb {R} }^{3}} with endpoint E ( Ο 1 ) β Ξ± β« R 3 β Ο 1 β
I β I β² β 2 d x + Ξ² β« R 3 ( β Ο 1 β
I β β β I β² β ) 2 d x ) . {\displaystyle E(\phi _{1})\doteq \alpha \int _{{\mathbb {R} }^{3}}\|\phi _{1}\cdot I-I^{\prime }\|^{2}\,dx+\beta \int _{{\mathbb {R} }^{3}}(\|\phi _{1}\cdot I\|-\|I^{\prime }\|)^{2}\,dx).} becomes min v : Ο Λ β Ο β 1 1 2 β« 0 1 β« R 3 A v t β
v t d x d t + Ξ± β« R 3 β Ο 1 β
I β I β² β 2 d x
|
{
"page_id": 49418115,
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+ Ξ² β« R 3 ( β Ο 1 β
I β β β I β² β ) 2 d x . {\displaystyle \min _{v:{\dot {\phi }}\circ \phi ^{-1}}{\frac {1}{2}}\int _{0}^{1}\int _{R^{3}}Av_{t}\cdot v_{t}dxdt+\alpha \int _{{\mathbb {R} }^{3}}\|\phi _{1}\cdot I-I^{\prime }\|^{2}\,dx+\beta \int _{{\mathbb {R} }^{3}}(\|\phi _{1}\cdot I\|-\|I^{\prime }\|)^{2}\,dx\ .} === Dense matching problem onto DTI MATRIX === The variational problem matching onto: M β² ( x ) , x β R 3 {\displaystyle M^{\prime }(x),x\in {\mathbb {R} }^{3}} with endpoint E ( Ο 1 ) β β« R 3 β Ο 1 β
M ( x ) β M β² ( x ) β F 2 d x {\displaystyle E(\phi _{1})\doteq \int _{{\mathbb {R} }^{3}}\|\phi _{1}\cdot M(x)-M^{\prime }(x)\|_{F}^{2}dx} with β β
β F {\displaystyle \|\cdot \|_{F}} Frobenius norm, giving variational problem == LDDMM ODF == High angular resolution diffusion imaging (HARDI) addresses the well-known limitation of DTI, that is, DTI can only reveal one dominant fiber orientation at each location. HARDI measures diffusion along n {\displaystyle n} uniformly distributed directions on the sphere and can characterize more complex fiber geometries by reconstructing an orientation distribution function (ODF) that characterizes the angular profile of the diffusion probability density function of water molecules. The ODF is a function defined on a unit sphere, S 2 {\displaystyle {\mathbb {S} }^{2}} . Denote the square-root ODF ( ODF {\displaystyle {\sqrt {\text{ODF}}}} ) as Ο ( s ) {\displaystyle \psi ({\bf {s}})} , where Ο ( s ) {\displaystyle \psi ({\bf {s}})} is non-negative to ensure uniqueness and β« s β S 2 Ο 2 ( s ) d s = 1 {\displaystyle \int _{{\bf {s}}\in {\mathbb {S} }^{2}}\psi ^{2}({\bf {s}})d{\bf {s}}=1} . The metric defines the distance between two ODF {\displaystyle {\sqrt {\text{ODF}}}} functions Ο 1 , Ο 2 β Ξ¨ {\displaystyle \psi _{1},\psi _{2}\in
|
{
"page_id": 49418115,
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\Psi } as Ο ( Ο 1 , Ο 2 ) = β log Ο 1 β‘ ( Ο 2 ) β Ο 1 = cos β 1 β‘ β¨ Ο 1 , Ο 2 β© = cos β 1 β‘ ( β« s β S 2 Ο 1 ( s ) Ο 2 ( s ) d s ) , {\displaystyle {\begin{aligned}\rho (\psi _{1},\psi _{2})=\|\log _{\psi _{1}}(\psi _{2})\|_{\psi _{1}}=\cos ^{-1}\langle \psi _{1},\psi _{2}\rangle =\cos ^{-1}\left(\int _{{\bf {s}}\in {\mathbb {S} }^{2}}\psi _{1}({\bf {s}})\psi _{2}({\bf {s}})d{\bf {s}}\right),\end{aligned}}} where β¨ β
, β
β© {\displaystyle \langle \cdot ,\cdot \rangle } is the normal dot product between points in the sphere under the L 2 {\displaystyle \mathrm {L} ^{2}} metric. The template and target are denoted Ο t e m p ( s , x ) {\displaystyle \psi _{\mathrm {temp} }({\bf {s}},x)} , Ο t a r g ( s , x ) {\displaystyle \psi _{\mathrm {targ} }({\bf {s}},x)} , s β S 2 {\displaystyle {\bf {s}}\in {{\mathbb {S} }^{2}}} x β X {\displaystyle x\in X} indexed across the unit sphere and the image domain, with the target indexed similarly. Define the variational problem assuming that two ODF volumes can be generated from one to another via flows of diffeomorphisms Ο t {\displaystyle \phi _{t}} , which are solutions of ordinary differential equations Ο Λ t = v t ( Ο t ) , t β [ 0 , 1 ] , Ο 0 = i d {\displaystyle {\dot {\phi }}_{t}=v_{t}(\phi _{t}),t\in [0,1],\phi _{0}={id}} . The group action of the diffeomorphism on the template is given according to Ο 1 β
Ο ( x ) β ( D Ο 1 ) Ο β Ο 1 β 1 ( x ) , x β X {\displaystyle \phi _{1}\cdot \psi (x)\doteq (D\phi _{1})\psi \circ \phi
|
{
"page_id": 49418115,
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_{1}^{-1}(x),x\in X} , where ( D Ο 1 ) {\displaystyle (D\phi _{1})} is the Jacobian of the affined transformed ODF and is defined as ( D Ο 1 ) Ο β Ο 1 β 1 ( x ) = det ( D Ο 1 β 1 Ο 1 ) β 1 β ( D Ο 1 β 1 Ο 1 ) β 1 s β 3 Ο ( ( D Ο 1 β 1 Ο 1 ) β 1 s β ( D Ο 1 β 1 Ο 1 ) β 1 s β , Ο 1 β 1 ( x ) ) . {\displaystyle {\begin{aligned}(D\phi _{1})\psi \circ \phi _{1}^{-1}(x)={\sqrt {\frac {\det {{\bigl (}D_{\phi _{1}^{-1}}\phi _{1}{\bigr )}^{-1}}}{\left\|{{\bigl (}D_{\phi _{1}^{-1}}\phi _{1}{\bigr )}^{-1}}{\bf {s}}\right\|^{3}}}}\quad \psi \left({\frac {(D_{\phi _{1}^{-1}}\phi _{1}{\bigr )}^{-1}{\bf {s}}}{\|(D_{\phi _{1}^{-1}}\phi _{1}{\bigr )}^{-1}{\bf {s}}\|}},\phi _{1}^{-1}(x)\right).\end{aligned}}} The LDDMM variational problem is defined as min v : Ο Λ t = v t β Ο t , Ο 0 = i d β« 0 1 β« R 3 A v t β
v t d x d t + Ξ» β« R 3 β log ( D Ο 1 ) Ο t e m p β Ο 1 β 1 ( x ) β‘ ( Ο t a r g ( x ) ) β ( D Ο 1 ) Ο t e m p β Ο 1 β 1 ( x ) 2 d x {\displaystyle {\begin{aligned}\min _{v:{\dot {\phi }}_{t}=v_{t}\circ \phi _{t},\phi _{0}={id}}\int _{0}^{1}\int _{R^{3}}Av_{t}\cdot v_{t}dx\ dt+\lambda \int _{R^{3}}\|\log _{(D\phi _{1})\psi _{\mathrm {temp} }\circ \phi _{1}^{-1}(x)}(\psi _{\mathrm {targ} }(x))\|_{(D\phi _{1})\psi _{\mathrm {temp} }\circ \phi _{1}^{-1}(x)}^{2}dx\end{aligned}}} . == Hamiltonian LDDMM for dense image matching == Beg solved the early LDDMM algorithms by solving the variational matching taking variations with respect to the vector fields. Another solution by Vialard, reparameterizes the optimization problem in
|
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"page_id": 49418115,
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terms of the state q t β I β Ο t β 1 , q 0 = I {\displaystyle q_{t}\doteq I\circ \phi _{t}^{-1},q_{0}=I} , for image I ( x ) , x β X = R 3 {\displaystyle I(x),x\in X=R^{3}} , with the dynamics equation controlling the state by the control given in terms of the advection equation according to q Λ t = β β q t β
v t {\displaystyle {\dot {q}}_{t}=-\nabla q_{t}\cdot v_{t}} . The endpoint matching term E ( q 1 ) β 1 2 β q 1 β J β 2 {\displaystyle E(q_{1})\doteq {\frac {1}{2}}\|q_{1}-J\|^{2}} gives the variational problem: == Software for diffeomorphic mapping == Software suites containing a variety of diffeomorphic mapping algorithms include the following: Deformetrica ANTS DARTEL Voxel-based morphometry(VBM) DEMONS LDDMM StationaryLDDMM === Cloud software === MRICloud == See also == Computational anatomy Β§ Dense image matching in computational anatomy Riemannian metric and Lie-bracket in computational anatomy Bayesian model of computational anatomy == References == == Further reading == Ceritoglu, Can; Wang, Lei; Selemon, Lynn D.; Csernansky, John G.; Miller, Michael I.; Ratnanather, J. Tilak (2010-05-28). "Large Deformation Diffeomorphic Metric Mapping Registration of Reconstructed 3D Histological Section Images and in vivo MR Images". Frontiers in Human Neuroscience. 4: 43. doi:10.3389/fnhum.2010.00043. ISSN 1662-5161. PMC 2889720. PMID 20577633.
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Yun Sing Koh (born 1978) is a New Zealand computer science academic, and is a full professor at the University of Auckland, specialising in machine learning and artificial intelligence. She is a co-director of the Centre of Machine Learning for Social Good, and the Advanced Machine Learning and Data Analytics Research (MARS) Lab at Auckland. == Academic career == Koh earned a Bachelor of Science with Honours and a Master of Software Engineering at the University of Malaya. She then completed a PhD titled Generating sporadic association rules at the University of Otago in 2007. Koh joined the faculty of the University of Auckland in 2010, rising to full professor. As of 2024, she is director of the Centre of Machine Learning for Social Good at Auckland, alongside Gillian Dobbie and Daniel Wilson, and is director of the Master of AI course at the university. Koh also co-directs the Advanced Machine Learning and Data Analytics Research (MARS) Lab. Koh's research covers machine learning and artificial intelligence. She is especially interested in designing machine learning algorithms for data streams, and has led research using AI systems to identify individual stoats for pest population research. In 2018 she was awarded a Marsden grant for a research project "An Adaptive Predictive System for Life-long Learning on Data Streams", and has been part of three MBIE projects. Koh was a finalist in the AI in Climate section of the Women in AI Australia and New Zealand Awards in 2022. She was a 2023 Fellow at the United States National Science Foundation-funded Convergence Research (CORE) Institute. Koh has chaired a number of sessions at international conferences on data mining. == Selected works == Shafiq Alam; Gillian Dobbie; Yun Sing Koh; Patricia Riddle; Saeed Ur Rehman (August 2014). "Research on particle swarm optimization based clustering: A
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systematic review of literature and techniques". Swarm and evolutionary computation. 17: 1β13. doi:10.1016/J.SWEVO.2014.02.001. ISSN 2210-6502. Wikidata Q125185161. Yun Sing Koh; Nathan Rountree; Richard OβKeefe (1 April 2006). "Finding Non-Coincidental Sporadic Rules Using Apriori-Inverse". International Journal of Data Warehousing and Mining. 2 (2): 38β54. doi:10.4018/JDWM.2006040102. ISSN 1548-3924. Wikidata Q125185222. Russel Pears; Sripirakas Sakthithasan; Yun Sing Koh (11 January 2014). "Detecting concept change in dynamic data streams". Machine Learning. 97 (3): 259β293. doi:10.1007/S10994-013-5433-9. ISSN 1573-0565. Zbl 1319.68186. Wikidata Q125185156. David Tse Jung Huang; Yun Sing Koh; Gillian Dobbie; Russel Pears (December 2014), Detecting Volatility Shift in Data Streams, doi:10.1109/ICDM.2014.50, Wikidata Q125185151 Sidney Tsang; Yun Sing Koh; Gillian Dobbie (2011). "RP-Tree: Rare Pattern Tree Mining". Lecture Notes in Computer Science: 277β288. doi:10.1007/978-3-642-23544-3_21. ISSN 0302-9743. Wikidata Q125185206. Yun Sing Koh; Sri Devi Ravana (24 May 2016). "Unsupervised Rare Pattern Mining". ACM Transactions on Knowledge Discovery from Data. 10 (4): 1β29. doi:10.1145/2898359. ISSN 1556-4681. Wikidata Q125185136. Yun Sing Koh; Nathan Rountree (2010). Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection. IGI Global. doi:10.4018/978-1-60566-754-6. ISBN 978-1-60566-754-6. Wikidata Q125185213. == References == == External links == Continual Learning for Adaptive Predictive Systems - Yun Sing Koh, presentation at the 2022 Artificial Intelligence Researchers Association Conference, via YouTube Leading in the age of AI by leaving a legacy, Thousand Voices podcast episode interviewing Yun Sing Koh, 14 March 2022.
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Biopolymers are natural polymers produced by the cells of living organisms. Like other polymers, biopolymers consist of monomeric units that are covalently bonded in chains to form larger molecules. There are three main classes of biopolymers, classified according to the monomers used and the structure of the biopolymer formed: polynucleotides, polypeptides, and polysaccharides. The Polynucleotides, RNA and DNA, are long polymers of nucleotides. Polypeptides include proteins and shorter polymers of amino acids; some major examples include collagen, actin, and fibrin. Polysaccharides are linear or branched chains of sugar carbohydrates; examples include starch, cellulose, and alginate. Other examples of biopolymers include natural rubbers (polymers of isoprene), suberin and lignin (complex polyphenolic polymers), cutin and cutan (complex polymers of long-chain fatty acids), melanin, and polyhydroxyalkanoates (PHAs). In addition to their many essential roles in living organisms, biopolymers have applications in many fields including the food industry, manufacturing, packaging, and biomedical engineering. == Biopolymers versus synthetic polymers == A major defining difference between biopolymers and synthetic polymers can be found in their structures. All polymers are made of repetitive units called monomers. Biopolymers often have a well-defined structure, though this is not a defining characteristic (example: lignocellulose): The exact chemical composition and the sequence in which these units are arranged is called the primary structure, in the case of proteins. Many biopolymers spontaneously fold into characteristic compact shapes (see also "protein folding" as well as secondary structure and tertiary structure), which determine their biological functions and depend in a complicated way on their primary structures. Structural biology is the study of the structural properties of biopolymers. In contrast, most synthetic polymers have much simpler and more random (or stochastic) structures. This fact leads to a molecular mass distribution that is missing in biopolymers. In fact, as their synthesis is controlled by a template-directed
|
{
"page_id": 3974,
"source": null,
"title": "Biopolymer"
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process in most in vivo systems, all biopolymers of a type (say one specific protein) are all alike: they all contain similar sequences and numbers of monomers and thus all have the same mass. This phenomenon is called monodispersity in contrast to the polydispersity encountered in synthetic polymers. As a result, biopolymers have a dispersity of 1. == Conventions and nomenclature == === Polypeptides === The convention for a polypeptide is to list its constituent amino acid residues as they occur from the amino terminus to the carboxylic acid terminus. The amino acid residues are always joined by peptide bonds. Protein, though used colloquially to refer to any polypeptide, refers to larger or fully functional forms and can consist of several polypeptide chains as well as single chains. Proteins can also be modified to include non-peptide components, such as saccharide chains and lipids. === Nucleic acids === The convention for a nucleic acid sequence is to list the nucleotides as they occur from the 5' end to the 3' end of the polymer chain, where 5' and 3' refer to the numbering of carbons around the ribose ring which participate in forming the phosphate diester linkages of the chain. Such a sequence is called the primary structure of the biopolymer. === Polysaccharides === Polysaccharides (sugar polymers) can be linear or branched and are typically joined with glycosidic bonds. The exact placement of the linkage can vary, and the orientation of the linking functional groups is also important, resulting in Ξ±- and Ξ²-glycosidic bonds with numbering definitive of the linking carbons' location in the ring. In addition, many saccharide units can undergo various chemical modifications, such as amination, and can even form parts of other molecules, such as glycoproteins. == Structural characterization == There are a number of biophysical techniques for
|
{
"page_id": 3974,
"source": null,
"title": "Biopolymer"
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|
determining sequence information. Protein sequence can be determined by Edman degradation, in which the N-terminal residues are hydrolyzed from the chain one at a time, derivatized, and then identified. Mass spectrometer techniques can also be used. Nucleic acid sequence can be determined using gel electrophoresis and capillary electrophoresis. Lastly, mechanical properties of these biopolymers can often be measured using optical tweezers or atomic force microscopy. Dual-polarization interferometry can be used to measure the conformational changes or self-assembly of these materials when stimulated by pH, temperature, ionic strength or other binding partners. == Common biopolymers == Collagen: Collagen is the primary structure of vertebrates and is the most abundant protein in mammals. Because of this, collagen is one of the most easily attainable biopolymers, and used for many research purposes. Because of its mechanical structure, collagen has high tensile strength and is a non-toxic, easily absorbable, biodegradable, and biocompatible material. Therefore, it has been used for many medical applications such as in treatment for tissue infection, drug delivery systems, and gene therapy. Silk fibroin: Silk Fibroin (SF) is another protein rich biopolymer that can be obtained from different silkworm species, such as the mulberry worm Bombyx mori. In contrast to collagen, SF has a lower tensile strength but has strong adhesive properties due to its insoluble and fibrous protein composition. In recent studies, silk fibroin has been found to possess anticoagulation properties and platelet adhesion. Silk fibroin has been additionally found to support stem cell proliferation in vitro. Gelatin: Gelatin is obtained from type I collagen consisting of cysteine, and produced by the partial hydrolysis of collagen from bones, tissues and skin of animals. There are two types of gelatin, Type A and Type B. Type A collagen is derived by acid hydrolysis of collagen and has 18.5% nitrogen. Type B
|
{
"page_id": 3974,
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"title": "Biopolymer"
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is derived by alkaline hydrolysis containing 18% nitrogen and no amide groups. Elevated temperatures cause the gelatin to melts and exists as coils, whereas lower temperatures result in coil to helix transformation. Gelatin contains many functional groups like NH2, SH, and COOH which allow for gelatin to be modified using nanoparticles and biomolecules. Gelatin is an Extracellular Matrix protein which allows it to be applied for applications such as wound dressings, drug delivery and gene transfection. Starch: Starch is an inexpensive biodegradable biopolymer and copious in supply. Nanofibers and microfibers can be added to the polymer matrix to increase the mechanical properties of starch improving elasticity and strength. Without the fibers, starch has poor mechanical properties due to its sensitivity to moisture. Starch being biodegradable and renewable is used for many applications including plastics and pharmaceutical tablets. Cellulose: Cellulose is very structured with stacked chains that result in stability and strength. The strength and stability comes from the straighter shape of cellulose caused by glucose monomers joined by glycogen bonds. The straight shape allows the molecules to pack closely. Cellulose is very common in application due to its abundant supply, its biocompatibility, and is environmentally friendly. Cellulose is used vastly in the form of nano-fibrils called nano-cellulose. Nano-cellulose presented at low concentrations produces a transparent gel material. This material can be used for biodegradable, homogeneous, dense films that are very useful in the biomedical field. Alginate: Alginate is the most copious marine natural polymer derived from brown seaweed. Alginate biopolymer applications range from packaging, textile and food industry to biomedical and chemical engineering. The first ever application of alginate was in the form of wound dressing, where its gel-like and absorbent properties were discovered. When applied to wounds, alginate produces a protective gel layer that is optimal for healing and
|
{
"page_id": 3974,
"source": null,
"title": "Biopolymer"
}
|
tissue regeneration, and keeps a stable temperature environment. Additionally, there have been developments with alginate as a drug delivery medium, as drug release rate can easily be manipulated due to a variety of alginate densities and fibrous composition. == Biopolymer applications == The applications of biopolymers can be categorized under two main fields, which differ due to their biomedical and industrial use. === Biomedical === Because one of the main purposes for biomedical engineering is to mimic body parts to sustain normal body functions, due to their biocompatible properties, biopolymers are used vastly for tissue engineering, medical devices and the pharmaceutical industry. Many biopolymers can be used for regenerative medicine, tissue engineering, drug delivery, and overall medical applications due to their mechanical properties. They provide characteristics like wound healing, and catalysis of bioactivity, and non-toxicity. Compared to synthetic polymers, which can present various disadvantages like immunogenic rejection and toxicity after degradation, many biopolymers are normally better with bodily integration as they also possess more complex structures, similar to the human body. More specifically, polypeptides like collagen and silk, are biocompatible materials that are being used in ground-breaking research, as these are inexpensive and easily attainable materials. Gelatin polymer is often used on dressing wounds where it acts as an adhesive. Scaffolds and films with gelatin allow for the scaffolds to hold drugs and other nutrients that can be used to supply to a wound for healing. As collagen is one of the more popular biopolymers used in biomedical science, here are some examples of their use: Collagen based drug delivery systems: collagen films act like a barrier membrane and are used to treat tissue infections like infected corneal tissue or liver cancer. Collagen films have all been used for gene delivery carriers which can promote bone formation. Collagen sponges: Collagen
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{
"page_id": 3974,
"source": null,
"title": "Biopolymer"
}
|
sponges are used as a dressing to treat burn victims and other serious wounds. Collagen based implants are used for cultured skin cells or drug carriers that are used for burn wounds and replacing skin. Collagen as haemostat: When collagen interacts with platelets it causes a rapid coagulation of blood. This rapid coagulation produces a temporary framework so the fibrous stroma can be regenerated by host cells. Collagen based haemostat reduces blood loss in tissues and helps manage bleeding in organs such as the liver and spleen. Chitosan is another popular biopolymer in biomedical research. Chitosan is derived from chitin, the main component in the exoskeleton of crustaceans and insects and the second most abundant biopolymer in the world. Chitosan has many excellent characteristics for biomedical science. Chitosan is biocompatible, it is highly bioactive, meaning it stimulates a beneficial response from the body, it can biodegrade which can eliminate a second surgery in implant applications, can form gels and films, and is selectively permeable. These properties allow for various biomedical applications of chitosan. Chitosan as drug delivery: Chitosan is used mainly with drug targeting because it has potential to improve drug absorption and stability. In addition, chitosan conjugated with anticancer agents can also produce better anticancer effects by causing gradual release of free drug into cancerous tissue. Chitosan as an anti-microbial agent: Chitosan is used to stop the growth of microorganisms. It performs antimicrobial functions in microorganisms like algae, fungi, bacteria, and gram-positive bacteria of different yeast species. Chitosan composite for tissue engineering: Chitosan powder blended with alginate is used to form functional wound dressings. These dressings create a moist, biocompatible environment which aids in the healing process. This wound dressing is also biodegradable and has porous structures that allows cells to grow into the dressing. Furthermore, thiolated chitosans (see
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{
"page_id": 3974,
"source": null,
"title": "Biopolymer"
}
|
thiomers) are used for tissue engineering and wound healing, as these biopolymers are able to crosslink via disulfide bonds forming stable three-dimensional networks. === Industrial === Food: Biopolymers are being used in the food industry for things like packaging, edible encapsulation films and coating foods. Polylactic acid (PLA) is very common in the food industry due to is clear color and resistance to water. However, most polymers have a hydrophilic nature and start deteriorating when exposed to moisture. Biopolymers are also being used as edible films that encapsulate foods. These films can carry things like antioxidants, enzymes, probiotics, minerals, and vitamins. The food consumed encapsulated with the biopolymer film can supply these things to the body. Packaging: The most common biopolymers used in packaging are polyhydroxyalkanoates (PHAs), polylactic acid (PLA), and starch. Starch and PLA are commercially available and biodegradable, making them a common choice for packaging. However, their barrier properties (either moisture-barrier or gas-barrier properties) and thermal properties are not ideal. Hydrophilic polymers are not water resistant and allow water to get through the packaging which can affect the contents of the package. Polyglycolic acid (PGA) is a biopolymer that has great barrier characteristics and is now being used to correct the barrier obstacles from PLA and starch. Water purification: Chitosan has been used for water purification. It is used as a flocculant that only takes a few weeks or months rather than years to degrade in the environment. Chitosan purifies water by chelation. This is the process in which binding sites along the polymer chain bind with the metal ions in the water forming chelates. Chitosan has been shown to be an excellent candidate for use in storm and wastewater treatment. == As materials == Some biopolymers- such as PLA, naturally occurring zein, and poly-3-hydroxybutyrate can be used
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{
"page_id": 3974,
"source": null,
"title": "Biopolymer"
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|
as plastics, replacing the need for polystyrene or polyethylene based plastics. Some plastics are now referred to as being 'degradable', 'oxy-degradable' or 'UV-degradable'. This means that they break down when exposed to light or air, but these plastics are still primarily (as much as 98 per cent) oil-based and are not currently certified as 'biodegradable' under the European Union directive on Packaging and Packaging Waste (94/62/EC). Biopolymers will break down, and some are suitable for domestic composting. Biopolymers (also called renewable polymers) are produced from biomass for use in the packaging industry. Biomass comes from crops such as sugar beet, potatoes, or wheat: when used to produce biopolymers, these are classified as non food crops. These can be converted in the following pathways: Sugar beet > Glyconic acid > Polyglyconic acid Starch > (fermentation) > Lactic acid > Polylactic acid (PLA) Biomass > (fermentation) > Bioethanol > Ethene > Polyethylene Many types of packaging can be made from biopolymers: food trays, blown starch pellets for shipping fragile goods, thin films for wrapping. === Environmental impacts === Biopolymers can be sustainable, carbon neutral and are always renewable, because they are made from plant or animal materials which can be grown indefinitely. Since these materials come from agricultural crops, their use could create a sustainable industry. In contrast, the feedstocks for polymers derived from petrochemicals will eventually deplete. In addition, biopolymers have the potential to cut carbon emissions and reduce CO2 quantities in the atmosphere: this is because the CO2 released when they degrade can be reabsorbed by crops grown to replace them: this makes them close to carbon neutral. Almost all biopolymers are biodegradable in the natural environment: they are broken down into CO2 and water by microorganisms. These biodegradable biopolymers are also compostable: they can be put into an industrial
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{
"page_id": 3974,
"source": null,
"title": "Biopolymer"
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