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2.3. Adverse Events | As shown in | PMC10177844 | ||
2.4. Monitoring Plasma PEITC Levels | As shown in | PMC10177844 | ||
2.5. Effects of Nutri-PEITC Jelly on Health-Related Quality of Life (HRQoL) | As shown in | PMC10177844 | ||
2.6. Effects of Nutri-PEITC Jelly on Tumor Response and Progression-Free Survival Time | Tumor | TUMOR | Tumor response was evaluated according to RECIST criteria and shown in | PMC10177844 |
2.7. Effects of Nutri-PEITC Jelly on Body Mass Index | As shown in | PMC10177844 | ||
2.8. Effects of Nutri-PEITC Jelly on Karnofsky Performance Status Scale (KPS) | As shown in | PMC10177844 | ||
2.10. Effects of Nutri-PEITC Jelly on Serum Cytochrome c Levels | cancer | CANCER | High serum cytochrome c is associated with poor prognosis and poor survival in cancer patients [ | PMC10177844 |
3. Discussion | cancers, death, tumor, oropharyngeal cancers, cancer, head and neck cancer | CANCERS, CANCER PROGRESSION, TUMOR, CANCER, DISEASE, OROPHARYNGEAL CANCER, HEAD AND NECK CANCER, HEAD AND NECK CANCER | Head and neck cancer, especially oral and oropharyngeal cancers, are one of the most devastating cancers in its effect on quality of life [To our knowledge, only a few human studies have investigated cancer preventive and therapeutic effects of PEITC. A clinical trial in cigarette smokers showed the benefit of PEITC to reduce metabolic activation of lung cancer-specific carcinogens [In this study, the number of interventions taken was aimed at a nutritional supplement (200 kcal per serving). Supplementation with Nutri-Jelly was previously shown to improve quality of life and reduced the requirement for an NG tube for head and neck cancer patients [Reactivation of p53 is a critical approach to regain apoptosis and halt cancer progression [The strength of this study was the triple-blinded design with matched study and control arms. In addition, we evaluated the participants in various aspects that could affect their quality of life and survival. Subject diaries to record intervention intake as well as serum PEITC levels were analyzed to ensure participants’ compliance. Nevertheless, we encountered some limitations. First, dropout rates were quite high (51.22% and 32.2% in control and study groups, respectively), mostly due to death or progressive disease. Notably, the percentage of dropouts in the control group was higher than that of the study group. The difference may be a result of the intervention’s efficacy in stabilizing the disease in study group [To address the above-mentioned flaws and limitations, future studies should aim to reduce dropout rates, characterize the genetic background of participants, analyze p53 levels in tumor samples, and explore additional molecular pathways that may contribute to the cancer-stabilizing effects of Nutri-PEITC Jelly. | PMC10177844 |
4. Materials and Methods | PMC10177844 | |||
4.1. Ethical Aspects and Setting | cancer, Cancer | CANCER, CANCER | Data were collected at Chonburi Cancer Hospital, Lopburi Cancer Hospital, National Cancer Institute, and Maharat Nakhonratchasima Hospital. The study protocol was in compliance with the Declaration of Helsinki and the International Conference on Harmonization Guidelines for Good Clinical Practice (ICH-GCP), and was approved by the Ethical committees for human research of Chonburi cancer hospital (protocol No. 10/2015), Lopburi cancer hospital (Approval No. LEC5712), National cancer institute (protocol No. 302014RC_OUT360), and Maharat Nakhonratchasima hospital (Approval No. 058/2014). This trial was registered with | PMC10177844 |
4.2. Study Design, Blinding, Random Allocation, and Concealment | oropharyngeal cancer | OROPHARYNGEAL CANCER, BLIND | A multi-center blind randomized placebo-controlled trial was conducted. Seventy-two patients with advanced-stage oral or oropharyngeal cancer were randomly assigned with minimization for age and baseline quality of life scores into the study group ( | PMC10177844 |
4.3. Participants | squamous cell carcinoma, primary cancers, Cancer | CAVITY, ONCOLOGY, SQUAMOUS CELL CARCINOMA, PRIMARY CANCER, CANCER | Inclusion criteria of the study population included patients with primary cancers at the lip, oral cavity, oropharynx, pyriform sinus, or hypopharynx (ICD10: C00-C14) whose treatment aimed for palliative care or who denied definitive/standard treatments. If the patients previously received radiotherapy or chemotherapy, those treatments had to be discontinued at least 1 month before enrollment. Cancer had to be diagnosed histopathologically as squamous cell carcinoma and have at least one measurable target lesion. The patients had to have a baseline Karnofsky Performance Status Scale (KPS) of at least 40% or Eastern Cooperative Oncology Group (ECOG) of 0–3, and have acceptable laboratory values (white blood cells ≥ 1.5 × 10 | PMC10177844 |
4.4. Sample Size | head and neck cancer | HEAD AND NECK CANCER | The estimated sample size was identified by a priori power analysis using G Power 3.1. The effect size was calculated from our previous study on head and neck cancer patients receiving palliative radiotherapy [ | PMC10177844 |
4.5. Interventions | Nutri-Jelly and Nutri-PEITC Jelly products ( | PMC10177844 | ||
4.6. Study Procedure | cancer, tumor | ADVERSE EVENTS, CANCER, TUMOR, SECONDARY | Baseline assessment was performed before the randomization, including physical examination, cancer size, location and stage, complete blood count, and liver and kidney function tests. General information about the participants, including age, sex, height, and medical history was retrieved from patients’ charts. The participants were asked to consume either 2 cups of 100 g (total of 200 g) of Nutri-Jelly or Nutri-PEITC Jelly in the morning on Monday to Friday (5 days a week) for 3 months. All participants were asked to record their use of the product daily in subject diaries to ensure adherence to the intervention protocol. The intake of paracetamol was also recorded. The outcome measures were evaluated at 0, 1, and 3 months after interventions. The primary outcome measure included adverse events, health-related quality of life (HRQoL), nutritional status, progression-free survival (PFS), and tumor response. The secondary outcome measures were functional assessment outcome (Karnofsky performance status scale: KPS) and serum p53 and cytochrome c levels.Questionnaires, body weight measurements, blood collection, and tumor size measurement by caliper were performed at all time points. CT scan was performed at 0 and 3 months. | PMC10177844 |
4.7. Outcomes | PMC10177844 | |||
4.7.1. Adverse Events | gastrointestinal disturbance, nausea, vomiting | ADVERSE EVENTS | The physicians assessed the adverse events at 1 and 3 months after the intervention by physical examination, blood hematology, and chemistry. Moreover, adverse events such as nausea, vomiting, and gastrointestinal disturbance were recorded and reported throughout the study period by the participants. The adverse events were graded by the physicians for severity, seriousness, and relatedness to the intervention. | PMC10177844 |
4.7.2. Health-Related Quality of Life and Karnofsky Performance STATUS Scale | Health-related quality of life (HRQoL) was determined by using the Thai version of the FACT-HN questionnaire form after receiving approval from FACIT [ | PMC10177844 | ||
4.7.3. Nutritional Status | Nutritional status was evaluated by body mass index and the levels of serum albumin. Body weight was measured by using a body composition monitor machine (TANITA BC-730, Tanita Corporation, Tokyo, Japan). Body mass index (kg/m | PMC10177844 | ||
4.7.4. Tumor Responses and Progression-Free Survival Time | DISEASE | Progression-free survival (PFS) time was calculated from the time of the intervention until any signs or symptoms of progressive disease be recorded [ | PMC10177844 | |
4.7.5. Serum Levels of p53 and Cytochrome c | The serum was centrifuged at 4 °C for 10 min at 1000× The Cytochrome c ELISA assay was performed by using a Cytochrome c Human ELISA Kit (Catalog No. ab119521, Abcam, Cambridge, UK). Briefly, 100 µL of serum samples were plated in duplicate in a 96-well microtiter plate pre-coated with anti-Cytochrome c monoclonal antibody. Then 50 µL of biotinylated detection antibody was added to each well. The plate was then incubated at room temperature for 2 h. After the washing step, 100 uL of streptavidin-horseradish peroxidase was added and incubated at room temperature for 1 h. The plate was then washed, followed by the addition of TMB substrate and stop solution. Optical density was measured by spectrophotometer at 450 nm (reference wavelength 620 nm) using a microplate reader. | PMC10177844 | ||
4.7.6. Plasma Level of PEITC | To ensure that the participants did consume Nutri-PEITC Jelly, the plasma level of PEITC was measured by using Liquid chromatography Tandem Mass Spectrometry (LC-MS/MS), as previously described [ | PMC10177844 | ||
4.8. Statistical Analysis | The primary efficacy parameters were analyzed for the intention-to-treat (ITT) using the last observation carried forward (LOCF) method for the replacement of missing data points.The normality of data distribution was verified by a D’Agostino and Pearson omnibus test. Parametric statistical tests were used only when the data passed the normality test ( | PMC10177844 | ||
5. Conclusions | OROPHARYNGEAL CANCER, ADVERSE EFFECTS, DISEASE | The findings of this study suggest that intake of Nutri-PEITC Jelly with 20 mg PEITC/day for 1–3 months is safe with minimal adverse effects. The supplementation may re-activate p53, stabilize the disease, improve the quality of life and progression-free survival in patients with advanced-stage oral and oropharyngeal cancer. Further studies in a larger population and various dosages are warranted to confirm that Nutri-PEITC Jelly could be functional food for tertiary chemoprevention in oral and oropharyngeal cancer. | PMC10177844 | |
Author Contributions | Conceptualization, A.L.-U. and D.T.; methodology, A.L.-U. and D.T.; obtain ethical approval, A.L-U.; investigation, A.L.-U., J.S., W.R., P.T., T.T. and D.T.; data curation and formal analysis, A.L.-U. and D.T.; writing—original draft preparation, A.L.-U.; writing—review and editing, D.T.; funding acquisition, A.L.-U. and D.T. All authors have read and agreed to the published version of the manuscript. | PMC10177844 | ||
Institutional Review Board Statement | cancer | CANCER | This study was approved by the Ethical committees for human research of Chonburi cancer hospital (protocol No. 10/2015), Lopburi cancer hospital (Approval No. LEC5712), National cancer institute (protocol No. 302014RC_OUT360), and Maharat Nakhonratchasima hospital (Approval No. 058/2014). | PMC10177844 |
Informed Consent Statement | Informed consent was obtained from all subjects involved in the study. | PMC10177844 | ||
Data Availability Statement | All data collected in this project have been described in this work. No further data are available. Since the participants only gave consent to report the summary of data, no individual data can be shared. | PMC10177844 | ||
Conflicts of Interest | D.T. and A.L.-U. received a research grant and Nutri-PEITC Jelly products from a non-profit organization, Dental Innovation Foundation under Royal Patronage, Thailand. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. The authors have full control of all data and reports. | PMC10177844 | ||
1. Introduction | CVDs | BLOOD, CARDIOVASCULAR DISEASE | These authors contributed equally to this work.This study aimed to investigate the impact of influencing factors (sex, eicosapentaenoic acid (EPA) status at baseline, linoleic acid (LA) intake, milk fat intake) on the conversion of α-linolenic acid (ALA) obtained from linseed oil into its long-chain metabolites. In addition, the effect of ALA on cardiovascular risk markers was investigated. This study used a parallel design approach by randomly assigning the 134 subjects to one of four diets (high in LA (HLA); low in LA (LLA); high in milk fat (MF); control (Western diet)) each enriched with linseed oil (10 en%, 22–27 mL ≙ 13–16 g ALA). Blood samples were taken at baseline and after 4, 8, and 12 weeks of dietary intervention. The study was fully completed by 105 subjects (57.4 ± 12.1 years; 65.7% female). Results showed that ALA (296–465%), C-20:4n3 (54–140%), and EPA (37–73%) concentrations in erythrocytes increased in all groups (Cardiovascular diseases (CVDs) are among the greatest threats to human health worldwide [The traditional Western diet in Germany is characterized by a high intake of energy, simple carbohydrates, and refined starch, as well as saturated fats, with an inadequate consumption of monounsaturated fatty acids (MUFA), PUFA, and dietary fiber [In general, the human organism can synthesize the long-chain metabolites EPA and DHA from ALA using elongases and desaturases. However, the conversion rate to EPA and DHA is limited to 8% and 0.02–4%, respectively [The present study aims to investigate the changes in the fatty acid distribution of erythrocyte lipids by evaluating the influence of simultaneous LA intake, milk fat intake, sex, and The influence of background diet on the conversion of ALA from linseed oil into the long-chain metabolites EPA and DHA was studied by implementation of defined menu plans (high in LA (HLA); low in LA (LLA); high in milk fat (MF)). The comparison was made against a control group who followed a typical Western diet. In addition to fatty acid distribution, the impact on cardiovascular risk factors was also investigated. | PMC10610546 |
2. Materials and Methods | PMC10610546 | |||
2.1. Study Design (Screening) | weight gain, infections, period).Weight loss | FOOD ALLERGIES, INFECTIONS, CHRONIC DISEASES | The KoALA study was conducted as a randomized, single-center intervention study in parallel design (four arms: defined consumption of linseed oil; differing background diets for three groups using prepared menu plans; one control group; the figure in In early 2018, participants were recruited using flyers and press releases. The flyers were distributed in public facilities, medical practices, and pharmacies in Jena.The following inclusion criteria were applied:Women (in menopause) and men (50% each), aged between 40 and 65 years, body mass index (BMI) < 30 kg/mModerately elevated low-density lipoprotein (LDL) cholesterol (>3 mmol/L).Consumption of a traditional “Western diet” composed of meat, sausage, dairy products, cereals, vegetables, fruits, etc.Stable eating habits at least one year before enrollment.No antihypertensive medication or stable dose for >3 months prior to the start of the study and during the entire study period.The following exclusion criteria were applied:Acute or chronic diseases which could affect the results of the present study.Use of medication, including systemic glucocorticoids or lipid-lowering medication.Use of dietary supplements, incl. multivitamins, fish oil capsules, minerals and trace elements (three months before and during the entire study period).Weight loss or weight gain (>3 kg) during the last three months before the study began.Relevant food allergies (e.g., milk, nuts).Pregnancy or lactation.Adherence of the subjects to the dietary habits as defined (Western diet, stable eating habits before enrollment, renunciation of dietary supplements) was verified by a personal interview and a questionnaire.Before the preliminary phase, 200 subjects were screened for enrollment and 134 participants met the inclusion criteria (Following the informed consent and after confirmation of the inclusion and exclusion criteria, participants were scheduled for the baseline assessment.Participants could be withdrawn from the study at any time after enrollment for the following reasons: at the patient’s request, due to severe infections, or if patient compliance with the study protocol was in doubt. The study was conducted in accordance to the Helsinki Declaration of 1975, as revised in 1983. The study protocol was approved by the Ethical Committee of the Friedrich Schiller University Jena (protocol code 5419-01/18) and registered by ClinicalTrails.gov (NCT03558776). | PMC10610546 |
2.2. Baseline Assessment | DISEASE | To record and document the habitual dietary patterns within and between groups, the preliminary phase of the KoALA study included full self-reporting of the individual’s dietary intake over seven days. The dietary record was based on the template “Freiburger Ernährungsprotokoll Standard”, which was provided by PRODI software version 6.4 (Nutri-Science, Stuttgart, Germany) and includes foods and usual portion sizes of a typical German diet. Foods not listed in the template were documented manually by the participants, including the name and the amount of the consumed food. The daily energy and nutrient intake was calculated by the software package PRODI.In addition, participants filled out questionnaires to assess lifestyle, health, and disease status (including medication use). | PMC10610546 | |
2.3. Study Diet—The KoALA Concept | After one week of the preliminary phase, each participant was randomly assigned to one of the four groups. The intervention phase of the study ranged over 12 weeks for each participant. Visits to the study center took place at baseline and after 4, 8, and 12 weeks, to take samples, provide study materials and solve potential problems owing to the implementation of the menu plans (The daily intake of linseed oil constituted 27 mL for men and 22 mL for women. This dosage corresponds to around 10% of the daily energy intake (en%). In addition, the HLA, LLA, and MF groups received defined menu plans for each study day to modify the background diet and homogenize the energy intake. Participants in the control group were asked to maintain a typical Western diet (without menu plans). They also consumed the pre-defined amount of linseed oil.For the HLA group, the menu plans ensured an additional 20% of daily energy intake via fat which consisted of 7 ± 2 en% LA, up to 10 en% saturated fatty acids (SFA) and 3 ± 2 en% MUFA. The menu plans included oils rich in For the LLA group, the additional 20 en% of fat consisted of below 2.5 en% LA, at least 15 en% MUFA provided by olive oil and nuts such as almond, cashew, and hazelnut plus around 2.5 en% of SFA.For the MF group, the additional 20 en% of fat mainly was provided by milk fat from milk and dairy products (15 ± 2 en%) plus 5 ± 2 en% SFA, MUFA, and All menu plans provided 2500 calories for men and 2000 for women, split into 55 en% of carbohydrates, 15 en% of protein, and 30 en% of fat. In addition, the menu plans were characterized by the following criteria:Absence of other foods providing Reduced intake of monosaccharides and increased intake of dietary fiber.Reduction in salt.Increased consumption of fruits and vegetables.Reduction in foods which are highly processed, calorie-rich, and low in nutrients, such as fast food and convenience products.The menu plans included up to five meals per day split into breakfast, lunch, dinner, and up to two snacks. For each meal, detailed information on the type and amount of the food was provided. Recipes for meals that required preparation were also included.To increase compliance, linseed oil was provided to each participant. The fatty acid distribution for the linseed oil is shown in | PMC10610546 | ||
2.4. Sample Collection, Biochemical Analyses, and Further Measurements | erythrocyte fatty acid, peripheral venous blood | BLOOD, CREST | Parameters measured as part of the study were biochemical parameters (fasting lipid profile, high-sensitivity c-reactive protein (CRP), apolipoproteins A1 and B, lipoprotein(a), homocysteine, fasting glucose and insulin, glycated hemoglobin A1c (HbA1c)), erythrocyte fatty acid distribution, anthropometric parameters (body weight and composition, blood pressures, heart rate), and micronutrient status (vitamins, minerals, trace elements) (Blood was taken by venipuncture between 7:30 AM and 10:30 AM after at least 12 h overnight fasting. Furthermore, consumption of alcohol and excessive physical activity was not allowed on the day before and on the morning before the venipuncture.Fasting peripheral venous blood samples were centrifuged (10 min, 2.762 g, 4 °C) to separate plasma and serum. Study parameters were analyzed immediately after blood sampling or by using serum and plasma aliquots stored at –80 °C until the analysis. Samples were prepared according to standard operation procedures. Many of the study parameters were analyzed at the Institute of Clinical Chemistry and Laboratory Diagnostics, Jena University Hospital using an Abbott Architect CI 16200 analyzer (Abbott, Wiesbaden, Germany), HPLC (Shimadzu, Kyoto, Japan) or with regard to HbA1c using the Tosoh HLC-723G11 (Sysmex, Norderstedt, Germany) according to the manufacturer’s recommendations (The same trained nurse always performed the anthropometric parameters, blood pressure, and heart rate measurements with participants barefoot and in light clothing (single measurement). Body weight was measured in kilograms to the first decimal place and height and waist circumferences to the nearest half centimeter. Waist circumference was measured midway between the lower rib margin and the iliac crest (a thumb’s breadth above the navel). Arterial blood pressure was measured with the subject in a sitting position using the upper arm after the subject had been seated for at least 10 min.Calibrated instruments were used (scale with integrated stadiometer: seca813; Hamburg, Germany; ergonomic tape measure: seca212; Hamburg, Germany; automatic blood pressure device: boso-medicus uno; BOSCH + SOHN, Jungingen, Germany). Body composition was assessed by a Body Impedance Analyzer (Data Input, Pöcking, Germany; exactness of measurement: 0.5% of measurement value (reactance)/±2.0% of measurement value (resistance)). | PMC10610546 |
2.5. Statistical Methods | RECRUITMENT | The power calculation was based on the data from Dittrich et al. (2015) [The global power was calculated based on a linear model (analysis of variance) to compare the EPA concentrations at the end of the study for the four groups. The power was 91.1%, assuming a standard deviation of 0.35 and a significance level of 5%.Contrasts are considered in the linear model mentioned above for power calculation for single comparisons. The most considerable difference in EPA concentration is expected between the HLA and LLA groups or the LLA and MF groups. Based on these data, a group size of 37 subjects has 81% power to achieve an EPA difference of 0.2% FAME between the LLA and control groups (EPA difference between μ1 = 1.2% FAME; μ2 = 1.3% FAME), assuming that the standard deviation is 0.3. In addition, a group size of 37 subjects has 99% power to achieve an EPA difference of 0.3% FAME between the HLA and LLA groups (EPA difference between μ1 = 1.1% FAME; μ2 = 1.4% FAME), assuming that the standard deviation is 0.3. The number of cases was planned using SAS proc power version 9.4 (SAS Institute, Cary, NC, United States). Based on the power calculation with the described data, 37 subjects per group were to be enrolled. Due to the lack of availability of suitable subjects in the recruitment period, only 134 instead of the planned 148 subjects could be included (For assigning the participants to the four groups, a randomization list was generated with the statistical software R version 3.5.2 (The R Foundation for Statistical Computing, Vienna, Austria).The primary endpoint of the study was the change in EPA (% FAME) in erythrocyte lipids. Secondary endpoints were the effects on blood lipids, markers of glucose metabolism, micronutrient status, and anthropometric parameters.For statistical analyses, the statistical software IBM SPSS Statistics version 28.0.1.1 (14) (IBM Germany, Ehningen, Germany) was used. If the data followed a normal distribution, this was tested with the Shapiro–Wilk test. Differences between groups were assessed using one-way ANOVA for normally distributed variables or the Kruskal–Wallis test for not normally distributed variables. Differences within groups comparing baseline and weeks 4, 8, and 12 were assessed using ANOVA for repeated measurements for normally distributed variables or the Friedman test for not normally distributed variables. Fisher’s least significant difference test was performed as a post-hoc test and calculated For calculations of the sum of We divided our study collective according to EPA status at baseline (<0.9% FAME vs. ≥0.9% FAME) and LA change (% FAME) throughout the study period (<1.5% FAME vs. ≥1.5% FAME) to evaluate the influence of these factors on the conversion of ALA into its long-chain metabolites. The limits represent the cut-off values of each 50% of our participants to compare groups of equal size, as no reference values are available. | PMC10610546 | |
3. Results | PMC10610546 | |||
3.1. Baseline Characteristics of the Study Collective | The baseline characteristics of the subjects (The distribution for sex and age per group is shown in The 7-day dietary self-report in the week before the start of the intervention showed a comparable intake of energy and macronutrients, selected carbohydrate sources, fatty acids and micronutrients between the four groups ( | PMC10610546 | ||
3.2. Changes in Fatty Acid Distribution in Erythrocyte Lipids within the Diet Groups | The 12-week intervention resulted in a median increase in ALA by 296–465%, in ETA by 54–140%, and in EPA by 37–73% in each group (An increase in DPA concentration was only observed in the MF (36 ± 44%) and control groups (11 ± 15%) (In contrast, the DHA concentration, which represents the main An increase in the total content of Concerning In the HLA, LLA, and control groups, there was an increase in C-16:0 and a decrease in C-18:0 (The trans-fatty acids (TFA) fell in the HLA and increased in the MF group ( | PMC10610546 | ||
3.3. Changes in Fatty Acid Distribution in Erythrocyte Lipids per Diet Group Subdivided into Subgroups by Sex, EPA Status, and LA Change over the Intervention Period | To evaluate the conversion rate of ALA into its long-chain metabolites, we examined the influence of the following three influencing factors: sex (men vs. women), EPA status at baseline (<0.9% FAME vs. ≥0.9% FAME), and LA change throughout the study period (<1.5% FAME vs. ≥1.5% FAME). The subgroups mentioned above were formed within the four diet groups (A sex-specific difference was only observed for the DPA concentration in the LLA group, which increased significantly in men and remained unchanged in women.According to EPA status, the subdivision shows that increases in both ETA and EPA were more pronounced at low EPA status than at high EPA status. In contrast, the DHA and The change in LA concentration throughout the study seems to have less of an impact, as only a few independent significant changes were observed. As expected, the increase in LA differs between the LA change ≥1.5% FAME subgroup and the LA change <1.5% FAME subgroup (Independent of sex or EPA status (EPA baseline status: <0.9 vs. <0.9% FAME), the comparison of diet groups shows a higher increase in DPA and a lower decrease in DHA and the | PMC10610546 | ||
3.4. Influence on Fatty Acid Distribution in Erythrocyte Lipids Depending on Sex, EPA Status, and Total LA Change without the Original Diet Group Split | The intended fatty acid intake provided via the menu plans (This evaluation shows that in women, EPA increased by a median of 39% (Subjects with an initial EPA value of <0.9% FAME had a median increase in EPA of 79% (In subjects with LA change <1.5% FAME, median EPA increased by 58% ( | PMC10610546 | ||
3.5. Correlation between Micronutrient Status and EPA Percentage Change from Baseline in the Entire Study Population | A correlation analysis between micronutrient status (calcium, potassium, ferritin, transferrin, folic acid, biotin, holo-transcobalamin, vitamins A, B | PMC10610546 | ||
3.6. Influence on Biochemical Parameters and Anthropometric Measurements per Diet Group | fasting blood glucose, diabetes’ | Regarding the analyzed cardiovascular risk factors (total, LDL, MDA-LDL, high-density lipoprotein (HDL) and non-HDL cholesterol, triglycerides, high-sensitivity CRP, apolipoprotein A1 and B, lipoprotein(a), homocysteine), no significant differences were found between the different groups, both at baseline and at the end of the study (For diabetes’ risk markers (fasting blood glucose, fasting insulin, HbA1c), significant changes only were observed within groups. Here, the mean fasting glucose decreased from 5.89 mmol/L to 5.63 mmol/L (The vitamin E status was not different between and within groups at any point and the change from baseline did also not show any significant differences. Within groups, mean vitamin E status decreased in the LLA and MF groups (No significant differences were found at baseline or at the end of the study for all anthropometric measures. However, significant changes in BMI were found in the HLA, LLA, and MF groups. The BMI decreased the most in the LLA group by an average of −0.78 kg/mFor systolic and diastolic blood pressure, significant changes only were observed within groups. Here, median systolic and diastolic blood pressure decreased each by −1 mmHG in the HLA group ( | PMC10610546 | |
4. Discussion | PMC10610546 | |||
4.1. Effects on Fatty Acid Distribution in Erythrocytes in Response to Linseed Oil Supplementation | desaturation | ZINC DEFICIENCY, ZINC DEFICIENCY, IRON DEFICIENCY | An increased amount of EPA and DHA in erythrocytes is associated with reduced cardiovascular risk, which cannot be clearly confirmed for ALA [Our study shows that linseed oil supplementation (10 en%, 22–27 mL ≙ 13–16 g ALA) significantly increases ALA, ETA, and EPA concentrations in erythrocytes in all groups. In contrast, the DHA concentration dropped significantly in the HLA, LLA, and control groups. Since DHA is the most prominent fatty acid in erythrocytes in quantity, the Greupner and Kutzner et al. (2018) observed a significant increase in ALA, EPA, and DPA concentrations and a significant decrease in C-20:3n6, ARA, C-22:4n6, and DHA concentrations due to a daily intake of 13 g ALA for 12 weeks. In contrast to our study, the LA concentration did not increase [In the study of Wilkinson et al. (2005), a 12-week intervention with 15 g ALA per day led to a significant increase in ALA (225%) and EPA (150%) concentrations. Thus, the ALA increase was weaker, but the EPA increase was more pronounced compared to our study. A significant effect on the DHA concentration could not be determined [Even small amounts of ALA can significantly increase EPA concentration in erythrocytes. In a study by Kuhnt et al. (2016), 5 g of ALA per day for 8 weeks increased ALA, EPA, and DPA concentrations by 201, 32, and 12%, respectively. Again, C-20:3n6 (−5%), C-22:5n6 (−4%), and DHA (−10%) concentrations decreased significantly. LA and ARA did not change significantly [Furthermore, it is described in reviews that ALA supplementation leads to an increase in EPA and, in some studies, also to an increase in DPA concentration, but the DHA concentration mostly remains unchanged or even decreases [One reason for the unchanged or falling DHA concentration due to ALA supplementation could be that ∆6 desaturase is needed for the desaturation of ALA into stearidonic acid (C-18:4) and is not available for the last step of DHA formation (desaturation of C-24:5n3 to C-24:6n3) at the same time. Both substrates compete for the same enzyme. However, the ∆6 desaturase has a higher affinity for ALA, so less DHA is produced [In addition to A study on hamsters confirms this assumption. Higher intakes of ALA resulted in lower levels of DHA and ARA in erythrocytes (LA intake unchanged). The LA concentration, however, increased [The characteristic fatty acid intake, which the menu plans should provide, was not reflected by the changes in fatty acid distribution in the erythrocyte lipids.Differences in fatty acid distribution between the diet groups only rarely occurred. Due to the intended intake of sunflower oil in the HLA and olive oil in the LLA group, LA in the HLA and oleic acid in the LLA group should have increased significantly compared to the other three groups [To investigate the influence of sex, EPA status, and the total change in LA throughout the study on ALA conversion, we first observed the influence of these factors in the diet groups. Subsequently, to achieve a larger sample size, the division into the four groups was removed, and an analysis within the subgroups was performed again.While including the diet groups, no sex-specific difference could be found. However, after dissolving the groups, men showed a significantly higher EPA concentration than women. Previous reviews describe a more efficient conversion of ALA into EPA and DHA in women than in men. The reason for this could be a lower β-oxidation rate (women 22% vs. men 33%; measured over 24 h) of ALA and increased activity of desaturases and elongases due to estrogen [The subdivision according to EPA status within diet groups shows that both ETA and EPA increase significantly more in participants with low EPA status (<0.9% FAME) and DHA as well as the Welch et al. (2010) described a higher conversion of ALA into In the analysis for changes in LA throughout the study within the diet groups, only isolated differences were found, so no clear statement can be made.In general, it must be taken into account that only a small sample size was available for some of the calculations, so these results must be critically evaluated.After removing the diet group subdivision, the In rats and pigs, EPA, DPA, and DHA concentrations in liver lipids or plasma phospholipids were found to be lower at higher LA intakes than at lower LA intakes when ALA intake was unchanged [Goyens et al. (2006) showed that in healthy men and women, with the same ALA intake (0.4 en%) but different LA intake (7 vs. 3 en%), EPA in plasma phospholipids increased significantly more with lower LA intake. The decrease in DHA concentration did not differ significantly between the two groups [Rosell et al. (2005) also confirmed in their study that a high LA intake correlates inversely with the EPA and DHA plasma concentration (% of total fatty acids) [When interpreting the results, however, it should be noted that the actual percentage of ALA metabolized to EPA, DPA, and DHA cannot be determined, as we could not conduct our study with marked, stable isotopes. Thus, it cannot be concluded that the LC Tracer studies in men have shown that only 6–8% of the ingested ALA is found as EPA, 4–8% as DPA, and 0–4% as DHA in plasma lipids [In addition to influencing factors like EPA status, sex, or change in LA status, genetic factors, in particular, polymorphisms in the fatty acid desaturase (FADS) and fatty acid elongase (ELOVL) genes, and the transcription factors sterol regulatory element-binding protein-1c (SREBP-1c) and peroxisome proliferator-activated receptor α (PPARα) can also influence the expression of desaturases and elongases and thus the conversion of ALA into LC Whether micronutrient status influences the activity of desaturases has mainly been investigated in rats, so human studies are still required.Rat studies indicate that vitamin A supplementation raises the ∆5 and ∆6 desaturase activity (based on product-to-precursor ratios) but decreases the Fads1 (encode ∆5 desaturase) messenger ribonucleic acid (mRNA) concentration [There are contradictory results regarding the influence of folate and vitamin BIron and zinc are cofactors of desaturases. Therefore, it is plausible that iron and zinc status affect desaturase activities. Zinc deficiency in both rats and humans leads to a decrease in ∆6 desaturase activity. Regarding the ∆5 desaturase activity, rat and human studies show contradictory results. In rats, zinc deficiency leads to a decrease in ∆5 desaturase activity, whereas high serum zinc was associated with low ∆5 desaturase activity in humans. Moreover, iron deficiency impairs LC-PUFA synthesis in rats and humans [ | PMC10610546 |
4.2. Discussion of the Observed Effects on Biochemical and Anthropometric Parameters | In general, effects on cardiovascular risk markers in the intervention groups differ from the literature in terms of adherence to a healthy diet [ | PMC10610546 | ||
5. Conclusions | Our data show that a daily intake of approx. 25 g linseed oil (≙ approx. 15 g ALA) leads to a significant increase in EPA concentrations and a simultaneous decrease in DHA concentrations in erythrocyte lipids. The increase in EPA was significantly stronger in individuals with a lower EPA status at baseline (<0.9% FAME), highlighting that converting ALA to EPA is more efficient in participants with low EPA. In contrast to most previous findings, we did not find a more efficient conversion of ALA to EPA in women, possibly because our female participants were in menopause. Our data suggest that a high LA status attenuates the conversion of ALA. The micronutrient status seems to have no clear effect on conversion from ALA to EPA or DHA.The absence of effects on blood lipids, markers of glucose metabolism, and fatty acid distribution in erythrocyte lipids supports the hypothesis of lacking compliance with the menu plans. The fact that no apparent effects on blood lipids and further cardiovascular risk factors were achieved by linseed oil supplementation alone is in line with the literature since effects were not consistently visible. | PMC10610546 | ||
6. Strengths and Limitations | The KoALA study was designed to evaluate influencing factors on the metabolism of land-based The strengths of the KoALA study are the comprehensive health status assessment focusing on nutrient status and cardiovascular risk factors. Combined with the broad analysis of fatty acids in the erythrocyte lipids, it is possible to picture a variety of influences on | PMC10610546 | ||
Supplementary Materials | The following supporting information can be downloaded at: Click here for additional data file. | PMC10610546 | ||
Author Contributions | Conceptualization, C.D.; methodology, T.D., T.S.B. and C.D.; software, T.D., T.S.B. and P.S.; validation, T.D., T.S.B. and C.D.; formal analysis, T.D., T.S.B. and S.L.; investigation, T.D., T.S.B., M.K. and C.D.; resources, T.D., T.S.B., M.K. and C.D.; writing—original draft preparation, T.D. and T.S.B.; writing—review and editing, M.K., P.S., S.L. and C.D.; visualization, T.D. and T.S.B.; supervision, C.D.; project administration, C.D.; funding acquisition, C.D. All authors have read and agreed to the published version of the manuscript. | PMC10610546 | ||
Institutional Review Board Statement | The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of the Friedrich-Schiller-University Jena (protocol code 5419-01/18). | PMC10610546 | ||
Informed Consent Statement | Informed consent was obtained from all subjects involved in the study. | PMC10610546 | ||
Data Availability Statement | Requests to access the data sets should be directed to the corresponding author. | PMC10610546 | ||
Conflicts of Interest | The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. | PMC10610546 | ||
References | high-density lipoprotein | Flowchart diagram of the study population in the different phases of the study. A total of 200 subjects were screened for eligibility. In total, 66 subjects had to be excluded, so that 134 subjects were randomized to the four diet groups. After completion of the study, sorted by group, 27, 27, 23 and 28 participants were included in the statistical analysis.Study design of the KoALA study. Abbreviations: ARA, arachidonic acid; LA, linoleic acid; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acids.Plots (Fatty acid distribution of the provided linseed oil expressed as fatty acid methyl esters (FAME).Abbreviations: MUFA, monounsaturated fatty acids; FAME, fatty acid methyl esters; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acids.Characteristics of the study collective—baseline assessment.Variables expressed as mean (±SD) or as median (25th, 75th percentile) depending on the data distribution. Abbreviations: BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein.Sex distribution and age per group—baseline assessment.Variable expressed as mean (±SD) and/or as median (25th, 75th percentile) depending on the statistical test that was performed; groups without a common letter are significantly different, Comparison of percentage change from baseline within diet groups split in dependence of sex, EPA baseline status, and LA change over the intervention period.* Variables expressed as mean (±SD) and/or as median (25th, 75th percentile) depending on the statistical tests that were performed; ∆ comparison of subgroups within diet groups; ◊ comparison of subgroups between diet groups, groups without a common letter are significantly different, Fasting biochemical parameters and anthropometric measurements at baseline (week 0) and at the end of the intervention period (week 12).* Variables expressed as mean (±SD) and/or as median (25th, 75th percentile) depending on the statistical tests that were performed; ◊ groups without a common letter are significantly different, | PMC10610546 | |
Background | RPC and SAM are joint senior authors.The public’s confidence in vaccinations has eroded, and anti-vaccination movements have gained traction around the world, including in the Philippines. ‘Salubong’, a Filipino term, refers to welcoming someone back into one’s life and elicits ideas about friendship and family relationships. We extended this concept to vaccines in efforts to design an intervention that would re-welcome vaccines into homes. | PMC10603469 | ||
Methods | Using human-centred design, we developed and refined a story-based intervention that engages Filipino families, community leaders and community health workers. We conducted a randomised controlled trial among 719 caregivers of small children to test the developed intervention against a control video. We assessed the binary improvement (improvement vs no improvement) and the amount of improvement in vaccine attitudes and intentions after intervention exposure. | PMC10603469 | ||
Results | Although the intervention group began with marginally higher baseline vaccine attitude scores, we found that 62% of the intervention group improved their vaccine attitude scores versus 37% of the control group (Fisher’s exact, p<0.001). Among individuals whose scores improved after watching the assigned video, the intervention group saw higher mean attitude score improvements on the 5-point scale (Cohen’s d=0.32 with 95% CI 0.10 to 0.54, two-sided t-test, p<0.01). We observed similar patterns among participants who stated that they had previously delayed or refused a vaccine for their child: 67% of 74 in the intervention group improved their vaccine attitude scores versus 42% of 54 in the control group (Fisher’s exact, p<0.001). Among the subset of these individuals whose scores improved after watching the assigned video, the intervention group saw higher mean attitude score improvements on the 5-point scale that were marginally significant (Cohen’s d=0.35 with 95% CI −0.01 to 0.70, two-sided t-test, p=0.06). | PMC10603469 | ||
Conclusions | Our results provide solid evidence for the potential of co-designed vaccine confidence campaigns and regulations. | PMC10603469 | ||
WHAT IS ALREADY KNOWN IN THIS TOPIC | DISEASES | Vaccine hesitancy can have serious public health consequences, as it can lead to outbreaks of vaccine-preventable diseases, particularly in countries with low vaccination rates.Concerns about the safety and effectiveness of vaccinations, including misinformation, mistrust of healthcare workers or pharmaceutical companies, religious or philosophical convictions and fear of side effects are all potential causes of vaccine hesitancy.While human-centred design (HCD) has proven beneficial in several health campaigns, evidence regarding whether, how or to what effect HCD can be used to bolster vaccination confidence in low and middle-income countries is lacking. | PMC10603469 | |
WHAT THIS STUDY ADDS | We designed and refined a story-based intervention that involves Filipino families (especially those who are vaccine-hesitant), community leaders and community health workers using HCD.Our findings highlighted the potential of real-life narratives in developing and honing an intervention rooted in the local context.Our HCD-driven intervention boosts vaccine confidence and increases positive feelings about vaccines. We thereby reinforce the importance of HCD as a method of meaning-making that affects attitudes and behavioural intent in relation to vaccinations. | PMC10603469 | ||
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY | Time, vulnerability and volatility (ie, roller-coaster emotions) elements of vaccine hesitancy emphasise the necessity of integrating context and ongoing public sentiments into interventions targeted at promoting vaccine confidence.Additional and larger-scale research is warranted, particularly concerning vaccine messaging revitalisation in a time of pervasive disinformation and with vaccine uptake outcomes in addition to intentions. | PMC10603469 | ||
Introduction | dengue | DENGUE, EROSION, MEASLES | The need for interventions and products that are personalised to human experiences and their cultural and environmental contexts is increasingly recognised. Human-centred design (HCD) has gained popularity in the field of global health as a means to co-create and rapidly assess products and services.Several studies have demonstrated the value of HCD in fostering cultural sensitivity and local adaptability.As vaccine hesitancy constitutes a significant threat to global health,While HCD-driven interventions have yielded promising results in terms of increasing vaccine confidence and uptake, their scope did not always acknowledge vaccine-hesitant families’ own lived experiences and narratives. Several authors have argued about the importance of tailoring health interventions based on vaccination concerns and experiences, and aligning interventions to fit cultural and environmental contexts.To fill gaps in the literature and lay the groundwork for a meaningful campaign that restores trust in vaccines, we drew on local narratives to design, refine and ultimately test a story-based intervention that connects vaccine-hesitant caregivers (eg, parents, other family members, legal guardians), policymakers, healthcare workers (HCWs) and other community actors. We developed and tested our HCD-driven intervention in a country that has experienced an unprecedented erosion of vaccine confidence in childhood vaccinations: The Philippines. Dramatic declines in vaccine confidence and uptake in the Philippines are linked to a dengue vaccination controversy in 2017, which sparked widespread distrust in childhood vaccinations and led to large-scale measles outbreaks and the loss of a 20-year polio-free status in 2019.In this article, we present the randomised controlled trial (RCT) results of testing the final story-based vaccine confidence intervention. Our work provides evidence that can inform upcoming campaigns and regulations targeted at restoring public confidence in vaccines. | PMC10603469 |
Methods | PMC10603469 | |||
Study oversight | Prior to commencement, permission to undertake this study was obtained from Department of Health officials (national, regional and provincial offices). Further, through official letters and Zoom courtesy calls, we also acquired permission from local authorities and leaders in the Calabarzon region to carry out the study in their respective communities. Informed consent was obtained from all participants prior to their enrolment. | PMC10603469 | ||
Experimental design and set-up | ’ | We randomly selected barangays (‘small communities’) from Dasmariñas City (urban arm) and Silang, Cavite (rural arm) that had not previously participated in a qualitative component of the study (results of which are described elsewhereWe performed a multistage stratified sampling frame to select barangays. From each of the two study sites, two barangays with the highest population, based on the most recent population report available, were selected to ensure enough potential participants. The two selected barangays (per urban and rural arms) were randomly allocated as an intervention and as a control site. A listing of households with under-five children was obtained from the local health officials. The household listing served as a sampling frame from which 200 households were randomly selected and invited to participate in the study. In four originally sampled barangays (two each for control and intervention groups), the number of interviewed caregivers was less than 200. In line with the processes defined in the research protocol, we therefore sampled additional barangays as per the criteria above.We collaborated with community health workers who conducted house visits, obtained caregivers’ mobile phone numbers and obtained consent to be contacted by the research team, following the selection and allocation of the potential participants to intervention or control groups. Community health workers also distributed consent forms and informed potential participants that a member of the research team would contact them. Afterwards, the potential participants were invited to participate during a phone call where the study aims were briefly introduced. If individuals expressed interest in the initial phone contact, we either directly continued with a detailed study discussion and obtained online informed consent (via Facebook Messenger video call) or scheduled a separate appointment. To ensure participants’ internet connectivity throughout the consent process and trial procedures, we purchased and transmitted mobile data packages to participants.Once consent was obtained, the videos (intervention and control) and surveys (pre and post) were delivered online. We developed and used an online version of the survey forms, which we pilot-tested among 30 caregivers to ensure feasibility (either self-administered or data collector-assisted) and alleviate operational challenges. Following the pilot testing of the survey forms, we therefore decided to conduct data collector-assisted surveys (ie, data collectors read the questions to the participants and are responsible for encoding the answers in the online form). After completion of the baseline survey, the Salubong video was then screened for members belonging to the intervention group, while the ‘Before and after watching the intervention or control video, participants in both groups were asked to provide information about their attitudes toward vaccinations, with statements such as, ‘Children get more shots than are good for them’, ‘I believe that many of the illnesses that vaccinations prevent are severe’ and ‘It is better for my child to develop immunity by getting sick than to get a shot’, among others. We used the parents’ attitudes about childhood vaccination (PACV-15) adapted from Opel and colleagues.
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Data treatment and analysis | ’ | REGRESSION | Achieving the originally envisioned sample size proved challenging. As outlined above, we sampled participants from more barangays than initially envisioned, (a total of 8 in control and 4 intervention barangays across urban and rural study sites), following the pre-defined procedures, due to difficulties reaching participants fulfilling the inclusion criteria under pandemic conditions, and as many potential participants refused to participate online. We considered shifting to in-person data collection but ultimately decided against it due to the COVID-19 concerns raised by the selected barangays and budgetary constraints. Instead, we analysed the data sets available after more than 1 year of data collection (n=719) to see if adding more information could impact the primary outcomes. We calculated whether knowledge had increased in total (ie, the total points in the suggested approach are higher in pre-intervention and post-intervention) and in which particular domain knowledge had increased. Furthermore, we did linear regression analysis with ‘change in scores’ as the result, ‘intervention’ as the major factor and ‘demographics’ as the other components. As there was little room for improvement via the intervention because of the high percentage of participants in the intervention and control groups expressing the desired response to D1 (‘delays in taking vaccines’), we concluded that additional sampling to include the originally envisioned n=800 participants could not change the study’s conclusions with regard to this outcome. Secondary outcomes would similarly be unaffected by additional data collection. We therefore stopped collecting data and analysed the available data sets.Overall, we assessed the binary improvement (improvement vs no improvement) and the amount of improvement in vaccine attitudes and intentions after intervention exposure. The PACV-15 Likert Scales were labelled D4–D13 (10 items), and the responses were transformed from a 1 to 5 scale to a −2 to 2 scale, with −2 representing the least desired option (regardless of whether that was 1 or 5 in the original scale). The more items we included, the more granular the differences we could discern both person-to-person and within a person over time. Additionally, the Likert scale responses were analysed inferentially by coding answers from 1 (strongly disagree) to 5 (strongly agree) and drawing on parametrical (paired t-test) or non-parametrical (Wilcoxon signed rank test) approaches, depending on sample characteristics. Electronic copies of all data were saved offline and external hard drives were stored in a locked cabinet at the Research Institute for Tropical Medicine in the Philippines. All data management and analyses were performed using STATA (Stata Corp, College Station, Texas, USA) and R (R Development Core Team, Vienna, Austria) statistical software. An author reflexivity statement on our partnership is included as
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Patient and public involvement | Patients and the public were not directly involved in the design, conduct, reporting, or dissemination plans for this study. However, the research team consistently gathered participant narratives and feedbacks in accordance with the principles of HCD (for the overall study) and qualitative research, and the findings provided here give voice to these participant experiences. | PMC10603469 | ||
Results | PMC10603469 | |||
Demographic characteristics and participant flow | RECRUITMENT | Between 11 August 2021 and 15 August 2022, 719 participants were surveyed; 396 participants were from urban areas, while 323 were from rural areas (Sociodemographic characteristicsTrial recruitment and retention of participants. | PMC10603469 | |
Intervention showed vaccine confidence score improvements among those who did not trust HCWs | Participants who listed HCWs as among their most trusted sources of vaccine information had baseline average scores that were higher than those who did not (0.15 vs 0.03; t-test, p=0.02) (Caregiver’s attitudes regarding HCWs pre-intervention and post-intervention. HCWs, healthcare workers.We narrowed our analysis to people whose most trusted source of information was someone other than HCWs, as they are an important group to reach with vaccine confidence messaging and they had a significantly different baseline score than others (Caregiver’s who do not list HCWs as their most trusted source of information. HCWs, healthcare workers. | PMC10603469 | ||
Human-centred video boosts positive feelings about vaccines | ’ affective | We assessed participants’ affective responses to the videos both before and after they watched the intervention or control videos (Perception to the intervention and control videos. | PMC10603469 | |
Discussion | INFLUENZA | To the best of our knowledge, this is the first RCT that examined the efficacy of a video-based, HCD-driven intervention improving parental confidence in childhood vaccinations in the Philippines. We found that our HCD-driven intervention, the Salubong animated video, positively impacted caregiver attitudes and confidence toward childhood vaccinations. Our intervention also improved vaccine confidence among participants who previously delayed or refused a vaccine for their children. Our findings reaffirm the value of HCD as a meaning-making approach that influences attitudes and behavioural intent in generalOur results support the use of HCD to boost vaccine confidence along the vaccine hesitancy continuum. A number of research studies have used HCD when developing vaccine confidence interventions with promising results, for example, to design mobile Apps to inform parents about the vaccination status of their children in GermanySome studies also provide evidence of the effectiveness of different types of vaccine confidence interventions and highlight the importance of addressing vaccine confidence as a barrier to vaccine uptake. Prior successful interventions include text message reminders for influenza vaccine uptake in Australia,Our findings also provide concrete evidence of the opportunities of empathic-driven interventions, particularly for low-resource settings combating vaccine losses brought on by controversies.While our findings are generally encouraging, we note limitations. First, confidence and intent to vaccinate do not always translate into actual vaccination uptake. We invite future researchers to implement similar interventions that include actual vaccine uptake as an outcome measure. Second, certain concerns might be associated with this study being conducted online, especially regarding internet connectivity concerns and informed consent processes. However, we developed online data collection and standard operating procedures to allay these operational worries. | PMC10603469 | |
Data availability statement | Data are available upon reasonable request. Data are not publicly available due to the sensitive and personal nature of data and the collected information. Data may be available on request to authors, with restrictions following ethical approval. Please contact the corresponding author. | PMC10603469 | ||
Ethics statements | PMC10603469 | |||
Patient consent for publication | Consent obtained from parent(s)/guardian(s). | PMC10603469 | ||
Ethics approval | This study involves human participants and was approved. Ethical approval was obtained from the Institutional Review Board of the Research Institute for Tropical Medicine (approval no. 2019-44) and the Ethical Commission of Heidelberg University, Faculty of Medicine (approval No. S-833/2019). Participants gave informed consent to participate in the study before taking part. | PMC10603469 | ||
References | PMC10603469 | |||
Subject terms | death, tumor, cancer, UCEC, TCGA, gynecological cancer, Uterine Corpus Endometrial Carcinoma, Cancer | TUMOR, CANCER, MINOR, DYSFUNCTION, SOMATIC MUTATION, CANCER | Disulfidptosis, the demise of cells caused by the abnormal breakdown of disulfide bonds and actin in the cytoprotein backbone, has attracted attention in studies concerning disulfide-related cell death and its potential implications in cancer treatment. This study utilized bioinformatics to detect disulfidptosis associated lncRNA prognostic markers (DALPMs) with Uterine Corpus Endometrial Carcinoma (UCEC)-related to investigate the correlation between these indicators and the tumor immune microenvironment. The RNA sequencing data and somatic mutation information of patients with UCEC were obtained from the Cancer Genome Atlas (TCGA) database. Patients were randomly divided into Train and Test groups. The findings revealed a potential prognostic model comprising 14 DALPMs. Both univariate and multivariate Cox analyses demonstrated that the model-derived risk score functioned as a standalone prognostic indicator for patients. Significant disparities in survival outcomes were observed between the high- and low-risk groups as defined by the model. Differences in tumor mutational burden (TMB), tumor immune dysfunction and exclusion (TIDE), and tumor microenvironment (TME) stromal cells between patients of the high- and low-risk groups were also observed. The forecast model comprising long non-coding RNAs (lncRNAs) associated with disulfidptosis can effectively anticipate patients' prognoses.Uterine Corpus Endometrial Carcinoma (UCEC) is a prevalent gynecological cancer among females, presenting a significant risk to both physical and psychological well-beingAccording to Ingenbleek and KimuraAlthough a considerable amount of RNA is transcribed from the human genome, only a minor proportion is responsible for protein encodingIn this study, we developed a predictive model using lncRNAs associated with disulfidptosis to predict the prognosis of patients with UCEC and performed immune correlation analysis. The findings of our study introduce novel possibilities and concepts for UCEC research. | PMC10721879 |
Materials and methods | PMC10721879 | |||
Collection and collation of data | TCGA, Cancer | CANCER, SOMATIC MUTATIONS | Data on RNA sequencing and somatic mutations of the individuals were obtained from the Cancer Genome Atlas (TCGA) ( | PMC10721879 |
Acquisition of disulfidptosis-associated lncRNA | UCEC | The sequencing data for UCEC patients were obtained using the strawberry Perl (5.30.0.1). Subsequently, the expression data for both lncRNA and disulfide genes in UCEC patients were acquired. We utilized the R package “limma” to conduct correlation tests between the expression data of every lncRNA and the gene expression data of the patients related to disulfidptosis. The filter condition was set as corFilter > 0.3 and | PMC10721879 | |
Establishing a prognostic model of disulfidptosis-associated lncRNA prognostic markers for UCEC | UCEC | Patients were randomly divided into two groups, namely Train and Test, with equal proportions using the R package “caret.” Subsequently, we performed univariate Cox analysis to identify lncRNAs linked to disulfidptosis that exhibited a correlation with the prognosis of UCEC patients ( | PMC10721879 | |
Precision assessment of the model created using DALPMs | The model's verification involved a comprehensive assessment of the risk score determined by the model. Initially, we employed principal component analysis (PCA) with the assistance of the R package ‘scatterplot3d’ to visually represent the distinction between DALPMs and other variables in relation to patients categorized as high and low risks, then employed the R libraries ‘survival’ and “survminer” to determined possible variations in overall survival (OS) and progression-free survival (PFS) among individuals with varying risk scores. Furthermore, the risk score underwent independent prognostic analysis through univariate and multivariate Cox analyses using the R package “survival.” We generated Receiver Operating Characteristic (ROC) curves utilizing the R packages “survival,” “survminer,” and “timeROC” to assess the precision of our risk scores in predicting patient outcomes. For the same objective, the C-index analysis was conducted utilizing the R packages “dplyr,” “survival,” “rms,” and “pec.” | PMC10721879 | ||
Nomogram composition and accuracy detection | To create a nomogram that offers a thorough and precise prognosis for individuals diagnosed with UCEC, we utilized various R packages (“survival,” “regplot,” “rms,” and “survcomp”). This nomogram incorporated all relevant patient clinical factors to accurately predict individual patient survival. We utilized the calibration curve to assess the precision of our developed nomogram. | PMC10721879 | ||
Model prediction of the survival of patients at various clinical stages | UCEC | To assess the accuracy of the model, we determined possible difference of survival status among different risk scores UCEC patients at different clinical stages by plotting survival curves with the help of the R packages “survival” and “survminer.” | PMC10721879 | |
Analysis of GO, KEGG, and GSEA | Using the R package “limma,” we identified differentially expressed genes (DEGs) by comparing patients in the high and low risk groups. The criteria for identifying DEGs were a log2 |fold change|> 1 and a false discovery rate < 0.05. To better understand the biological role and pathway of these DEGs, we employed the R packages “clusterProfiler” and “org.” The packages used are “Hs. eg. Db,” “enrichplot.” We utilized software packages for the execution of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). The gene lists 'c5. go. v7. 4. symbols. gmt' and 'c2. cp. kegg. v7. 4. symbols. gmt' were obtained from the Molecular Signature Database (MsigDB) ( | PMC10721879 | ||
Tumor microenvironment and immune invasion analysis | ’ | INFILTRATION | The stromal score, immune score, and ESTIMATE score of each patient were calculated using the ESTIMATE algorithm with R packages “limma” and “estimate.” We employed the R packages ‘reshape2’ and ‘ggpubr to examine the aforementioned scores among the high and low risk groups. Subsequently, we generated a violin plot to investigate potential disparities among the three patients in the high and low risk groups. Moreover, the examination of immune cell infiltration in each individual was conducted utilizing the R software package called “CIBERSORT,” and the outcomes were presented visually with the aid of the R packages “reshape2” and “ggpubr.” Furthermore, we conducted examination to assess immune-related functions and generated box plots to display the outcomes, utilizing the R packages “limma,” “GSVA,” and “GSEABase.” | PMC10721879 |
Somatic mutation data analysis | tumor | TUMOR, SOMATIC MUTATION | Using PERL, the somatic mutation data of patients were gathered, extracting the data for each patient and calculating the tumor mutational burden (TMB) value. To determine the genes with the highest number of mutations, we used the software package “maftools” to collate the somatic mutation data of patients at high and low risk for UCEC. Next, we presented the survival differences between high and low TMB patients, as well as the survival differences among patients when comprehensively evaluating their TMB and risk scores. | PMC10721879 |
Tumor immune evasion, immunotherapy response, and drug susceptibility analysis | Tumor | IMMUNE DYSFUNCTION, TUMOR | The Tumor Immune Dysfunction and Exclusion (TIDE) scoring file of patients was obtained from the TIDE website, which focuses on TIDE and used to determine possible variation in the response to immune checkpoint blocking among patients in both groups, using the software package “ggpubr.”We performed a drug susceptibility analysis to assess the difference in drug susceptibility between patients in high and low risk groups. The evaluation criterion was the IC50 value, representing the semi-inhibitory concentration of the drug being tested. Lower IC50 measurement indicates better drug sensitivity. For this analysis, we employed the R package “pRRophetic.” | PMC10721879 |
Statistical analysis | Statistical analyses were conducted utilizing R software (version 4.2.1), considering | PMC10721879 | ||
Results | PMC10721879 | |||
Acquisition of disulfidptosis gene co-expression lncRNA | disulfidptosis death | A total of 16,877 lncRNAs were extracted from the TCGA-UCEC RNA-seq sequencing data. Co-expression of these 10 disulfidptosis genes with lncRNAs showed 1,136 lncRNAs associated with disulfidptosis death, with a significant correlation (|Pearson R|> 0.3 and Acquisition of disulfidptosis gene co-expression lncRNA. ( | PMC10721879 | |
Establishment of the DALPM model | A total of 543 patients were divided into two groups: Train (n = 272) and Test (n = 271). The validation results for clinical grouping indicated that our grouping was justified, and there were no disparities between the two groups in terms of diverse clinical factors (Table Clinical grouping validation for the train and test groups.The Train group was subsequently utilized for constructing the model, while the Test group and all patients were employed for testing. Initially, we conducted univariate Cox analysis on 1,136 lncRNAs associated with disulfidptosis identified through co-expression analysis. A total of 53 prognostically relevant genes were identified (Fig. Establishment of the DALPM model. (Distribution of survival status and DALPMs in patients with elevated risk scores. ( | PMC10721879 | ||
Validation of model accuracy | We examined the accuracy of the prognostic model created by DALPMs. PCA analysis (Fig. PCA analysis of all patients. (Validation of the accuracy of the model from multiple perspectives. ( | PMC10721879 | ||
Construction of the nomogram | UCEC | A comprehensive score was calculated for every patient, considering factors such as age, grade, stage, and risk score. Next, we created a corresponding nomogram to precisely forecast the 1-, 3-, and 5-year outlook for every individual (Fig. Construction of the nomogram and exploration of the correlation between risk scores and the clinical stage of UCEC. ( | PMC10721879 | |
The correlation between risk scores and the clinical stage of UCEC | To further investigate the practicality of DALPMs, we examined their use in forecasting risks in various clinical phases. The results from the KM curve showed a notable variation in survival rates among patients with varying risk scores in clinical stages I-II and III-IV (Fig. | PMC10721879 | ||
Results from the analysis of GO, KEGG, and GSEA | A total of 512 DEGs were extracted from patients in the high- and low-risk groups. The findings from the analysis of GO enrichment indicated that the primary biological processes (BPs) enriched by DEGs included microtubule-dependent motion, organization of cilia, and ciliary motion. The primary cellular components (CCs) were motile cilia, cytoplasmic area, and cytoplasmic extensions bounded by the plasma membrane. Additionally, the main molecular functions (MFs) identified were binding to tubulin, as peptidase inhibitors, and functioning as a cytoskeletal motor (Fig. The results of GO, KEGG, GSEA, TME, immune invasion TMB, and TIDE analyses. ( | PMC10721879 | ||
Tumor microenvironment and immune invasion analysis | tumor | TUMOR | To examine variations in tumor microenvironment (TME) between the high- and low-risk groups, we computed the TME score for every individual. Figure | PMC10721879 |
TMB analysis | TTN, TP53 | SOMATIC MUTATION | Using somatic mutation data, the connection between TMB and the risk score was established. According to the waterfall chart, the low-risk group exhibited a higher gene mutation rate compared with the high risk group. Moreover, the PTEN, PIK3CA, ARID1A, TTN, TP53, PIK3R1, KMT2D, CTNNB1, MUC16, and CTCF genes were identified as the top 10 genes with the greatest likelihood of mutation in both high- and low-risk groups. Notably, PTEN, PIK3CA, and ARID1A exhibited the highest mutation probabilities, as shown in F | PMC10721879 |
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