bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increased Risk for Type 2 Diabetes in Relation to Adiposity in Middle-Aged Black South African Men compared to Women
Authors: Kufe Clement N. , Micklesfield Lisa K. , Masemola Maphoko , Chikowore Tinashe , Kengne Andre Pascal , Karpe Fredrik , Norris Shane A. , Crowther Nigel J. , Olsson Tommy , Goedecke Julia H. 
Published: October 2021

AbstractAimsDespite a higher prevalence of overweight/obesity in black South African women compared to men, the prevalence of type 2 diabetes does not differ. We explored if this could be due to sex differences in insulin sensitivity, clearance and/or beta-cell function, and also sex-specific associations with total and regional adiposity.MethodsThis cross-sectional study included 804 black South African men (n=388) and women (n=416). Dual-energy x-ray absorptiometry was used to measure total and regional adiposity. Insulin sensitivity (Matsuda index), secretion (C-peptide index) and clearance (C-peptide/insulin ratio) were estimated from an oral glucose tolerance test.ResultsAfter adjusting for sex differences in fat mass index, men were less insulin sensitive and had lower beta cell function than women (p<0.001), with the strength of the associations with measures of total and central adiposity being greater in men than women (p<0.001 for interactions). Further, the association between total adiposity and type 2 diabetes risk was also greater in men than women (relative risk ratio (95% confidence interval): 2.05 (1.42– 2.96), p<0.001 vs. 1.38 (1.03–1.85), p=0.031).ConclusionWith increasing adiposity, particularly increased centralisation of body fat linked to decreased insulin sensitivity and beta cell function, black African men are at greater risk for type 2 diabetes than their female counterparts.
Intimate partner violence and unmet need for family planning among currently married Afghan women aged 18-49 years: findings from a nationally representative survey in Afghanistan
Authors: Dadras Omid , Nakayama Takeo , Kihara Masahiro , Ono-Kihara Masako , Thanapop Chamnong , Thirarattanasunthon Phiman , Jandee Kasemsak 
Published: October 2021

AbstractBackgroundIntimate Partner Violence (IPV) is a serious public health issue, particularly in poor-resourced countries. It has been linked to a range of adverse health outcomes. In this study, we explored the prevalence and the relationship between the IPV and unmet need for family planning and identified the associated sociodemographic factors among a nationally representative sample of married Afghan women aged 18-49 years in Afghanistan.MethodsThis study used the data from Afghanistan Demographic and Health Survey (DHS) conducted in 2015. The data for IPV, unmet need for family planning, and sociodemographic characteristics of Afghan women aged 18-24 were extracted from the available databases. Sampling weights and survey design were accounted for in bivariate and multivariate analyses using the STATA software version 14. The significant alpha level was determined at p-value < .05ResultsMore than half of the study population, with a prevalence of 55.89%, experienced some types of intimate partner violence during the last 12 months. Unmet need for family planning was documented in less than a third of the population. Illiterate employed women from poorer families who were living in the rural areas were more likely to suffer from any type of IPV. Moreover, those from Pashtun (OR = 2.12, 95% CI:1.30-3.45), Tajik (OR = 1.69, 95% CI:1.06-2.71), and Pashai (OR = 2.23, 95% CI:1.17-4.26) ethnic groups had a higher chance of being a victim of any type of violence compared to the reference group (Turkmen). Illiterate women (OR = 1.37, 95% CI:1.02-1.83) with more than 5 pregnancy experiences (OR = 1.44, 95% CI: 1.19-1.74) had more unmet needs for family planning compared to the reference group. The unmet needs were almost 40% and 30% less likely to be observed among women from Pashtun and Tajik ethnic backgrounds compared to the reference group (Turkmen), respectively. The likelihood of having unmet needs was 30% less in those women who suffered from any type of violence.ConclusionIPV is an important predictor of several adverse health outcomes. The findings of present study portray the disastrous situation of Afghan women right violation and violence against them in a conflict setting in one the poor-resourced countries in the world and communicate an important message to the international communities and human right advocate to take immediate actions to mitigate the current situation and prevent the violence against Afghan women to improve the integrity of their reproductive health.
Analyzing human knockouts to validate GPR151 as a therapeutic target for reduction of body mass index
Authors: Gurtan Allan , Dominy John , Khalid Shareef , Vong Linh , Caplan Shari , Currie Treeve , Richards Sean , Lamarche Lindsey , Denning Daniel , Shpektor Diana , Gurinovich Anastasia , Rasheed Asif , Hameed Shahid , Saeed Subhan , Saleem Imran , Jalal Anjum , Abbas Shahid , Sultana Raffat , Rasheed Syed Zahed , Memon Fazal-ur-Rehman , Shah Nabi , Ishaq Mohammad , Khera Amit , Danesh John , Kathiresan Sekar , Frossard Philippe , Saleheen Danish 
Published: October 2021

AbstractNovel drug targets for sustained reduction in body mass index (BMI) are needed to curb the epidemic of obesity, which affects 650 million individuals worldwide and is a causal driver of cardiovascular and metabolic disease and mortality. Previous studies reported that the Arg95Ter nonsense variant of GPR151, an orphan G protein-coupled receptor, is associated with reduced BMI and reduced risk of Type 2 Diabetes (T2D). Here, we follow up on GPR151 with the Pakistan Genome Resource (PGR), which is one of the largest exome biobanks of human homozygous loss-of-function carriers (knockouts) in the world. Among PGR participants, we identify 3 GPR151 putative loss-of-function (plof) variants (Arg95Ter, Tyr99Ter, and Phe175LeufsTer7) with a cumulative allele frequency of 2.2% and present at homozygosity. We confirm these alleles in vitro as loss-of-function. We test if GPR151 plof is associated with BMI, T2D, or other metabolic traits. GPR151 deficiency in complete human knockouts is not associated with a clinically significant difference in BMI. Moreover, loss of GPR151 confers a nominally significant increase in risk of T2D (odds ratio = 1.2, p value = 0.03). Relative to wild-type mice, Gpr151-/- animals exhibit no difference in body weight on normal chow, and higher body weight on a high-fat diet, consistent with the findings in humans. Together, our findings indicate that GPR151 antagonism is not a compelling therapeutic approach for obesity.
Omega-3 Index is Directly Associated with a Healthy Red Blood Cell Distribution Width
Authors: McBurney Michael I. , Tintle Nathan L. , Harris William S. 
Published: October 2021

SummaryLow red blood cell (RBC) membrane content of EPA and DHA, i.e., the omega-3 index (O3I), and elevated RBC distribution width (RDW) are risk factors for all-cause mortality. O3I and RDW are related with membrane fluidity and deformability. Our objective was to determine if there is a relationship between O3I and RDW in healthy adults. Subjects without inflammation or anemia, and with values for O3I, RDW, high-sensitivity C-reactive protein (CRP), body mass index (BMI), age and sex were identified (n=25,485) from a clinical laboratory dataset of >45,000 individuals. RDW was inversely associated with O3I in both sexes before and after (both p<0.00001) adjusting models for sex, age, BMI and CRP. Stratification by sex revealed a sex-O3I interaction with the RDW-O3I slope (p<0.00066) being especially steep in females with O3I ≤5.6%. In healthy adults of both sexes, the data suggested that an O3I of >5.6% may help maintain normal RBC structural and functional integrity.
Assessing the potential impact of immunity waning on the dynamics of COVID-19: an endemic model of COVID-19
Authors: Rabiu Musa , Iyaniwura Sarafa A. 
Published: October 2021

AbstractWe developed an endemic model of COVID-19 to assess the impact of vaccination and immunity waning on the dynamics of the disease. Our model exhibits the phenomenon of back-ward bifurcation and bi-stability, where a stable disease-free equilibrium co-exists with a stable endemic equilibrium. The epidemiological implication of this is that the control reproduction number being less than unity is no longer sufficient to guarantee disease eradication. We showed that this phenomenon could be eliminated by either increasing the vaccine efficacy or by reducing the disease transmission rate (adhering to non-pharmaceutical interventions). Furthermore, we numerically investigated the impacts of vaccination and waning of both vaccine-induced immunity and post-recovery immunity on the disease dynamics. Our simulation results show that the waning of vaccine-induced immunity has more effect on the disease dynamics relative to post-recovery immunity waning, and suggests that more emphasis should be on reducing the waning of vaccine-induced immunity to eradicate COVID-19.
Plasma metabolomics profiling and machining learning-driven prediction of nonalcoholic steatohepatitis
Authors: Ji Moongi , Jo Yunju , Choi Seung Joon , Kim Seong Min , Kim Kyoung Kon , Oh Byung-Chul , Ryu Dongryeol , Paik Man-Jeong , Lee Dae Ho 
Published: October 2021

AbstractRationaleWe performed targeted metabolomics with machine learning (ML)-based interpretation to identify metabolites that distinguish the progression of nonalcoholic fatty liver disease (NAFLD) in a cohort.MethodsWe conducted plasma metabolomics analysis in healthy control subjects (n=25) and patients with NAFL (n=42) and nonalcoholic steatohepatitis (NASH, n=19) by gas chromatography-tandem mass spectrometry (MS/MS) and liquid chromatography-MS/MS as well as RNA sequencing (RNA-seq) analyses on liver tissues from patients with varying stages of NAFLD (n=12). The resulting metabolomic data were subjected to routine statistical and ML-based analyses and multiomics interpretation with RNA-seq data.ResultsWe found six metabolites that were significantly altered in NAFLD among 79 detected metabolites. Random-forest and multinomial logistic regression analyses showed that eight metabolites (glutamic acid, cis-aconitic acid, aspartic acid, isocitric acid, α-ketoglutaric acid, oxaloacetic acid, myristoleic acid, and tyrosine) could distinguish the three groups. Then, the recursive partitioning and regression tree algorithm selected three metabolites (glutamic acid, isocitric acid, and aspartic acid) from these eight metabolites. With these three metabolites, we formulated an equation, the MetaNASH score that distinguished NASH with excellent performance. Finally, metabolic map construction and correlation assays integrating metabolomics data into the transcriptome datasets of the liver showed correlations between the concentration of plasma metabolites and the expression of enzymes governing metabolism and specific alterations of these correlations in NASH.ConclusionsWe found several metabolites that distinguish NASH from non-NASH via metabolomics analysis and ML approaches, developed the MetaNASH score, and suggested the pathophysiologic implications of metabolite profiles in relation to NAFLD progression.Graphical Abstract
Vaccine hesitancy for coronavirus SARS-CoV-2 in North India
Authors: Srivastava Utkarsh , Tripathi Avanish Kumar , Kaur Jagjeet , Devi Sabita , Verma Shipra , Singh Vanya , Das Debashruti , Singh Prajjval Pratap , Kumar Pradeep , Rai Vandana , Pandey Rakesh , Chaubey Gyaneshwer 
Published: October 2021

ABSTRACTWith the roll-out of world’s largest vaccine drive for Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) by Government of India on January 16 2021, India has targeted to vaccinate its entire population by the end of year 2021. Struggling with vaccine procurement and production earlier, India came up with these hurdles but the Indian population still did not seem to be mobilizing swiftly towards vaccination centers. With the initial hesitancy, as soon as the vaccination started to speedup, India was hit severely by the second wave. The severe second wave has slowed down the vaccination pace and also it was one of the major contributing factor of vaccine hesitancy. To understand the nature of vaccine hesitancy and factors underlying it, we conducted an extensive online and offline surveys in Varanasi and adjoining regions using structured questions. Majority of respondents though were students (0.633), respondents from other occupations such as government officials (0.10) were also included in the study. We observed several intriguing opinions on our eleven questions. It is interesting to note that the majority of the people (0.75) relied on fake news and did not take COVID-19 seriously. Most importantly, we noticed that a substantial proportion of respondents (relative frequency 0.151; mean age 24.8 years) reported that they are still not interested in vaccination. People who have neither been vaccinated nor have ever been infected may become the medium for spreading the virus and creating new variants. This could also lead to a resistant variant of the vaccine in the future. We expect that this extensive survey may help the government to upgrade their vaccination policies for COVID-19 in North India.
Integrating melt-electrowriting and inkjet bioprinting for engineering structurally organized articular cartilage
Authors: Dufour A. , Barceló Gallostra X. , O’Keeffe C. , Eichholz K. , Von Euw S. , Garcia O. , Kelly D. J. 
Published: October 2021

ABSTRACTSuccessful cartilage engineering requires the generation of biological grafts mimicking the structure, composition and mechanical behaviour of the native tissue. Here melt-electrowriting (MEW) was used to produce arrays of polymeric structures whose function was to orient the growth of cellular aggregates spontaneously generated within these structures, and to provide tensile reinforcement to the resulting tissues. Inkjeting was used to deposit defined numbers of cells into MEW structures, which self-assembled into an organized array of spheroids within hours, ultimately generating a hybrid tissue that was hyaline-like in composition. Structurally, the engineered cartilage mimicked the histotypical organization observed in skeletally immature synovial joints. This biofabrication framework was then used to generate scaled-up (50mm × 50mm) cartilage implants containing over 3,500 cellular aggregates in under 15 minutes. After 8 weeks in culture, a 50-fold increase in the compressive properties of these MEW reinforced tissues were observed, while the tensile properties were still dominated by the polymer network, resulting in a composite construct demonstrating tension-compression nonlinearity mimetic of the native tissue. Helium ion microscopy further demonstrated the development of an arcading collagen network within the engineered tissue. This hybrid bioprinting strategy provides a versatile and scalable approach to engineer cartilage biomimetic grafts for biological joint resurfacing.
Ongoing use of SSRIs and the hospital course of COVID-19 patients: a retrospective outcome analysis
Authors: Rauchman Steven H. , Mendelson Sherri G. , Rauchman Courtney , Kasselman Lora J. , Pinkhasov Aaron , Reiss Allison B. 
Published: October 2021

AbstractBackgroundThe SARS-CoV2 virus continues to have devastating consequences worldwide. Though vaccinations have helped to reduce the impact of the virus, new strains still pose a threat to unvaccinated, and to a lesser extent vaccinated, individuals. Therefore, it is imperative to identify treatments that can prevent the development of severe COVID-19. Recently, acute use of SSRI antidepressants in COVID+ patients has been shown to reduce the severity of symptoms compared to placebo. Since SSRIs are a widely used anti-depressant, the aim of this study was to determine if COVID+ patients already on SSRI treatment upon admission to the hospital had reduced mortality compared to COVID+ patients not on chronic SSRI treatment.MethodsA retrospective observational study design was used. Electronic medical records of 9,043 patients with a laboratory-confirmed diagnosis of Covid-19 from 03/2020 to 03/2021from six hospitals were queried for demographic and clinical information. Using R, a logistic regression model was run with mortality as the outcome and SSRI status as the exposure. An adjusted logistic regression model was run to account for age category, gender, and race. All tests were considered significant at p of 0.05 or less.ResultsIn this sample, no patients admitted on SSRIs had them discontinued. This is consistent with current recommendations. There was no significant difference in the odds of dying between COVID+ patients on chronic SSRIs vs COVID+ patients not taking SSRIs, after controlling for age category, gender, and race. The odds of COVID+ patients on SSRIs dying was 0.98 (95%CI: 0.81, 1.18) compared to COVID+ patients not on SSRIs (p=0.83).ConclusionIn times of pandemics due to novel infectious agents it is difficult, but critical to evaluate safety and efficacy of drugs that might be repurposed for treatment. This large sample size of 9,043 patients suggests that there will be no significant benefit to use of SSRIs to decrease mortality rates for hospitalized patients with Covid-19 who are not currently on SSRI medications. This study shows the utility of large clinical databases in addressing the urgent issue of determining what commonly prescribed drugs might be useful in treating COVID-19.
ProS-GNN: Predicting effects of mutations on protein stability using graph neural networks
Authors: Wang Shuyu , Tang Hongzhou , Shan Peng , Zuo Lei 
Published: October 2021

AbstractMotivationPredicting protein stability change upon variation through computational approach is a valuable tool to unveil the mechanisms of mutation-induced drug failure and help to develop immunotherapy strategies. However, some machine learning based methods tend to be overfitting on the training data or show anti-symmetric biases between direct and reverse mutations. Moreover, this field requires the methods to fully exploit the limited experimental data.ResultsHere we pioneered a deep graph neural network based method for predicting protein stability change upon mutation. After mutant part data extraction, the model encoded the molecular structure-property relationships using message passing and incorporated raw atom coordinates to enable spatial insights into the molecular systems. We trained the model using the S2648 and S3412 datasets, and tested on the Ssym and Myoglobin datasets. Compared to existing methods, our proposed method showed competitive high performance in data generalization and bias suppression with ultra-low time consumption. Furthermore, method was applied to predict the Pyrazinamide’s Gibbs free energy change for a real case study.Availabilityhttps://github.com/shuyu-wang/ProS-GNN.Contactvincentwang622@126.com
Optimization of growth and electrosynthesis of PolyHydroxyAlcanoates by the thermophilic bacterium Kyrpidia spormannii
Authors: Pillot Guillaume , Sunny Soniya , Comes Victoria , Kerzenmacher Sven 
Published: October 2021

ABSTRACTThe electrosynthesis of valuable compounds by biofilms on electrodes is being intensively studied since few years. However, so far, the actual biofilms growing on cathodes produce mainly small and relatively inexpensive compounds such as acetate or ethanol. Recently, a novel Knallgas bacterium, Kyrpidia spormannii EA-1 has been described to grow on cathodes under thermophilic and microaerophilic conditions, producing significant amounts of PolyHydroxyAlkanoates (PHAs). These PHA are promising sustainable bioplastic polymers with the potential to replace petroleum-derived plastics in a variety of applications. However, the effect of culture conditions and electrode properties on the growth of K. spormannii EA-1 biofilms and PHA production is still unclear.In this study, we report on the optimization of growth and PHA production in liquid culture and on the cathode of a Microbial Electrosynthesis System. Optimization of the preculture allows to obtain high cell density of up to 8.5 Log10 cells·ml-1 in 48h, decreasing the time necessary by a factor of 2.5. With respect to cathodic biofilm formation, this study was focused on the optimization of three main operating parameters, which are the applied cathode potential, buffer pH, and the oxygen concentration in the feed gas. Maximum biofilm formation and PHA production was observed at an applied potential of −844mV vs. SCE, pH 6.5, O2 saturation of 2.5%. The PHA concentration in the biofilm reached a maximum of ≈26.8 μg·cm-2 after optimization, but at 2.9% the coulombic efficiency remains relatively low. We expect that further nutrient limitation will allow the accumulation of more PHA, based on a dense biofilm growth. In conclusion, these findings take microbial electrosynthesis of PHA a step forward towards practical implementation.
Hi-C Resolution Enhancement with Genome Sequence Data
Authors: Kriukov Dmitrii , Zaretckii Mark , Kozlovskii Igor , Zybin Mikhail , Koritskiy Nikita , Bazarevich Mariia , Khrameeva Ekaterina 
Published: October 2021

AbstractThe increasing interest in chromatin conformation inside the nucleus and the availability of genome-wide experimental data make it possible to develop computational methods that can increase the quality of the data and thus overcome the limitations of high experimental costs. Here we develop a deep-learning approach for increasing Hi-C data resolution by appending additional information about genome sequence. In this approach, we utilize two different deep-learning algorithms: the image-to-image model, which enhances Hi-C resolution by itself, and the sequence-to-image model, which uses additional information about the underlying genome sequence for further resolution improvement. Both models are combined with the simple head model that provides a more accurate enhancement of initial low-resolution Hi-C data. The code is freely available in a GitHub repository: https://github.com/koritsky/DL2021_HI-C.
Domestic pigs experimentally infected with Mycobacterium bovis and Mycobacterium tuberculosis exhibit different disease outcomes
Authors: Niroula Nirajan , Lim Ze Long , Walker Stewart , Huang Yanyun , Gerdts Volker , Zriba Slim , Drever Kylee , Chen Jeffrey M. 
Published: October 2021

AbstractDomestic pigs share many similarities with humans in their pulmonary anatomy, physiology, and immunology. Accordingly, pigs have been shown to be valuable models to study human tuberculosis (TB). Here we examined the outcome of disease in domestic pigs challenged via two different routes with either the human-adapted TB bacillus Mycobacterium tuberculosis or the zoonotic bovine TB bacillus M. bovis in head-to-head comparisons. We found that pigs challenged intravenously with M. bovis AF2122/97 exhibited severe morbidity and rapid onset of mortality, accompanied by higher tissue bacterial burden and necrosis compared to pigs challenged similarly with M. tb Erdman. Concordantly, pigs challenged with aerosolized M. bovis AF2122/97 exhibited reduced weight gain and more severe pathology than pigs challenged similarly with M. tb Erdman. Moreover, pigs aerosol-challenged with M. bovis AF2122/97 exhibited a spectrum of granulomatous lesions ranging from small well-contained granulomas to caseous-necrotic lesions mimicking active TB disease in humans. In contrast, pigs aerosol-challenged with M. tb Erdman exhibited arrested granuloma development. Irrespective of challenge dose and pathological outcome however, peripheral IFN-γ responses were similar in both M. bovis AF2122/97 and M. tb Erdman challenged pigs. This study demonstrates domestic pigs can support infections with M. bovis and M. tb and develop pathology similar to what is observed in humans. And although M. bovis AF2122/97 appears to be more virulent than M. tb Erdman, both strains can be used to model TB in domestic pigs, depending on whether one wishes to recapitulate either acute and active TB or latent TB infections.