bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence and determinants of central obesity among adults 18–69 years in Kenya: a cross-sectional study
Authors: Nyakundi Caleb , Okemwa Sharonmercy , Ngesa Romeo Warera , Gatimu Samwel Maina 
Published: September 2024

AbstractBackgroundCentral obesity affects about 4 out of every 10 people globally, and it is a notable public health concern linked with premature morbidity and mortality. In Kenya, regional studies have approximated the prevalence to range from 37% to 50%. However, these studies have been done in specific regions or population groups, such as among urban residents or women. Therefore, we aimed to assess the general and sex-specific prevalence and determinants of central obesity among adults in Kenya.MethodsAn analysis of the prevalence and determinants of central obesity was assessed using data from the 2015 Kenya STEPwise survey on non-communicable diseases and injuries. We included a final sample of 4 003 participants. Participants’ characteristics and prevalence of central obesity were described and summarized using frequencies and percentages. The bivariate and multivariate logistic regression were used to assess the determinants of central obesity.ResultsThe overall weighted prevalence of central obesity was 46.7% [95% confidence interval (CI): 43.2, 50.3], with women exhibiting a significantly higher prevalence compared to men (58.3% vs. 35.6%, p=0.001). Sex, age, household wealth index, and smoking were among the factors significantly associated with central obesity. Men had 66% lower odds of central obesity compared to women, while the risk increased with age, ranging from 1.6 to 4 times higher odds among those aged 30—39 and 50—69 years, respectively, compared to 18—29–year–olds. Other predictors of central obesity were wealthier households and non-smoking.ConclusionAbout half of the adult Kenyan population is centrally obese, with a higher prevalence among women than men. Kenya’s policymakers should consider targeting high-risk groups in this population to reduce the burden of central obesity.
A mapping review of good practices of participatory research for an impactful collaboration in disabilities studies
Authors: Corcuff Maëlle , Jribi Rania , Rodrigue Guillaume , Lamontagne Marie-Eve , Raymond Émilie , Archambault Philippe S. , Routhier François 
Published: September 2024

AbstractIntroductionParticipatory research is particularly relevant to understanding the challenges faced by people with disabilities (PWDs), as it actively involves them as partners, enabling methodologies to be better adapted to lived realities and producing more relevant and applicable results. By reducing systemic barriers and promoting inclusion, this approach improves understanding and consideration of the specific needs of PWDs in research. Yet, studies have identified hurdles associated with this approach, prompting questions about how organizations portray PWDs, the dynamics among research stakeholders, the distribution of decision-making power, and the actual impact of research on its partners.AimThis study aims to identify the factors that influence the process and results of participatory research in the field of disability studiesMethodsWe conducted a mapping review following the PRISMA-ScR guidelines, and analysis the results according to the input-throughput-outcomes Bergen modelResultsThis study identifies partners skills and training, power sharing and benefits of active involvement as facilitators of participatory research. On the other hand, contextual challenges, and lack of guidance are reported as obstacles.ConclusionThis study provides insight into how the various facilitators and obstacles to participatory research and its different processes interact to produce positive, valid and rigorous results.
Development of Machine Learning Algorithms Using EEG Data to Detect the Presence of Chronic Pain
Authors: Miller Jonathan , Jacobs Skylar , Koppes William , Minella Frank , Porta Federica , White Fletcher A. , Lovelace Joseph A. 
Published: September 2024

AbstractChronic pain impacts more than one in five adults in the United States (US) and the costs associated with the condition amount to hundreds of billions of dollars annually. Despite the tremendous impact of chronic pain in the US and worldwide, the standard of care for diagnosis depends on subjective self-reporting of pain state, with no effective objective assessment procedure available. This study investigated the application of signal processing and machine learning to electroencephalography (EEG) data for the development of classification algorithms capable of differentiating subjects in pain from pain free subjects. In this study, nineteen (19) channels of EEG data were obtained from subjects in an eyes closed resting state, and ultimately data from 186 participants were used for algorithm development, including 35 healthy controls and 151 chronic pain patients. Signal processing was applied to identify noise free segments of EEG data and 6375 quantitative EEG (qEEG) measures were calculated for each subject. Various machine learning methodologies were applied to the data, with Elastic Net chosen as the optimal methodology. The final classifier developed using Elastic Net contained 34 qEEG features with non-zero weights. The classifier was able to differentiate pain versus no pain subjects with an accuracy of 79.6%, sensitivity of 82.2%, and specificity of 66.7%. The features used in the classifier were evaluated and found to align well with contemporary literature regarding changes in neurological characteristics associated with chronic pain.
Interactive effects of bacterial vaginal colonization and HIV on pregnancy outcomes: A Systematic Review and Meta-analysis
Authors: Matovelo Dismas , Goddard Quinn , Sabuni Paul , Kidenya Benson , Downs Jennifer , Magoma Moke , Seni Jeremiah , Chaput Kathleen Helen 
Published: September 2024

AbstractBackgroundThe independent impact of HIV and bacterial vaginal colonization on pregnancy outcomes has been documented and is compounded by the burden of rapidly escalating antimicrobial resistance. However, the interactive effect of HIV and lower genital tract bacterial colonization, on pregnancy outcomes has not been thoroughly studied and is examined in our study.MethodsWe performed a systematic review and meta-analysis to quantitatively assess the interaction between HIV and vaginal bacterial colonization and associations with birth weight and preterm birth. We searched Ovid MEDLINE, Ovid EMBASE, CINAHL, Scopus, Web of Science, Cochrane Library, African Journals Online, and PubMed databases to identify studies published up to December 31, 2023. We included observational reporting on vaginal colonization with bacterial pathogens stratified by HIV status that reported pregnancy outcomes. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and used a modified Newcastle-Ottawa Scale to assess study quality. Meta-analysis was conducted using random-effects modeling in STATA Version 18. Pooled log-odds ratios were calculated. The study protocol was registered in PROSPERO(CRD42023485123).ResultsWe selected 13 studies, involving 6,073 pregnant women, from 5,807 studies identified. The overall pooled prevalence of bacterial colonization was 26%(95%CI:17.3-37.4). There was no significant effect of HIV status and vaginal colonization on birth weight(OR=1.2, 95%CI:-2.57-2.20,p=0.88) and borderline increased odds of preterm birth (OR=2.64, 95%CI:-0.01-1.94,p=0.05). There was no significant association between HIV status and bacterial colonization(OR=1.08, 95%CI =-0.91-1.07), nor in antimicrobial resistance between pregnant women with HIV and those without.ConclusionBacterial colonization is prevalent among pregnant women, but there is no clear evidence to suggest that HIV and bacterial colonization interact to affect birth weight or preterm birth. Research with large sample sizes, strict selection criteria, reliable and valid measurement, adequate control for confounding variables, and birthweight and gestational age at delivery assessment as continuous outcomes are still needed to provide robust evidence.
A Minimal PBPK Model Describes the Differential Disposition of Silica Nanoparticles In Vivo
Authors: Parrot Madison , Cave Joseph , Pelaez Maria J , Ghandehari Hamidreza , Dogra Prashant , Yellepeddi Venkata 
Published: September 2024

AbstractNanoparticles (NPs) have emerged as promising candidates for drug delivery due to their tunable physical and chemical properties. Among these, silica nanoparticles (SiNPs) are particularly valued for their biocompatibility and adaptability in applications like drug delivery and medical imaging. However, predicting SiNP biodistribution and clearance remains a significant challenge. To address this, we developed a minimal physiologically-based pharmacokinetic (mPBPK) model to simulate the systemic disposition of SiNPs, calibrated using in vivo PK data from mice. The model assesses how variations in surface charge, size, porosity, and geometry influence SiNP biodistribution across key organs, including the kidneys, lungs, liver, and spleen. A global sensitivity analysis identified the most influential parameters, with the unbound fraction and elimination rate constants for the kidneys and MPS emerging as critical determinants of SiNP clearance. Non-compartmental analysis (NCA) further revealed that aminated SiNPs exhibit high accumulation in the liver, spleen, and kidneys, while mesoporous SiNPs primarily accumulate in the lungs. Rod-shaped SiNPs showed faster clearance compared to spherical NPs. The mPBPK model was extrapolated to predict SiNP behavior in humans, yielding strong predictive accuracy with Pearson correlation coefficients of 0.98 for mice and 0.92 for humans. This model provides a robust framework for predicting the pharmacokinetics of diverse SiNPs, offering valuable insights for optimizing NP-based drug delivery systems and guiding the translation of these therapies from preclinical models to human applications.
What are the best practices for curating eDNA custom barcode reference libraries? A case study using Australian subterranean fauna
Authors: Guzik Michelle T. , Stringer Danielle N. , Thornhill Jake , Coates Peterson J. , van der Heyde Mieke , Hillyer Mia J. , White Nicole E , Saccò Mattia , Beasley-Hall Perry , Humphreys William F. , Harvey Mark S. , Huey Joel A. , Wilson Nerida G. , Alexander Jason , Humphreys Garth , King Rachael A. , Cooper Steve J. B. , Pinder Adrian , Perina Giulia , Nevill Paul , Austin Andy D. 
Published: September 2024

AbstractIdentification of species for environmental assessment and monitoring is essential for understanding anthropogenic impacts on biodiversity, but for subterranean fauna this task is frequently difficult and time consuming. The implementation of environmental DNA (eDNA) metabarcoding for biodiversity discovery and assessment offers considerable promise for improving the rate, accuracy and efficiency of species detection in ecosystems both above and below the ground. Importantly, for a better understanding of the biodiversity and ecology of organisms detected using eDNA, a custom library of known reference sequences with associated correct taxonomic metadata—i.e., a barcode reference library (BRL)—is required. Yet, minimal guidance is currently available on how an effective (i.e. shareable, multi-sequence, that permits metadata and has a unified nomenclature) and accurate (i.e. verified) custom BRL can be achieved. Here, we present a detailed roadmap for curation of a BRL for subterranean fauna. To do this, we (1) curated a custom sequence database of subterranean fauna at an environmentally sensitive location, Bungaroo Creek in the Pilbara region of Western Australia, for four gene loci useful for eDNA metabarcoding (COI,18SrRNA,12SrRNA and16SrRNA); (2) addressed major gaps in taxonomy and disparate nomenclature of subterranean fauna by estimating 17–29 putative new species with standard delimitation methods, including 34 Barcode Index Numbers (BINs) in BOLD, and (3) summarised a best practice workflow for curation of a custom BRL that has broad applicability and can be applied to any taxa.Scientific Significance StatementIn threatened ecosystems, environmental DNA (eDNA) metabarcoding for biodiversity discovery and assessment offers considerable promise for improvement in the rate, efficiency and accuracy of species detection. For a better understanding of the biodiversity and ecology of organisms detected using eDNA, a custom library of known reference sequences with associated correct taxonomic metadata is required. Minimal guidance is currently available on how an effective (i.e. shareable, multi-sequence, permits metadata and provides a unified nomenclature) custom barcode reference library (BRL) can be achieved for subterranean fauna. Here, we present a road map for sound and reliable curation of a BRL using subterranean fauna from Australia as a case study.
Chromatin folding motifs define the basic grammar of TAD architecture in single alleles
Authors: Messina Olivier , Fiche Jean-Bernard , Youhanna Christel Elkhoury , Ganesh Gautham , Kemkem Yasmine , Mesnager Alexandre , Akerman Ildem , Hodson David J. , Schaeffer Marie , Nollmann Marcelo 
Published: September 2024

AbstractChromatin structure varies dramatically among single cells, yet the specific motifs underpinning this organization remain poorly understood. Using imaging-based spatial genomics, we visualized 3D chromatin organization across seven mouse tissues. We demonstrate that single chromatin traces can be decomposed into loop and domain Chromatin Folding Motifs (CFMs). Polymer simulations revealed that loop-extrusion reproduces loop CFMs, while cis-regulatory interactions are primarily responsible for domain CFMs. Notably, a unique set of CFMs describes single-cell chromatin architecture across multiple cell types, underscoring the universality of CFMs in organizing chromatin. In the pancreas, cells with different transcriptional programs exhibited distinct CFM usage, highlighting the functional relevance of CFMs. Perturbation of transcription and CTCF levels in a type 2 diabetes model altered CFM usage, demonstrating that disease induction affects both architectural and cis-regulatory interactions. Our results uncover how chromatin is organized in single cells and reveal the alterations that occur during disease.
A general substitution matrix for structural phylogenetics
Authors: Garg Sriram G , Hochberg Georg KA 
Published: September 2024

AbstractSequence-based maximum likelihood (ML) phylogenetics is a widely used method for inferring evolutionary relationships, which has illuminated the evolutionary histories of proteins and the organisms that harbour them. But modern implementations with sophisticated models of sequence evolution struggle to resolve deep evolutionary relationships, which can be obscured by excessive sequence divergence and substitution saturation. Structural phylogenetics has emerged as a promising alternative, because protein structure evolves much more slowly than protein sequences. Recent developments protein structure prediction using AI have made it possible to predict protein structures for entire protein families, and then to translate these structures into a sequence representation - the 3Di structural alphabet - that can in theory be directly fed into existing sequence based phylogenetic software. To unlock the full potential of this idea, however, requires the inference of a general substitution matrix for structural phylogenetics, which has so far been missing. Here we infer this matrix from large datasets of protein structures and show that it results in a better fit to empirical datasets that previous approaches. We then use this matrix to re-visit the question of the root of the tree of life. Using structural phylogenies of universal paralogs, we provide the first unambiguous evidence for a root between and archaea and bacteria. Finally, we discuss some practical and conceptual limitations of structural phylogenetics. Our 3Di substitution matrix provides a starting point for revisiting many deep phylogenetic problems that have so far been extremely difficult to solve.
Maf-family bZIP transcription factor NRL interacts with RNA-binding proteins and R-loops in retinal photoreceptors
Authors: Corso-Díaz Ximena , Liang Xulong , Preston Kiam , Tegshee Bilguun , English Milton A. , Nellissery Jacob , Yadav Sharda Prasad , Marchal Claire , Swaroop Anand 
Published: September 2024

AbstractRNA-binding proteins (RBPs) perform diverse functions including the regulation of chromatin dynamics and the coupling of transcription with RNA processing. However, our understanding of their actions in mammalian neurons remains limited. Using affinity purification, yeast-two-hybrid and proximity ligation assays, we identified interactions of multiple RBPs with NRL, a Maf-family bZIP transcription factor critical for retinal rod photoreceptor development and function. In addition to splicing, many NRL-interacting RBPs are associated with R-loops, which form during transcription and increase during photoreceptor maturation. Focusing on DHX9 RNA helicase, we demonstrate that its expression is modulated by NRL and that the NRL-DHX9 interaction is positively influenced by R-loops. ssDRIP-Seq analysis reveals both stranded and unstranded R-loops at distinct genomic elements, characterized by active and inactive epigenetic signatures and enriched at neuronal genes. NRL binds to both types of R-loops, suggesting an epigenetically independent function. Our findings suggest additional functions of NRL during transcription and highlight complex interactions among transcription factors, RBPs, and R-loops in regulating photoreceptor gene expression in the mammalian retina.
GDNF family receptor alpha-like (GFRAL) expression is restricted to the caudal brainstem
Authors: Hes Cecilia , Gui Luting , Bay Alexandre , Alvarez Fernando , Katz Pierce , Paul Tanushree , Bozadjieva-Kramer Nadejda , Seeley Randy J. , Piccirillo Ciriaco A. , Sabatini Paul 
Published: September 2024

AbstractThe TGF-β cytokine, growth differentiation factor 15 (GDF15) is a critical mediator of the physiologic response to a range of cellular stresses. While circulating levels of GDF15 are normally very low, these levels increase substantially under a number of acute and chronic pathogenic states including mycotoxin exposure, infection and cancer. GDF15 controls a range of physiologic outputs including reduced appetite, gastric motility, hyperalgesia, emesis, energy expenditure and immune cell function via the GDNF family receptor alpha-like (GFRAL). While the area postrema and nucleus of the solitary tract (AP/NTS) within the caudal brainstem are the only known sites ofGfral-expressing cells,Gfralmay also be expressed in other cell types. We therefore utilized single moleculein-situhybridizations and genetic mouse models to labelGfral-expressing cells from development to adult mouse. With both approaches, we foundGfral-labelled cells in the brainstem and extremely rareGfral-labelled cells in peripheral tissues in the mouse under normal physiological conditions. Confirming these findings, single nucleus RNA-sequencing of human tissues demonstrated nearly undetectable levels ofGfralmRNA in sites outside the AP/NTS. Our findings confirm AP/NTS neurons are the major site ofGfralexpression.
Inward transport of organelles drives outward migration of the spindle duringC. elegansmeiosis
Authors: Peraza Alma A. , Li Wenzhe , Lele Aastha , Lazureanu Denisa , Hampton Megan F. , Do Rebecca M. , Lafrades Melissa C. , Barajas Maria G. , Batres Antonio A. , McNally Francis J. 
Published: September 2024

AbstractCortical positioning of the meiotic spindle within an oocyte is required to expel chromosomes into polar bodies to generate a zygote with the correct number of chromosomes. InC. elegans, yolk granules and mitochondria are packed inward, away from the cortex while the spindle moves outward, both in a kinesin-dependent manner. The kinesin-dependent inward packing of yolk granules suggests the existence of microtubules with minus ends at the cortex and plus ends extending inward, making it unclear how kinesin moves the spindle outward. We hypothesized that inward packing of organelles might indirectly force the spindle outward by volume exclusion. To test this hypothesis, we generated a strain in which the only kinesin consists of motor domains with no cargo-binding tail optogenetically attached to mitochondria. This mitochondria-only kinesin packed mitochondria into a tight ball and efficiently moved the meiotic spindle to the cortex, supporting the volume exclusion hypothesis.
SoyOD: An Integrated Soybean Multi-omics Database for Mining Genes and Biological Research
Authors: Li Jie , Ni Qingyang , He Guangqi , Huang Jiale , Chao Haoyu , Li Sida , Chen Ming , Hu Guoyu , Whelan James , Shou Huixia 
Published: September 2024

AbstractSoybean is a globally important crop for food, feed, oil, and nitrogen fixation. A variety of multi-omics research has been carried out generating datasets ranging from genotype to phenotype. To utilise this data, a soybean multi-omics database that has broad data coverage and comprehensive data analysis tools would be of value for basic and applied research. We present the soybean omics database (SoyOD), which integrates significant new datasets with existing public datasets for the most comprehensive collection of soybean multi-omics information. Compared to the existing soybean database, SoyOD incorporates an extensive collection of novel data derived from the deep-sequencing of 984 germplasms, 162 novel transcriptome datasets from seeds at different developmental stages, 53 phenotypic datasets, and over 2500 phenotypic images. In addition, SoyOD integrates existing data resources, including 59 assembled genomes, genetic variation data from 3904 soybean accessions, 225 sets of phenotypic data, and 1097 transcriptomic sequences covering 507 different tissues and treatment conditions. SoyOD is a novel tool, as it can be used to mine and analyze candidate genes for important agronomic traits, as shown in a case study on plant height. Additionally, powerful analytical and easy-to-use toolkits enable users to easily access the available multi-omics datasets, and to rapidly search genotypic and phenotypic data in a particular germplasm. The novelty, comprehensiveness, and user-friendly features of SoyOD make it a valuable resource for soybean molecular breeding and biological research. SoyOD is publicly accessible athttps://bis.zju.edu.cn/soyod.
Immobilized Nucleoside 2′-Deoxyribosyltransferases from Extremophiles for Nucleoside Biocatalysis
Authors: Hernández Martínez Saúl Antonio , Tang Peijun , Parra-Saldívar Roberto , Melchor-Martínez Elda M. , Czekster Clarissa Melo 
Published: September 2024

ABSTRACTThe synthesis of nucleosides is crucial for pharmaceutical and biotechnological applications, acting as drugs and as essential building blocks for numerous therapeutic agents. However, most enzymes employed in nucleoside biocatalysis are not recycled, possess limit stability and strict substrate selection for ribonucleosides or 2′deoxyribonucleosides. We employed 2′deoxyribonucleoside transferase (NDT) enzymes from thermophilic and psychrophilic bacteria to demonstrate they can be immobilized to en-hance specific activity, stability, and recyclability. NDT enzymes fromChroococcidiopsis thermalis(CtNDT), andBacillus psychrosaccharolyticus(BpNDT) were immobilized by covalent attachment to chitosan beads. A double mutant of CtNDT, capable of generating 3′deoxyribonucleosides, showed remarkable and increased stability after immobilization when compared to the same enzyme in solution. Furthermore, we demonstrated the recyclability of immobilized biocatalysts, with a tenfold improvement in reaction yield over 20 consecutive cycles, highlighting the practicality and sustainability of the developed immobilization method. We used our strategy to produce a pharmaceutically relevant 3′deoxyribonucleoside (2-fluoro-3′-deoxyadenosine). This highlights the importance of efficient immobilization techniques to enhance catalytic properties of NDT enzymes, expanding their utility in biocatalysis.