bluuebunny/crossref_metadata_2025_split huggingface dataset:
BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks
Authors: Kumagai Yutaro 
Published: February 2024

AbstractRecent advances in measurement technologies, particularly single-cell RNA sequencing (scRNA-seq), have revolutionized our ability to acquire large amounts of omics-level data on cellular states. As measurement techniques evolve, there has been an increasing need for data analysis methodologies, especially those focused on cell-type identification and inference of gene regulatory networks (GRNs). We have developed a new method named BootCellNet, which employs smoothing and resampling to infer GRNs. Using the inferred GRNs, BootCellNet further infers the minimum dominating set (MDS), a set of genes that determines the dynamics of the entire network. We have demonstrated that BootCellNet robustly infers GRNs and their MDSs from scRNA-seq data and facilitates unsupervised identification of cell clusters using scRNA-seq datasets of peripheral blood mononuclear cells and hematopoiesis. It has also identified COVID-19 patient-specific cells and their potential regulatory transcription factors. BootCellNet not only identifies cell types in an unsupervised and explainable way but also provides insights into the characteristics of identified cell types through the inference of GRNs and MDS.Author SummarySingle-cell omics technologies, such as single-cell RNA-seq (scRNA-seq), are instrumental in identifying novel cell subsets that are involved in various biological processes and diseases. These technologies, however, require further development in data analysis, especially in areas focused on cell-type identification and inference of interactions between genes. The problem of cell-type identification essentially involves clustering, which necessitates a balance between distinguishing different cell states and grouping similar ones together. Current clustering methods still suffer from uncertainty in determining the appropriate number of clusters and in explaining why some cells are clustered together but others are separated. The inference of interactions between genes, gene regulatory network (GRN), remains challenging due to the noisy nature of scRNA-seq. We have developed BootCellNet, a method that infers GRNs and a set of genes dominating the network dynamics and utilizes the set to cluster cells and identify cell types. The method addresses challenges in GRN identification and clustering methods simultaneously and will facilitate the generation of the working hypotheses from a large amount of scRNA-seq data.
Disentangling competitive and cooperative components of the interactions between microbial species
Authors: Ansari Aamir Faisal , Sambamoorthy Gayathri , Alexander Thrisha C , Reddy Yugandhar B.S. , Raut Janhavi , Dixit Narendra M. 
Published: February 2024

ABSTRACTInteractions between microbial species have been characterized by the net influences, positive or negative, that each species in a pair exerts on the other. This conventional view of interactions being either positive or negative proves restrictive in predicting the behaviour of microbial communities and, more importantly, influencing them towards desired community structures. Here, we propose a more fundamental characterization of the interactions. The net interactions typically comprise positive and negative underlying components. Yet, the conventional view prevails because the components have been difficult to disentangle. We have developed a methodology to disentangle them when metabolic interactions predominate. We conceived a theoretical resource partitioning between species that helps estimate the positive components. The negative components then follow from knowledge of the net interactions. The interactions between two species are then characterized by the ‘quartet’ of these components. We applied the methodologyin silicoto 28 species pairs from the human oral microbiome, yielding 56 net interactions and their 112 quartet components. We found that on average the net interactions comprised positive and negative components of comparable strengths. Interestingly, weak net interactions often arose from the cancellation of strong underlying components. Furthermore, we found species pairs with similar net interactions but vastly different underlying components. Extant community ecology theories, based on net interactions, cannot distinguish between such pairs. The quartet explained several confounding experimental observations and offered new insights into microbial community ecology. We envision its implications in the construction of more refined ecological theories and the engineering of synthetic microbial communities.
Whole Genome Sequencing of DENV-2 isolated fromAedes aegyptimosquitoes in Esmeraldas, Ecuador. Genomic epidemiology of genotype III Southern Asian-American in the country
Authors: Carrazco-Montalvo Andrés , Gutiérrez-Pallo Diana , Arévalo Valentina , Ponce Patricio , Rodríguez-Polit Cristina , Alarcón Damaris , Echeverría-Garcés Gabriela , Coloma Josefina , Nipaz Victoria , Cevallos Varsovia 
Published: February 2024

AbstractEcuador is a tropical country reporting Dengue virus (DENV) outbreaks with areas of hyperendemic viral transmission. Entomo-virological surveillance and monitoring effort conducted in the Northwestern border province of Esmeraldas in April 2022, five pools of femaleAedes aegyptimosquitoes from a rural community tested positive for DENV serotype 2 by RT-qPCR. One pool was sequenced by Illumina MiSeq, and it corresponded to genotype III Southern Asian-American. Comparison with other genomes revealed genetic similarity to a human DENV genome sequenced in 2021, also from Esmeraldas. Potential introduction events to the country could have originated from Colombia, considering the vicinity of the collection sites to the neighboring country and high human movement. The inclusion of genomic information complements entomo-virological surveillance, providing valuable insights into genetic variants. This contribution enhances our understanding of Dengue virus (DENV) epidemiology in rural areas and guides evidence-based decisions for surveillance and interventions.Author SummaryIn this study, the complete genetic information of the dengue virus isolated from the mosquito vectorAedes aegyptiwas characterized using molecular biology, sequencing, and bioinformatics analysis. The isolation of the virus from the vector has contributed significantly to our understanding of the transmission dynamics of the disease and its genetic relationship with human cases. Identifying the serotypes and genotypes circulating in Ecuador has enabled us to comprehend the evolution of the virus from 2014 to 2023. Therefore, surveillance of genetic variability would aid in adapting precise prevention and control strategies to the genetic variants present in a specific geographical area. Entomo-virological surveillance is essential for assessing changes in risk and the impact of control measures.
Comparative analysis of 136,401 Admixed Americans and 419,228 Europeans reveals ancestry-specific genetic determinants of clonal haematopoiesis
Authors: Wen Sean , Kuri-Morales Pablo , Hu Fengyuan , Nag Abhishek , Tachmazidou Ioanna , Vishnu Vardhan Deevi Sri , Taiy Haeyam , Smith Katherine , Loesch Douglas P. , Burren Oliver S. , Dhindsa Ryan S. , Wasilewski Sebastian , Alegre-Díaz Jesus , Berumen Jaime , Emberson Jonathan , Torres Jason M. , Collins Rory , Carss Keren , Wang Quanli , Petrovski Slavé , Tapia-Conyer Roberto , Fabre Margarete A. , Harper Andrew R. , Vassiliou George , Mitchell Jonathan 
Published: February 2024

AbstractThe development of clonal haematopoiesis (CH), the age-related expansion of mutated haematopoietic stem cell (HSC) clones, is influenced by genetic and non-genetic factors. To date, large-scale studies of CH have focused on individuals of European descent, such that the impact of genetic ancestry on CH development remains incompletely understood. Here, we investigate this by studying CH in 136,401 admixed participants from the Mexico City Prospective Study (MCPS) and 419,228 European participants from the UK Biobank (UKB). We observe that CH was significantly less common in MCPS compared to UKB (adjusted odds ratio (OR) = 0.56 [95% Cl = 0.55-0.59],P= 1.60 x 10-206), a difference that persisted when comparing MCPS participants whose genomes were >50% ancestrally Indigenous American to those whose genomes were >50% ancestrally European (adjusted OR = 0.76 [0.70-0.83],P= 1.78 x 10-10). Genome- and exome-wide association analyses in MCPS participants identified two novel loci associated with CH (CSGALNACT1andDIAPH3), and ancestry-specific variants in theTCL1Blocus with opposing effect onDNMT3A-versus non-DNMT3A-CH. Meta-analysis of the MCPS and UKB cohorts identified another five novel loci associated with overall or gene specific CH, including polymorphisms atPAPR11/CCND2,MEIS1andUBE2G1/SPNS3. Our CH study, the largest in a non-European population to date, demonstrates the profound impact of ancestry on CH development and reveals the power of cross-ancestry comparisons to derive novel insights into CH pathogenesis and advance health equity amongst different human populations.
Cytoplasmic protein-free mRNA induces stress granules by two G3BP1/2-dependent mechanisms
Authors: Ihn Sean J. , Farlam-Williams Laura , Palazzo Alexander F. , Lee Hyun O. 
Published: February 2024

AbstractStress granules are cytoplasmic membraneless organelles that sequester proteins and non-translating mRNAs in response to various stressors. To assess the contributions of mRNA and RNA-binding proteins to stress granule formation, we use microinjection to deliver protein-free mRNA into the cytoplasm in a controlled manner. We demonstrate that mRNAs trigger stress granule formation through two mechanisms that are enhanced by the presence of G3BP1 and G3BP2. Low concentrations ofin vitrotranscribed mRNA activated protein kinase R (PKR), leading to phosphorylation and inhibition of the eukaryotic translation initiation factor eIF2α and stress granule formation. This was inhibited by replacing uridine with pseudouridine in the mRNA or by treating it with RNase III, which cleaves double-stranded RNA. High concentrations of mRNA triggered stress granule formation by a mechanism that was independent of PKR and enhanced by G3BP1/2, highlighting the importance of both protein-free mRNA and RNA-binding proteins in stress granule formation.Graphical Abstract/ModelSummaryMicroinjected mRNA induces stress granules in mammalian cells by two G3BP1/2-dependent mechanisms: one requires the stress-sensing protein kinase PKR to phosphorylate the translation initiation factor eIF2α, and the other is independent of PKR and phospho-eIF2α and acts when the cytoplasmic concentration of ribosome-free mRNA is increased acutely.
MS-DIAL 5 multimodal mass spectrometry data mining unveils lipidome complexities
Authors: Takeda Hiroaki , Matsuzawa Yuki , Takeuchi Manami , Takahashi Mikiko , Nishida Kozo , Harayama Takeshi , Todoroki Yoshimasa , Shimizu Kuniyoshi , Sakamoto Nami , Oka Takaki , Maekawa Masashi , Chung Mi Hwa , Kurizaki Yuto , Kiuchi Saki , Tokiyoshi Kanako , Buyantogtokh Bujinlkham , Kurata Misaki , Kvasnička Aleš , Takeda Ushio , Uchino Haruki , Hasegawa Mayu , Miyamoto Junki , Tanabe Kana , Takeda Shigenori , Mori Tetsuya , Kumakubo Ryota , Tanaka Tsuyoshi , Yoshino Tomoko , Arita Makoto , Tsugawa Hiroshi 
Published: February 2024

ABSTRACTLipidomics and metabolomics communities comprise various informatics tools; however, software programs that can handle multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 to facilitate the in-depth structural elucidation of lipids through electron-activated dissociation (EAD)-based tandem MS, as well as determine their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section (CCS) values. With the optimized EAD settings using 14 eV kinetic energy conditions, the program correctly delineated the lipid structures based on EAD-MS/MS data from 96.4% of authentic standards. Our workflow was showcased by annotating thesn- and double-bond positions of eye-specific phosphatidylcholine molecules containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and HeLa cells supplemented with n-3-VLC-PUFA, we identified glycerol 3-phosphate (G3P) acyltransferase (GPAT) as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into thesn-1 position of phospholipids in mammalian cells, which was confirmed using recombinant proteins in a cell-free system. Therefore, the MS-DIAL 5 environment, combined with optimized MS data acquisition methods, facilitates a better understanding of lipid structures and their localization, offering novel insights into lipid biology.
Measurement of adhesion and traction of cells at high yield (MATCHY) reveals an energetic ratchet driving nephron condensation
Authors: Liu Jiageng , Prahl Louis S. , Huang Aria , Hughes Alex J. 
Published: February 2024

AbstractEngineering of embryonic strategies for tissue-building has extraordinary promise for regenerative medicine. This has led to a resurgence in interest in the relationship between cell biophysical properties and morphological transitions. However, mapping gene or protein expression data to cell biophysical properties to physical morphogenesis remains challenging with current techniques. Here we present MATCHY (multiplexedadhesion and traction ofcells athighyield). MATCHY advances the multiplexing and throughput capabilities of existing traction force and cell-cell adhesion assays using microfabrication and an automated computation scheme with machine learning-driven cell segmentation. Both biophysical assays are coupled with serial downstream immunofluorescence to extract cell type/signaling state information. MATCHY is especially suited to complex primary tissue-, organoid-, or biopsy-derived cell mixtures since it does not rely ona prioriknowledge of cell surface markers, cell sorting, or use of lineage-specific reporter animals. We first validate MATCHY on canine kidney epithelial cells engineered for RET tyrosine kinase expression and quantify a relationship between downstream signaling and cell traction. We go on to create a biophysical atlas of primary cells dissociated from the mouse embryonic kidney and use MATCHY to identify distinct biophysical states along the nephron differentiation trajectory. Our data complement expression-level knowledge of adhesion molecule changes that accompany nephron differentiation with quantitative biophysical information. These data reveal an ‘energetic ratchet’ that explains spatial nephron progenitor cell condensation from the niche as they differentiate, which we validate through agent-based computational simulation. MATCHY offers automated cell biophysical characterization at >104-cell throughput, a highly enabling advance for fundamental studies and new synthetic tissue design strategies for regenerative medicine.
Systematic review of contemporary improvement interventions on care coordination, discharge support and transitional care from the patient experience perspective
Authors: Jesus Tiago S , Stern Brocha Z. , Lee Dongwook , Zhang Manrui , Struhar Jan , Heinemann Allen W. , Jordan Neil , Deutsch Anne 
Published: February 2024

AbstractAimTo synthesize the impact of improvement interventions related to care coordination and discharge support on patient experience measures.MethodSystematic review. Searches were completed in six scientific databases, five specialty journals and through snowballing. Eligibility included studies in English (2015-2022) on improving care coordination, discharge support, or transitional care assessed by standardized patient experience measures as a primary outcome. Two independent reviewers made eligibility decisions and performed quality appraisals.ResultsOf 1087 papers initially screened, 15 were finally included. Seven studies (three randomized controlled trials [RCTs]) focused on care coordination activities and used enhanced supports (e.g., improvement coaching; tailoring for vulnerable populations) for Patient-Centered Medical Homes or other primary care sites. Effectiveness was mixed or neutral relative to standard supports or models of care. Eight studies (three RCTs) focused on enhanced discharge support, including patient education (e.g., “teach back” method) and telephone follow-up or transitional support; mixed or neutral results on the patient experience were also found and with more substantive risks of bias.ConclusionEnhanced supports for improving care coordination, discharge education, and post-discharge follow-up had mixed or neutral effectiveness for improving the patient experience with care, compared to standard or simpler improvement approaches. Studies on the improvement of patient experiences, especially for enhanced patient discharge, need further strengthening such as including the patient perspective for its co-development.
Assessment of Magnitude of Transfusion Transmissible Infections and Associated Factors among Blood Donors at Woliso Blood Bank, South-West Shewa Zone, Oromia, Ethiopia: Across-Sectional Study
Authors: W/Amlak Alemnesh , Oljira Habtamu , Tafa Belay , Darcho Samuel Demissie , Begna Sisay Dabi 
Published: February 2024

AbstractBackgroundBlood transfusion is an effective treatment for saving millions of lives, even though transfusion-transmissible infections are the major problem. The prevalence of transfusion-transmissible infections varies across different geographical populations. This study aims to assess the prevalence of transfusion-transmissible infections and associated factors among blood donors at Woliso Blood Bank, South-West Shewa Zone, Oromia, Ethiopia.MethodAn institutional-based cross-sectional study design was conducted. A structured and pretested questionnaire was used to collect data through a face-to-face interview. Data was entered into Epi Data version 3.1, and it was exported to STATA version 17.0 for data cleaning and analysis. A binary logistic regression analysis was carried out to identify factors associated with outcome variables. Accordingly, variables that fulfilled p-values <0.25 on the bivariate logistic regression were considered candidates for multivariate logistic regression to control for possible confounders. The odds ratios along with the 95% confidence interval were used to present the finding, and statistical significance was reported at a p-value of 0.05.ResultsThe overall prevalence of transfusion-transmissible infections was 9.5% (95% CI: 6.3– 12.9%). Participants with no formal education [AOR=4.84; 95% CI= 1.09, 21.46], unprotected sexual intercourse with multiple partners [AOR=4.77; 95% CI= 1.38, 16.44], and participants with less frequency of blood donation [AOR=2.85; 95% CI: 1.16, 6.99] were significantly associated with transfusion transmissible infections.ConclusionThe prevalence of transfusion-transmissible infections was high in this study area. Educational level, unprotected sexual intercourse with more partners, and a number of blood donations were found to be independent predictors of transfusion-transmitted infections. Blood banks and regional health bureaus should work on community mobilization and enhancing health promotion through prevention and control by considering the identified associated factors.
The association between time-weighted remnant cholesterol and cardiovascular and non-cardiovascular mortality: A population-based cohort study
Authors: Li Lifang , Cheng Chou Vanessa Hou , In Chou Oscar Hou , Roy Sakshi , Kai Chan Jeffrey Shi , Wong Wing Tak , Liu Tong , Lip Gregory , Yung Cheung Bernard Man , Tse Gary , Zhou Jiandong 
Published: February 2024

AbstractBackgroundRemnant cholesterol (RC) have been suggested as a significant mediator of atherosclerotic cardiovascular diseases. However, the relationship between RC with cause-specific mortality in long-term remained uncertain. This study aimed to investigate the association between time-weighted RC and cause-specific mortality outcomes.MethodsThis retrospective population-based study enrolled patients attending family medicine clinics in Hong Kong between 1stJanuary 2000, to 31stDecember 2003 with at least three RC testing results during follow-up. The time-weighted RC was calculated by the products of the sums of two consecutive measurements and the time interval divided by the total time. The primary outcomes were all-cause mortality and cause-specific mortality outcomes. Cox regression and marginal effective plots were applied to identify associations between time-weighted RC and mortality.ResultsA cohort of 75,342 patients (39.69% males, mean age: 61.3 years old) with at least three valid RC test were included. During up to 19 years of follow-up, in the multivariate model adjusted for demographics, comorbidities, medications, and time-weighted laboratory results, time-weighted RC was associated with all-cause mortality (Hazard ratio [HR]: 1.41; 95% Confidence Interval [CI]: 1.35-1.48) but not RC (HR: 0.99; 95% CI: 0.89-1.10). Time-weighted RC was also associated with increased risks of cardiovascular-related mortality (HR: 1.40; 95% CI: 1.27-1.54), cancer-related mortality (HR: 1.59; 95% CI: 1.43-1.77), and respiratory-related mortality (HR: 1.33; 95% CI: 1.20-1.47). The exploratory analysis of the cause of death demonstrated that time-weighted RC was associated with Ischaemic heart disease, cerebrovascular-related and pneumonia.ConclusionsTime-weighted RC was independently associated with all-cause mortality and cause-specific mortality outcomes amongst the general population.
Can longitudinal electronic health record data identify patients at higher risk of developing long COVID?
Authors: Shanmugam Priya , Bair Molly , Pendl-Robinson Emma , Hu Xindi C. 
Published: February 2024

AbstractWith hundreds of millions of COVID-19 infections to date, a considerable portion of the population has developed or will develop long COVID. Understanding the prevalence, risk factors, and healthcare costs of long COVID can be of significant societal importance. To investigate the utility of large-scale electronic health record (EHR) data in identifying and predicting long COVID, we analyzed a sample of 1.23 million participants from the National COVID Cohort Collaborative (N3C), a longitudinal EHR data repository from 80 sites in the US with over 8 million COVID-19 patients. We characterized the prevalence of long COVID using a few different types of definitions to illustrate their relative strengths and weaknesses. Then we developed machine learning models to predict the risk of developing long COVID using demographic factors and comorbidity in the EHR. The risk factors for long COVID include patient age; sex; smoking status; and comorbidities characterized by the Charlson Comorbidity Index (CCI). We were able to predict three types of long COVID with low to moderate levels of accuracy (AUC 0.599 – 0.734). We found that age and CCI were most predictive of long COVID diagnosis. Ongoing work includes applying the fair machine learning framework to the long COVID predictive models. We are implementing fairness and bias mitigation methods to model fitting through the following steps, selecting fairness metrics, preparing data and model, evaluating fairness metrics, applying bias mitigation methods to the dataset, and comparing model results and fairness metrics before and after the mitigation. The objective is to achieve equalized odds, a statistical notion that ensures classification algorithms do not discriminate against protected groups (such as sex and race/ethnicity). Results from the fairness-based machine learning will be included in the conference presentation.