bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection
Authors: Zhang Martin Jinye , Durvasula Arun , Chiang Colby , Koch Evan M. , Strober Benjamin J. , Shi Huwenbo , Barton Alison R. , Kim Samuel S. , Weissbrod Omer , Loh Po-Ru , Gazal Steven , Sunyaev Shamil , Price Alkes L. 
Published: December 2023

ABSTRACTThe genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (averageN=306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., −0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., −0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., −0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., −0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and −0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)—even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.
Understanding the key determinants of an HPV therapeutic vaccine: a modeling analysis
Authors: Cohen Jamie A. , Stuart Robyn M. , Lee Serin , Klein Daniel J. , Kerr Cliff C. , Rao Darcy W. , Shin Haina , Achilles Sharon L. 
Published: December 2023

AbstractDespite incredibly effective tools to prevent HPV infection and treat precancerous lesions, the scale-up of existing interventions in most low and middle-income countries has been slow, leaving a residual burden of invasive cervical cancer that will persist for decades. An HPV therapeutic vaccine may overcome some of the scalability and infrastructure challenges of traditional screening and treatment programs, though its potential public health value depends upon its characteristics, delivery strategy, and the underlying immunity of the population on which it would act. This analysis uses HPVsim, an open-access agent-based simulation framework, to evaluate the impact of a range of potential HPV therapeutic vaccines with varying scale-up of existing preventive interventions in nine high-burden low- and middle-income countries (LMICs). For each setting, the model is populated with context-specific demographic and behavioral data, and calibrated to fit estimates of HPV and cervical disease by age. We find that an HPV therapeutic vaccine that clears 90% of virus and regresses 50% of high-grade lesions, reaching 70 percent of 35-45 year old women starting in 2030, could avert 1.2-2.2 million incident cases of cervical cancer, 500,000-1.2 million cervical cancer deaths and 20-40 million disability adjusted life years (DALYs) in the modeled high-burden LMICs over 30 years. The size of the impact is sensitive to rates of background intervention scale-up and the characteristics of the vaccine, including ability to establish long-lasting immune memory.
STIL overexpression shortens lifespan and reduces tumor formation in mice
Authors: Moussa Amira-Talaat , Cosenza Marco R. , Wohlfromm Timothy , Brobeil Katharina , Hill Anthony , Patrizi Annarita , Müller-Decker Karin , Holland-Letz Tim , Jauch Anna , Kraft Bianca , Krämer Alwin 
Published: December 2023

AbstractCentrosomes are the major microtubule organizing centers of animal cells. Supernumerary centrosomes are a common feature of human tumors and associated with karyotype abnormalities and aggressive disease, but whether they are cause or consequence of cancer remains controversial. Here, we analyzed the consequences of centrosome amplification by generating transgenic mice in which centrosome numbers can be increased by overexpression of the structural centrosome protein STIL. We show that STIL overexpression induces centrosome amplification and aneuploidy, leading to senescence, apoptosis, and impaired proliferation in mouse embryonic fibroblasts, and microcephaly with increased perinatal lethality and shortened lifespan in mice. Importantly, both overall tumor formation in mice with constitutive, global STIL overexpression and chemical skin carcinogenesis in animals with inducible, skin-specific STIL overexpression were reduced, an effect that was not rescued by concomitant p53 inactivation. These results suggest that supernumerary centrosomes impair proliferationin vitroas well asin vivo, resulting in reduced lifespan and spontaneous as well as carcinogen-induced tumor formation.
Concomitant investigation of crustacean amphipods lipidome and metabolome during molting stage by Zeno SWATH Data-Independent Acquisition coupled with Electron Activated Dissociation and machine learning
Authors: Brunet Thomas Alexandre , Clément Yohann , Calabrese Valentina , Lemoine Jérôme , Geffard Olivier , Chaumot Arnaud , Degli-Esposti Davide , Salvador Arnaud , Ayciriex Sophie 
Published: December 2023

AbstractBackgroundDIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) in metabolomics and lipidomics, for comprehensive profiling of molecules in biological samples. It provides unbiased coverage, improved reproducibility, and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipodGammarus fossarum, successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field.ResultsDIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to study molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified statistically significant features responsible for group segregation. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra DB annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness.SignificanceReproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing and EAD synergistically enhances detection sensitivity while providing orthogonal fragmentation information, thereby facilitating a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying biomarkers of significance in the field of environmental assessment.HighlightsAdvancements in Data-Independent-Acquisition methods for lipidomics and metabolomics.Zeno pulsing improves sensitivity in fragment detection and compound identification.Comprehensive structure elucidation of lipids and metabolites using EAD fragmentation.
Spatial and Temporal Coordination of Force-generating Actin-based Modules Drives Membrane RemodelingIn Vivo
Authors: Heydecker Marco , Shitara Akiko , Chen Desu , Tran Duy , Masedunskas Andrius , Tora Muhibullah , Ebrahim Seham , Appaduray Mark A. , Galeano Niño Jorge Luis , Bhardwaj Abhishek , Narayan Kedar , Hardeman Edna C. , Gunning Peter W. , Weigert Roberto 
Published: December 2023

SummaryMembrane remodeling drives a broad spectrum of cellular functions, and it is regulated through mechanical forces exerted on the membrane by cytoplasmic complexes. Here, we investigate how actin filaments dynamically tune their structure to control the active transfer of membranes between cellular compartments with distinct compositions and biophysical properties. Using intravital subcellular microscopy in live rodents we show that: a lattice composed of linear filaments stabilizes the granule membrane after fusion with the plasma membrane; and a network of branched filaments linked to the membranes by Ezrin, a regulator of membrane tension, initiates and drives to completion the integration step. Our results highlight how the actin cytoskeleton tunes its structure to adapt to dynamic changes in the biophysical properties of membranes.
Unsupervised learning reveals landscape of local structural motifs across protein classes
Authors: Derry Alexander , Altman Russ B. 
Published: December 2023

ABSTRACTProteins are known to share similarities in local regions of 3D structure even across disparate global folds. Such correspondences can help to shed light on functional relationships between proteins and identify conserved local structural features that lead to function. Self-supervised deep learning on large protein structure datasets has produced high-fidelity representations of local structural microenvironments, enabling comparison of local structure and function at scale. In this work, we leverage these representations to cluster over 15 million environments in the Protein Data Bank, resulting in the creation of a “lexicon” of local 3D motifs which form the building blocks of all known protein structures. We characterize these motifs and demonstrate that they provide valuable information for modeling structure and function at all scales of protein analysis, from full protein chains to binding pockets to individual amino acids. We devise a new protein representation based solely on its constituent local motifs and show that this representation enables state-of-the-art performance on protein structure search and model quality assessment. We then show that this approach enables accurate prediction of drug off-target interactions by modeling the similarity between local binding pockets. Finally, we identify structural motifs associated with pathogenic variants in the human proteome by leveraging the predicted structures in the AlphaFold structure database.
Germ granule compartments coordinate specialized small RNA production
Authors: Chen Xiangyang , Wang Ke , Feng Xuezhu , Mufti Farees ud din , Xu Demin , Zhu Chengming , Huang Xinya , Zeng Chenming , Jin Qile , Huang Xiaona , Yan Yong-hong , Dong Meng-qiu , Shi Yunyu , Kennedy Scott , Guang Shouhong 
Published: December 2023

AbstractGerm granules are biomolecular condensates present in most animal germ cells. One function of germ granules is to help maintain germ cell totipotency by organizing mRNA regulatory machinery, including small RNA-based gene regulatory pathways. TheC. elegansgerm granule is compartmentalized into multiple subcompartments whose biological functions are largely unknown. Here, we identify a new subcompartment of theC. elegansgerm granule, which we term the E compartment. The E compartment is nonrandomly positioned within the germ granule. We identified five proteins that localize to the E compartment, including the RNA-dependent RNA polymerase (RdRP) EGO-1, the Dicer-related helicase DRH-3, the Tudor domain-containing protein EKL-1, and two intrinsically disordered proteins, EGC-1 and ELLI-1. Localization of EGO-1 to the E granule enables synthesis of a specialized class of 22G RNAs, which derive exclusively from 5’regions of a subset of germline-expressed mRNAs. Defects in E compartment assembly elicit disordered production of endogenous siRNAs, which disturbs fertility and the RNAi response. Our results define a new subcompartment of theC. elegansgerm granule and suggest that one function of germ granule compartmentalization is to facilitate the localized production of specialized classes of small regulatory RNAs.
Spatially resolved single-cell analysis uncovers protein kinase Cδ-expressing microglia with anti-tumor activity in glioblastoma
Authors: Mirzaei Reza , McNeil Reid , D’Mello Charlotte , Wong Britney , Sarkar Susobhan , Visser Frank , Poon Candice , Bose Pinaki , Yong V Wee 
Published: December 2023

AbstractGlioblastoma (GBM) is a brain tumor that poses a formidable challenge to treatment options available. The tumor microenvironment (TME) in GBM is highly complex, marked by immunosuppression and cellular heterogeneity. Understanding the cellular interactions and their spatial organization within the TME is crucial for developing effective therapeutic strategies. In this study, we integrated single-cell RNA sequencing and spatial transcriptomics in a GBM mouse model to unravel the spatial landscape of the brain TME. We identified a previously unrecognized microglia subtype expressing protein kinase Cδ (PKCδ) associated with potent anti-tumor functions. The presence of PKCδ-expressing microglia was confirmed in resected human GBM specimens. Elevating tumoral PKCδ expression using niacin or adeno-associated virus in mice enhanced the phagocytosis of GBM cells by microglia in culture and increased the lifespan of mice with intracranial GBM. These findings were corroborated in analyses of the TCGA GBM datasets where low PKCδ samples showed negative pathway enrichment for apoptosis, phagocytosis, and immune signaling pathways, as well as lower levels of immune cell infiltration overall. Our study underscores the importance of integrating spatial context to unravel the TME, resulting in the identification of previously unrecognized subsets of microglia with anti-tumor functions. These findings provide valuable insights for advancing innovative immunotherapeutic strategies in GBM.
Age-related Muscle Fat Infiltration in Lung Screening Participants: Impact of Smoking Cessation
Authors: Xu Kaiwen , Li Thomas Z. , Terry James G. , Krishnan Aravind R. , Deppen Stephen A. , Huo Yuankai , Maldonado Fabien , Carr J. Jeffrey , Landman Bennett A. , Sandler Kim L. 
Published: December 2023

RationaleSkeletal muscle fat infiltration progresses with aging and is worsened among individuals with a history of cigarette smoking. Many negative impacts of smoking on muscles are likely reversible with smoking cessation.ObjectivesTo determine if the progression of skeletal muscle fat infiltration with aging is altered by smoking cessation among lung cancer screening participants.MethodsThis was a secondary analysis based on the National Lung Screening Trial. Skeletal muscle attenuation in Hounsfield unit (HU) was derived from the baseline and follow-up low-dose CT scans using a previously validated artificial intelligence algorithm. Lower attenuation indicates greater fatty infiltration. Linear mixed-effects models were constructed to evaluate the associations between smoking status and the muscle attenuation trajectory.Measurements and Main ResultsOf 19,019 included participants (age: 61 years, 5 [SD]; 11,290 males), 8,971 (47.2%) were actively smoking cigarettes. Accounting for body mass index, pack-years, percent emphysema, and other confounding factors, actively smoking predicted a lower attenuation in both males (β0=-0.88 HU,P<.001) and females (β0=−0.69 HU,P<.001), and an accelerated muscle attenuation decline-rate in males (βl=−0.08 HU/y,P<.05). Age-stratified analyses indicated that the accelerated muscle attenuation decline associated with smoking likely occurred at younger age, especially in females.ConclusionsAmong lung cancer screening participants, active cigarette smoking was associated with greater skeletal muscle fat infiltration in both males and females, and accelerated muscle adipose accumulation rate in males. These findings support the important role of smoking cessation in preserving muscle health.
WITHDRAWN: Molecular Analysis of Non-structural Protein 1 (NSP1) in Children Infected with Rotavirus in Babylon Province, Iraq: A Cross-Sectional Study
Authors: Mohsen M. Mohammed , Al-khafaji Zaytoon A , Mohammed Layth Jasim 
Published: December 2023

Withdrawal StatementThe authors have withdrawn their manuscript owing to [The research paper has been submitted to your esteemed journal, and actions have been taken regarding the paper without my knowledge (corresponding author), which is a violation of ethical standards in scientific research and reputable publishing. Kindly withdraw the research as this goes against the principles upheld by all contributors and those who do not support the unethical dissemination of work]. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.”
LWU-Net approach for Efficient Gastro-Intestinal Tract Image Segmentation in Resource-Constrained Environments
Authors: Sai Marreddi Jayanth , Punn Narinder Singh 
Published: December 2023

AbstractThis paper introduces a Lightweight U-Net (LWU-Net) method for efficient gastro-intestinal tract segmentation in resource-constrained environments. The proposed model seeks to strike a balance between computational efficiency, memory efficiency, and segmentation accuracy. The model achieves competitive performance while reducing computational power needed with improvements including depth-wise separable convolutions and optimised network depth. The evaluation is conducted using data from a Kaggle competition-UW Madison gastrointestinal tract image segmentation, demonstrating the model’s effectiveness and generalizability. The findings demonstrate that the LWU-Net model has encouraging promise for precise medical diagnoses in resource-constrained settings, enabling effective image segmentation with slightly less than a fifth of as many trainable parameters as the U-Net model.
Multi-omics analysis of the molecular response to glucocorticoids - insights into shared genetic risk from psychiatric to medical disorders
Authors: Knauer-Arloth Janine , Hryhorzhevska Anastasiia , Binder Elisabeth B. 
Published: December 2023

AbstractBackgroundGlucocorticoids play a crucial role as mediators of negative health effects associated with chronic stress, including increased risk for psychiatric disorders as well as cardiovascular and metabolic diseases. This study investigates the impact of genetic variants and glucocorticoid receptor (GR)-activation on gene expression and DNA methylation in peripheral blood and the relationship of these variants with disease risk.MethodsWe conducted a comprehensive molecular quantitative trait locus (QTL) analysis, mapping GR-methylation (me)QTLs, GR-expression (e)QTLs, and GR-expression quantitative trait methylation (eQTM) in a cohort of 199 individuals, with DNA methylation and RNA expression data collected before and after GR-activation with dexamethasone. A multi-level network analysis was employed to map the complex relationships between the transcriptome, epigenome, and genetic variation.ResultsWe identified 3,772 GR-meQTL CpGs corresponding to 114,134 local GR-meQTLs. eQTM and eQTL analyses revealed distinct genetic influences on RNA expression and DNA methylation. Multi-level network analysis uncovered GR-network trio QTLs, characterised by SNP-CpG-transcript combinations where meQTLs act as both eQTLs and eQTMs. These trios’ genes demonstrated enrichment in immune response and cell activation pathways and showed a significant overlap with transcripts altered by GR-activation in the mouse brain. GR-trio variants were enriched in GWAS for bipolar disorder, schizophrenia, autoimmune and cardiovascular diseases and traits, cytokines levels and BMI.ConclusionsGenetic variants modulating the molecular effects of glucocorticoids are associated with psychiatric as well as medical diseases. Our findings support stress as a shared risk factor for transdiagnostic negative health outcomes and may lead to innovative interventions targeting shared underlying molecular mechanisms.
The remarkable ups and downs of birth rate in Switzerland 2020 to 2023 in a historical context
Authors: Le Vu Mathilde , Matthes Katarina L. , Staub Kaspar 
Published: December 2023

AbstractWe follow population trends in the monthly birth rate in Switzerland almost up to the present and place the latest developments in a historical context. Birth rates in 2022 were the lowest since the 1870s, and the trend is continuing in 2023. The latest decline had already begun 1-2 years before Covid-19. Previous pandemics (1890, 1918, 1920, 1957) had led to a temporary decline in births ∽9 months after the epidemic peaks. With Covid-19, this appears more complex. During and shortly after the first two waves and shutdowns in 2020, there were more conceptions and thus excess birth rates in 2021, in all available subgroups except Italian-speaking Switzerland, and somewhat more pronounced among >30-year-old mothers and second parities. Possible reasons for the mini-boom include: The increased time at home during the shutdowns has – planned or not – led to more conceptions which has brought pregnancies forward; the corona virus was still circulat-ing too infrequently in this 1st phase of the pandemic to have a negative impact on pregnancies or fertility; at the end of the waves and shutdowns, the perceived end of the pandemic threat could have led to an optimistic mood and thus also more conceptions. The subsequent decline from January 2022 was stronger than the in-crease before. The first part of the decline in 2022 is most likely due to a negative rebound from the advance-ment of births in 2020/2021 and deliberately postponed pregnancies due to the start of the vaccination pro-gram. The second part of the decline in 2022 is associated with conceptions during the large Omicron wave in the winter of 2021/2022, when many people in Switzerland fell ill. In addition, prices have been rising and real wages falling since 2021, the global political situation has become more unstable, and a general change in values regarding the willingness to have children may also be underway. Following these observations at population level (with limited depth of variables), more in-depth studies must now follow to better under-stand the dynamic ups and downs in the birth rate in Switzerland in recent years.