bluuebunny/crossref_metadata_2025_split huggingface dataset:
NetREm Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation
Authors: Khullar Saniya , Huang Xiang , Ramesh Raghu , Svaren John , Wang Daifeng 
Published: October 2023

AbstractTranscription factor (TF) coordination plays a key role in target gene (TG) regulation via protein-protein interactions (PPIs) and DNA co-binding to regulatory elements. Single-cell technologies facilitate gene expression measurement for individual cells and cell-type identification, yet the connection between TF coordination and TG regulation of various cell types remains unclear. To address this, we have developed a novel computational approach, Network Regression Embeddings (NetREm), to reveal cell-type TF-TF coordination activities for TG regulation. NetREm leverages network-constrained regularization using prior knowledge of direct and/or indirect PPIs among TFs to analyze single-cell gene expression data. We test NetREm by simulation data and benchmark its performance in 4 real-world applications that have gold standard TF-TG networks available: mouse (mESCs) and simulated human (hESCs) embryonic stem (ESCs), human hematopoietic stem (HSCs), and mouse dendritic (mDCs) cells. Further, we showcase NetREm’s ability to prioritize valid novel TF-TF coordination links in human Peripheral Blood Mononuclear cell (PBMC) sub-types. We apply NetREm to analyze various cell types in both central (CNS) and peripheral (PNS) nerve system (NS) (e.g. neuronal, glial, Schwann cells (SCs)) as well as in Alzheimer’s disease (AD). Our findings uncover cell-type coordinating TFs and identify new TF-TG candidate links. We validate our top predictions using Cut&Run and knockout loss-of-function expression data in rat/mouse models and compare results with additional functional genomic data, including expression quantitative trait loci (eQTL) and Genome-Wide Association Studies (GWAS) to link genetic variants (single nucleotide polymorphisms (SNPs)) to TF coordination. NetREm is open-source available on GitHub as a software package.
Dealing with lipid effects and lipid-extraction biases in δ13C and δ15N isotopic studies: a solution based on 28 marine invertebrate, fish and mammal species
Authors: Ouellet Jean-François , Cabrol Jory , Rioux Ève , Bordeleau Xavier , Lesage Véronique 
Published: October 2023

ABSTRACTLipids are naturally depleted in13C isotope in relation to its C sources, causing a bias in δ13C in bulk samples that varies with lipid content. Failure to take this issue into account results in inaccurate conclusions in food web and habitat use studies. Two approaches to resolve this issue are 1) to extract lipids from samples prior to measurement, a resource-intensive process that also can alter δ15N or 2) estimating a lipid-free δ13C using one of several equations that differ in levels of sophistication and generalization across taxa. Here δ13C and δ15N were measured on bulk and lipid-extracted muscle samples of a dataset of over 2000 specimens of 28 species of marine invertebrates, fishes and mammals. Our objectives were to 1) compare the effect of lipid extraction on δ13C and δ15N across taxa; 2) compare the performance of five normalization models, overall and on subsets of species; 3) propose a model to revert lipid-extracted δ15N back to their bulk values; and 4) identify the most suitable approach for dealing with lipid biases in isotopic ratios. Extraction caused an uneven enrichment in δ13C and δ15N across species. Model taxonomic specificity increased estimate accuracy in both isotopes. Models from Logan et al. (2008) and McConnaughey and McRoy (1979) performed better than the other models tested. δ15Nbulkcould be reliably estimated based on δ15Nlipid-extractedusing a linear model. This study provides a way forward for obtaining reliable δ13C and δ15N values in muscle tissue without the costs of duplicate analyses and represents a major step toward the harmonization of datasets collected under the two different approaches.
Replicability of bulk RNA-Seq differential expression and enrichment analysis results in cancer research
Authors: Degen Peter , Medo Matúš 
Published: October 2023

AbstractThe high-dimensional and heterogeneous nature of transcriptomics data from RNA sequencing (RNA-Seq) experiments poses a challenge to routine down-stream analysis steps, such as differential expression analysis and enrichment analysis. Additionally, due to practical and financial constraints, RNA-Seq experiments are often limited to a small number of biological replicates; three replicates is a commonly employed minimum cohort size. In light of recent studies on the low replicability of preclinical cancer research, it is essential to understand how the combination of population heterogeneity and underpowered cohort sizes affects the replicability of RNA-Seq research. Using 7’000 simulated RNA-Seq experiments based on real gene expression data from seven different cancer types, we find that the analysis results from underpowered experiments exhibit inflated effect sizes and are unlikely to replicate well. However, the ground-truth results obtained by analyzing large cohorts show that the precision of differentially expressed genes can be high even for small cohort sizes. The poor replicability of underpowered experiments is thus a direct consequence of their low recall (sensitivity). In other words, the low replicability of underpowered RNA-Seq cancer studies does not necessarily indicate a high prevalence of false positives. Instead, the results obtained from such studies are limited to small and mostly random subsets of a larger ground truth. We conclude with a set of practical recommendations to alleviate problems with underpowered RNA-Seq studies.Author SummaryTranscriptomics data from RNA sequencing (RNA-Seq) experiments are complex and challenging to analyze due to their high dimensionality and variability. These experiments often involve limited biological replicates due to practical and financial constraints. Recent concerns about the replicability of cancer research highlight the need to explore how this combination of limited cohort sizes and population heterogeneity impacts the reliability of RNA-Seq studies. To investigate these issues, we conducted 7’000 simulated RNA-Seq experiments based on real gene expression data from seven different cancer types. We show that experiments with small cohort sizes tend to produce results with exaggerated effects that can be difficult to replicate. We further found that while underpowered studies with few replicates indeed lead to little-replicable results, the identified differentially expressed genes are reliable as shown by low rates of false positives. Each underpowered study thus discovers a small subset of the ground truth. Our study concludes with practical recommendations for RNA-Seq studies with small cohort sizes.
ABIN1 is a negative regulator of effector functions in cytotoxic T cells
Authors: Janusova Sarka , Paprckova Darina , Michalik Juraj , Uleri Valeria , Drobek Ales , Salyova Eva , Chorfi Louise , Neuwirth Ales , Prochazka Jan , Sedlacek Radislav , Draber Peter , Stepanek Ondrej 
Published: October 2023

AbstractT cells are pivotal in the adaptive immune defense, necessitating a delicate balance between robust response against infections and self-tolerance. Their activation involves intricate cross-talk among signaling pathways triggered by the T-cell antigen receptors (TCR) and co-stimulatory or inhibitory receptors. The molecular regulation of these complex signaling networks is still incompletely understood. We identified an adaptor protein, ABIN1 as a component of the signaling complexes of GITR and OX40 co-stimulation receptors. T cells lacking ABIN1 are hyper-responsive ex vivo, and exhibit enhanced responses to cognate infections, and superior ability to induce experimental autoimmune diabetes in mice. We observed that ABIN1 negatively regulates NF-κB and p38 pathways. The latter was at least partially responsible for the upregulation of key effector proteins, IFNG and GZMB in ABIN1-deficient T cells after TCR stimulation. Our findings reveal the intricate role of ABIN1 in T-cell regulation and its potential as a target for therapeutic fine-tuning of T-cell responses.
Assessing the overlap between fishing activities and chondrichthyans distribution exposes high-risk areas for bycatch of threatened species
Authors: Maioli Federico , Weigel Benjamin , Lindmark Max , Manfredi Chiara , Zupa Walter , Bitetto Isabella , Russo Tommaso , Casini Michele 
Published: October 2023

AbstractSharks, rays, and chimaeras (chondrichthyans) play a crucial role in marine ecosystem functioning but are highly vulnerable to fishing. Hence, understanding the spatial overlap between chondrichthyans and fishing effort is essential for effective conservation and management. Here, we propose an integrated approach that combines Vessel Monitoring System data with geostatistical species distribution models to assess the potential impact of fishing on chondrichthyan populations in the western Adriatic Sea. By mapping the overlap between model-based chondrichthyan distribution, species richness, and the proportion of threathened species with bottom trawl fishing activities, we identify areas at high risk for chondrichthyan bycatch. Our findings show that many of these species are at risk across a large part of their distribution within the study area. Notably, there is a substantial spatial overlap between regions where threatened chondrichthyans are found and species-rich areas with locations of intensive bottom trawl fishing in the northern and central offshore regions of the western Adriatic, emphasizing the vulnerability of these species to fishing pressure. Furthermore, differences in overlap between distinct fishing gears highlight the importance of considering specific fishing practices when formulating management strategies. While our work provides novel insights to potential bycatch hotspots, limitations related to data sources, spatial resolution, and the inability to directly quantify fishing impacts should be considered. Nonetheless, our findings contribute to the development of targeted conservation and spatial management measures, offering a general approach to study model-based spatial hotspots aimed at protecting and sustaining chondrichthyan populations in the heavily exploited Adriatic Sea.
Fibrinogen and complement factor H: The two crucial markers of Parkinson’s disease with cognitive impairment
Authors: Naskar Aditi , Sachin M , Sengupta Senjuti , Bhadrachalam Pallavi , Hegde Shantala , Yadav Ravi , Pal Pramod Kumar , Alladi Phalguni Anand 
Published: October 2023

AbstractAnimal model-assisted validation is vital for biomarker studies. It provides better means for understanding disease pathogenesis and opens avenues for addressing therapeutics. Our earlier non-targeted label free proteomics-based biomarker study on CSF of Parkinson’s disease (PD) patients with cognitive impairment (PDCI), revealed the presence of elevated levels of fibrinogen and complement factor H (CFAH) in PDCI-CSF. In the present study, we aimed to determine if these proteins harbor a pathogenic potential, when present above physiological levels. Native fibrinogen and recombinant CFAH were intraperitoneally injected in adult C57BL/6J mice and 48h later, motor and cognitive behavioral deficits as well as their neuroanatomical correlates were noted. The reduction in stride length in fibrinogen and CFAH injected mice indicate shuffling gait, often seen in PD patients. Motor deficit was complemented by the loss of dopaminergic (DA) neurons in SNpc, compensatory hypertrophy of the surviving neurons, and reduction in TH expression in striatum, thus reminiscing PD pathology. The low discrimination index in (novel object recognition) NOR test complemented by morphological alterations in Nissl-stained CA-1 and subiculum neurons in the fibrinogen-injected mice imply recognition memory deficits. Thus, our study provides objective evidence that fibrinogen and CFAH harbor the potential to induce motor deficits and cognitive impairments in mice, akin to the PDCI-associated neuro-pathological deficits, and thus are potential biomarkers.
Land use and oriental pied hornbill occurrence in Singapore
Authors: Yahya Zaheedah , Chin Min Yi , Syaddad Adlan , Johns Philip 
Published: October 2023

AbstractOriental pied hornbills (Anthracoceros albirostris)disappeared from Singapore in the 1800s but were reintroduced in the 2000s. Since then, they have multiplied and even thrived in Singapore, spreading throughout much of the country. Because Singapore is extremely urban and densely populated, here we examine where hornbills have been seen as a function of land-use. We combine citizen science data from eBird and iNaturalist with GIS information to model hornbill sightings. We find that the percent Park and Beach cover have strong positive effects on the probability of hornbill sightings, and that percent Park cover has a positive interaction with percent Built-up and Sea cover. Our results are broadly consistent with sightings of oriental pied hornbills in the region.
Structure-Based Discovery of a NPFF1R Antagonist with Analgesic Activity
Authors: Bender Brian J. , Pickett Julie E. , Braz Joao , Kang Hye Jin , Gahbauer Stefan , Bhardwaj Karnika , Rodriguez-Rosado Sian , Liu Yongfeng , Jain Manish , Basbaum Allan I. , Roth Bryan L. , Shoichet Brian K. 
Published: October 2023

AbstractWhile opioid drugs remain among the most effective analgesics for pain management, adverse effects limit their use. Molecules that synergize with opioids, increasing analgesia without increasing side effects, could prove beneficial. A potential way to do so is via the RF-amide receptor system, as NPFFR1 agonists reduce µ- opioid receptor (µOR)-based analgesia while antagonists increase it. These inferences are, however, clouded by the lack of selectivity of most NPFF1R ligands. Seeking selective antagonists of the NPFF1R, we screened a large virtual library against a homology model of NPFF1R. From 26 high-ranking molecules that were synthesized and tested, one antagonized NPFF1R with a Kiof 319 nM. Structure-based optimization led to a 22 nM antagonist of NPFF1R, compound56, with selectivity against a large panel of GPCRs. When administered alone,56has no activity in mouse tail-flick nociception assays. However, coadministration of compound 56 and morphine produced significantly greater antinociception than did morphine alone, consistent with the notion that NPFF1R nociceptive activity occurs via modulation of µOR signaling. Surprisingly, in the hot-plate assays56was analgesic by itself, suggesting that NPFF1R alone can also confer analgesia. At equi-analgesic doses, combinations of56with morphine reduced the common constipation side effect of morphine versus using morphine alone. The high selectivity of56and its activity in cooperation with morphine supports further analgesic development against NPFF1R and against the RF-amide family of receptors more generally.
Uncovering uncharacterized binding of transcription factors from ATAC-seq footprinting data
Authors: Schultheis Hendrik , Bentsen Mette , Heger Vanessa , Looso Mario 
Published: October 2023

AbstractTranscription factors (TFs) are crucial epigenetic regulators, which enable cells to dynamically adjust gene expression in response to environmental signals. Computational procedures like digital genomic footprinting on chromatin accessibility assays such as ATACseq can be used to identify bound TFs in a genome-wide scale. This method utilizes short regions of low accessibility signals due to steric hindrance of DNA bound proteins, called footprints (FPs), which are combined with motif databases for TF identification. However, while over 1600 TFs have been described in the human genome, only ∼700 of these have a known binding motif. Thus, a substantial number of FPs without overlap to a known DNA motif are normally discarded from FP analysis. In addition, the FP method is restricted to organisms with a substantial number of known TF motifs. Here we present DENIS (DE Novo motIf diScovery), a framework to generate and systematically investigate the potential of de novo TF motif discovery from FPs. DENIS includes functionality i) to isolate FPs without binding motifs, ii) to perform de novo motif generation and iii) to characterize novel motifs. Here, we show that the framework rediscovers artificially removed TF motifs, quantifies de novo motif usage during an early embryonic development example dataset, and is able to analyze and uncover TF activity in organisms lacking canonical motifs. The latter task is exemplified by an investigation of a scATAC-seq dataset in zebrafish which covers different cell types during hematopoiesis.
A data-adaptive method for investigating effect heterogeneity with high-dimensional covariates in Mendelian randomization
Authors: Tian Haodong , Tom Brian D. M. , Burgess Stephen 
Published: October 2023

AbstractMendelian randomization is a popular method for causal inference with observational data that uses genetic variants as instrumental variables. Similarly to a randomized trial, a standard Mendelian randomization analysis estimates the population-averaged effect of an exposure on an outcome. Dividing the population into subgroups can reveal effect heterogeneity to inform who would most benefit from intervention on the exposure. However, as covariates are measured post-”randomization”, naive stratification typically induces collider bias in stratum-specific estimates. We extend a previously proposed stratification method (the “doubly-ranked method”) to form strata based on a single covariate, and introduce a data-adaptive random forest method to calculate stratum-specific estimates that are robust to collider bias based on a high-dimensional covariate set. We also propose measures to assess heterogeneity between stratum-specific estimates (to understand whether estimates are more variable than expected due to chance alone) and variable importance (to identify the key drivers of effect heterogeneity). We show that the effect of body mass index (BMI) on lung function is heterogeneous, depending most strongly on hip circumference and weight. While for most individuals, the predicted effect of increasing BMI on lung function is negative, it is positive for some individuals and strongly negative for others.
Boosting the power of rare variant association studies by imputation using large-scale sequencing population
Authors: Dai Jinglan , Zhang Yixin , Li Zaiming , Li Hongru , Du Sha , You Dongfang , Zhang Ruyang , Zhao Yang , Liu Zhonghua , Christiani David C. , Chen Feng , Shen Sipeng 
Published: October 2023

AbstractRare variants can explain part of the heritability of complex traits that are ignored by conventional GWASs. The emergence of large-scale population sequencing data provides opportunities to study rare variants. However, few studies systematically evaluate the extent to which imputation using sequencing data can improve the power of rare variant association studies. Using whole genome sequencing (WGS) data (n = 150,119) as the ground truth, we described the landscape and evaluated the consistency of rare variants in SNP array (n = 488,377) imputed from TOPMed or HRC+UK10K in the UK Biobank, respectively. The TOPMed imputation covered more rare variants, and its imputation quality could reach 0.5 for even extremely rare variants. TOPMed-imputed data was closer to WGS in all MAC intervals for three ethnicities (average Cramer’s V>0.75). Furthermore, association tests were performed on 30 quantitative and 15 binary traits. Compared to WGS data, the identified rare variants in TOPMed-imputed data increased 27.71% for quantitative traits, while it could be improved by ∼10-fold for binary traits. In gene-based analysis, the signals in TOPMed-imputed data increased 111.45% for quantitative traits, and it identified 15 genes in total, while WGS only found 6 genes for binary traits. Finally, we harmonized SNP array and WGS data for lung cancer and epithelial ovarian cancer. More variants and genes could be identified than from WGS data alone, such asBRCA1,BRCA2, andCHRNA5. Our findings highlighted that incorporating rare variants imputed from large-scale sequencing populations could greatly boost the power of GWAS.
The roles of DDR2 and substrate stiffness on cancer cell transcriptome and proliferation
Authors: Vessella Theadora , Xiang Steven , Xiao Cong , Stilwell Madelyn , Shohet Jason , Rozen Esteban , Zhou Susan , Wen Qi 
Published: October 2023

AbstractThe interactions between cancer cells and the ECM regulate carcinogenesis. The collagen receptor kinase DDR2 is dysregulated in certain cancer cells, but its precise role in these malignancies remains unclear. In this study, we perform RNA-seq to determine how DDR2 and the biomechanical environment regulate cancer cell behaviors. We show that DDR2 knockdown in SH-SY5Y neuroblastoma cells inhibits proliferation and promotes senescence by regulating relevant genes. Increasing substrate stiffness reduces proliferation and promotes cell spreading but does not change senescence or transcriptome. Furthermore, DDR2 knockdown modulates cellular responses to substrate stiffness changes, unraveling a crosstalk between DDR2 and mechanosensing. These findings indicate DDR2 and ECM biomechanics regulate cancer cell behavior through distinct mechanisms, providing new mechanistic insights of cancer progression.
Spatiotemporal dynamics and epidemiological impact of SARS-CoV-2 XBB lineages dissemination in Brazil in 2023
Authors: Arantes Ighor , Gomes Marcelo , Ito Kimihito , Sarafim Sharbilla , Miyajima Fábio , Khouri Ricardo , Gräf Tiago , Siqueira Marilda Mendonça , Resende Paola Cristina , Naveca Felipe Gomes , Bello Gonzalo ,   COVID-19 Fiocruz Genomic Surveillance Network
Published: October 2023

ABSTRACTThe SARS-CoV-2 XBB is a group of highly immune-evasive lineages of the Omicron VOC that emerged by recombining BA.2-descendent lineages and spread worldwide during 2023. In this study, we combine SARS-CoV-2 genomic data (n =11,065 sequences) with epidemiological data of Severe Acute Respiratory Infection (SARI) cases collected in Brazil between October 2022 and July 2023 to reconstruct the space-time dynamics and epidemiologic impact of XBB dissemination in the country. Our analyses revealed that the introduction and local emergence of lineages carrying convergent mutations within the Spike protein, especially F486P, F456L, and L455F, propelled the spread of XBB* lineages in Brazil. The average relative instantaneous reproduction numbers of XBB*+F486P, XBB*+F486P+F456L, and XBB*+F486P+ F456L+L455F lineages in Brazil were estimated to be 1.24, 1.33, and 1.48 higher than that of other co-circulating lineages (mainly BQ.1*/BE*), respectively. Despite such a growth advantage, the dissemination of these XBB* lineages had a reduced impact on Brazil’s epidemiological scenario concerning previous Omicron subvariants. The peak number of SARI cases from SARS-CoV-2 during the XBB wave was approximately 90%, 80%, and 70% lower than that observed during the previous BA.1*, BA.5*, and BQ.1* waves, respectively. These findings revealed the emergence of multiple XBB lineages with progressively increasing growth advantage, yet with relatively limited epidemiological impact in Brazil throughout 2023. The XBB*+F486P+F456L+L455F lineages stand out for their heightened transmissibility, warranting close monitoring in the months ahead.