bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correction of the scientific production: publisher performance evaluation using a dataset of 4844 PubMed retractions
Authors: Toma Catalin , Padureanu Liliana , Toma Bogdan 
Published: January 2022

BackgroundWithdrawal of problematic scientific articles after publication is one of the mechanisms for correcting the literature available to publishers, especially in the conditions of the ever-increasing trend of publishing activity in the medical field. The market volume and the business model justify publishers’ involvement in the post-publication quality control(QC) of scientific production. The limited information about this subject determined us to analyze retractions and the main retraction reasons for publishers with many withdrawn articles. We also propose a score to measure the evolution of their performance. The data set used for this article consists of 4844 PubMed retracted papers published between 1.01.2009 and 31.12.2020.MethodsWe have analyzed the retraction notes and retraction reasons, grouping them by publisher. To evaluate performance, we formulated an SDTP score whose calculation formula includes several parameters: speed (article exposure time(ET)), detection rate (percentage of articles whose retraction is initiated by the editor/publisher/institution without the authors’ participation), transparency (percentage of retracted articles available online and clarity of retraction notes), precision (mention of authors’ responsibility and percentage of retractions for reasons other than editorial errors).ResultsThe 4844 withdrawn articles were published in 1767 journals by 366 publishers, the average number of withdrawn articles/journal being 2.74. Forty-five publishers have more than ten withdrawn articles, holding 88% of all papers and 79% of journals. Combining our data with data from another study shows that less than 7% of PubMed journals withdrew at least one article. Only 10.5% of the withdrawal notes included the individual responsibility of the authors. Nine of the top 11 publishers had the largest number of articles withdrawn in 2020, in the first 11 places finding, as expected, some big publishers. Retraction reasons analysis shows considerable differences between publishers concerning the articles ET: median values between 9 and 43 months (mistakes), 9 and 73 months (images), 10 and 42 months (plagiarism & overlap).The SDTP score shows, between 2018 and 2020, an improvement in QC of four publishers in the top 11 and a decrease in the gap between 1st and 11th place. The group of the other 355 publishers also has a positive evolution of the SDTP score.ConclusionsPublishers have to get involved actively and measurably in the post-publication evaluation of scientific products. The introduction of reporting standards for retraction notes and replicable indicators for quantifying publishing QC can help increase the overall quality of scientific literature.
Rapid Selectivity to Natural Images Across Layers of Primate V1
Authors: Chen Xiaomo , Zhu Shude , Bai Kunlun , Xia Ruobing , Kong Nathan C.L. , Norcia Anthony M , Moore Tirin 
Published: January 2022

AbstractVisual systems are thought to have adapted to the statistical properties of natural scenes. However, the extent to which visual neurons respond selectively to natural images, and the stage at which that selectivity emerges remains unclear. To address these questions, we recorded the visual activity of neurons in macaque V1 using high-density electrode arrays (Neuropixels), and compared neuronal responses to images presented at three levels of naturalness. We found that within 60 ms of stimulus onset, neurons in all cortical layers, including input layers 4C alpha and beta, responded more vigorously to natural images than to statistically matched naturalistic texture and noise images. The result remained when residual variations in the local image statistics were factored out. V1 neurons also showed high population and lifetime sparseness for natural images. Across the population of V1 neurons, sensitivity to natural images exceeded the sensitivity to other image categories. The results reveal a rapid and pervasive preference for natural images is present at the earliest stages of cortical processing.
Variant to function mapping at single-cell resolution through network propagation
Authors: Yu Fulong , Cato Liam D. , Weng Chen , Liggett L. Alexander , Jeon Soyoung , Xu Keren , Chiang Charleston W.K. , Wiemels Joseph L. , Weissman Jonathan S. , de Smith Adam J. , Sankaran Vijay G. 
Published: January 2022

ABSTRACTWith burgeoning human disease genetic associations and single-cell genomic atlases covering a range of tissues, there are unprecedented opportunities to systematically gain insights into the mechanisms of disease-causal variation. However, sparsity and noise, particularly in the context of single-cell epigenomic data, hamper the identification of disease- or trait-relevant cell types, states, and trajectories. To overcome these challenges, we have developed the SCAVENGE method, which maps causal variants to their relevant cellular context at single-cell resolution by employing the strategy of network propagation. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation including enrichment of blood traits at distinct stages of human hematopoiesis, defining monocyte subsets that increase the risk for severe coronavirus disease 2019 (COVID-19), and identifying intermediate lymphocyte developmental states that are critical for predisposition to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution, but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.
LMM-MQM time series mapping - An application in a murine advanced intercross line identifies novel growth QTLs
Authors: Arends Danny , Hesse Deike , Kärst Stefan , Heise Sebastian , Lyu Shijie , Korkuc Paula , Delpero Manuel , Mulligan Megan K. , Prins Pjotr , Brockmann Gudrun A. 
Published: January 2022

AbstractThe Berlin Fat Mouse Inbred line 860 (BFMI860) is a mouse model for juvenile obesity. Previously, a recessive major effect locus (jObes1) was identified on chromosome 3 explaining around 26% of the body weight variance in an BFMI860xC57BL/6NCrl advanced intercross line. The aim of this study was to discover additional QTL.Time series body weight data were modeled using linear mixed models (LMM), while a multiple QTL mapping (MQM) approach compensated for the jObes1 locus effect. LMM-MQM identified five additional loci significantly associated with body weight. Variance explained by the jObes1 locus increased to 38.1% when using LMM-MQM mapping, while the additional loci explained between 2.0% and 3.9% of the body weight variance. Several positional candidate genes within the novel QTL regions were found in KEGG pathways for insulin signaling and insulin resistance. Strong distortion with preference for the BFMI allele was observed within a newly identified QTL containing the well-known Foxo1 regulator of adipocyte differentiation.Here, we present a novel method for QTL detection in time series data: LMM-MQM time series mapping. We show that our method is more powerful in detecting QTLs compared to single timepoint mapping approaches. Thus, the time series structure should be considered for optimal detection of small effect QTLs. LMM-MQM time series mapping can be used to find genetic determinants of all kind of “phenotypes over time” be it lactation curves in cattle, plant biomass, drug clearance in human clinical trials, or cognitive decline during disease.
Interactions between nuclear and mitochondrial SNPs and Parkinson’s disease risk
Authors: Pickett Sarah J. , Deen Dasha , Pyle Angela , Santibanez-Koref Mauro , Hudson Gavin 
Published: January 2022

AbstractInteractions between the products of the nuclear and mitochondrial genomes are critical for the function of most eukaryotic cells. Recently the introduction of mitochondrial replacement therapy has raised the question of incompatibilities between mitochondrial and nuclear variants, and their potential influence on the genetic makeup of human populations. Such interactions could also contribute to the variability of the penetrance of pathogenic DNA variants. This led us to investigate the frequencies of combinations of nuclear and mitochondrial SNP alleles (mitonuclear combinations) in healthy individuals (n=5375) and in a cohort of patients with Parkinson’s disease (PD, n=2210). In the unaffected population, we were not able to find associations between nuclear and mitochondrial variants with a false discovery rate below 0.05 after accounting for multiple testing (i.e., the number of combinations examined). However, in the PD cohort, five combinations surpassed this threshold. Next, combining both cohorts, we investigated whether these associations were modulated by disease status. All five combinations were significant (p<10−3 for all tests).These combinations also showed significant evidence for an effect of the interaction between the mitochondrial and nuclear variants on disease risk. Their nuclear components mapped to TBCA, NIBAN3 and GLT25D1 and an uncharacterised intergenic region. In summary, starting from a single cohort design we identified combinations of nuclear and mitochondrial variants affecting PD disease risk.
Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics
Authors: Cancino-Muñoz Irving , López Mariana G. , Torres-Puente Manuela , Villamayor Luis M. , Borrás Rafael , Borrás-Máñez María , Bosque Montserrat , Camarena Juan J. , Colijn Caroline , Colomer-Roig Ester , Colomina Javier , Escribano Isabel , Esparcia-Rodríguez Oscar , García-García Francisco , Gil-Brusola Ana , Gimeno Concepción , Gimeno-Gascón Adelina , Gomila-Sard Bárbara , González-Granda Daminana , Gonzalo-Jiménez Nieves , Guna-Serrano María Remedio , López-Hontangas José Luis , Martín-González Coral , Moreno-Muñoz Rosario , Navarro David , Navarro María , Orta Nieves , Pérez Elvira , Prat Josep , Rodríguez Juan Carlos , Ruiz-García Ma. Montserrat , Vanaclocha Hermelinda ,   Valencia Region Tuberculosis Working Group, Comas Iñaki 
Published: January 2022

AbstractBackgroundTransmission has been proposed as a driver of tuberculosis (TB) epidemics in high-burden regions, with negligible impact in low-burden areas. Genomic epidemiology can greatly help to quantify transmission in different settings but the lack of whole genome sequencing population-based studies has hampered its use to compare transmission dynamics and contribution across settings.MethodsWe generated an additional population-based sequencing dataset from Valencia Region, a low burden setting, and compared it with available datasets from different TB settings to reveal heterogeneity of transmission dynamics and its public health implications. We sequenced the whole genome of 785 M. tuberculosis strains and linked genomes to patient epidemiological data. We applied a pairwise distance clustering approach and phylodynamics methods to characterize transmission events over the last 150 years, in Valencia, Spain (low burden), Oxfordshire, United Kingdom (low burden) and a high-burden (Karonga, Malawi).ResultsOur results revealed high local transmission in the Valencia Region (47.4% clustering), in contrast to Oxfordshire (27% clustering), and similar to a high-burden setting like Malawi (49.8% clustering). By modelling times of the transmission events, we observed that settings with high transmission are associated with uninterrupted transmission of strains over decades, irrespective of burden.ConclusionsOur results underscore significant differences in transmission between TB settings even with similar burdens, reveal the role of past epidemic in on-going TB epidemic and highlight the need for in-depth characterization of transmission dynamics and specifically-tailored TB control strategies.FundingEuropean Research Council under the European Union’s Horizon 2020 research and innovation program (Grants 638553-TB-ACCELERATE, 101001038-TB-RECONNECT), and Ministerio de Ciencia e Innovación (Spanish Government, SAF2016-77346-R and PID2019-104477RB-I00)
Reduced resilience of brain state transitions in anti-N-Methyl-D-Aspartate receptor encephalitis
Authors: von Schwanenflug Nina , Ramirez-Mahaluf Juan P , Krohn Stephan , Romanello Amy , Heine Josephine , Prüss Harald , Crossley Nicolas A , Finke Carsten 
Published: January 2022

ABSTRACTObjectivePatients with anti-NMDA receptor encephalitis suffer from a severe neuropsychiatric syndrome, yet most patients show no abnormalities in routine magnetic resonance imaging. In contrast, advanced neuroimaging studies have consistently identified disrupted functional connectivity in these patients, with recent work suggesting increased volatility of functional state dynamics. Here, we investigate these network dynamics through the spatiotemporal trajectory of meta-state transitions, yielding a time-resolved account of brain state exploration in anti-NMDA receptor encephalitis.MethodsResting-state functional magnetic resonance imaging data were acquired in 73 patients with NMDAR encephalitis and 73 age- and sex-matched healthy controls. Time-resolved functional connectivity was clustered into brain meta-states, giving rise to a time-resolved transition network graph with states as nodes and transitions between brain meta-states as weighted, directed edges. Network topology, robustness, and transition cost of these transition networks were compared between groups.ResultsTransition networks of patients showed significantly lower local efficiency (t = -2.54, pFDR = 0.026), lower robustness (t = -2.01, pFDR = 0.048) and higher leap size (t = 2.33, pFDR = 0.026) compared to controls. Furthermore, the ratio of within-to-between module transitions and state similarity was significantly lower in patients. Importantly, alterations of brain state transitions correlated with disease severity.InterpretationThese findings reveal systematic alterations of transition networks in patients, suggesting that anti-NMDA receptor encephalitis is characterized by reduced stability of brain state transitions and that this reduced resilience of transition networks plays a clinically relevant role in the manifestation of the disease.
A metric and its derived protein network for evaluation of ortholog database inconsistency
Authors: Yang Weijie , Ji Jingsi , Ling Shuyang , Fang Gang 
Published: January 2022

AbstractOrthology prediction is challenging yet rewarding. Orthologs are the cornerstone of almost all comparative genomics studies. Dozens of ortholog resources have been available and broadly used over the past decades. However, the inconsistency between these resources has drawn growing concerns, especially when more proteomes are available and ortholog databases expand. It is no longer easy to decide which ortholog database to use, and it becomes necessary to compare conclusions based on different resources. We are presenting here a metric to assess ortholog functional consistency. Using this metric, we built a network connecting proteins based on their functional similarity. We then detected network communities as ortholog groups, and each protein in our ortholog group inherited the network degree centrality. By benchmarking Quest for Orthologs (QfO) and some representative ortholog resources, we concluded the degree centrality could serve as the index for the reliability of functional consistency. The numerical nature of degree centrality could also open a door for quantitative study in pan-genome and other comparative genomics studies.
Tuned geometries of hippocampal representations meet the demands of social memory
Authors: Boyle Lara M. , Posani Lorenzo , Irfan Sarah , Siegelbaum Steven A. , Fusi Stefano 
Published: January 2022

AbstractSocial recognition consists of multiple memory processes, including the detection of familiarity – the ability to rapidly distinguish familiar from novel individuals – and recollection – the effortful recall of where a social episode occurred and who was present. At present, the neural mechanisms for these different social memory processes remain unknown. Here, we investigate the population code for novel and familiar individuals in mice using calcium imaging of neural activity in a region crucial for social memory, the dorsal CA2 area of the hippocampus. We report that familiarity changes CA2 representations of social encounters to meet the different demands of social memory. While novel individuals are represented in a low-dimensional geometry that allows for rapid generalization, familiar individuals are represented in a higher-dimensional geometry that supports high-capacity memory storage. The magnitude of the change in dimensionality of CA2 representations for a given individual predicts the performance of that individual in a social recognition memory test, suggesting a direct relationship between the representational geometry and memory-guided behavior. Finally, we show that familiarity is encoded as an abstract variable with neural responses generalizing across different identities and spatial locations. Thus, through the tuning of the geometry of structured neural activity, CA2 is able to meet the complex demands of multiple social memory processes.
Shelterin is a Dimeric Complex with Extensive Structural Heterogeneity
Authors: Zinder John C , Olinares Paul Dominic B , Svetlov Vladimir , Bush Martin W , Nudler Evgeny , Chait Brian T , Walz Thomas , de Lange Titia 
Published: January 2022

AbstractHuman shelterin is a six-subunit complex – comprised of TRF1, TRF2, Rap1, TIN2, TPP1, and POT1 – that binds telomeres, protects them from the DNA-damage response, and regulates the maintenance of telomeric DNA. Although high-resolution structures have been generated of the individual structured domains within shelterin, the architecture and stoichiometry of the full complex are currently unknown. Here we report the purification of shelterin subcomplexes and reconstitution of the entire complex using full-length, recombinantly produced components. By combining negative-stain electron microscopy (EM), crosslinking mass spectrometry (XLMS), mass photometry, and native mass spectrometry (MS), we obtain stoichiometries as well as domain-scale architectures of shelterin subcomplexes and determine that they are extensively conformationally heterogenous. For POT1/TPP1 and POT1/TPP1/TIN2, we observe high variability in the positioning of the POT1 DNA-binding domain, the TPP1 OB fold, and the TIN2 TRFH domain with respect to the C-terminal domains of POT1. Truncation of unstructured linker regions in TIN2, TPP1, and POT1 did not reduce the conformational variability of the heterotrimer. Both shelterin and the TRF1/TIN2/TPP1/POT1 subcomplex primarily adopt fully dimeric complexes, even in the absence of DNA substrates. TRF1/TIN2/TPP1/POT1 and shelterin complex showed extensive conformational variability, regardless of the presence of DNA substrates. We conclude that shelterin adopts a multitude of conformations and argue that its unusual architectural variability is beneficial for its many functions at telomeres.
Chemical-induced degradation of PreS2 mutant surface antigen reverses HBV-mediated hepatocarcinogenesis
Authors: Yang Joey Yi , Wu Yi-Hsuan , Pan Max Yu-Chen , Chiou Yu-Ting , Lee Richard Kuan-Lin , Li Tian-Neng , Wang Lily Hui-Ching 
Published: January 2022

AbstractNaturally evolved immune-escape PreS2 mutant is an oncogenic caveat of liver cirrhosis and hepatocellular carcinoma (HCC) during chronic hepatitis B virus (HBV) infection. Notably, PreS2 mutants is prevalent in above 50% of patients with HCC. Intrahepatic expression of PreS2 mutant large surface antigen (PreS2-LHBS) induces endoplasmic reticulum stress, mitochondria dysfunction, cytokinesis failure and subsequent chromosome hyperploidy. In this study, we ask if long-term inhibition of PreS2-LHBS may act to reverse HBV-mediated hepatocarcinogenesis. We set up a stability reporter platform and identified ABT199 as an inhibitor of PreS2-LHBS from a library of 1068 FDA-approved drugs. Treatment of ABT199 induced PreS2-LHBS degradation without affecting the general cell viability, as shown in hepatoma and immortalized hepatocyte cell lines. We found that ABT199 induced the recruitment of PreS2-LHBS to ring-shaped structures in close proximity to lysosomal marker Lamp1 and multivesicular body marker Rab7. Simultaneously, inhibitions of lysosomal degradation or microautophagy restored the expression of PreS2-LHBS. Specifically, a 24-hr treatment of ABT199 reduced DNA damages and cytokinesis failure induced by PreS2-LHBS. Persistent treatment of ABT199 for 3 weeks reversed chromosome hyperploidy in PreS2-LHBS cells and suppressed anchorage-independent growth of HBV-positive hepatoma cell line. Together, we showed that ABT199 provoked selective degradation of PreS2-LHBS through the induction of microautophagy, and a long-term treatment of ABT199 reversed oncogenic mechanisms induced by HBV. Our results indicate that long-term degradation of PreS2-LHBS may serve as a novel therapeutic strategy to constrain HBV-mediated hepatocarcinogenesis.Graphical abstractAuthor summaryHBV PreS2 mutant large surface antigen (PreS2-LHBS) is an oncoprotein that induces liver cirrhosis and liver cancer. This study identified ABT199 as a potential inhibitor of PreS2-LHBS. We found that ABT199 could trigger the degradation of PreS2-LHBS through the induction of microautophagy. Moreover, a long-term treatment of ABT199 significantly reversed LHBS-induced oncogenic events including DNA damage, mitotic failure, chromosome hyperploidy, and anchorage-independent growth. This study not only identifies a specific inhibitor of PreS2-LHBS but also highlights a plausible strategy to constrain HBV-mediated hepatocarcinogenesis through targeting the degradation of PreS2-LHBS.
GAGAM: a genomic annotation-based enrichment of scATAC-seq data for Gene Activity Matrix
Authors: Martini Lorenzo , Bardini Roberta , Savino Alessandro , Di Carlo Stefano 
Published: January 2022

AbstractSingle-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) is rapidly becoming a powerful technology to assess the epigenetic landscape of thousands of cells. However, the current great sparsity of the resulting data poses significant challenges to their interpretability and informativeness. Different computational methods are available, proposing ways to generate significant features from accessibility data and process them to obtain meaningful results. In particular, the most common way to interpret the raw scATAC-seq data is through peak-calling, generating the peaks as features. Nevertheless, this method is dataset-dependent because the peaks are related to the given dataset and can not be directly compared between different experiments. For this reason, this study wants to improve on the concept of the Gene Activity Matrix (GAM), which links the accessibility data to the genes, by proposing a Genomic-Annotated Gene Activity Matrix (GAGAM), which aims to label the peaks and link them to the genes through functional annotation of the whole genome. Using genes as features solves the problem of the feature dataset dependency allowing for the link of gene accessibility and expression. The latter is crucial for gene regulation understanding and fundamental for the increasing impact of multi-omics data. Results confirm that our method performs better than the previous GAMs.