bluuebunny/crossref_metadata_2025_split huggingface dataset:
TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile
Authors: Yang Tianqi , Henao Ricardo 
Published: February 2022

ABSTRACTDetermining transcriptional factor binding sites (TFBSs) is critical for understanding the molecular mechanisms regulating gene expression in different biological conditions. Biological assays designed to directly mapping TFBSs require large sample size and intensive resources. As an alternative, ATAC-seq assay is simple to conduct and provides genomic cleavage profiles that contain rich information for imputing TFBSs indirectly. Previous footprint-based tools are inheritably limited by the accuracy of their bias correction algorithms and the efficiency of their feature extraction models. Here we introduce TAMC (Transcriptional factor binding prediction fromATAC-seq profile atMotif-predicted binding sites usingConvolutional neural networks), a deep-learning approach for predicting motif-centric TF binding activity from paired-end ATAC-seq data. TAMC does not require bias correction during signal processing. By leveraging a onedimensional convolutional neural network (1D-CNN) model, TAMC captures both footprint and non-footprint features at binding sites for each TF and outperforms existing footprinting tools in TFBS prediction particularly for ATAC-seq data with limited sequencing depth.AUTHOR SUMMARYApplications of deep-learning models are rapidly gaining popularity in recent biological studies because of their efficiency in analyzing non-linear patterns from feature-rich data. In this study, we developed a 1D-CNN model to predict TFBSs from ATAC-seq data. Compared to previous models using scoring functions and classical machine learning algorithms, our 1D-CNN model forgoes the need for bias correction during signal processing and significantly increases the efficiency in extracting features for TFBS prediction. In addition, the performance of our 1D-CNN model improves when the sequencing depth of training ATAC-seq data increases. Importantly, we showed that our method outperforms existing tools in TFBS prediction particularly when the sequencing depth of training ATAC-seq data is higher than the ATAC-seq data for prediction. This widened the applicability of our model to ATAC-seq data with both deep and shallow sequencing depth. Based on these results, we discussed about the potential application of our method to TFBS predication using bulk and single-cell ATAC-seq data.
MoveApps - a serverless no-code analysis platform for animal tracking data
Authors: Kölzsch Andrea , Davidson Sarah C. , Gauggel Dominik , Hahn Clemens , Hirt Julian , Kays Roland , Lang Ilona , Lohr Ashley , Russell Benedict , Scharf Anne K. , Schneider Gabriel , Vinciguerra Candace M. , Wikelski Martin , Safi Kamran 
Published: February 2022

AbstractBackgroundBio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills.ResultsWe developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface.Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository.The platform was beta launched in spring 2021 and currently contains 44 Apps that are used by 156 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements.ConclusionsThe MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.
TCRen: predicting TCR recognition of unseen epitopes based on residue-level pairwise statistical potential
Authors: Karnaukhov Vadim K. , Shcherbinin Dmitrii S. , Chugunov Anton O. , Chudakov Dmitriy M. , Efremov Roman G. , Zvyagin Ivan V. , Shugay Mikhail 
Published: February 2022

AbstractPrediction of TCR-peptide interactions has great importance for therapy of cancer, infectious and autoimmune diseases, but remains a major challenge, particularly for unseen epitopes. We present a structure-based method that enables scoring of TCR-peptide interactions using an energy potential (TCRen) derived from statistics of TCR-peptide contacts in existing crystal structures. We show that TCRen has high performance in discriminating cognate/unrelated peptides and can facilitate the identification of cancer neoepitopes recognized by tumor-infiltrating lymphocytes.
Cold-inducible promoter-driven knockdown of Brachypodium antifreeze proteins confers freeze sensitivity
Authors: Juurakko Collin L. , Bredow Melissa , diCenzo George C. , Walker Virginia K. 
Published: February 2022

AbstractThe model forage crop, Brachypodium distachyon, has a family of ice recrystallization inhibition (BdIRI) genes, which encode antifreeze proteins that function by adsorbing to ice crystals and inhibiting their growth. The genes were previously targeted for knockdown using a constitutive CaMV 35S promoter and the resulting transgenic Brachypodium showed reduced antifreeze activity and a greater susceptibility to freezing. However, the transgenic plants also showed developmental defects with shortened stem lengths and were almost completely sterile, raising the possibility that their reduced freeze tolerance could be attributed to developmental deficits. A cold-induced promoter from rice (prOsMYB1R35) has now been substituted for the constitutive promoter to generate temporal miRNA-mediated Brachypodium antifreeze protein knockdowns. Although transgenic lines showed no apparent pleiotropic developmental defects, they demonstrated reduced antifreeze activity as assessed by assays for ice-recrystallization inhibition, thermal hysteresis, electrolyte leakage, leaf infrared thermography, and leaf damage after infection with an ice nucleating phytopathogen. Strikingly, the number of cold-acclimated transgenic plants that survived freezing at -8 °C was reduced by half or killed entirely, depending on the line, compared to cold-acclimated wild type plants. Although these proteins have been studied for almost 60 years, this is the first unequivocal demonstration in any organism of the utility of antifreeze protein function and their contribution to freeze protection, independent of obvious developmental defects. These proteins are thus of potential interest in a wide range of biotechnological applications from accessible cryopreservation, to frozen product additives, to the engineering of transgenic crops with enhanced freezing tolerance.
Squamation and scale morphology at the root of jawed vertebrates
Authors: Wang Yajing , Zhu Min 
Published: February 2022

AbstractPlacoderms, the most basal jawed vertebrates, are crucial to understanding how the characters of crown gnathostomes comprising Chondrichthyes and Osteichthyes evolved from their stem relatives. Despite the growing knowledge on the anatomy and diversity of placoderms over the past decade, the dermal scales of placoderms are predominantly known from isolated material, either morphologically or histologically, resulting in their squamation being poorly understood. Here we provide a comprehensive description of the squamation and scale morphology of a primitive taxon of Antiarcha (a clade at the root of jawed vertebrates),Parayunnanolepis xitunensis, based on the virtual restoration of an articulated specimen by using X-ray computed tomography. Thirteen morphotypes of scales are classified to exhibit how the morphology changes with their position on the body in primitive antiarchs, based on which nine areas of the post-thoracic body are distinguished to show their scale variations in the dorsal, flank, ventral, and caudal lobe regions. In this study, the histological structure of yunnanolepidoid scales was described for the first time based on disarticulated scales from the type locality and horizon ofP. xitunensis, demonstrating that yunnanolepidoid scales are remarkably different from the dermal plates of antiarchs including yunnanolepidoids in the absence of developed middle layer. Together, our study reveals that the high regionalization of squamation and the bipartite histological structure of scale might be plesiomorphic for antiarchs, and jawed vertebrates in general.
Managing beach access and vehicle impacts following reconfiguration of the landscape by a natural hazard event
Authors: Orchard Shane , Fischman Hallie S. , Schiel David R. 
Published: February 2022

AbstractAfter New Zealand’s 7.8 Mw Kaikōura earthquake in late 2016 an unexpected anthropogenic effect involved increased motorised vehicle access to beaches. We show how these effects were generated by landscape reconfiguration associated with coastal uplift and widening of high-tide beaches, and present analyses of the distribution of natural environment values in relation to vehicle movements and impacts. Access changes led to extensive vehicle tracking in remote areas that had previously been protected by natural barriers. New dunes formed seaward of old dunes and have statutory protection as threatened ecosystems, yet are affected by vehicle traffic. Nesting grounds of nationally vulnerable banded dotterel (Charadrius bicinctus bicinctus) co-occur with vehicle tracking. An artificial nest experiment showed that vehicle strikes pose risks to nesting success, with 91% and 83% of nests destroyed in high and moderate-traffic areas, respectively, despite an increase in suitable habitat. Despite gains for recreational vehicle users there are serious trade-offs with environmental values subject to legal protection and associated responsibilities for management authorities. In theory, a combination of low-impact vehicle access and environmental protection could generate win-win outcomes from the landscape changes, but is difficult to achieve in practice. Detailed information on sensitive areas would be required to inform designated vehicle routes as a potential solution, and such sensitivities are widespread. Alternatively, vehicle access areas that accommodate longstanding activities such as boat launching could be formally established using identified boundaries to control impacts further afield. Difficulties for the enforcement of regulatory measures in remote areas also suggest a need for motivational strategies that incentivise low-impact behaviours. We discuss options for user groups to voluntarily reduce their impacts, the importance of interactions at the recreation-conservation nexus, and need for timely impact assessments across the social-ecological spectrum after physical environment changes -- all highly transferable principles for other natural hazard and disaster recovery settings worldwide.
Reclassifying Cancer: Defining tumour cell cycle activity in terms of its tissue of origin in over 13,000 samples
Authors: Lundberg Arian , Yi Joan Jong Jing , Lindström Linda S. , Tobin Nicholas P. 
Published: February 2022

AbstractGenomic alterations resulting in loss of control over the cell cycle is a fundamental hallmark of human malignancies. Whilst pan-cancer studies have broadly assessed tumour genomics and their impact on oncogenic pathways, analyses taking the baseline signalling levels in normal tissue into account are lacking. To this end, we aimed to reclassify the cell cycle activity of tumours in terms of their tissue of origin and determine the DNA mutations, chromosome arm-level changes and signalling pathways driving cell cycle activity. Combining normal tissue and pan-cancer data from over 13,000 samples we demonstrate that tumours of gynaecological origin show the highest levels of baseline corrected cell cycle activity, partially owing to hormonal signalling and gene expression changes. We also show that normal and tumour tissues can be separated into groups (quadrants) of low/high cell cycle activity and propose the novel hypothesis of an upper limit on these activity levels in tumours.
Mechanistic model for human brain metabolism and its connection to the neurovascular coupling
Authors: Sundqvist Nicolas , Sten Sebastian , Engström Maria , Cedersund Gunnar 
Published: February 2022

AbstractThe neurovascular and neurometabolic couplings (NVC and NMC) connects cerebral activity, blood flow, and metabolism. This interconnection is used in for instance functional imaging, which analyses the blood-oxygen-dependent (BOLD) signal. The mechanisms underlying the NVC are complex, which warrants a model-based analysis of data. We have previously developed a mechanistically detailed model for the NVC, and others have proposed detailed models for cerebral metabolism. However, existing metabolic models are still not fully utilizing available magnetic resonance spectroscopy (MRS) data and are not connected to detailed models for NVC. Therefore, we herein present a new model that integrates mechanistic modelling of both MRS and BOLD data. The metabolic model covers central metabolism, using a minimal set of interactions, and can describe time-series data for glucose, lactate, aspartate, and glutamate, measured after visual stimuli. Statistical tests confirm that the model can describe both estimation data and predict independent validation data, not used for model training. The interconnected NVC model can simultaneously describe BOLD data and can be used to predict expected metabolic responses in experiments where metabolism has not been measured. This model is a step towards a useful and mechanistically detailed model for cerebral blood flow and metabolism, with potential applications in both basic research and clinical applications.Author summaryThe neurovascular and neurometabolic couplings are highly central for several clinical imaging techniques since these frequently use blood oxygenation (the BOLD signal) as a proxy for neuronal activity. This relationship is described by the highly complex neurovascular and neurometabolic couplings, which describes the balancing between increased metabolic demand and blood flow, and which involves several cell-types and regulatory systems, which all change dynamically over time. While there are previous works that describe the neurovascular coupling in detail, neither we nor others have developed connections to corresponding mechanistic models for the third aspect, the metabolic aspect. Furthermore, magnetic resonance spectroscopy (MRS) data for such modelling readily is available. In this paper we present a minimal mechanistic model that can describe the metabolic response to visual stimuli. The model is trained to describe experimental data for the relative change in metabolic concentrations of several metabolites in the visual cortex during stimulation. The model is also validated against independent validation data, that was not used for model training. Finally, we also connect this metabolic model to a detailed mechanistic model of the neurovascular coupling. Showing that the model can describe both the metabolic response and a neurovascular response simultaneously.
Mismatches in gene deletions and kidney-related proteins are novel histocompatibility factors in kidney transplantation
Authors: Markkinen Salla , Helanterä Ilkka , Lauronen Jouni , Lempinen Marko , Partanen Jukka , Hyvärinen Kati 
Published: February 2022

ABSTRACTBackgroundThe genomic mismatch level between donor and recipient is associated with the risk of acute rejection and long-term graft survival. In the present study, we determined the association of genome-level matching with acute rejection in a single-center kidney transplantation cohort.MethodsAltogether, 1025 pairs of deceased donors and kidney transplant recipients transplanted in 2007–2017 were genotyped. The associations between the sums of whole genome missense variant mismatches and missense mismatches in transmembrane, secretory, and kidney-related proteins, with acute rejection were estimated using Cox proportional hazards model. Additionally, we analyzed 40 common deletion-tagging variants using Cox model.ResultsThe increasing mismatch sum in kidney-related proteins associated with acute rejection with an unadjusted HR of 1.15 (95% CI, 1.01–1.30; P=0.029) when dividing the sum into quartiles. The sums of other mismatches were not associated with acute rejection. In deletion analysis, a mismatch in rs7542235 (NC_000001.11:g.196854483A>G), genotype GG tagging a homozygous deletion at the complement Factor H-related (CFHR) proteins locus, predisposed to acute rejection with adjusted HR of 2.97 (95% CI, 1.46–6.05; P=0.003).ConclusionsThe present study supports that mismatches in gene deletions and kidney-related proteins are novel histocompatibility factors in kidney transplantation. The relative importance of different gene deletions varies between populations, as we found evidence for CFH-related gene deletion but not for the previously reported LIMS1 deletion.SIGNIFICANCE STATEMENTThe first genome-wide association studies have not identified strong candidate genes for complication risks of kidney transplantation whereas matching of non-HLA genes may be promising. The current study determined the association of genome-level matching with acute rejection among 1025 kidney transplant pairs. The increasing mismatch sum in kidney-related proteins was associated with acute allograft rejection. Also, an association between acute allograft rejection and rs7542235 genotype GG, tagging a homozygous deletion at the complement factor H-related (CFHR) loci on chr 1 was found. The present study suggests that mismatches in gene deletions and kidney-related proteins are important novel histocompatibility factors in kidney transplantation.
Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer
Authors: Challoner Benjamin R. , Woolston Andrew , Lau David , Buzzetti Marta , Fong Caroline , Barber Louise J. , Anandappa Gayathri , Crux Richard , Assiotis Ioannis , Fenwick Kerry , Begum Ruwaida , Begum Dipa , Lund Tom , Sivamanoharan Nanna , Sansano Harold B. , Domingo-Arada Melissa , Tran Amina , Eccles Bryony , Ellis Richard , Falk Stephen , Hill Mark , Krell Daniel , Murugaesu Nirupa , Nolan Luke , Potter Vanessa , Saunders Mark , Shiu Kai-Keen , Guettler Sebastian , Alexander James L. , Lázare-Iglesias Héctor , Kinross James , Murphy Jamie , Loga Katharina von , Cunningham David , Chau Ian , Starling Naureen , Ruiz-Bañobre Juan , Dhillon Tony , Gerlinger Marco 
Published: February 2022

AbstractMismatch repair deficient colorectal cancers have high mutation loads and many respond to immune checkpoint-inhibitors. We investigated how genetic and immune landscapes co-evolve in these tumors. All cases had high truncal mutation loads. Driver aberrations showed a clear hierarchy despite pervasive intratumor heterogeneity: Those in WNT/βCatenin, mitogen-activated protein kinase and TGFβ receptor family genes were almost always truncal. Immune evasion drivers were predominantly subclonal and showed parallel evolution. Pan-tumor evolution, subclonal evolution, and evolutionary stasis of genetic immune evasion drivers defined three MMRd CRC subtypes with distinct T-cell infiltrates. These immune evasion drivers have been implicated in checkpoint-inhibitor resistance. Clonality and subtype assessments are hence critical for predictive immunotherapy biomarker development. Cancer cell PD-L1 expression was conditional on loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and likely contributes to the high recurrence risk of MMRd CRCs with impaired CDX2 expression.
Polyfunctional pathogen-specific CD4+ T cells reside in the lungs and tumors of NSCLC patients
Authors: Oja Anna E. , Morgana Florencia , Hagen Ruth , Ghandour Cherien A. , Nolte Martijn A. , Rooijakkers Suzan H.M. , van Lier René A.W. , Bardoel Bart W. , Hombrink Pleun 
Published: February 2022

AbstractLocal T cell responses are required for optimal protection of the lungs against airborne pathogens. This localized protection is mediated by various immune cells, including resident memory T cells (TRM). While human lung CD8+ TRM line the epithelium and are enriched for recognition of respiratory viruses, we found CD4+ TRM to exhibit more heterogeneous localization patterns, surrounding airways, forming clusters in the lung parenchyma, and lining the epithelium. This heterogeneity was also reflected functionally, as lung CD4+ TRM were enriched for recognition of diverse classes of respiratory pathogens. Upon stimulation, lung CD4+ TRM expressed different polyfunctional cytokine profiles depending on the pathogen recognized. CD4+ TRM responding to respiratory viruses and bacteria were biased for production of IFN-γ and IL-17, respectively. Strikingly, pathogen-specific CD4+ TRM also represent a significant fraction in NSCLC tumors that remained polyfunctional despite high PD-1 expression. These findings are not only important for vaccine design, but also provide a rationale for reinvigorating anti-tumor immunity through triggering of polyfunctional pathogen-specific CD4+ tumor infiltrating lymphocytes.