bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring Machine Learning Strategies in COVID-19 Prognostic Modelling: A Systematic Analysis of Diagnosis, Classification and Outcome Prediction
Authors: Najjar Reabal , Hossain Md Zakir , Ahmed Khandaker Asif , Hasan Md Rakibul 
Published: March 2024

AbstractBackgroundThe COVID-19 pandemic, which has impacted over 222 countries resulting in incalcu-lable losses, has necessitated innovative solutions via machine learning (ML) to tackle the problem of overburdened healthcare systems. This study consolidates research employing ML models for COVID-19 prognosis, evaluates prevalent models and performance, and provides an overview of suitable models and features while offering recommendations for experimental protocols, reproducibility and integration of ML algorithms in clinical settings.MethodsWe conducted a review following the PRISMA framework, examining ML utilisation for COVID-19 prediction. Five databases were searched for relevant studies up to 24 January 2023, resulting in 1,824 unique articles. Rigorous selection criteria led to 204 included studies. Top-performing features and models were extracted, with the area under the receiver operating characteristic curve (AUC) evaluation metric used for performance assessment.ResultsThis systematic review investigated 204 studies on ML models for COVID-19 prognosis across automated diagnosis (18.1%), severity classification (31.9%), and outcome prediction (50%). We identified thirty-four unique features in five categories and twenty-one distinct ML models in six categories. The most prevalent features were chest CT, chest radiographs, and advanced age, while the most frequently employed models were CNN, XGB, and RF. Top-performing models included neural networks (ANN, MLP, DNN), distance-based methods (kNN), ensemble methods (XGB), and regression models (PLS-DA), all exhibiting high AUC values.ConclusionMachine learning models have shown considerable promise in improving COVID-19 diagnostic accuracy, risk stratification, and outcome prediction. Advancements in ML techniques and their integration with complementary technologies will be essential for expediting decision-making and informing clinical decisions, with long-lasting implications for healthcare systems globally.
GeneSurv: Multi-Gene Cancer Survival Analysis Tool
Authors: Xu Zikang , Wu Jamin , Shin Sung-young , Nguyen Lan K. 
Published: March 2024

AbstractSummaryTraditional cancer survival analysis tools often restrict their analysis to single genes, thereby limiting their analytical scope. GeneSurv, a novel Web-Based Multi-Gene Cancer Survival Analysis Tool, addresses this limitation by enabling multi-gene analyses that correlates the expression of multiple genes, without restriction on their number, in various combinations, with patient survival outcomes. GeneSurv offers dynamic functionalities and an intuitive interface for flexible and precise adjustments of gene expression thresholds. Among its demonstrated applications, GeneSurv identified a significant association between high expression of CCND1 and CDK4 with poor breast cancer prognosis, and related the combined expression of five genes to patient survival, showcasing its capacity to unravel the complexities of genetic interactions and their impact on patient outcomes.ConclusionAvailable with user-friendly tutorials athttps://can-sat.erc.monash.edu/, GeneSurv is an invaluable addition to the existing suite of bioinformatic tools, significantly enhancing the investigation of cancer prognosis.
An updated review of the marine ornamental fish trade in the European Union
Authors: Biondo Monica V. , Burki Rainer P. , Aguayo Francisco , Calado Ricardo 
Published: March 2024

AbstractWild-caught fishes from coral reefs, one of the most threatened ecosystems on the planet, continue to supply the marine aquarium trade. Despite customs and veterinary checks during imports, comprehensive data on this global industry remains scarce. This study provides an updated review on one of its largest import markets, the European Union (EU): 24-million-euro annual trade value, detailed exporting and importing countries also diversity of species and families of the 26 million specimens imported between 2014 and 2021. We then show how a watchlist alert system based on the number of specimens traded, import trends, and vulnerability index according to FishBase and IUCN Red List conservation status can provide key information on which species should require a closer scrutiny. The stark decline in trade of the most traded species,Chromis viridis,may warrant monitoring through the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). While the European TRAde Control and Expert System (TRACES) electronically monitors the movement of live animals to respond quickly to biosecurity risks, one-third of marine ornamental fishes imported lack species-level information. With minor adjustments, TRACES could enhance the monitoring of wildlife trade, with marine ornamental fish being an interesting case study.
Expanded methylome and quantitative trait loci detection by long-read profiling of personal DNA
Authors: Groza Cristian , Ge Bing , Cheung Warren , Pastinen Tomi , Bourque Guillaume 
Published: March 2024

AbstractStructural variants (SVs) are omnipresent in human DNA, yet their genotype and methylation status is rarely characterized due to previous limitations in genome assembly and detection of modified nucleotides. Because of this, the extent to which these regions act as quantitative-trait loci is also largely unknown.Here, we generated a pangenome graph summarizing the SVs in 782 de novo assembled genomes obtained from the Genomic Answers for Kids rare disease cohort, that captures 14.6 million CpGs in DNA segments that are absent from the CHM13v2 assembly (SV-CpGs), expanding their number by 43.6%. Next, using 435 methylomes from the same samples, we genotyped a total of 7.99 million SV-CpGs, of which 5.18 million (64.8%) were found to be methylated (SV-5mCpGs) in at least one sample.To understand the provenance and impact of these novel SV-CpGs, we noted that non-repeat sequences were the leading contributor of SV-CpGs (3.3 × 106), followed by centromeric satellites (1.58 × 106), simple repeats (1.19 × 106), Alus (0.67 × 106), satellites (0.39 × 106), L1s (0.27 × 106), and SVAs (0.19 × 106). Meanwhile, the methylation rate of SV-CpGs was the highest in repeat sequences. Moreover, in contrast to Alus and L1s, centromeric satellites, simple repeats and SVA sequences were overrepresented in SV-5mCpGs compared to reference CpGs. Similarly, we established that non-reference CpGs were more than twice (37% vs. 15%) as likely to be variable, showing intermediate methylation levels in the population.Lastly, to explore if SVs detected in this pangenome are potentially causal for functional variation in population we measured methylation quantitative trait loci (SV-mQTLs) using CHM13v2 as a backbone. This revealed over 230,464 methylation bins within 100 kbp of a common SV (>5% MAF) showing significant association (at 5% FDR) with methylation variation. Finally, we assessed how many of these SVs-mQTLs were the leading QTL variant compared to SNVs and identified 65,659 methylation bins (28.5%) where the leading variant was an SV.In conclusion, our results demonstrate that graph genome references providing full SV structures in combination with the associated methylation variation reveal tens-of-thousands of QTLs that are more accurately mapped in personal genomes, underscoring the importance of assembly-based analyses of human traits.
DNA metabarcoding revealed how time and space do matter -sex does not- in the dietary variation of the endangered Dupont’s Lark
Authors: Zurdo Julia , Bustillo-de la Rosa Daniel , Barrero Adrián , Gómez-Catasús Julia , Reverter Margarita , Pérez-Granados Cristian , García Jesús T. , Viñuela Javier , Domínguez Julio C. , Morales Manuel B. , Traba Juan 
Published: March 2024

AbstractA species’ diet is highly dependent on the availability of food resources in space and time, as well as on intrinsic factors such as sex or age. Accurate assessments of variations in the diet composition of bird populations across spatial scales, seasons and demographic groups are essential not only for understanding the basic ecology of species, but also for the conservation of endangered ones. However, our current knowledge about how birds’ diet change according to spatio-temporal variations or intrinsic factors is very limited. Here, we used a multi-marker metabarcoding approach to characterize the diet of a declining shrub-steppe passerine, the Dupont’s Lark (Chersophilus duponti), throughout a large part of its global distribution range. We also investigated spatial, phenological and sexual variations in its diet. Using markers from two genomic regions (18S and COI), we analyzed fecal samples from 303 adult Dupont’s larks from Morocco and Spain during the breeding and non-breeding seasons. Overall, arthropods from the orders Coleoptera, Lepidoptera, Julida and Orthoptera were the main prey consumed by Dupont’s Larks. We found that Dupont’s Lark diet varied spatially, as well as temporally, reflecting dietary plasticity in response to changes in prey availability across landscapes and the species’ phenological periods. High dietary overlap and no differences between sexes were observed, suggesting similar foraging behavior and nutritional requirements in both sexes. This is the first study providing detailed information on Dupont’s Lark food ecology over much of its distribution, which is fundamental for the management and conservation of this declining steppe species.
Endocrine, immune and disease dynamics in a patient with rheumatoid arthritis during flare and medication change
Authors: Seizer Lennart , Gostner Johanna , Garbers Christoph , Licht Melina , Sager Sebastian , Schubert Christian 
Published: March 2024

AbstractObjectiveRheumatoid arthritis (RA) is a chronic autoimmune disease of widely unknown etiology and pathophysiology. In this integrative single-case study on a patient with RA, we had the unique opportunity to closely monitor the individual dynamics of endocrine, immune and disease variables during a naturally occurring flare-up and subsequent medication change.MethodsThe female RA patient collected her entire urine over 30 days in 12-h intervals (60 consecutive measurements in total). Subsequently, interleukin-6 (IL-6), orosomucoid-2, cortisol (ELISA), neopterin and creatinine (HPLC) levels were determined in the urine samples. Further, each morning and evening, the patient completed the DIARI, a set of questionnaires on variables such as subjective pain, subjective RA disease activity and emotional states. Once a week, besides an online video interview, the patient had an appointment at her rheumatologist, in which several indices of RA disease activity were determined: SDAI, CDAI and DAS28. From these data various time series were constructed for statistical analysis.ResultsRA disease state increased from low to high activity during the first 12 study days. Thereupon, the medication was changed, which proved effective in reducing RA disease activity. However, the levels of urinary neopterin, urinary orosomucoid-2, and urinary IL-6 did not show any response, neither to the increasing disease activity nor the medication change. The patient’s daily reports on pain, RA disease activity, and emotional states, however, mirrored the course of the rheumatologic indices.ConclusionThis integrative single-case study clearly demonstrated the importance of process analysis for the evaluation of therapeutic measures in RA. In the patient studied, urinary levels of neopterin, orosomucoid-2 and urinary IL-6 were not found to be appropriate biomarkers of short-term fluctuations in RA disease activity. Instead, the results reported by the patient proved to be a useful tool for ambulatory and longitudinal monitoring of RA.
Multicenter Development and Prospective Validation of eCARTv5: A Gradient Boosted Machine Learning Early Warning Score
Authors: Churpek Matthew M. , Carey Kyle A. , Snyder Ashley , Winslow Christopher J , Gilbert Emily , Shah Nirav S , Patterson Brian W. , Afshar Majid , Weiss Alan , Amin Devendra N. , Rhodes Deborah J. , Edelson Dana P. 
Published: March 2024

ABSTRACTOBJECTIVEEarly detection of clinical deterioration using machine learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and were not tested in important subgroups. Our objective was to develop and prospectively validate a gradient boosted machine model (eCARTv5) for identifying clinical deterioration on the wards.DESIGNMulticenter retrospective and prospective observational study.SETTINGInpatient admissions to the medical-surgical wards at seven hospitals in three health systems for model development (2006-2022) and at 21 hospitals from three health systems for retrospective (2009-2023) and prospective (2023-2024) external validation.PATIENTSAll adult patients hospitalized at each participating health system during the study years.INTERVENTIONSNoneMEASUREMENTS AND MAIN RESULTSPredictor variables (demographics, vital signs, documentation, and laboratory values) were used in a gradient boosted trees algorithm to predict intensive care unit transfer or death in the next 24 hours. The developed model (eCART) was compared to the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS) using the area under the receiver operating characteristic curve (AUROC). The development cohort included 901,491 admissions, the retrospective validation cohort included 1,769,461 admissions, and the prospective validation cohort included 205,946 admissions. In retrospective validation, eCART had the highest AUROC (0.835; 95%CI 0.834, 0.835), followed by NEWS (0.766 (95%CI 0.766, 0.767)), and MEWS (0.704 (95%CI 0.703, 0.704)). eCART’s performance remained high (AUROC ≥0.80) across a range of patient demographics, clinical conditions, and during prospective validation.CONCLUSIONSWe developed eCART, which performed better than the NEWS and MEWS retrospectively, prospectively, and across a range of subgroups. These results served as the foundation for Food and Drug Administration clearance for its use in identifying deterioration in hospitalized ward patients.KEY POINTSQuestionHow can we best identify deterioration in hospitalized ward patients?FindingsIn retrospective validation, a gradient boosted machine model (eCARTv5) developed for identifying clinical deterioration on the wards had the highest area under the receiver operating characteristic curve when compared to the Modified Early Warning Score and the National Early Warning Score. eCART’s performance remained high across a range of patient demographics, clinical conditions, and during prospective validation.MeaningThis paper evaluating eCART’s performance served as the foundation for Food and Drug Administration clearance for its use in identifying deterioration in hospitalized ward patients.
CORACLE (COVID-19 liteRAture CompiLEr): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement
Authors: Piontkovskaya Kristina , Luo Yulian , Lindberg Pia , Gao Jing , Runold Michael , Kolosenko Iryna , Li Chuan-Xing , Wheelock Åsa M. 
Published: March 2024

AbstractBackgroundDuring the COVID-19 pandemic there emerged a need to efficiently monitor and process large volumes of scientific literature on the subject. Currently, as the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID- 19 (PASC) - that affects over 10% of those who contract SARS-CoV-2 and presents a significant and growing challenge in the medical field. The continuous influx of new research publications underscores a critical need for efficient tools for navigating the literature.ObjectivesWe aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to be able to quickly identify key publications and publication networks.MethodsWe introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed for the analysis of COVID-19-related scientific articles and the identification of research trends. CORACLE features three primary interfaces: The “Search” interface, which displays research trends and citation links; the “Citation Map” interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the “MeSH” interface, highlighting current MeSH trends and associations between MeSH terms.ResultsOur web application, CORACLE, leverages regularly updated PubMed data to aggregate and categorize the extensive literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications.ConclusionCORACLE proves to be an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of relevant information and emerging trends in COVID-19 and PASC research.
Gene editing ofCD3 epsilongene to redirect regulatory T cells for adoptive T cell transfer
Authors: Du Weijie , Noyan Fatih , McCallion Oliver , Drosdek Vanessa , Kath Jonas , Glaser Viktor , Fuster-Garcia Carla , Yang Mingxing , Stein Maik , Weber Olaf , Polansky Julia K. , Cathomen Toni , Jaeckel Elmar , Hester Joanna , Issa Fadi , Volk Hans-Dieter , Schmueck-Henneresse Michael , Reinke Petra , Wagner Dimitrios L. 
Published: March 2024

I.AbstractAdoptive transfer of regulatory T cells (Tregs) is a promising strategy to combat immunopathologies in transplantation and autoimmune diseases. Antigen-specific Tregs are more effective in modulating undesired immune reactions, but their low frequency in peripheral blood poses challenges for manufacturing and their clinical application. Chimeric antigen receptors (CARs) have been used to redirect the specificity of Tregs, employing retroviral vectors. However, retroviral gene transfer is costly, time consuming, and raises safety issues. Here, we explored non-viral gene editing to redirect Tregs with CARs, using HLA-A2-specific constructs for proof-of-concept studies in transplantation models. We introduce a virus-free CRISPR-Cas12a approach to integrate an antigen-binding domain into theCD3 epsilon(CD3ε) gene, generating Tregs expressing a T cell receptor fusion construct (TruC). TheseCD3ε-TruC Tregs exhibit potent antigen-dependent activation while maintaining responsiveness to TCR/CD3 stimulation. This enables preferential enrichment of TruC-redirected Tregs via repetitive CD3/CD28-stimulation in a GMP-compatible expansion system. Non-viral gene editedCD3ε-TruC Tregs retained their phenotypic, epigenetic, and functional identity. In a humanized mouse model, HLA-A2-specificCD3ε-TruC Tregs demonstrate superior protection of allogeneic HLA-A2+skin grafts from rejection compared to polyclonal Tregs. This approach provides a pathway for developing clinical-gradeCD3ε-TruC-based Treg cell products for transplantation immunotherapy and other immunopathologies.
VLK drives extracellular phosphorylation of EphB2 to govern the EphB2-NMDAR interaction and injury-induced pain
Authors: Srikanth Kolluru D. , Elahi Hajira , Chander Praveen , Washburn Halley R. , Hassler Shayne , Mwirigi Juliet M. , Kume Moeno , Loucks Jessica , Arjarapu Rohita , Hodge Rachel , Shiers Stephanie I. , Sankaranarayanan Ishwarya , Erdjument-Bromage Hediye , Neubert Thomas A. , Campbell Zachary T. , Paik Raehum , Price Theodore J. , Dalva Matthew B. 
Published: March 2024

AbstractPhosphorylation of hundreds of protein extracellular domains is mediated by two kinase families, yet the significance of these kinases is underexplored. Here, we find that the presynaptic release of the tyrosine directed-ectokinase, Vertebrate Lonesome Kinase (VLK/Pkdcc), is necessary and sufficient for the direct extracellular interaction between EphB2 and GluN1 at synapses, for phosphorylation of the ectodomain of EphB2, and for injury-induced pain.Pkdccis an essential gene in the nervous system, and VLK is found in synaptic vesicles, and is released from neurons in a SNARE-dependent fashion. VLK is expressed by nociceptive sensory neurons where presynaptic sensory neuron-specific knockout renders mice impervious to post-surgical pain, without changing proprioception. VLK defines an extracellular mechanism that regulates protein-protein interaction and non-opioid-dependent pain in response to injury.One-Sentence SummarySynaptic protein-protein interactions and pain are regulated by the presynaptic release of the extracellular kinase VLK in the spinal cord.
Granzyme B-based CAR T cells block metastasis by eliminating circulating tumor cells
Authors: Sun Bin , Guo Jing , Yang Dong , Hu Qiancheng , Ma Haiyan , Tian Panwen , Liu Nan , Lv Longbao , Yan Lanzhen , Ding Hao , Fu Maoyong , Gou Hongfeng , Cao Dan , Liu Dan , Chen Nianyong , Shi Peng , Li Weimin , Zhao Xudong 
Published: March 2024

AbstractChimeric antigen receptor (CAR) T cells have limited efficacy against solid tumors due to the hostile microenvironment. Circulating tumor cells (CTCs) are essential to metastasis, which is the cause of most of cancer-related death. Here, we generated GrB-CAR T cells targeting membrane-bound HSP70 (mHSP70), a highly tumor-specific antigen detected in numerous cancers. GrB-CAR T cells exhibited potent cytotoxicity against a broad spectrum of cancer cell lines and stem-like cancer cellsin vitroand effectively inhibited xenograft tumor growthin vivo. Importantly, GrB-CAR T cells markedly decreased the number of CTCs and, therefore, hindered cancer metastasis in spontaneous metastasis models with uncontrollable primary tumor growth, a scenario commonly encountered in clinical trials of CAR T therapies for solid tumors. Furthermore, despite the 100% homology between human and macaque HSP70 protein, the autotransplantation of macaque T cells expressing human GrB-CAR did not cause any obvious toxic effects. These results not only demonstrate GrB-CAR T cells as a safe and effective tactic with broad-spectrum anticancer activity, but also offer strong experimental evidence and proof-of-concept validation for CAR T cell-mediated metastasis inhibition by targeting CTCs.
Myc upregulates Ggct, γ-glutamylcyclotransferase to promote development ofp53-deficient osteosarcoma
Authors: Ueno Tomoya , Otani Shohei , Date Yuki , Katsuma Yu , Nagayoshi Yuma , Ito Tomoko , Ii Hiromi , Kageyama Susumu , Nakata Susumu , Ito Kosei 
Published: March 2024

SUMMARYOsteosarcoma (OS) in humans is characterized by alterations in theTP53gene. In mice, loss of p53 triggers OS development, for which c-Myc (Myc) oncogenicity is indispensable. However, little is known about which genes are targeted by Myc to promote tumorigenesis. Here, we examined the role of Ggct, γ-glutamylcyclotransferase which is a component enzyme of γ-glutamyl cycle essential for glutathione homeostasis, in human and mouse OS development. We found thatGGCTis a poor prognostic factor for human OS, and that deletion ofGgctsuppressesp53-deficient osteosarcomagenesis in mice. Myc upregulates Ggct directly by binding to theGgctpromoter, and deletion of a Myc binding site therein by genome editing attenuated the tumorigenic potential ofp53- deficient OS cells. Taken together, these results show a rationale that GGCT is widely upregulated in cancer cells and solidify its suitability as a target for anticancer drugs.