bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of key genes and biological pathways in chronic obstructive pulmonary disease using bioinformatics and next generation sequencing data analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya 
Published: February 2024

AbstractIdentification of accurate biomarkers is still particularly urgent for improving the poor survival of chronic obstructive pulmonary disease (COPD) patients. In this investigation, we aimed to identity the potential biomarkers in COPD via bioinformatics and next generation sequencing (NGS) data analysis. In this investigation, the differentially expressed genes (DEGs) in COPD were identified using NGS dataset (GSE239897) from Gene Expression Omnibus (GEO) database. Subsequently, gene ontology (GO) and pathway enrichment analysis was conducted to evaluate the underlying molecular mechanisms involved in progression of COPD. Protein-protein interaction (PPI), modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis were performed to determine the hub genes, miRNAs and TFs. The receiver operating characteristic (ROC) analysis was performed to determine the diagnostic value of hub genes. A total of 956 overlapping DEGs (478 up regulated and 478 down regulated genes) were identified in the NGS dataset. DEGs were mainly associated with GO functional terms and pathways in cellular response to stimulus. response to stimulus, immune system and neutrophil degranulation. There were 10 hub genes (MYC, LMNA, VCAM1, MAPK6, DDX3X, SHMT2, PHGDH, S100A9, FKBP5 and RPS6KA2) identified by PPI, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network analysis. In conclusion, the DEGs, relative GO terms, pathways and hub genes identified in the present investigation might aid in understanding of the molecular mechanisms underlying COPD progression and provide potential molecular targets and biomarkers for COPD.
Probing the Depths for Diagnostic Performance of Biparametric and Multiparametric MRI for Prostate Cancer Detection- A Meta-Analysis
Authors: Desai Dev , Gami Vismit , Shah Abhijay B. , Raval Dwija , Gupta Parth , Shah Hetvi 
Published: February 2024

AbstractBackgroundProstate cancer is a malignancy that originates in the prostate gland,and can vary in aggressiveness, often requiring a combination of diagnostic methods and imaging for accurate detection and management. In an attempt to ensure timely diagnosis and prevent complications, the choice of the right diagnostic modality becomes crucial. MRI has gained prominence in the diagnosis of prostate cancer. MRI aids prostate cancer diagnosis by pinpointing suspicious areas for in-depth investigation and guiding precise biopsies, enhancing accuracy. It also informs treatment plans by visualizing tumour extent and assists in monitoring disease progression during active surveillance. The purpose of this meta-analysis is to ascertain the accuracy of MRI in diagnosing prostate cancer.MethodologyMedical literature was comprehensively searched and reviewed without restrictions to particular study designs, or publication dates using PubMed, Cochrane Library, and Google Scholar databases for all relevant literature. The extraction of necessary data proceeded after specific inclusion and exclusion criteria were applied. In this Meta-Analysis, A total of 47 RCTs with 13,211 subjects were selected for comparing Multiparametric MRI vs. Gold Standard and A total of 23 RCTs with 3440 subjects were selected for comparing Biparametric MRI vs Gold Standard.Two writers independently assessed the calibre of each study as well as the use of the Cochrane tool for bias risk apprehension. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), and Excel in Stata 14 were used to perform the statistical analyses.ResultsWe calculated the sensitivity and specificity of multiparametric as well as biparametric MRI. The Multiparametric MRI demonstrates a sensitivity of 0.84 (95% confidence interval: 0.83 - 0.85) and specificity of 0.69 (95% confidence interval: 0.68 - 0.70). Meanwhile, Biparametric MRI shows a sensitivity of 0.85 (95% confidence interval: 0.84 - 0.86) and specificity of 0.71 (95% confidence interval: 0.69 - 0.73).ConclusionIn conclusion, both Multiparametric MRI and Biparametric MRI exhibit high sensitivity values of 0.84 and 0.85, respectively, indicating their ability to accurately detect prostate cancer. MRI is a robust diagnostic tool for prostate cancer due to its high-resolution imaging and multiparametric approach. It enables targeted biopsies, informs treatment plans, and aids in active surveillance.
Time-varying Spatial Propagation of Brain Networks in fMRI data
Authors: Bostami Biozid , Lewis Noah , Agcaoglu Oktay , Turner Jessica A. , van Erp Theo , Ford Judith M , Calhoun Vince , Iraji Armin 
Published: February 2024

AbstractSpontaneous neural activity coherently relays information across the brain. Several efforts have been made to understand how spontaneous neural activity evolves at the macro-scale level as measured by resting-state functional magnetic resonance imaging (rsfMRI). Previous studies observe the global patterns and flow of information in rsfMRI using methods such as sliding window or temporal lags. However, to our knowledge, no studies have examined spatial propagation patterns evolving with time across multiple overlapping 4D networks. Here, we propose a novel approach to study how dynamic states of the brain networks spatially propagate and evaluate whether these propagating states contain information relevant to mental illness. We implement a lagged windowed correlation approach to capture voxel-wise network-specific spatial propagation patterns in dynamic states. Results show systematic spatial state changes over time, which we confirmed are replicable across multiple scan sessions using human connectome project data. We observe networks varying in propagation speed; for example, the default mode network (DMN) propagates slowly and remains positively correlated to blood oxygenation level-dependent (BOLD) signal for 6-8 seconds, whereas the visual network propagates much quicker. We also show that summaries of network specific propagative patterns are linked to schizophrenia. More specifically, we find significant group differences in multiple dynamic parameters between schizophrenia patients and controls within four large-scale networks: default mode, temporal lobe, subcortical, and visual network. Individuals with schizophrenia spend more time in certain propagating states. In summary, this study introduces a promising general approach to exploring the spatial propagation in dynamic states of brain networks and their associated complexity and reveals novel insights into the neurobiology of schizophrenia.
Cross-species real time detection of trends in pupil size fluctuation
Authors: Kronemer Sharif I. , Gobo Victoria E. , Walsh Catherine R. , Teves Joshua B. , Burk Diana C. , Shahsavarani Somayeh , Gonzalez-Castillo Javier , Bandettini Peter A. 
Published: February 2024

AbstractPupillometry is a popular method because pupil size is easily measured, sensitive to central neural activity, and associated with behavior, cognition, emotion, and perception. Currently, there is no method for online monitoring phases of pupil size fluctuation. We introducertPupilPhase– an open source software that automatically detects trends in pupil size in real time, enabling novel implementations of real time pupillometry towards achieving numerous research and translational goals. We validated the performance of rtPupilPhase on human, rodent, and monkey pupil data and propose future applications of real time pupillometry.
Identification of hippocampal area CA2 in hamster and vole brain
Authors: Siegler Preston Nicole , Shaughnessy Emma K. , Horman Brian , Vierling Tia T. , King Darron H. , Patisaul Heather B. , Huhman Kim L. , Alexander Georgia M. , Dudek Serena M. 
Published: February 2024

AbstractPrairie voles (Microtus ochrogaster) and Syrian, or golden, hamsters (Mesocricetus auratus) are closely related to mice (Mus musculus) and rats (Rattus norvegicus, for example) and are commonly used in studies of social behavior including social interaction, social memory, and aggression. The CA2 region of the hippocampus is known to play a key role in social memory and aggression in mice and responds to social stimuli in rats, likely owing to its high expression of oxytocin and vasopressin 1b receptors. However, CA2 has yet to be identified and characterized in hamsters or voles. In this study, we sought to determine whether CA2 could be identified molecularly in vole and hamster. To do this, we used immunofluorescence with primary antibodies raised against known molecular markers of CA2 in mice and rats to stain hippocampal sections from voles and hamsters in parallel with those from mice. Here, we report that, like in mouse and rat, staining for many CA2 proteins in vole and hamster hippocampus reveals a population of neurons that express regulator of G protein signaling 14 (RGS14), Purkinje cell protein 4 (PCP4) and striatal-enriched protein tyrosine phosphatase (STEP), which together delineate the borders with CA3 and CA1. These cells were located at the distal end of the mossy fiber projections, marked by the presence of Zinc Transporter 3 (ZnT-3) and calbindin in all three species. In addition to staining the mossy fibers, calbindin also labeled a layer of CA1 pyramidal cells in mouse and hamster but not in vole. However, Wolframin ER transmembrane glycoprotein (WFS1) immunofluorescence, which marks all CA1 neurons, was present in all three species and abutted the distal end of CA2, marked by RGS14 immunofluorescence. Staining for two stress hormone receptors—the glucocorticoid (GR) and mineralocorticoid (MR) receptors—was also similar in all three species, with GR staining found primarily in CA1 and MR staining enriched in CA2. Interestingly, although perineuronal nets (PNNs) are known to surround CA2 cells in mouse and rat, we found that staining for PNNs differed across species in that both CA2 and CA3 showed staining in voles and primarily CA3 in hamsters with only some neurons in proximal CA2 showing staining. These results demonstrate that, like in mouse, CA2 in voles and hamsters can be molecularly distinguished from neighboring CA1 and CA3 areas, but PNN staining is less useful for identifying CA2 in the latter two species. These findings reveal commonalities across species in molecular profile of CA2, which will facilitate future studies of CA2 in these species. Yet to be determined is how differences in PNNs might relate to differences in social behavior across species.
The discovery of antimicrobial peptides from the gut microbiome of cockroachBlattella germanicausing deep learning pipeline
Authors: Chen Sizhe , Qi Huitang , Zhu Xingzhuo , Liu Tianxiang , Teng Yingda , Gong Qiuyu , Jia Cangzhi , Liu Tian , Chen S , Qi H , Zhu X , Liu T , Teng Y , Gong Q , Jia C , Liu T 
Published: February 2024

AbstractAntimicrobial peptides (AMPs) are candidates for use against antibiotic-resistant microorganisms. However, due to high cytotoxicity and poor performance in biological contexts, most AMPs are unable to satisfy the requirements. The gut microbiomes of pathogenic species likeBlattella germanicarepresent unexploited reservoirs of naturally evolved biocompatible AMPs. Here we developed a lightweight AI pipeline called AMPidentifer with two nine-layers Dense-Net blocks and one embedded new self-attention module to enable the discovery of biocompatible AMPs from microbiome. The core structure of AMPidentifer is simple, not requiring complexing code basis. On the independent test dataset, it showed robust performance and avoided high false-positive results. From the gut microbiome ofB. germanica, new AMP candidates with potential low toxicities and antimicrobial activities were identified by AMPidentifer. The selected two AMPs demonstrated good antimicrobial effectsin vitroandin vivo. The Cys residue was demonstrated to perform different action mechanisms in the antimicrobial activity of two AMPs, providing insights for future rational design. New efficient AMPs with low cytotoxicity identified by the new high-throughput AI pipeline from the gut microbiome ofB. germanicasuccessfully showed an important interdisciplinary strategy for discovering bio-safe AMPs from nature.Abstract FigureThe Graphic Abstract
Contributions of short and long-range white matter tracts in dynamic compensation with aging
Authors: Chakraborty Priyanka , Saha Suman , Deco Gustavo , Banerjee Arpan , Roy Dipanjan 
Published: February 2024

AbstractBrain function is shaped by the local and global connections between its dynamical units and biological parameters. With aging, the anatomical connectivity undergoes significant deterioration (e.g., long-range white matter fiber loss), which affects the brain’s overall function. Despite the structural loss, previous research has shown that normative patterns of functions remain intact across the lifespan, defined as the compensatory mechanism of the aging brain. However, the crucial components in guiding the compensatory preservation of the dynamical complexity and the underlying mechanisms remain uncovered. Moreover, it remains largely unknown how the brain readjusts its biological parameters to maintain optimal brain dynamics with age; in this work, we provide a parsimonious mechanism using a whole-brain generative model to uncover the role of sub-communities comprised of short-range and long-range connectivity in driving the dynamic compensation process in the aging brain. We utilize two neuroimaging datasets to demonstrate how short—and long-range white matter tracts affect compensatory mechanisms. We unveil their modulation of intrinsic global scaling parameters, such as global coupling strength and conduction delay, via a personalized large-scale brain model. Our two key findings suggest that (1) the optimal coupling strength and delay play complementary roles in preserving the brain’s optimal working state. (2) Short-range tracts predominantly amplify global coupling strength with age, potentially representing an epiphenomenon of the compensatory mechanism. This mechanistically explains the significance of short-range connections in compensating for the major loss of long-range connections during aging. This insight could help identify alternative avenues to address aging-related diseases where long-range connections are significantly deteriorated.
The unified proposal for classification of human respiratory syncytial virus below the subgroup level
Authors: Goya Stephanie , Ruis Christopher , Neher Richard A. , Meijer Adam , Aziz Ammar , Hinrichs Angie S. , von Gottberg Anne , Roemer Cornelius , Amoako Daniel G. , Acuña Dolores , McBroome Jakob , Otieno James R. , Bhiman Jinal N. , Everatt Josie , Muñoz-Escalante Juan C. , Ramaekers Kaat , Duggan Kate , Presser Lance D. , Urbanska Laura , Venter Marietjie , Wolter Nicole , Peret Teresa C. T. , Salimi Vahid , Potdar Varsha , Borges Vítor , Viegas Mariana 
Published: February 2024

AbstractA globally implemented unified classification for human respiratory syncytial virus (HRSV) below the subgroup level remains elusive. Here, we formulate the global consensus of HRSV classification based on the challenges and limitations of our previous proposals and the future of genomic surveillance. From a high-quality dataset of 1,480 HRSV-A and 1,385 HRSV-B genomes submitted to NCBI and GISAID up to March 2023, we categorized HRSV-A/B sequences into lineages based on phylogenetic clades and amino acid markers. We defined 24 lineages within HRSV-A and 16 within HRSV-B, providing guidelines for prospective lineages definition. Our classification demonstrated robustness in its applicability to both complete and partial genomes. In addition, it allowed the observation of notable lineage replacements and the identification of lineages exclusively detected since the COVID-19 pandemic. We envision that this unified HRSV classification proposal will strengthen and facilitate HRSV molecular epidemiology on a global scale.
Enabling Advanced Multi-Modal Neuroimaging Analysis within a Trusted Research Environment
Authors: Hotchkiss L , Squires E , Gallacher J E , Newbury M , Morris C , Lyons RA , Thompson S 
Published: February 2024

AbstractIntroductionGlobally, 55 million individuals have dementia, with an increasing annual incident of 10 million. Enabling development of new multi-modal models can improve the current diagnostic pathways and potentially contribute to early diagnosis and treatment of dementia. Here, we report how multi-modal resources is achieved within the successful Trusted Research Environment (TRE) providing access to 60+ cohort datasets for dementia research, the Dementias Platform UK (DPUK).ObjectivesWe aimed to identify the challenges of the storage, distribution and analysis of neuroimaging data and how we could implement a comprehensive infrastructure to deal with these. The problems we specifically aimed to address were how to: anonymise scans, store large amounts of data, standardise datasets to a common format, extract metadata, provision the data, and allow for analysis.MethodsWhile, data within majority of existing research platforms are focused on a single aspect, DPUK data provides an enriched view of disease dynamic for dementia cohorts by providing access to linkable brain imaging and genomic data at the individual-level. We document various stages and capacities required for multi-modal neuroimaging analysis for dementia and conclude that achieving research ready assets to enable neuroimaging analysis for dementia from existing resources requires an engineered process to facilitate multiple aspects of curation, provisioning and large scale analysis.ResultsWe developed an ingest pipeline for neuroimaging data to meet the requirements set out in the objectives. This involved standardising all datasets to the Brain Imaging Data Structure, defacing scans and anonymising data, using MinIO for data storage and extracting metadata from header information for data discovery and provisioning.ConclusionThe neuroimaging ingest pipeline developed has allowed for the distribution of imaging datasets within DPUK which has facilitated multi-modal research on anonymised and standardised data. Our pipelines create research-ready datasets in a simplified way, reducing the time and effort of getting these datasets ready for data sharing and making the process easier for the data owners.
Difference in TMPRSS2 usage by Delta and Omicron variants of SARS-CoV-2: Implication for a sudden increase among children
Authors: Kakee Sosuke , Kanai Kyosuke , Tsuneki-Tokunaga Akeno , Okuno Keisuke , Namba Noriyuki , Tomita Katsuyuki , Chikumi Hiroki , Kageyama Seiji 
Published: February 2024

AbstractIt has been postulated from a combination of evidence that a sudden increase in COVID-19 cases among pediatric patients after onset of the Omicron wave was attributed to a reduced requirement for TMPRSS2-mediated entry in pediatric airways with lower expression levels of TMPRSS2. Epidemic strains were isolated from the indigenous population in an area, and the levels of TMPRSS2 required for Delta and Omicron variants were assessed. As a result, Delta variants proliferated fully in cultures of TMPRSS2-positive Vero cells but not in TMPRSS2-negative Vero cell culture (350-fold, Delta vs 9.6-fold, Omicron). There was no obvious age-dependent selection of Omicron strains affected by the TMPRSS2 (9.6-fold, Adults vs. 12-fold, Children). A phylogenetic tree was generated and Blast searches (up to 100 references) for the spread of strains in the study area showed that each strain had almost identical homology (>99.5%) with foreign isolates, although indigenous strains had obvious differences from each other. This suggested that the differences had been present abroad for a long period. Therefore, the lower requirement for TMPRSS2 by Omicron strains might be applicable to epidemic strains globally. In conclusion, the property of TMPRSS2-independent cleavage makes Omicron proliferate with ease and allows epidemics among children with fewer TMPRSS2 on epithelial surfaces of the respiratory organs.
Primary causes and direct medical cost of heart failure among adults admitted with acute decompensated heart failure in a public tertiary hospital, Kenya
Authors: Wauye Victor M. , Oduor Chrispine O. , Barasa Felix A. , Ngeno G. Titus 
Published: February 2024

AbstractHeart failure (HF) is a major contributor of cardiovascular morbidity and mortality globally. Despite its adverse impact on health outcomes in low- and middle-income countries such as Kenya, data on the direct medical cost of HF hospitalization is limited.This was a prospective study conducted at Moi Teaching and Referral Hospital. Patients with HF were identified by sequential medical chart abstraction. Primary causes were extracted from echocardiogram reports and adjudicated by a cardiologist. Direct medical cost of hospitalization was derived using activity-based costing, micro-costing method, and payers’ system perspective. Drivers of overall cost were explored using linear regression models.142 participants were consecutively recruited from September to November 2022. 51.4% were females, and the overall mean age was 54 (SD 20). The leading primary cause was cor pulmonale (CP), 28.9%; then dilated cardiomyopathy (DCM), 26.1%; rheumatic heart disease (RHD), 19.7%; hypertensive heart disease (HHD), 16.9%; ischaemic heart disease (IHD), 6.3%; and pericardial disease (PD), 2.1%. Overall direct cost of HF hospitalization was Kshs. 11,470.94 (SD 8,289.57) per patient per day, with the mean length of hospital stay of 10.1 (SD 7.1). RHD incurred the highest costs, Kshs. 15,299.08 (SD 13,196.89) per patient per day, then IHD, Kshs. 12,966.47 (SD 6656.49), and DCM, Kshs.12,268.08 (SD 7,816.12). Cost of medications was the leading driver, β = 0.56 (0.55 – 0.56), followed by inpatient fees, β = 0.27 (0.27 – 0.28) and laboratory investigations, β = 0.19 (0.18 – 0.19).Cor pulmonale, CM, RHD and HHD were the major causes of HF. The overall direct medical cost of hospitalization was extremely expensive compared with the average monthly household income per capita in Kenya. Widespread insurance cover is therefore recommended to cushion families against such catastrophic health expenditures beside public health measures aimed at addressing primary causes of HF.