bluuebunny/crossref_metadata_2025_split huggingface dataset:
Barriers to upper gastrointestinal screening among the general population in high-prevalence areas: a cross-sectional study
Authors: Chen Xin , Ze Yuan , Yi Wanya , Yang Yuling , Sun Renjuan , Tu Huiming 
Published: November 2023

ABSTRACT

Background:
In China, there are large differences between regions in the use of gastroscopies and public awareness of upper gastrointestinal (UGI) screening.

Objective:
This study investigated the current context and analyzed the barriers that influence UGI screening behavior among the general population in UGI cancer high-prevalence areas.

Methods:
A total of 320 participants anonymously answered an online questionnaire. The rank sum test was used to analyze the difference in the scores of the UGI screening awareness questionnaire among participants with different socio-demographic characteristics. Using the awareness level of UGI screening and gastroscopy as the dependent variable, and the socio-demographic characteristics as the independent variable, simple linear regression and binary logistic regression analysis were used to determine the factors influencing attitudes toward gastroscopy screening. We used Spearman's correlation analysis to examine the correlation between UGI screening awareness level and willingness to undergo a gastroscopy.

Results:
There was a correlation between the willingness to undergo gastroscopy and the awareness level of UGI screening (r = 0.243, p < 0.001). Linear regression analysis found that age, type of residence, education level, employment status, monthly income, history of gastroscopy, dietary habits, physical exercise, and convenience in obtaining information were significantly correlated with the awareness level of UGI screening (p < 0.05). Binary logistic regression analysis found that factors significantly associated with gastric cancer screening behavior include residence, monthly income, and self-perceived health status (p < 0.05).

Conclusion:
It is necessary to improve education about UGI cancer and screening knowledge, with a focus on populations with lower education and income.
Adverse childhood experiences predict internet gaming disorder in university students: the mediating role of resilience
Authors: Ma Jinghao , Yang Bo , Wang Shizhen , Yao Yujie , Wu Chencheng , Li Mei , Dong Guang-Heng 
Published: November 2023

Background
To investigate the relationship between adverse childhood experiences and internet gaming disorder (IGD) and the mediating role of resilience in the relationship between these two factors.

Methods
The adverse childhood experience scale, resilience scale and IGD Scale were administered to 9349 university students. Correlations and mediating effects were calculated among these scores.

Results
After controlling for sex and age, significant correlations among adverse childhood experiences, resilience and IGD were observed; resilience was a partial mediator variable in the relationship between adverse childhood experiences and IGD.

Conclusions
The more adverse childhood experiences an individual has, the less their mental toughness and the greater their tendency to become addicted to internet games. Adverse childhood experiences can effectively predict IGD, and the risk of becoming addicted to the internet can be decreased by increasing one's mental toughness.
A case of pleural Mycobacterium tuberculosis infection with reversion of Quantiferon Gold Plus results.
Authors: Goire Namraj , Suchard Melinda , Barling Andrew , Fernando Ruchira , Dreyer Linda , Mahony Andrew 
Published: November 2023

Introduction: Mycobacterium tuberculosis (MTB) infections continue to have a high mortality and morbidity burden globally. Interferon-Gamma Release Assays (IGRA) such as Quantiferon Gold Plus (QFT-Plus) aid significantly in diagnosis of latent TB. We present a case of active extra-pulmonary MTB infection with reversion of IGRA result as well as negative Xpert MTB/RIF Ultra PCR result from tissues obtained from pleural biopsy.
Case summary: A 52-year-old male presented in August 2022 with a two-week history of pleuritic chest pain associated with modest elevation in inflammatory markers. The patient had had a positive QFG-Plus result in 2018, however QFG-Plus during this admission was negative. Needle thoracocentesis showed an exudative left pleural effusion with predominant lymphocytes. The patient’s symptoms failed to resolve with empiric antimicrobial therapy for community-acquired pneumonia. Broncho-Alveolar Lavage as well as biopsies of pleural tissues via video-assisted thoracoscopic surgery from the left lower lobe yielded negative results on routine microbiological culture as well as Xpert Ultra PCR. Growth of acid fast bacilli was noted from mycobacterial cultures of pleural tissues which were identified as MTB.
Conclusion: Despite significant technological advances, microbiological diagnosis of MTB infections remains challenging. We document QFG reversion during development from latent to active pleural TB. Decline in the ability of CD4 and CD8 T cells to produce interferon gamma in response to TB antigens was likely associated with loss of host control of latent MTB. This case serves as a reminder that despite exhaustive testing with state-of-art diagnostic platforms, MTB infections can still elude discovery.
Using cluster-based permutation tests to estimate MEG/EEG onsets: how bad is it?
Authors: Rousselet Guillaume A. 
Published: November 2023

AbstractLocalising effects in space, time and other dimensions is a fundamental goal of magneto- and electro-encephalography (EEG) research. A popular exploratory approach applies mass-univariate statistics followed by cluster-sum inferences, an effective way to correct for multiple comparisons while preserving high statistical power by pooling together neighbouring effects. Yet, these cluster-based methods have an important limitation: each cluster is associated with a uniquepvalue, such that there is no error control at individual time points, and one must be cautious about interpreting when and where effects start and end. Sassenhagen & Draschkow (2019) provided an important reminder of this limitation. They also reported results from a simulation, suggesting that onsets estimated from EEG data are both positively biased and very variable. However, the simulation lacked comparisons to other methods. Here I report such comparisons in a new simulation, replicating the positive bias of the cluster-sum method, but also demonstrating that it performs relatively well, in terms of bias and variability, compared to other methods that provide point-wisepvalues: two methods that control the false discovery rate, and two methods that control the family-wise error rate (cluster-depth and maximum statistic methods). I also present several strategies to reduce estimation bias, including group calibration, group comparison, and using binary segmentation, a simple change point detection algorithm that outperformed mass-univariate methods in simulations. Finally, I demonstrate how to generate onset hierarchical bootstrap confidence intervals that integrate variability over trials and participants, a substantial improvement over standard group approaches that ignore measurement uncertainty.
Snowball: a novel gene family required for developmental patterning in fruiting bodies of mushroom-forming fungi (Agaricomycetes)
Authors: Földi Csenge , Merényi Zsolt , Balázs Bálint , Csernetics Árpád , Miklovics Nikolett , Wu Hongli , Hegedüs Botond , Virágh Máté , Hou Zhihao , Liu Xiao-Bin , Galgóczy László , Nagy László G. 
Published: November 2023

AbstractThe morphogenesis of sexual fruiting bodies of fungi is a complex process determined by a genetically encoded program. Fruiting bodies reached the highest complexity levels in the Agaricomycetes, yet, the underlying genetics is currently poorly known. In this work, we functionally characterized a highly conserved unannotated gene termedsnb1, whose expression level increases rapidly during fruiting body initiation. According to phylogenetic analyses, orthologues ofsnb1are present in almost all agaricomycetes and may represent a novel conserved gene family that plays a substantial role in fruiting body development. We disruptedsnb1using CRISPR/Cas9 in the agaricomycete model organismCoprinopsis cinerea. Snb1deletion mutants formed unique, snowball-shaped, rudimentary fruiting bodies that could not differentiate caps, stipes and lamellae. We took advantage of this phenotype to study fruiting body differentiation using RNA-Seq analyses. This revealed differentially regulated genes and gene families that, based on wild-type RNA-Seq data, were upregulated early during development and showed tissue-specific expression, underscoring their potential role in differentiation. Taken together, the novel gene family ofsnb1and the differentially expressed genes in thesnb1mutants provide valuable insights into the complex mechanisms underlying developmental patterning in the Agaricomycetes.ImportanceFruiting bodies of mushroom-forming fungi (Agaricomycetes) are complex multicellular structures, with a spatially and temporally integrated developmental program that is, however, currently poorly known. In this study we present a novel, conserved gene family, Snowball (snb), termed after the unique, differentiation-less fruiting body morphology ofsnb1knockout strains in the model mushroomCoprinopsis cinerea. Snbis a hitherto unannotated gene that is highly conserved among agaricomycetes and encodes a protein of unknown function. A comparative transcriptomic analysis of the early developmental stages of differentiated wild-type and non-differentiated mutant fruiting bodies revealed conserved differentially expressed genes which may be related to tissue differentiation and developmental patterning fruiting body development.
Multifaceted impact of specialized neuropeptide-intensive neurons on the selective vulnerability in Alzheimer’s disease
Authors: Li Manci , Flack Nichole , Larsen Peter A. 
Published: November 2023

AbstractINTRODUCTIONWidespread disruption of neuropeptide (NP) networks in Alzheimer’s disease (AD) and disproportionate absence of neurons expressinghighNP-producing, coined as HNP neurons, have been reported for the entorhinal cortex (EC) of AD brains. Hypothesizing that functional features of HNP neurons are involved in the early pathogenesis of AD, we aim to understand the molecular mechanisms underlying these observations.METHODSMultiscale and spatiotemporal transcriptomic analysis was used to investigate AD-afflicted and healthy brains. Our focus encompassed NP expression dynamics in AD,AD-associatedNPs (ADNPs) trajectories with aging, and the neuroanatomical distribution of HNP neuron.RESULTSFindings include that 1) HNP neurons exhibited heightened metabolic needs and an upregulation of gene expressions linked to protein misfolding; 2) dysfunctions of ADNP production occurred in aging and mild cognitive decline; 3) HNP neurons co-expressing ADNPs were preferentially distributed in brain regions susceptible to AD.DISCUSSIONWe identified potential mechanisms that contribute to the selective vulnerability of HNP neurons to AD. Our results indicate that the functions of HNP neurons predispose them to oxidative stress and protein misfolding, potentially serving as inception sites for misfolded proteins in AD.
kmerDB: A Database Encompassing the Set of Genomic and Proteomic Sequence Information for Each Species
Authors: Mouratidis Ioannis , Baltoumas Fotis A. , Chantzi Nikol , Chan Candace S.Y. , Montgomery Austin , Konnaris Maxwell A. , Georgakopoulos George C. , Das Anshu , Chartoumpekis Dionysios , Kovac Jasna , Pavlopoulos Georgios A. , Georgakopoulos-Soares Ilias 
Published: November 2023

ABSTRACTThe rapid decline in sequencing cost has enabled the generation of reference genomes and proteomes for a growing number of organisms. However, at the present time, there is no established repository that provides information about organism-specific genomic and proteomic sequences of certain lengths, also known as kmers, that are either present or absent in each genome or proteome. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 45,785 and 22,386 reference genomes and proteomes, respectively, as well as 14,658,776 and 149,264,442 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences that are absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at:www.kmerdb.com.
Branch Length Transforms using Optimal Tree Metric Matching
Authors: Arasti Shayesteh , Tabaghi Puoya , Tabatabaee Yasamin , Mirarab Siavash 
Published: November 2023

AbstractThe abundant discordance between evolutionary relationships across the genome has rekindled interest in ways of comparing and averaging trees on a shared leaf set. However, most attempts at reconciling trees have focused on tree topology, producing metrics for comparing topologies and methods for computing median tree topologies. Using branch lengths, however, has been more elusive, due to several challenges. Species tree branch lengths can be measured in many units, often different from gene trees. Moreover, rates of evolution change across the genome, the species tree, and specific branches of gene trees. These factors compound the stochasticity of coalescence times. Thus, branch lengths are highly heterogeneous across both the genome and the tree. For many downstream applications in phylogenomic analyses, branch lengths are as important as the topology, and yet, existing tools to compare and combine weighted trees are limited. In this paper, we make progress on the question of mapping one tree to another, incorporating both topology and branch length. We define a series of computational problems to formalize finding the best transformation of one tree to another while maintaining its topology and other constraints. We show that all these problems can be solved in quadratic time and memory using a linear algebraic formulation coupled with dynamic programming preprocessing. Our formulations lead to convex optimization problems, with efficient and theoretically optimal solutions. While many applications can be imagined for this framework, we apply it to measure species tree branch lengths in the unit of the expected number of substitutions per site while allowing divergence from ultrametricity across the tree. In these applications, our method matches or surpasses other methods designed directly for solving those problems. Thus, our approach provides a versatile toolkit that finds applications in similar evolutionary questions.Code availabilityThe software is available athttps://github.com/shayesteh99/TCMM.git.Data availabilityData are available on Githubhttps://github.com/shayesteh99/TCMM-Data.git.
Effects of testosterone and metformin on the GlycanAge index of biological age and the composition of the IgG glycome
Authors: Vinicki Martina , Pribić Tea , Vučković Frano , Frkatović-Hodžić Azra , Plaza-Andrade Isaac , Tinahones Francisco , Raffaele Joseph , Fernández-García José Carlos , Lauc Gordan 
Published: November 2023

ABSTRACTWith aging, there is a correlation between a decline in the body’s ability to maintain regular functioning and greater susceptibility to age-related diseases. Therapeutic interventions targeting the underlying biological changes of aging hold promise for preventing or delaying multiple age-related diseases. Metformin, a drug commonly used for diabetes treatment, has emerged as a potential gerotherapeutic agent due to its established safety record and preclinical and clinical data on its anti-aging effects. Glycosylation, one of the most common and complex co- and post-translational protein modifications, plays a crucial role in regulating protein function and has been linked to aging and various diseases. Changes in IgG glycosylation patterns have been observed with age, and these alterations may serve as valuable biomarkers for disease predisposition, diagnosis, treatment monitoring, and overall health assessment. In this study, we analyzed the IgG glycosylation patterns of individuals under treatment with metformin, testosterone, metformin plus testosterone and placebo, and investigated the longitudinal changes in glycosylation over time. We observed statistically significant differences in the IgG glycome composition between participants on testosterone therapy and placebo, with decreased agalactosylation and increased galactosylation and sialylation. However, metformin therapy did not result in statistically significant changes in glycosylation patterns. These findings contribute to our understanding of the impact of therapeutic interventions on IgG glycosylation and confirm the value of IgG glycosylation as a significant biomarker, capable of assessing biological age using the GlycanAge index and providing insight into overall health compared to chronological age.
DIISCO: A Bayesian framework for inferring dynamic intercellular interactions from time-series single-cell data
Authors: Park Cameron , Mani Shouvik , Beltran-Velez Nicolas , Maurer Katie , Gohil Satyen , Li Shuqiang , Huang Teddy , Knowles David A. , Wu Catherine J. , Azizi Elham 
Published: November 2023

AbstractCharacterizing cell-cell communication and tracking its variability over time is essential for understanding the coordination of biological processes mediating normal development, progression of disease, or responses to perturbations such as therapies. Existing tools lack the ability to capture time-dependent intercellular interactions, such as those influenced by therapy, and primarily rely on existing databases compiled from limited contexts. We present DIISCO, a Bayesian framework for characterizing the temporal dynamics of cellular interactions using single-cell RNA-sequencing data from multiple time points. Our method uses structured Gaussian process regression to unveil time-resolved interactions among diverse cell types according to their co-evolution and incorporates prior knowledge of receptor-ligand complexes. We show the interpretability of DIISCO in simulated data and new data collected from CAR-T cells co-cultured with lymphoma cells, demonstrating its potential to uncover dynamic cell-cell crosstalk.AvailabilityDIISCO is publicly accessible athttps://github.com/azizilab/DIISCO_public. All data will be deposited to GEO upon publication.
Integrative multiomics analysis of neointima proliferation in human saphenous vein: implications for bypass graft disease
Authors: Kim David , Goo Brandee , Shi Hong , Coffey Philip , Veerapaneni Praneet , Chouhaita Ronnie , Cyriac Nicole , Aboud Ghaith , Cave Stephen , Greenway Jacob , Mundkur Rohan , Ahmadieh Samah , Harb Ragheb , Ogbi Mourad , Fulton David J. , Huo Yuqing , Zhang Wei , Long Xiaochun , Guha Avirup , Kim Ha Won , Shi Yang , Rice Robert D. , Gallo Dominic R. , Patel Vijay , Lee Richard , Weintraub Neal L. 
Published: November 2023

AbstractIntroductionHuman saphenous veins (SV) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima proliferation (NP). NP involves complex interplay between vascular smooth muscle cells (VSMC) and fibroblasts. Little is known, however, regarding the transcriptomic and proteomic dynamics of NP. Here, we performed multi-omics analysis in anex vivotissue culture model of NP in human SV procured for CABG surgery.Methods and resultsHistological examination demonstrated significant elastin degradation and NP (indicated by increased neointima area and neointima/media ratio) in SV subjected to tissue culture. Analysis of data from 73 patients suggest that the process of SV adaptation and NP may differ according to sex and body mass index. RNA sequencing confirmed upregulation of pro-inflammatory and proliferation-related genes during NP and identified novel processes, including increased cellular stress and DNA damage responses, which may reflect tissue trauma associated with SV harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics detected transdifferentiating VSMC in the intima on the day of harvesting and highlighted dynamic alterations in fibroblast and VSMC phenotype and behavior during NP. Specifically, we identified new cell subpopulations contributing to NP, includingSPP1+, LGALS3+VSMC andMMP2+, MMP14+fibroblasts.ConclusionDynamic alterations of gene and protein expression occur during NP in human SV. Identification of the human-specific molecular and cellular mechanisms may provide novel insight into SV bypass graft disease.
Deciphering the Functional Roles of Individual Cancer Alleles Across Comprehensive Cancer Genomic Studies
Authors: Ma Jiayan (Yoshii) , Ting Stephanie , Tam Bartholomew , Pham Timothy , Reich Michael , Mesirov Jill , Tamayo Pablo , Kim William 
Published: November 2023

AbstractCancer genome data has been growing in both size and complexity, primarily driven by advances in next-generation sequencing technologies, such as Pan-cancer data from TCGA, ICGC, and single-cell sequencing. Yet, discerning the functional role of individual genomic lesions remains a substantial challenge due to the complexity and scale of the data. Previously, we introduced REVEALER, which identifies groups of genomic alterations that significantly associate with target functional profiles or phenotypes, such as pathway activation, gene dependency, or drug response. In this paper, we present a new mathematical formulation of the algorithm. This version (REVEALER 2.0) is considerably more powerful than the original, allowing for rapid processing and analysis of much larger datasets and facilitating higher-resolution discoveries at the level of individual alleles. REVEALER 2.0 employs the Conditional Information Coefficient (CIC) to pinpoint features that are either complementary or mutually exclusive but still correlate with the target functional profile. The aggregation of these features provides a better explanation for the target functional profile than any single alteration on its own. This is indicative of scenarios where several activating genomic lesions can initiate or stimulate a key pathway or process. We replaced the initial three-dimensional kernel estimation with multiple precomputed one-dimensional kernel estimations, resulting in an approximate 150x increase in speed and efficiency. This improvement, combined with its efficient execution, makes REVEALER 2.0 suitable for much larger datasets and a more extensive range of genomic challenges.