bluuebunny/crossref_metadata_2025_split huggingface dataset:
Human Papillomavirus Genotype Attribution and Integration in High-Grade Vaginal Intraepithelial Neoplasia
Authors: Shen Yuanming , Tang Sangsang , Zhou Yumei , Zhang Qiuxue , Chen Tingting , Li Jingnan , Wang Yu , Wan Xiaoyun , Lu Weiguo , Xu Junfen 
Published: December 2024

Objective
The aim of the study was to investigate the distribution and association between human papillomavirus (HPV) genotypes and integration as well as their correlation with cervical lesions.

Methods
Two hundred seven patients diagnosed with high-grade vaginal intraepithelial neoplasia (HG-VaIN) were recruited from the Women's Hospital School of Medicine Zhejiang University between 2015 and 2021 and assayed for HPV genotyping. HPV integration sequencing analysis was conducted using tissues from 53 patients with HG-VaIN and 4 patients with invasive vaginal carcinoma (IVC), along with paired cervical lesion specimens.

Results
A total of 207 patients with HG-VaIN were categorized as having cervical lesions unrelated to HG-VaIN (group A, 71 patients, 34.30%) or cervical lesion-related HG-VaIN (group B, 136 patients, 65.70%). With an average follow-up of 42.19 months, 12 of 153 patients progressed to IVC and were all from group B. HPV16 infection and the presence of cervical lesions were the 2 main factors associated with disease progression, with cervical lesion coexistence being an independent factor. Compared with group A (5/20, 25%), group B (17/33, 51.52%) showed a higher rate of HPV integration, as demonstrated using HPV integration sequencing analysis, with HPV16 being the most integrated genotype (72.73%). The integration analysis of 4 patients with IVC paired with cervical lesion specimens showed that 3 of the 4 pairs exhibited the same HPV infection and integration sites, indicating a high degree of homology in HPV integration between cervical lesions and HG-VaIN-induced IVC.

Conclusions
Patients with HG-VaIN associated with cervical lesions exhibited a higher risk of malignant transformation, necessitating more proactive treatment approaches.
The incidence of hepatitis B reactivation in patients receiving ustekinumab: a systematic review and proportional meta-analysis
Authors: Alhalabi Marouf M. , Almokdad Rasha 
Published: December 2024

Background:
This meta-analysis will evaluate the risk of hepatitis B reactivation in patients treated with ustekinumab for inflammatory bowel disease and psoriasis. We aim to determine the true incidence of this adverse event, reconcile discrepancies in reported reactivation rates, and elucidate the associated risk.

Methods:
We conducted a rigorous systematic review adhering to established guidelines. Major databases like MEDLINE, Google Scholar, CENTRAL, and ClinicalTrials.gov were searched. Studies involving patients with documented hepatitis B infection undergoing ustekinumab therapy were included. Patients receiving concurrent antiviral medications were excluded. To account for potential underreporting, studies without reactivation events or with sample sizes ≥3 were also considered by using generalized linear mixed models and Clopper–Pearson confidence intervals. This review was prospectively registered in PROSPERO (CRD42023418130).

Results:
We analyzed data from nine studies involving 104 hepatitis B virus (HBV)-infected patients. The pooled HBV reactivation (HBVr) incidence among hepatitis B surface antigen-positive patients was 10% [95% confidence interval (CI): 0–31%], with low heterogeneity (I
2 = 7.13%, τ
2 = 0.4) and a nonsignificant Q-statistic (Q = 5.38, P = 0.37). For the occult HBV-infected patients, the pooled HBVr incidence was 3% (95% CI: 0–11%), with no heterogeneity (I
2 = 0%, τ
2 = 0.0) and a nonsignificant Q-statistic (Q = 2.7, P = 0.61). The reactivation rates showed high consistency across studies, with no significant difference between the two groups.

Conclusions:
While our data suggest lower HBVr risk with ustekinumab, confirmation is needed due to limited sample size and retrospective design.
The Catatonia Quick Screen (CQS): A Rapid Screening Tool for Catatonia in Adult and Pediatric Populations
Authors: Luccarelli James , Kalinich Mark , Wilson Jo Ellen , Liu Jinyuan , Fuchs D. Catherine , Francis Andrew , Heckers Stephan , Fricchione Gregory , Smith Joshua Ryan 
Published: November 2024

AbstractIntroductionCatatonia is a neuropsychiatric disorder marked by significant disturbances in motor, cognitive, and affective functioning and that is frequently under-diagnosed. To enhance clinical detection of catatonia, this study aimed to develop a rapid, sensitive Catatonia Quick Screen (CQS) using a reduced set of catatonic signs to facilitate screening in adult and pediatric patients.MethodsData were derived from two retrospective cohorts totaling 446 patients (254 adults, 192 children) who screened positive for catatonia using the Bush Francis Catatonia Screening Instrument (BFCSI). Sensitivity analyses were performed for all combinations of BFCSI signs, with sensitivity defined as the proportion of patients identified by each subset relative to the full BFCSI. The CQS was developed by selecting signs from the BFCSI based on sensitivity, ease of assessment, and relevance to diverse catatonia presentations.ResultsScreening for the presence of any one of four signs—excitement, mutism, staring, or posturing—using the CQS yielded a theoretical sensitivity of 97% (95% CI: 95 to 98%) relative to the full BFCSI (which requires two signs out of 14). The CQS demonstrated 97% sensitivity across both pediatric and adult subsets.ConclusionThe Catatonia Quick Screen provides a rapid screening alternative to the BFCSI with high sensitivity, potentially improving early detection of catatonia in clinical settings. Future prospective studies are necessary to validate the CQS’s sensitivity and to determine its specificity in clinical populations.Significant OutcomesThe Catatonia Quick Scale (CQS) is a newly developed rapid screen for catatonia.Assessment for any one of four signs—excitement, mutism, staring, and posturing—has 97% sensitivity for detecting catatonia relative to the BFCSI.This screening is sensitive in both adult and pediatric populations.LimitationsThe study relies on retrospective data.Only patients who initially screened positive for catatonia were included, so the specificity of the CQS could not be assessed.Most of the sample has a primary psychiatric diagnosis so the generalizability to patients with primary medical disorders is unclear.
Investigating causal relationships between loneliness, social isolation and health
Authors: Hilliard Darren D. , Wootton Robyn E. , Sallis Hannah M. , Van De Weijer Margot P. , Treur Jorien L. , Qualter Pamela , Dixon Padraig , Sanderson Eleanor C.M. , Carslake David J. , Richmond Rebecca C. , Beloe Patricia , Turner-Harris Lucy , Byatt Lauren Bowes , Munafò Marcus R. , Reed Zoe E. 
Published: November 2024

AbstractLoneliness and social isolation are important public health concerns due to their associations with a range of health outcomes. However, it is difficult to ascertain whether loneliness and social isolation cause those outcomes or whether the observed associations are biased by confounding and reverse causation. In this study we used a triangulation approach combining observational analysis, sibling control design, and Mendelian Randomisation (a genetically informed causal inference approach), to draw robust conclusions about these relationships. Using a combination of publicly available genome-wide association study (N= 17,526 to 2,083,151) and UK Biobank data (N= 8,075 to 414,432), we examined relationships between loneliness and social isolation and outcomes related to physical health, mental health and wellbeing and general health (reflecting both physical and mental health e.g., multimorbidity). Our results provide evidence for causal effects of loneliness and social isolation on poorer mental health and wellbeing and of loneliness on poorer general health. Evidence was generally stronger for loneliness compared to social isolation. We do not find evidence of effects on specific physical health outcomes; however, we cannot definitively rule out causal relationships. Interventions targeting loneliness and social isolation may be effective strategies for improving general health, mental health and wellbeing outcomes.
Identification of a Highly Functional Effector CD8+T Cell Program after Transplantation in Mice and Humans
Authors: Cohen Gregory S. , Freibaum Joel S. , Leathem Riley P. , Hatano Ryo , Morimoto Chikao , Krummey Scott M. 
Published: December 2024

ABSTRACTAcute T cell mediated rejection of allografts remains a significant risk factor for early graft loss. Our prior work defined a population of graft-specific CD8+T cells positive for the activated receptor CD43 (expressing the 1B11 epitope) that form during acute rejection, leading us to further understand the in vivo fate and clinical relevance of this population. We found that during acute rejection, the CD43+ICOS+phenotype was sensitive for proliferative graft-specific CD8+T cells. We evaluated whether CD43 1B11 signaling could impact graft survival, and found that CD43 1B11 mAb treatment could overcome costimulation-blockade induced tolerance in the majority of mice. Using an adoptive transfer approach, we investigated the fate of CD43 1B11+and CD43 1B11-CD8+T cell populations, and found that CD43 1B11+CD8+T cells were more persistent three weeks after transplantation. A portion of CD43 1B11-CD8+T cells converted to CD43 1B11+, while CD43 1B11+CD8+T cells retained CD43 1B11+status. In healthy human donors, we found that the CD43 1D4 clone, which identifies the large CD43 isoform, defines a population of antigen-experienced CD8+T cells independent of the canonical CD8+T cell populations. CD43 1D4+CD8+T cells were efficient cytokine-producers after stimulation. In scRNA-seq analysis of graft-infiltrating cells from renal transplant patients experiencing acute rejection, a population of SPN+GCNT1+CD8+T cells had an effector phenotype that includes high expression of IFNG, ICOS, and perforins/granzymes. Together, these data provide evidence that the CD43 1B11 expression defines a proliferative and persistent population of CD8+T cells in mice, and that an analogous population of antigen-experienced CD8+T cells that participate in allograft rejection.
Optimization of a Multi-Feature AI Ensemble and Voting System for MAPKAPK2 Inhibitor Discovery
Authors: Chen Hayden 
Published: December 2024

1.AbstractThe identification of an effective inhibitor is an essential starting point in drug discovery. Unfortunately, many issues arise with conventional high-throughput screening methods. Thus, new strategies are needed to filter through large compound screening libraries to create target-focused, smaller libraries. Effective computational methods in this respect have emerged in the past decade or so; among these methods is machine learning. Herein, we explore an ensemble Deep Learning model trained on MAPKAPK2 bioactivity data. This ensemble ML model consists of ten individual models trained on different features, each optimized for MAPKAPK2 inhibitor identification. Voting systems were established alongside the model. Using these voting systems, the ensemble model achieved an accuracy score of 0.969 and precision score of 0.964 on a testing set, in addition to reporting a false positive rate of 0.014 on an inactive compound set. The reported metrics indicate an effective initial step for novel MAPKAPK2 inhibitor identification and subsequent drug development, with applicability to other kinase targets.
Bayesian phylodynamic inference of multi-type population trajectories using genomic data
Authors: Vaughan Timothy G. , Stadler Tanja 
Published: December 2024

AbstractPhylodynamic methods provide a coherent framework for the inference of population parameters directly from genetic data. They are an important tool for understanding both the spread of epidemics as well as long-term macroevolutionary trends in speciation and extinction. In particular, phylodynamic methods based on multi-type birth-death models have been used to infer the evolution of discrete traits, the movement of individuals or pathogens between geographic locations or host types, and the transition of infected individuals between disease stages. In these models, population heterogeneity is treated by assigning individuals to different discrete types. Typically, methods which allow inference of parameters under multi-type birth-death models integrate over the possible birth-death trajectories (i.e. the type-specific population size functions) to reduce the computational demands of the inference. As a result, it has not been possible to use these methods to directly infer the dynamics of trait-specific population sizes, infected host counts or other such demographic quantities. In this paper we present a method which infers these multi-type trajectories with almost no additional computational cost beyond that of existing methods. We demonstrate the practicality of our approach by applying it to a previously-published set of MERS-CoV genomes, inferring the numbers of human and camel cases through time, together with the number and timing of spillovers from the camel reservoir. This application highlights the multi-type population trajectory’s ability to elucidate properties of the population which are not directly ancestral to its sampled members.
The high quality Chinese white truffle genome and novel fossil-calibrated estimate of Pezizomycetes divergence reveal the tempo and mode of true truffles genome evolution
Authors: Martelossi Jacopo , Vujovic Jacopo , Huang Yue , Tatti Alessia , Xu Kaiwei , Puliga Federico , Chen Yuanxue , Stabelli Omar Rota , Ghiselli Fabrizio , Zhang Xiaoping , Zambonelli Alessandra 
Published: December 2024

AbstractThe genusTuber(family: Tuberaceae) includes the most economically valuable ectomycorrhizal (ECM), truffle-forming fungi. Previous genomic analyses revealed that massive transposable element (TE) proliferation represents a convergent genomic feature of mycorrhizal fungi, including Tuberaceae. Repetitive sequences are one of the major drivers of genome evolution shaping its architecture and regulatory networks. In this context, Tuberaceae represent an important model system to study their genomic impact; however, the family lacks high-quality assemblies. Here, we tested the interplay between TEs and Tuberaceae genome evolution by producing a highly contiguous assembly for the endangered Chinese truffleTuber panzhihuanense, along with a novel timeline for Tuberaceae diversification and comprehensive comparative genomic analyses. We found that concurrently with a Paleogene diversification of the family, pre-existing Chromoviridae-related Gypsy clades independently expand in different truffle lineages leading to increased genome size and high gene family turnover rates, but without resulting in highly scrambled genomes. Additionally, we found an enrichment of ECM-induced gene families among ancestral duplication events. Finally, we explored the repetitive structure of nuclear ribosomal DNA (rDNA) loci for the first time in the clade. We found that most of the 45S rDNA paralogues are undergoing concerted evolution, though an isolated divergent locus raises concerns about potential issues for metabarcoding and biodiversity assessments. Our study provides a fundamental genomic resource for future research on truffle genomics and showcases a clear example on how establishment and self-perpetuating expansion of heterochromatin can drive massive genome size variation due to activity of selfish genetic elements.
Comprehensive Enumeration of Cancer Stem-like Cell Heterogeneity Using Deep Neural Network
Authors: Chowdhury Debojyoti , Priyadarshi Shreyansh , Biswas Sayan , Neekhra Bhavesh , Gupta Debayan , Haldar Shubhasis 
Published: December 2024

AbstractCancer stem cells (CSCs), a distinct subpopulation within tumors, are pivotal in driving treatment resistance and tumor recurrence, posing substantial challenges to conventional therapeutic strategies. Precise quantification and profiling of these cells are essential for improving cancer treatment outcomes. We present ACSCeND, an advanced deep neural network model accompanied by a robust workflow, specifically developed to quantify cellular compositions from bulk RNA-seq data, enabling accurate CSC profiling. By integrating bulk RNA-seq data with insights derived from single-cell RNA-seq datasets, ACSCeND effectively captures the diversity and hierarchical organization of tumor-resident cell states, alongside cell-specific gene expression profiles (GEPs). Compared to current tissue deconvolution models, ACSCeND exhibits superior performance, achieving significantly higher Concordance Correlation Coefficient (CCC) values and lower Root Mean Square Error (RMSE) across various pseudobulk and real-world bulk tissue samples. Application of ACSCeND to TCGA and PRECOG datasets reveals a strong association between CSC abundance and poorer disease-free survival outcomes, underscoring the clinical relevance of CSCs in cancer progression. Furthermore, cell-specific GEPs for distinct CSC states unveil novel molecular signatures and illuminate the origins of CSC-driven tumor heterogeneity. In summary, ACSCeND provides a powerful, scalable platform for high-throughput quantification of cellular compositions and distinct potency states within normal tissues as well as highly heterogeneous tissues, such as tumors.
Identifying Family Structures from Obituaries and Matching them to Patients in an Electronic Heath Record
Authors: Mayer John , Delgoffe Brooke , Hebbring Scott 
Published: December 2024

AbstractMotivationFamily data is a valuable data source in bioinformatic research. This is because family members often share common genetic and environmental exposures. Collecting this family data is traditionally very labor intensive but advances in electronic health record (EHR) data mining has proven useful when identifying pedigrees linked to longitudinal health histories. These are called e-pedigrees. Unfortunately, e-pedigrees tend to miss the oldest generations who inherently have the longest and richest health histories. A good source of family data from older generations includes obituaries, as they have a formulaic nature making them a good candidate for natural language processing that can extract relationships to the decedent. While there have been several studies on obtaining such data from obituaries, we demonstrate for the first-time approaches that tie that information to an EHR.ResultsNLP extraction resulted in 8,166,534 family members being abstracted from 567,279 obituaries published in the state of Wisconsin. After matching decedent and family members to patients in the EHR, we identified 109,365 unique patients that were put in 34,158 pedigrees. The largest pedigree consisted of 21 individuals. Heritability of adult height was quantified (H2= 0.51 +- .04, P=< 1.00e-07) demonstrating this data’s use in genetic research. The heritability data, coupled with overlapping data in a biobank, suggested 80% - 90% of familial relationships were accurately defined. The totality of these findings demonstrate obituaries with the oldest generations can be highly informative for bioinformatic research.Availability and ImplementationCode is available on GitHub athttps://github.com/jgmayer672/ObituaryNLP.
Approximate Bayesian computation supports a high incidence of chromosomal mosaicism in blastocyst-stage human embryos
Authors: Yang Qingya , Carioscia Sara A. , Isada Matthew , McCoy Rajiv C. 
Published: December 2024

AbstractChromosome mis-segregation is common in human meiosis and mitosis, and the resulting aneuploidies are the leading cause of pregnancy loss. Preimplantation genetic testing for aneuploidy (PGT-A) seeks to prioritize chromosomally normal embryos for transfer based on genetic analysis of a biopsy of approximately five trophectoderm cells from blastocyst-stagein vitrofertilized (IVF) embryos. While modern PGT-A platforms classify these biopsies as aneuploid, euploid, or mosaic (possessing a mixture of normal and aneuploid cells), the underlying incidences of aneuploid, euploid, and mosaic embryos and the rates of meiotic and mitotic error that produced them remain largely unknown. To address this knowledge gap, we paired a recent method for embryo simulation with approximate Bayesian computation (ABC) to infer rates of meiotic and mitotic error that best explain published PGT-A data. By simulating from these posterior distributions, we also evaluated the chromosomal status of entire embryos. For a published clinical sample, we estimated a 39-43% probability of meiotic error per meiosis, as well as a 1.0-3.0% probability of mitotic error per mitosis, depending on assumptions about spatial clustering of aneuploid cells within mosaic embryos. In addition, our analyses suggest that less than 1% of blastocysts are fully euploid, and that many embryos possess low-level mosaic clones that are not captured during biopsy. These broad conclusions were relatively insensitive to potential misclassification of mosaic biopsies. Together, our work helps overcome the limitations of embryo biopsies to estimate the fundamental rates of cell division errors that are the main causes of human pregnancy loss.
Adherent-to-suspension transition promotes melanoma metastatic dissemination
Authors: Lee Dong Ki , Oh Jongwook , Lee Soyeon , Huh Hyunbin D. , Sub Yujin , Park Hyun Woo , Gee Heon Yung 
Published: December 2024

AbstractMelanoma is a highly metastatic skin cancer that often evades current therapeutic strategies primarily because of the complex mechanisms involved in metastasis. This study investigated the role of adherent-to-suspension transition (AST) in melanoma and its potential to facilitate metastasis by reprogramming cellular anchorage dependency. Using melanoma models, we demonstrated that the AST factors IKZF1, IRF8, and NFE2 are crucial for reprogramming, influencing gene expression related to cell adhesion and survival. Notably, our results highlight that AST factor expression undergoes dynamic changes during metastasis, which can be reversed in circulating tumor cells. Our findings revealed that AST contributes to the increased metastatic potential and invasiveness of melanoma cells and underscores its role independent of the epithelial-to-mesenchymal-like transition pathways. Based on the results, we highlight the potential of targeting AST mechanisms to develop new therapeutic strategies against metastasis.