bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural menopause timing and menopause symptoms among lesbian, bisexual, and heterosexual women in the Nurses' Health Study II
Authors: VanKim Nicole A. , Charlton Brittany M. , Berzansky Isa , Fields Nicole D. , Whitcomb Brian W. , Hankinson Susan E. , Sievert Lynnette Leidy , Bertone-Johnson Elizabeth R. 
Published: October 2024

Abstract

Objective
This study aimed to examine sexual orientation differences in natural menopause timing and symptoms between lesbian and bisexual women compared with heterosexual women.

Methods
We used longitudinal questionnaire data (1989-2015) from 92,314 women (858 lesbian, 375 bisexual) in the Nurses' Health Study II cohort. Women were 24-44 yr old at baseline and biennially reported their menopause status, including reasons for cessation of menstrual periods. In 2009 and 2013, women reported on their experience of hot flashes and night sweats. Covariates included age, age at menarche, body mass index, smoking, and parity. Sexual orientation was reported in 1995 and 2009.

Results
Age-adjusted Cox models and logistic regression models suggest that there were no statistically significant differences in menopause timing between lesbian or bisexual women when compared with heterosexual women. When examining menopause symptoms, lesbian women consistently had a statistically significantly (P < 0.05) higher odds of experiencing hot flashes or night sweats (odds ratio range: 1.17 to 1.72) and moderate/severe symptoms (OR range: 1.26 to 1.77) than heterosexual women, even after adjusting for covariates such as smoking and obesity. There were no statistically significant differences in menopause symptoms between bisexual and heterosexual women.

Conclusions
Our findings suggest no meaningful difference in menopause timing between sexual minority and heterosexual women. Additionally, menopause symptoms were more likely among lesbian women and warrants additional study.
Management of chronic septic nonunion of the femur associated with an extended drug resistant nosocomial germ: a case report
Authors: Kalantar Seyed Hadi , Bagheri Nima , Khabiri Seyyed Saeed , Oghbaee Behnam , Hoveidaei Amir Human 
Published: October 2024

Introduction and Importance:
Septic nonunion of long bones poses significant treatment challenges, often necessitating extended hospital stays and multiple surgical interventions. This report details a chronic septic nonunion of the femur, complicated by drug-resistant pathogens, managed through an integrated surgical approach.

Case Presentation:
A 32-year-old male with a history of infected nonunion and multiple failed surgeries presented with a vast bone defect and osteomyelitis. Treatment involved single-session debridement, bone resection, intramedullary fixation, and trifocal segment bone transport using the Limb Reconstruction System (LRS) and Masquelet technique. After eight months, the patient achieved radiologic and clinical bone healing, regained full ambulation, and resumed work without re-infection over an 18-months follow-up.

Clinical Discussion:
The management of septic nonunion, particularly with drug-resistant infections, requires a multifaceted approach. This case exemplifies the efficacy of combining radical bone resection, targeted debridement, and advanced reconstructive techniques. The use of antibiotic-impregnated cement beads and bone transport procedures played pivotal roles in the successful outcome. While such procedures can be complex and necessitate vigilant monitoring, they are crucial for improving treatment success and functional recovery.

Conclusion:
Septic nonunion caused by extended drug-resistant germs of the lower extremity long bones can be managed in a single-session bone resection and debridement, local antibiotic administration, and later bone defect reconstruction.
Understanding Behavior Change in Clinical Practice Guideline Implementation: A Qualitative Study
Authors: Tilson Julie K. , Martinez Clarisa , Mickan Sharon , D’Silva Linda J. , Howard Robbin , MacDowell Sara , Roth Heidi R. , Skop Karen M. , Dannenbaum Elizabeth , Farrell Lisa 
Published: October 2024

Background and Purpose:
Growing numbers of clinical practice guidelines (CPGs) are available to neurologic physical therapists to guide and inform evidence-based patient care. Adherence to CPG recommendations often necessitates behavior change for therapists and patients. The purpose of this qualitative study was to gain insight into the experiences, perspectives, and drivers of behavioral change for therapists working to improve adherence to a CPG. We also sought to understand the perspectives of patients impacted by this work.

Methods:
Five sites participated in a 6-month implementation study integrating a CPG into local practice using the Knowledge to Action model. At the conclusion of the intervention, therapists and patients were recruited to participate in semi-structured interviews or focus groups. An inductive phenomenological approach was used for data analysis. Two authors coded data to generate primary themes. A secondary analysis used the Capability, Opportunity, Motivation, Behavior (COM-B) model to explain the drivers of behavior change for therapists and patients.

Results:
Perspectives from 16 therapists generated 6 themes around feedback/accountability, teamwork/belonging, complexity/adaptability, leadership/prioritization, engagement/benefit, and motivation/growth. Twelve patients’ perspectives generated 2 themes around communication/personalization and support/recovery. Drivers for behavior change associated with the COM-B model are highlighted.

Discussion and Conclusions:
Therapist adherence to CPG recommendations was supported by inclusive and goal-directed teams, regular quantitative audit and feedback, opportunities for learning, and a sense of accountability to their coworkers, patients, and themselves. Patients’ engagement in rehabilitation was supported by personalized education, objective measures of progress, and a strong therapeutic relationship.

Video Abstract available
for more insights from the authors (see the video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A491).
Whole transcription analysis identified the regulation of hypoxia-inducible factors in monocytes with immune suppression: implications for clinical outcomes
Authors: Shuai Zhao , Hui Li , Wei Luo , Zhaolan Hu , Yulu Wang , Tao Liu , Yanling Zhang , RuPing Dai 
Published: October 2024

Abstract

Aims
Sepsis progression is marked by a complex immune response, where the involvement of hypoxia-inducible factors (HIF) plays an uncertain role. The study aims to elucidate the involvement of HIF-1α in monocyte function during sepsis and its potential as a prognostic indicator.

Methods and Results
Transcriptomic data from healthy individuals and septic patients in datasets GSE54514, GSE167363, and GSE46955 were analyzed. Additionally, human monocytes were employed to elucidate how HIF regulates immune responses in the context of sepsis. Septic non-survivors exhibited sustained upregulation of HIF-1α expression alongside compromised inflammatory response and antigen presentation, with downregulation of NF-κB and HLADRB1 genes associated with poor sepsis prognosis. Conversely, septic survivors displayed an increased proportion of classical monocytes and enhanced inflammation and expression of antigen presentation-related genes. During the recovery phase of sepsis, monocytes continued to demonstrate elevated HIF-1α expression. In cultured THP1 cells and septic CD14+ monocytes, HIF hindered inflammatory responses and antigen presentation, while also suppressing the proportion of classical monocytes after LPS stimulation. Mechanistically, HIF significantly attenuated LPS-induced immune responses in monocytes by inhibiting the phosphorylation of IKK.

Conclusions
HIF in monocytes acts as a suppressor of immune-inflammatory responses and antigen presentation, and may serve as a negative molecular marker for sepsis development.
The Current State of Surgical Ergonomics
Authors: Park Amy J. 
Published: October 2024

Objective
Work-related musculoskeletal disorders are widespread among surgeons, causing significant disability and career modification. Gender plays a role, as female surgeons have a two-fold greater risk for discomfort during certain operations due to generally smaller hand sizes and height as compared to male surgeons. There is a lack of appropriate surgical instrumentation geared toward smaller hand sizes. Maintaining a neutral position while operating, frequent changes in position, and increased awareness can contribute to decreasing the detrimental impact on surgeons' bodies from performing operations.
Statistically principled feature selection for single cell transcriptomics
Authors: Dollinger Emmanuel , Silkwood Kai , Atwood Scott , Nie Qing , Lander Arthur D. 
Published: October 2024

ABSTRACTThe high dimensionality of data in single cell transcriptomics (scRNAseq) requires investigators to choose subsets of genes (feature selection) for downstream analysis (e.g., unsupervised cell clustering). The evaluation of different approaches to feature selection is hampered by the fact that, as we show here, the performance of feature selection methods varies greatly with the task being performed. For routine cell type identification, even randomly chosen features can perform well, but for cell type differences that are subtle, both number of features and selection strategy can matter strongly. Here we present a simple feature selection method grounded in an analytical model that, without resorting to arbitrary thresholds or user-defined parameters, allows for interpretable delineation of both how many and which features to choose, facilitating identification of biologically meaningful rare cell types. We compare this method to default methods in scanpy and Seurat, as well as SCTransform, showing how greater accuracy can often be achieved with surprisingly few, well-chosen features.
Integrated Isoform-Resolved Transcriptomic Analysis ofGossypium barbadenseandGossypium hirsutumFibers
Authors: Tang Jiwei , Gu Xinxin , Ma Yue , Meng Qingying , Xie Peihao , Jiang Shihe , Hui Liuyang , Lang Yiyang , Tang Mengqin , Zheng Ying , Yuan Daojun 
Published: October 2024

AbstractA comprehensive understanding of RNA expression and splicing during cotton fiber development plays a crucial role in explaining the differences in fiber quality between two different cotton species. To date, most cotton transcriptomic studies have utilized short-read sequencing data, which limits the ability to capture full-length mRNAs. In this study, we compiled long-read RNA sequencing data from the PacBio platform, as well as short-read RNA sequencing data from 10 fiber developmental stages, for bothGossypium barbadenseandGossypium hirsutum. We identified 183,767 and 178,994 isoforms inGossypium barbadenseandGossypium hirsutum, respectively, generating the most comprehensive transcriptomic atlas of cotton to date. Alternative splicing events exhibited stage-specific variations during fiber development, and co-expression network analysis, combined with LASSO regression, identified isoforms highly correlated with each developmental stage. These findings reveal previously uncharacterized aspects of isoform regulation during fiber development and provide valuable resources for further research into the molecular mechanisms underlying fiber quality differences between cotton species.
Deep Learning Enhances Precision of Citrullination Identification in Human and Plant Tissue Proteomes
Authors: Gabriel Wassim , Meelker Gonzalez Rebecca , Laposchan Sophia , Riedel Erik , Dündar Gönül , Poppenberger Brigitte , Wilhelm Mathias , Lee Chien-Yun 
Published: October 2024

AbstractCitrullination is a critical yet understudied post-translational modification (PTM) implicated in various biological processes. Exploring its role in health and disease requires a comprehensive understanding of the prevalence of this PTM at a proteome-wide scale. Although mass spectrometry has enabled the identification of citrullination sites in complex biological samples, it faces significant challenges, including limited enrichment tools and a high rate of false positives due to the identical mass with deamidation (+0.9840 Da) and errors in monoisotopic ion selection. These issues often necessitate manual spectrum inspection, reducing throughput in large-scale studies. In this work, we present a novel data analysis pipeline that incorporates the deep learning model Prosit-Cit into the MS database search workflow to improve both the sensitivity and precision of citrullination site identification. Prosit-Cit, an extension of the existing Prosit model, has been trained on ∼53,000 spectra from ∼2,500 synthetic citrullinated peptides and provides precise predictions for chromatographic retention time and fragment ion intensities of both citrullinated and deamidated peptides. This enhances the accuracy of identification and reduces false positives. Our pipeline demonstrated high precision on the evaluation dataset, recovering the majority of known citrullination sites in human tissue proteomes and improving sensitivity by identifying up to 14 times more citrullinated sites. Sequence motif analysis revealed consistency with previously reported findings, validating the reliability of our approach. Furthermore, extending the pipeline to a tissue proteome dataset of the model plantArabidopsis thalianaenabled the identification of ∼200 citrullination sites across 169 proteins from 30 tissues, representing the first large-scale citrullination mapping in plants. This pipeline can be seamlessly applied to existing proteomics datasets, offering a robust tool for advancing biological discoveries and deepening our understanding of protein citrullination across species.
AlphaFold2’s training set powers its predictions of fold-switched conformations
Authors: Schafer Joseph W. , Porter Lauren L. 
Published: October 2024

ABSTRACTAlphaFold2 (AF2), a deep-learning based model that predicts protein structures from their amino acid sequences, has recently been used to predict multiple protein conformations. In some cases, AF2 has successfully predicted both dominant and alternative conformations of fold-switching proteins, which remodel their secondary and tertiary structures in response to cellular stimuli. Whether AF2 has learned enough protein folding principles to reliably predict alternative conformations outside of its training set is unclear. Here, we address this question by assessing whether CFold–an implementation of the AF2 network trained on a more limited subset of experimentally determined protein structures– predicts alternative conformations of eight fold switchers from six protein families. Previous work suggests that AF2 predicted these alternative conformations by memorizing them during training. Unlike AF2, CFold’s training set contains only one of these alternative conformations. Despite sampling 1300-4400 structures/protein with various sequence sampling techniques, CFold predicted only one alternative structure outside of its training set accurately and with high confidence while also generating experimentally inconsistent structures with higher confidence. Though these results indicate that AF2’s current success in predicting alternative conformations of fold switchers stems largely from its training data, results from a sequence pruning technique suggest developments that could lead to a more reliable generative model in the future.
Anticancer Target Combinations: Network-Informed Signaling-Based Approach to Discovery
Authors: Yavuz Bengi Ruken , Jang Hyunbum , Nussinov Ruth 
Published: October 2024

AbstractWhile anticancer drug discovery has seen dramatic innovations and successes, sequential single therapies are time-limited by resistance, and combinatorial strategies have been lagging. The number of possible drug combinations is vast. To select drug combinations the oncologist requires knowledge of the optimal combination of proteins to co-target. Currently, combinations that the oncologist considers are primarily from empirical observations and clinical praxis. Our aim is to develop a signaling-based method to discover optimal proteins for the oncologist to co-target with drug combinations, and test it on available, patient-derived data. To temper the expected resistance to single drug regimen, we offer a concept-based stratified pipeline aimed at selecting co-targets for drug combinations. Our strategy is unique in its co-target selection being based on signaling pathways. This is significant since in cancer, drug resistance commonly bypasses blocked proteins by wielding alternative, or complementary, routes to execute cell proliferation. Our network-informed signaling-based approach harnesses advanced network concepts and metrics, and our compiled, tissue-specific co-existing mutations. Co-existing driver mutations are common in resistance. Thus, to mimic cancer and counter drug resistance scenarios, our pipeline seeks co-targets that when targeted by drug combinations, can shut off cancer’smodus operandi. That is, its parallel or complementary signaling pathways would be blocked. Rotating through combinations could further lessen emerging resistance. We applied it to patient-derived breast and colorectalESR1|PIK3CAandBRAF|PIK3CAsubnetworks. Consistently, in breast cancer, our results suggest co-targeting proteins from theESR1|PIK3CAsubnetwork with an alpelisib-LJM716 combination. In colorectal cancer, they co-targetBRAF|PIK3CAwith alpelisib, cetuximab, and encorafenib combination. Collectively, our pipeline’s results are promising, and validated by patient-based xenografts.GRAPHICAL ABSTRACT
IVNS1ABP Deficiency Disrupts Actin Filament Organization and Leads to Cellular Senescence in a Newly Identified Progeroid Neuropathy Syndrome
Authors: Yuan Fang , Tan Ye Sing , Wang Haofei , Ali Ain Nur , Yuan Qiang , Chou Shu-Min , Yen Yu-Hsin , Narayanan Gunaseelan , Zhou Lei , Shboul Mohammad , Bonnard Carine , Reversade Bruno , Zhang Su-Chun 
Published: October 2024

SummaryA homozygous variant inIVNS1ABPwas identified in three siblings, displaying progeroid features with severe neuropathy. By generating isogenic induced pluripotent stem cells (iPSCs) from the patients’ fibroblasts and differentiating the iPSCs into neural progenitor cells (NPCs), we found that mutant IVNS1ABP fibroblasts, iPSCs, and NPCs exhibited disrupted cytokinesis, DNA damage and cellular senescence. Correspondingly, cerebral organoids displayed premature differentiation of NPCs to neurons. Molecular profiling as well as biochemical and cellular analysis revealed altered binding of mutant IVNS1ABP to actin /actin-associated proteins and dysregulated actin dynamics during cytokinesis. Taken together, we propose that mutant IVNS1ABP dysregulates actin polymerization and organization which is at least partly responsible for the cellular senescence phenotypes in this progeroid neuropathy syndrome.
A novel toolbox of GATEWAY-compatible vectors for rapid functional gene analysis in soybean composite plants
Authors: Mejias Joffrey , Margets Alexandra , Bredow Melissa , Foster Jessica , Khwanbua Ekkachai , Goshon Jackson , Maier Thomas R. , Whitham Steven A. , Innes Roger W. , Baum Thomas J. 
Published: October 2024

AbstractThe generation of transgenic plants is essential for plant biology research to investigate plant physiology, pathogen interactions and gene function. However, producing stable transgenic plants for plants such as soybean is a laborious and time-consuming process, which can impede research progress. Composite plants consisting of wild-type shoots and transgenic roots are an alternative method for generating transgenic plant tissues that can facilitate functional analysis of genes-of-interest involved in root development or root-microbe interactions. In this report, we introduce a novel set of GATEWAY-compatible vectors that enable a wide range of molecular biology uses in roots of soybean composite plants. These vectors incorporate in-frame epitope fusions of green fluorescent protein, 3x-HA, or miniTurbo-ID, which can be easily fused to a gene-of-interest using the GATEWAY cloning system. Moreover, these vectors allow for the identification of transgenic roots using either mCherry fluorescence or the RUBY marker. We demonstrate the functionality of these vectors by expressing subcellular markers in soybean, providing evidence of their effectiveness in generating protein fusions in composite soybean plants. Furthermore, we show how these vectors can be used for gene function analysis by expressing the bacterial effector, AvrPphB in composite roots, enabling the identification of soybean targets via immunoprecipitation followed by mass spectrometry. Additionally, we demonstrate the successful expression of stable miniTurbo-ID fusion proteins in composite roots. Overall, this new set of vectors is a powerful tool that can be used to assess subcellular localization and perform gene function analyses in soybean roots without the need to generate stable transgenic plants.Key MessageWe developed a set of GATEWAY vectors to accelerate gene function analysis in soybean composite plants to rapidly screen transgenic roots and investigate subcellular localization, protein-protein interactions, and root-pathogen interactions.
Efficient indexing and querying of annotations in a pangenome graph
Authors: Novak Adam M. , Chung Dickson , Hickey Glenn , Djebali Sarah , Yokoyama Toshiyuki T. , Garrison Erik , Narzisi Giuseppe , Paten Benedict , Monlong Jean 
Published: October 2024

AbstractThe current reference genome is the backbone of diverse and rich annotations. Simple text formats, like VCF or BED, have been widely adopted and helped the critical exchange of genomic information. There is a dire need for tools and formats enabling pangenomic annotation to facilitate such enrichment of pangenomic references. The Graph Alignment Format (GAF) is a text format, tab-delimited like BED/VCF files, which was proposed to represent alignments. GAF could also be used to store paths representing annotations in a pangenome graph, but there are no tools to index and query them efficiently.Here, we present extensions to vg and HTSlib that provide efficient sorting, indexing, and querying for GAF files. With this approach, annotations overlapping a subgraph can be extracted quickly. Paths are sorted based on the IDs of traversed nodes, compressed with BGZIP, and indexed with HTSlib/tabix via our extensions for the GAF format. Compared to the binary GAM format, GAF files are easier to edit or inspect because they are plain text, and we show that they are twice as fast to sort and half as large on disk. In addition, we updatedvg annotate, which takes BED or GFF3 annotation files relative to linear sequences and projects them into the pangenome. It can now produce GAF files representing these annotations’ paths through the pangenome.We showcase these new tools on several applications. We projected annotations for all Human Pangenome Reference Consortium Year 1 haplotypes, including genes, segmental duplications, tandem repeats and repeats annotations, into the Minigraph-Cactus pangenome (GRCh38-based v1.1). We also projected known variants from the GWAS Catalog and expression QTLs from the GTEx project into the pangenome. Finally, we reanalyzed ATAC-seq data from ENCODE to demonstrate what a coverage track could look like in a pangenome graph. These rich annotations can be quickly queried with vg and visualized using existing tools like the Sequence Tube Map or Bandage.