bluuebunny/crossref_metadata_2025_split huggingface dataset:
Population-Based Cohort Study on Treatment and Overall Survival of Patients Clinically Diagnosed With T1 Ampullary Cancer
Authors: de Wilde Anouk J. , de Jong Evelien J.M. , Bruno Marco J. , Besselink Marc G. , van der Geest Lydia G.M. , Geurts Sandra M.E. , Groot Koerkamp Bas , de Hingh Ignace H.J.T. , de Meijer Vincent E. , Miclea Razvan L. , Poley Jan-Werner , Samarska Iryna V. , van Santvoort Hjalmar C. , Stommel Martijn W.J. , Voermans Rogier P. , Olde Damink Steven W.M. , de Vos-Geelen Judith , Bouwense Stefan A.W. ,   for the Dutch Pancreatic Cancer Group
Published: October 2024

Objective:
To evaluate treatment outcomes, overall survival (OS), and prognostic factors for OS in patients diagnosed with T1 ampullary cancer.

Background:
Ampullary cancer is a rare gastrointestinal malignancy with limited data from large cohorts, especially regarding T1 disease.

Methods:
Patients diagnosed with clinical (c) T1 ampullary cancer and patients with pathological (p) T1 in the case of cTx were included from the Netherlands Cancer Registry (2014-2021). Primary endpoint was OS, analyzed using the Kaplan-Meier estimator. Multivariable Cox proportional hazards regression was used to identify OS predictors.

Results:
Overall, 244 patients with cT1 ampullary cancer were included, of whom 75% (n=184) underwent resection. Among these, 68% (n=125) were upstaged to a higher pathologically T classification (pT2:40%, pT3:22%, pT4:5%). Similarly, cN0 was upstaged to pN1 in 47% of patients (n=87). Next, 100 patients with pT1 and cTx ampullary cancer were included, making a total of 159 patients with pT1 tumor. 92% (146/159) underwent pancreatoduodenectomy while 8% (13/159) underwent endoscopic or local surgical resection. The 1- and 5-year OS for cT1N0 ampullary cancer were 72% and 36%, while for pT1N0 they were 94% and 75%. Independent poor prognostic factors for OS were pN1 classification (HR 2.12; 95%CI 1.15–3.94, P=0.017), pNx classification (i.e. locally resected patients) (HR 2.82; 95%CI 1.22–6.55, P=0.016), and poorly differentiated tumors (HR 4.05; 95%CI 1.33–12.40, P=0.014).

Conclusion:
In patients with cT1 ampullary cancer, more than two-thirds had a pathologically higher T classification, and almost half had a pathologically higher N classification. These findings suggest that pancreatoduodenectomy is recommended for cT1 ampullary cancer.
Fall prevention among psychiatric patients in an Iranian hospital: a best practice implementation project
Authors: Kabiri Neda , Alizadeh Mahasti , Ranjbar Fatemeh , Hajebrahimi Sakineh , Soleimanpour Hassan , Oladbaniadam Khatereh , Marjani Karim , Amini Behrouz , Soleimanpour Maryam 
Published: October 2024

ABSTRACT

Introduction:
Falls are the main cause of disability among psychiatric patients, as well as being the most common adverse event in hospitals.

Aim:
The aim of this evidence implementation project was to improve fall prevention and management among psychiatric patients in a neurology ward in an Iranian tertiary psychiatric hospital.

Methods:
This project used the JBI Evidence Implementation Framework, which recommends an audit, feedback, and re-audit strategy. A baseline audit was conducted to evaluate current fall prevention practices among 50 psychiatric patients and 20 health care professionals. The baseline audit was used to identify gaps in compliance. After the implementation of improvement strategies, a follow-up audit was conducted to measure any changes in practice.

Results:
The baseline and follow-up audits revealed that compliance with best practices improved in ward transfer fall risk assessment (Criterion 2: 87% to 90%), patient participation in fall risk assessment (Criterion 3: 95% to 96%), revising patient fall risk status (Criterion 9: 50% to 86%), and person-centered education of health care providers (Criterion 11: 78% to 96%). Other audit criteria remained unchanged. However, for Criterion 6 on patient engagement in goal-setting and treatment planning, compliance dropped from 100% at baseline to 94% at follow-up.

Conclusions:
This project successfully increased evidence-based practices regarding fall prevention and management, as well as providing mechanisms for sustaining the practice changes. Future audits are required to further improve outcomes.

Spanish abstract:

http://links.lww.com/IJEBH/A267
FieldDino: High-throughput physio-morphological phenotyping of stomatal characteristics for plant breeding research
Authors: Chaplin Edward , Coleman Guy , Merchant Andrew , Salter William 
Published: October 2024

AbstractStomatal anatomy and physiology define CO2availability for photosynthesis and regulate plant water use. Despite being key drivers of yield and dynamic responsiveness to abiotic stresses, conventional measurement techniques of stomatal traits are laborious and slow, limiting adoption in plant breeding. Advances in instrumentation and data analyses present an opportunity to screen stomatal traits at scales relevant to plant breeding. We present a high-throughput field-based phenotyping approach, FieldDino, for screening of stomatal physiology and anatomy. The method allows coupled measurements to be collected in <15 s and consists of: (1) stomatal conductance measurements using a handheld porometer; (2)in situcollection of epidermal images with a digital microscope, 3D-printed leaf clip and Python-based app; and (3) automated deep learning analysis of stomatal features. The YOLOv8-M model trained on images collected in the field achieved strong performance metrics with an mAP@0.5 of 97.1% for stomatal detection. Validation in large field trials of 200 wheat genotypes with two irrigation treatments captured wide diversity in stomatal traits. FieldDino enables stomatal data collection and analysis at unprecedented scales in the field. This will advance research on stomatal biology and accelerate the incorporation of stomatal traits into plant breeding programs for resilience to abiotic stress.HighlightChaplin et al., have developed FieldDino which enables rapid, high-throughput phenotyping of stomatal traits, advancing plant breeding research by integrating streamlined in-field measurements with automated deep learning analysis.
A CXCR4 partial agonist improves immunotherapy by targeting polymorphonuclear myeloid-derived suppressor cells and cancer-driven granulopoiesis
Authors: Qian Jin , Ma Chenkai , Waterbury Quin T. , Zhi Xiaofei , Moon Christine S. , Tu Ruhong , Kobayashi Hiroki , Wu Feijing , Zheng Biyun , Zeng Yi , Zheng Hualong , Ochiai Yosuke , White Ruth A. , Harle David W. , LaBella Jonathan S. , Zamechek Leah B. , Hu Lucas ZhongMing , Moy Ryan H. , Han Arnold S. , Daugherty Bruce , Lederman Seth , Wang Timothy C. 
Published: October 2024

AbstractPolymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) are pathologically activated neutrophils that potently impair immunotherapy responses. The chemokine receptor CXCR4, a central regulator of hematopoiesis, represents an attractive PMN-MDSC target1. Here, we fused a secreted CXCR4 partial agonist TFF2 to mouse serum albumin (MSA) and demonstrated that TFF2-MSA peptide synergized with anti-PD-1 to induce tumor regression or eradication, inhibited distant metastases, and prolonged survival in multiple gastric cancer (GC) models. Using histidine decarboxylase (Hdc)-GFP transgenic mice to track PMN-MDSCin vivo, we found TFF2-MSA selectively reduced the immunosuppressive Hdc-GFP+CXCR4hitumor PMN-MDSCs while preserving proinflammatory neutrophils, thereby boosting CD8+T cell-mediated anti-tumor response together with anti-PD-1. Furthermore, TFF2-MSA systemically reduced PMN-MDSCs and bone marrow granulopoiesis. In contrast, CXCR4 antagonism plus anti-PD-1 failed to provide a similar therapeutic benefit. In GC patients, expanded PMN-MDSCs containing a prominent CXCR4+LOX-1+subset are inversely correlated with the TFF2 level and CD8+T cells in circulation. Collectively, our studies introduce a strategy of using CXCR4 partial agonism to restore anti-PD-1 sensitivity in GC by targeting PMN-MDSCs and granulopoiesis.
DeepAllo: Allosteric Site Prediction using Protein Language Model (pLM) with Multitask Learning
Authors: Khokhar Moaaz , Keskin Ozlem , Gursoy Attila 
Published: October 2024

AbstractAllostery, the process by which binding at one site perturbs a distant site, is being rendered as a key focus in the field of drug development with its substantial impact on protein function. The identification of allosteric pockets (sites) is a challenging task and several techniques have been developed, including Machine Learning (ML) to predict allosteric pockets that utilize both static and pocket features. Our work, DeepAllo, is the first study that combines fine-tuned protein language model (pLM) with FPocket features and shows an increase in prediction performance of allosteric sites over previous studies. The pLM model was fine-tuned on Allosteric Dataset (ASD) in Multitask Learning (MTL) setting and was further used as a feature extractor to train XGBoost and AutoML models. The best model predicts allosteric pockets with 89.66% F1 score and 90.5% of allosteric pockets in the top 3 positions, outperforming previous results. A case study has been performed on proteins with known allosteric pockets, which shows the proof of our approach. Moreover, an effort was made to explain the pLM by visualizing its attention mechanism among allosteric and non-allosteric residues.
Identification of leaf rust resistance loci in hard winter wheat using genome-wide association mapping
Authors: Lakkakula Indira Priyadarshini , Kolmer James A , Sharma Rajat , St. Amand Paul , Bernardo Amy , Bai Guihua , Ibrahim Amir , Bowden Robert L. , Carver Brett F. , Boehm Jeffrey D. , Aoun Meriem 
Published: October 2024

AbstractLeaf rust, caused byPuccinia triticina(Pt), is a serious constraint to wheat production. Developing resistant varieties is the best approach to managing this disease. Wheat leaf rust resistance (Lr) genes have been classified into either all-stage resistance (ASR) or adult-plant resistance (APR). The objectives of this study were to identify sources of leaf rust resistance in contemporary U.S. hard winter wheat (HWW) and to dissect the genetic basis underlying leaf rust resistance in HWW. A panel of 732 elite HWW genotypes was evaluated for response to U.S.Ptraces at the seedling stage and at the adult plant stage in leaf rust nurseries in Oklahoma, Texas, and Kansas. Further, the panel was genotyped using Multiplex Restriction Amplicon Sequencing (MRA-Seq) and DNA markers linked to the known ASR genesLr18,Lr19,Lr21,Lr24,Lr37, andLr42and APR genesLr34,Lr46,Lr67,Lr68,Lr77, andLr78. Single nucleotide polymorphism (SNP) markers derived from MRA-Seq, DNA markers linked to the knownLrgenes, and the phenotypic data were used for genome-wide association study (GWAS) to identify markers associated with leaf rust response. Gene postulation based on leaf rust reactions, DNA markers, and GWAS suggested the presence ofLr1,Lr2a,Lr10,Lr14a,Lr16,Lr18,Lr19,Lr21,Lr24,Lr26,Lr34,Lr37, Lr39,Lr42,Lr46,Lr68,Lr77, andLr78in the HWW panel. The GWAS identified 59 SNPs significantly associated with leaf rust response, of which 20 were likely associated with novel resistance loci and can be used to enhance wheat leaf rust resistance.
Visualization and quantification of spatiotemporal disease progression in Arabidopsis using a bioluminescence-based imaging system
Authors: Taks Nanne W. , Batstra Mathijs , Kortekaas Ronald , Stevens Floris D. , Pfeilmeier Sebastian , van den Burg Harrold A. 
Published: October 2024

AbstractPlant pathogenic bacteria use various entry strategies to colonize their host, like entering through natural openings and wounds in leaves and roots. The vascular pathogenXanthomonas campestrispv. campestris (Xcc) enters through hydathodes, organs at the leaf margin involved in guttation. Subsequently, Xcc breaks out from infected hydathodes, progressing into the xylem vessels and causing systemic disease. To elucidate the mechanisms that underpin the different stages of Xcc pathogenesis, a need exists to image Xcc progressionin plantain a non-invasive manner. Here, we describe a phenotyping setup and Python image analysis pipeline capturing the Xcc infection in 16Arabidopsis thalianaplants in parallel over time. The setup used both an RGB to capture disease symptoms and an ultra-sensitive CCD camera to monitor bacterial progression inside the leaves using bioluminescence. We demonstrate that the image analysis pipeline reliably quantifies bacterial growthin plantafor two bacterial species, that is vascular Xcc and the mesophyll pathogenPseudomonas syringaepv. tomato. The resolution of the camera allowed early detection of Xcc in the hydathodes, yielding valuable information on this early stage of the Xcc infection process. The data obtained through the automated image analysis pipeline was robust and validated findings from other bioluminescence imaging methods, while requiring fewer samples. We can thus quantify the resistance level of a large number ofArabidopsis thalianaaccessions and mutant lines to different bacterial strains in a non-invasive manner for phenotypic screenings.
Positive correlations in susceptibility to a diverse panel of viruses across host species
Authors: Imrie Ryan M. , Wallace Megan A. , Longdon Ben 
Published: October 2024

AbstractOur ability to predict the emergence of novel viruses relies on there being generalisable patterns in the susceptibilities of hosts to novel infections. Studies investigating variation in susceptibility among host species have consistently shown that closely related hosts share similar susceptibilities to a given virus. However, the extent to which such phylogenetic patterns of susceptibility are correlated amongst diverse sets of viruses is unclear. Here, we investigate phylogenetic correlations in susceptibility amongDrosophilidaehosts to a panel of eleven different invertebrate viruses, comprising seven unique virus species, six unique families, and both RNA and DNA viruses. The susceptibility of hosts to each pair of viruses tested was either positively correlated across host species or did not show evidence of correlation. No negative correlations, indicative of evolutionary trade-offs in host susceptibility to different viruses, were detected between any virus pairs. The strength of correlations were generally higher in viruses of the same species and family, consistent with virus phylogenetic patterns in host infectivity. Our results suggest that generalised host susceptibility can result in positive correlations, even between highly diverged viruses, while specialised interactions with individual viruses cause a stepwise decrease in correlation strength between viruses from the within-species, to the within-family, to the across-family level.
Growth Rate Assessed by Vascular Deformation Mapping predicts Type B Aortic Dissection in Marfan Syndrome
Authors: Campello Jorge Carlos Alberto , Marway Prabhvir Singh , Tjahjadi Nicasius S , Knauer Heather A , Patel Himanshu J , Hofmann Bowman Marion , Eagle Kim , Burris Nicholas S. 
Published: October 2024

ABSTRACTBackgroundPatients with Marfan syndrome (MFS) are at a high risk of type B dissection (TBAD). Aortic growth and elongation have been suggested as risk factors for TBAD. Vascular deformation mapping (VDM) is an image analysis technique for mapping 3D aortic growth on rouine computed tomography angiography (CTA) scans. We aimed to use VDM to examine the value of aortic growth rate in the descending thoracic aorta (DescAo), among other imaging biomarkers, to identify the factors associated with risk of TBAD in MFS.Methods and ResultsCTA scans spanning 2004-2023 from adult MFS patients with native DescAo were analyzed by VDM. Other measurements included multi-level thoracoabdominal aortic diameters and the length of the DescAo by centerline analysis.Among the 105 MFS patients analyzed, 63.8% were male, with median age of 40 years (range 18-73) and a median surveillance interval of 5.3 years (range 2.0-18.3). During surveillance, 12 (11.4%) patients developed TBAD. Patients with TBAD had higher radial growth rate (0.63 vs. 0.23 mm/year;p< 0.001) and elongation rate (2.4 vs. 0.5 mm/year;p< 0.001), on univariate and multivariable analysis, but pre-dissection descending aortic diameter was not significantly different. Predictors of growth rate included younger age, higher baseline maximal diameter of the DescAo, smoking history and warfarin use.ConclusionsRadial growth and elongation rates of the DescAo were independent predictors of TBAD occurrence in MFS. TBAD often occurred in at non-aneurysmal diameters (<4.0 cm). These findings emphasize the role of growth over absolute diameter in risk stratification for TBAD in MFS.
Identification of Hub Genes and CDK1-Targeting Therapeutics in Hepatocellular Carcinoma: Bioinformatics and Simulation Study
Authors: Romero Ricardo , Toledo Cinthia C. 
Published: October 2024

AbstractBackgroundHepatocellular carcinoma (HCC) remains a significant global health challenge, often associated with chronic hepatitis B (HBV) and hepatitis C (HCV) infections. Novel therapeutic approaches are urgently needed to improve patient outcomes.ObjectiveTo identify and validate potential therapeutic targets and novel drug candidates for HBV, HCV, and associated HCC using integrative bioinformatics and molecular dynamics simulations.MethodsGene expression datasets from HCC studies were analyzed to identify dysregulated genes. Protein-protein interaction networks were constructed to determine hub genes. Virtual screening of kinase compound libraries against CDK1 was performed, followed by molecular docking and dynamics simulations. Drug-likeness and metabolic properties of hit compounds were evaluated.ResultsSeven hub genes were identified, including five upregulated (CDK1, AURKB, CCNA2, BUB1B, RRM2) and two downregulated (AGXT2, ESR1) genes. Virtual screening yielded three promising hit compounds (G213-0272, E130-0174, Z666960592) targeting CDK1. E130-0174 demonstrated the most favorable profile, with stable CDK1 binding and no inhibition of major cytochrome P450 enzymes. Two repurposed drugs, alvocidib and riviciclib, also showed potential as CDK1 inhibitors.ConclusionsThis study identified novel CDK1 inhibitors with promising profiles for HCC treatment. The integrative approach combining bioinformatics and molecular dynamics simulations provides a robust framework for identifying potential therapeutic targets and drug candidates in HCC and related liver diseases. Further experimental validation is warranted to confirm these findings and advance the development of new HCC treatments.
Estrogen Receptor 1 Signaling in Hepatic Stellate Cells Designates Resistance to Liver Fibrosis
Authors: Li Tianhao , Wang Gang , Zhao Han , Liu Fuhai , Chen Dingbao , Zhou Xin , Deng Zhangyuzi , Cao Ying , Fu Wei , Zhang Haoyue , Yang Jing 
Published: October 2024

AbstractThe prevalence and severity of liver fibrosis appear higher in men than in premenopausal women, while postmenopausal women exhibit the worsened disease. However, the pathophysiological mechanism underlying such clinical observations remains incompletely understood. Here, we show that sex hormone depletion in adult female mice exaggerates the model of liver fibrosis, while estradiol replacement in castrated male mice is sufficient to mitigate the disease severity. Transcriptomic analyses and immunohistochemistry then demonstrate that both human and mouse hepatic stellate cells (HSCs), the primary cell type responsible for extracellular fibrous depositions, predominantly express the estrogen receptor 1 (ESR1). Of importance, genetic deletion of ESR1 in mouse HSCs markedly promotes liver fibrosis. Moreover, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and in vitro manipulations reveal that ESR1 can directly target the expression of fibrosis-related genes in HSCs. Together, this study has elucidated a critical aspect of ESR1 signaling in the sexual dimorphism of liver fibrosis.
Uncovering Latent Biological Function Associations through Gene Set Embeddings
Authors: Huang Yuhang , Zhong Fan 
Published: October 2024

AbstractThe complexity of biological systems has increasingly been unraveled through computational methods, with biological network analysis now focusing on the construction and exploration of well-defined interaction networks. Traditional graph-theoretical approaches have been instrumental in mapping key biological processes using high-confidence interaction data. However, these methods often struggle with incomplete or/and heterogeneous datasets. In this study, we extend beyond conventional bipartite models by integrating attribute-driven knowledge from the Molecular Signatures Database (MSigDB) using the node2vec algorithm. Our approach explores unsupervised biological relationships and uncovers potential associations between genes and biological terms through network connectivity analysis. By embedding both human and mouse data into a shared vector space, we validate our findings cross-species, further strengthening the robustness of our method. This integrative framework reveals both expected and novel biological insights, offering a comprehensive perspective that complements traditional biological network analysis and paves the way for deeper understanding of complex biological processes and diseases.
Noncovarying storage effect: balancing and positive directional selection on mutant alleles that amplify random fitness and demographic fluctuations
Authors: Kim Yuseob 
Published: October 2024

ABSTRACTTemporally variable environments in natural populations generate fluctuations in not only the population size but also the fitness effects of mutant alleles. The theory of storage effect, a species/allelic diversity-promoting mechanism discovered in ecology, predicts that rare mutants with fluctuating fitness can be positively selected and then maintained in balanced polymorphism if the population is subdivided into two parts that are respectively exposed to and protected from fluctuating environment. Recent study found that, under pre-exisiting oscillation in population size, the mutant is positively selected to fixation if its fitness change correlates with the rate of population growth, which further amplifies population size oscillation. To further understand these eco-evolutionary dynamics and elucidate their generality in natural populations, this study built more realistic models that assume randomly, not cyclically, fluctuating selection and common demographic features, including heterogeneous ecological patches or an age-structured population. Mathematical analysis revealed that this novel evolutionary force is generated when the size of the subpopulation subject to weak selection does not covary with that of the other subpopulation. Simulations showed that this ‘noncovarying storage effect’ is robust to various perturbations in the model. Multi-locus simulations revealed that oscillatory polymorphism at many loci can be simultaneously maintained and that positive feedback between demography and selection can accelerate the sequential fixations of fluctuation-amplifying mutations and thus lead to a drastic amplification of population size fluctuation. These results suggest that the noncovarying storage effect is a potentially prevalent evolutionary force in nature for maintaining genetic variation and causing large demographic fluctuations.ARTICLE SUMMARYNatural populations experience rapid environmental changes that cause fluctuations in the fitness of genetic variants and population size. This study investigates how evolutionary changes due to fitness differences interact with concurrent demographic changes. The theory of the storage effect, which is a mechanism for promoting genetic diversity, was extended to add random population size fluctuation with heterogeneous environmental patches or in a population divided into different age classes. A novel evolutionary force that either increases genetic variation or drives evolution toward further amplification of population size fluctuation, an unconventional contributor to large demographic fluctuations in nature, was identified and analyzed.