bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing the Impact of Pretraining Domain Relevance on Large Language Models Across Various Pathology Reporting Tasks
Authors: Lu Yunrui , Srinivasan Gokul , Preum Sarah , Pettus Jason , Davis Matthew , Greenburg Jack , Vaickus Louis , Levy Joshua 
Published: September 2023

ABSTRACTDeep learning (DL) algorithms continue to develop at a rapid pace, providing researchers access to a set of tools capable of solving a wide array of biomedical challenges. While this progress is promising, it also leads to confusion regarding task-specific model choices, where deeper investigation is necessary to determine the optimal model configuration. Natural language processing (NLP) has the unique ability to accurately and efficiently capture a patient’s narrative, which can improve the operational efficiency of modern pathology laboratories through advanced computational solutions that can facilitate rapid access to and reporting of histological and molecular findings. In this study, we use pathology reports from a large academic medical system to assess the generalizability and potential real-world applicability of various deep learning-based NLP models on reports with highly specialized vocabulary and complex reporting structures. The performance of each NLP model examined was compared across four distinct tasks: 1) current procedural terminology (CPT) code classification, 2) pathologist classification, 3) report sign-out time regression, and 4) report text generation, under the hypothesis that models initialized on domain-relevant medical text would perform better than models not attuned to this prior knowledge. Our study highlights that the performance of deep learning-based NLP models can vary meaningfully across pathology-related tasks. Models pretrained on medical data outperform other models where medical domain knowledge is crucial, e.g., current procedural terminology (CPT) code classification. However, where interpretation is more subjective (i.e., teasing apart pathologist-specific lexicon and variable sign-out times), models with medical pretraining do not consistently outperform the other approaches. Instead, fine-tuning models pretrained on general or unrelated text sources achieved comparable or better results. Overall, our findings underscore the importance of considering the nature of the task at hand when selecting a pretraining strategy for NLP models in pathology. The optimal approach may vary depending on the specific requirements and nuances of the task, and related text sources can offer valuable insights and improve performance in certain cases, contradicting established notions about domain adaptation. This research contributes to our understanding of pretraining strategies for large language models and further informs the development and deployment of these models in pathology-related applications.
A Network Analysis of Molecular Interactions to Study the Development of New-onset Diabetes and Hypertension after COVID-19 Infection Using Bioinformatics Tools
Authors: de Oliveira Andrade Luis Jesuino , de Oliveira Luisa Correia Matos , de Oliveira Gabriela Correia Matos , de Oliveira Luís Matos 
Published: September 2023

ABSTRACTIntroductionThe association between COVID-19 infection and the development of new-onset diabetes and hypertension is an emerging area of research. However, a comprehensive understanding of the underlying molecular mechanisms is still lacking. Network analysis using bioinformatics tools can provide valuable insights into the complex molecular interactions involved in these conditions after COVID-19 infection.ObjectiveThis study aims to use bioinformatics tools to analyze the network of molecular interactions related to new-onset diabetes and hypertension following COVID-19 infection.MethodsData from publicly available databases were utilized, including gene expression profiles and protein-protein interaction information. Differential expression analysis was performed to identify genes that were differentially expressed in individuals with new-onset diabetes and hypertension after COVID-19 infection compared to healthy controls. A protein interaction network was constructed using bioinformatics tools to explore the functional relationships among the identified differentially expressed genes.ResultsThe network analysis revealed several key proteins and pathways related to the pathogenesis of new-onset diabetes and hypertension after COVID-19 infection. Notably, proteins involved in insulin signaling, glucose metabolism, inflammation, and blood pressure regulation were found to be prominently associated. The signaling pathway and the renin-angiotensin system were identified as key pathways in this context.ConclusionThis study provides insights by showing a network-based perspective on the molecular interactions involved in the development of new-onset diabetes and hypertension after COVID-19 infection.
IMBALANCED MACHINE LEARNING CLASSIFICATION MODELS FOR REMOVAL BIOSIMILAR DRUGS AND INCREASED ACTIVITY IN PATIENTS WITH RHEUMATIC DISEASES
Authors: Corredor David Castro , Calvo Pascual Luis Ángel 
Published: September 2023

ABSTRACTObjectivePredict long-term disease worsening and the removal of biosimilar medication in patients with rheumatic diseases.MethodologyObservational, retrospective descriptive study. Review of a database of patients with immune-mediated inflammatory rheumatic diseases who switched from a biological drug (biosimilar or non-biosimilar) to a biosimilar drug for at least 6 months. We selected the most important variables, from 18 variables, using mutual information tests. As patients with disease worsening are a minority, it is very difficult to make models with conventional machine learning techniques, where the best models would always be trivial. For this reason, we computed different types of imbalanced machine learning models, choosing those with better f1-score and mean ROC AUC.ResultsWe computed the best-imbalanced machine learning models to predict disease worsening and the removal of the biosimilar, with f1-scores of 0.52 and 0.63, respectively. Both models are decision trees. In the first one, two important factors are switching of biosimilar and age, and in the second, the relevant variables are optimization and the value of the initial PCR.ConclusionsBiosimilar drugs do not always work well for rheumatic diseases. We obtain two imbalanced machine learning models to detect those cases, where the drug should be removed or where the activity of the disease increases from low to high. In our decision trees appear not previously studied variables, such as age, switching, or optimization.Key points-This is a real-life study of a large number of patients with biosimilar bDMARDs.-Biosimilar drugs can be considered effective in rheumatic inflammatory diseases, as measured by ASDAS, DAPSA and DAS28.-The bDMARDs biosimilars are safe drugs with a low number of side effects.-After switching from the reference drug to a biosimilar drug, patients have a high withdrawal rate due to ineffectiveness.-Our machine learning model (imbalanced machine learning) is able to predict when drug withdrawal and disease activity occur.
Diet influences community dynamics following vaginal group B Streptococcus colonization
Authors: Megli Christina J. , DePuyt Allison E. , Goff Julie P. , Munyoki Sarah K. , Hooven Thomas A. , Jašarević Eldin 
Published: September 2023

ABSTRACTThe vaginal microbiota plays a pivotal role in reproductive, sexual, and perinatal health and disease. Unlike the well-established connections between diet, metabolism, and the intestinal microbiota, parallel mechanisms influencing the vaginal microbiota and pathogen colonization remain overlooked. In this study, we combine a mouse model of Streptococcus agalactiae strain COH1 (GBS) vaginal colonization with a mouse model of pubertal-onset obesity to assess diet as a determinant of vaginal microbiota composition and its role in colonization resistance. We leveraged culture-dependent assessment of GBS clearance and culture-independent, sequencing-based reconstruction of the vaginal microbiota in relation to diet, obesity, glucose tolerance, and microbial dynamics across time scales. Our findings demonstrate that excessive body weight gain and glucose intolerance are not associated with vaginal GBS density or timing of clearance. Diets high in fat and low in soluble fiber are associated with vaginal GBS persistence, and changes in vaginal microbiota structure and composition due to diet contribute to GBS clearance patterns in nonpregnant mice. These findings underscore a critical need for studies on diet as a key determinant of vaginal microbiota composition and its relevance to reproductive and perinatal outcomes.IMPORTANCEThis work sheds light on diet as a key determinant influencing the composition of vaginal microbiota and its involvement in group B Streptococcus (GBS) colonization in a mouse model. The study shows that dietary components, such as dietary fat and soluble fiber, impact GBS density and timing of clearance in the female reproductive tract. These findings are particularly significant given clear links between GBS and adverse reproductive and neonatal outcomes, advancing our understanding by identifying critical connections between dietary components, factors originating from the intestinal tract, vaginal microbiota, and reproductive outcomes.
Alternative splicing of a chromatin modifier alters the transcriptional regulatory programs of stem cell maintenance and neuronal differentiation
Authors: Nazim Mohammad , Lin Chia-Ho , Feng An-Chieh , Yeom Kyu-Hyeon , Li Mulin , Daly Allison E. , Tan Xianglong , Vu Ha , Ernst Jason , Carey Michael F. , Smale Stephen T. , Black Douglas L. 
Published: September 2023

ABSTRACTDevelopment of embryonic stem cells (ESCs) into neurons requires intricate regulation of transcription, splicing, and translation, but how these processes interconnect is not understood. We found that polypyrimidine tract binding protein 1 (PTBP1) alters splicing of DPF2, a subunit of BAF chromatin remodeling complexes.Dpf2exon 7 is inhibited by PTBP1 to produce the DPF2-S isoform early in development. During neuronal differentiation, loss of PTBP1 allows exon 7 splicing, resulting in a longer DPF2-L isoform. Gene expression changes are induced by DPF2-L in ESC, and by DPF2-S in neurons. In ESC, chromatin immunoprecipitation locates DPF2-S but not DPF2-L at sites bound by pluripotency transcription factors. In neuronal progenitors, DPF2-S sites coincide with NFI protein binding, and DPF2-L sites with CTCF. DPF2-S sites show enhancer chromatin modifications, while DPF2-L sites show modifications associated with promoters. In sum, alternative splicing events during neuronal development impact chromatin organization by altering BAF complex targeting.
Comparative analysis of intragroup intermale relationships: A study of wild bonobos (Pan paniscus) in Wamba, Democratic Republic of Congo and chimpanzees (Pan troglodytes) in Kalinzu Forest Reserve, Uganda
Authors: Shibata Shohei , Furuichi Takeshi 
Published: September 2023

AbstractAlthough chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) share a multi- male/multi-female societal organization and form male-philopatric groups, disparities in terms of male aggression and stability of temporary parties are thought to exist among them. However, existing research in bonobos has mainly focused on the high social status, prolonged receptivity, and characteristic sexual behaviors of females, leaving the behaviors of males understudied. Moreover, prior comparative studies onPansuffer from methodological inconsistencies. This study addresses these gaps by employing a uniform observation method to explore party attendance and aggressive interactions among male bonobos in Wamba and male chimpanzees in Kalinzu. Unlike male chimpanzees that exhibit dispersion in the absence of receptive females in the group, male bonobos showed a lesser degree of such dispersion. Although the overall frequency of aggressive interactions per observation unit did not significantly differ between the two species, the nature of these interactions varied. Notably, severe aggressive behaviors such as physical confrontations among adult males were absent in bonobos, with most aggression occurring between the sons of the two highest-ranking females. Additionally, in bonobos, females actively engaged in polyadic aggressive behavior as aggressors, while all instances of coalitionary aggression in chimpanzees originated from male aggressors. These findings underscore the substantial impact of female behaviors on the observed distinctions in male aggressive interactions between the two species.
Genome size is positively correlated with extinction risk in herbaceous angiosperms
Authors: Gomez Marybel Soto , Brown Matilda J.M. , Pironon Samuel , Veselý Pavel , Bureš Petr , Elliott Tammy L. , Zedek František , Pellicer Jaume , Forest Félix , Lughadha Eimear Nic , Leitch Ilia J. 
Published: September 2023

SummaryAngiosperms with large genomes experience nuclear-, cellular- and organism-level constraints that may limit their phenotypic plasticity and ecological niche. These constraints have been documented to vary across lineages, life-history strategies, ecogeographic patterns and environmental conditions. Therefore, we test the hypotheses that extinction risk is higher in large-genomed compared to small-genomed species, and that the effect of genome size varies across three selected covariates: life form, endemism, and climatic zones.We collated genome size and extinction risk information for a representative sample of angiosperms comprising 3,250 species, which we analyzed alongside life form, endemism and climate variables using a phylogenetic framework.Angiosperm genome size is positively correlated with extinction risk, a pattern driven by a signal in herbaceous but not woody species, regardless of climate and endemism. The influence of genome size is stronger in endemic herbaceous species, but is relatively homogenous across different climates. Beyond its indirect link via endemism and climate, genome size also influences extinction risk directly and significantly.Genome size may serve as a proxy for difficult-to-measure parameters associated with resilience and vulnerability in herbaceous angiosperms. Therefore, it merits further exploration as a useful biological attribute for understanding intrinsic extinction risk and augmenting plant conservation efforts.
Differential role for VPS4 isoforms in cytokinetic abscission confers a regulatory function for monomeric VPS4A and VTA1 in mammalian cells
Authors: Dvilansky Inbar , Atlaras Yarin , Nachmias Dikla , Elia Natalie 
Published: September 2023

ABSTRACTMutations in the human AAA-ATPase VPS4 isoform, VPS4A, cause severe Neurodevelopmental defects and Congenital Dyserythropoietic Anemia (CDA). VPS4 is a crucial component of the ESCRT system, which drives membrane remodeling in numerous cellular processes, including receptor degradation, cell division, and neural pruning. Notably, while most organisms encode for a single VPS4 gene, human cells have two VPS4 paralogs, namely VPS4A and VPS4B, but the functional differences between these paralogs is mostly unknown. Here, we set out to investigate the role of the human VPS4 paralogs in cytokinetic abscission using a series of knockout cell lines. We found that VPS4A and VPS4B hold both overlapping and distinct roles in abscission. VPS4A depletion resulted in a severe abscission delay, which was fully rescued by VPS4A expression but only partially rescued by VPS4B overexpression. Unexpectedly, expressing a monomeric-locked VPS4A mutant also partially rescued the abscission delay in VPS4A KO cells and bound the abscission checkpoint proteins CHMP4C and ANCHR. Depletion of VTA1, a co-factor of VPS4, disrupted VPS4A- ANCHR interactions and accelerated abscission, indicating a role for VTA1 in the abscission checkpoint. Our findings reveal a dual role for VPS4A in abscission, one that is canonical and can be compensated by VPS4B, and another that is regulatory and is mediated by its monomeric form. These observations provide a potential mechanistic explanation for the neurodevelopmental defects and other related disorders reported in VPS4A-mutated patients with a fully functional VPS4B paralog.
The determinants of export performance: perceived psychic distance and its antecedents
Authors: Demirağ Fatma , Kayabaşı Aydın 
Published: September 2023

Purpose
The Uppsala internationalization model is one of the widely accepted models for the development of exports. This model suggests that the explanation of relations between psychic distance, its antecedents and marketing mix adaptation would lead to successful export practices. Consequently, this study aims to determine the determinants of export performance, antecedents of psychic distance and marketing mix adaptation.

Design/methodology/approach
This study uses a mixed-methods research design in which qualitative and quantitative research methods were used together. The face-to-face interview method was used to identify the psychic distance antecedents. The face-to-face interview was with eight Turkish exporting firms. Based on the data obtained from face-to-face interviews, a scale for measuring the antecedents of psychic distance has been developed and used in the quantitative study. The scales used for measuring marketing mix adaptation, export performance and psychic distance perception, which has both individual and country dimensions, were adapted from the literature. Data were collected from 221 Turkish exporting companies for quantitative research. Structural equation modeling was used to test relationships between the variables.

Findings
As a result of the data analysis of face-to-face interviews, six antecedents of psychic distance were determined. According to the subsequent quantitative research results, it has been determined that employee expertise, which is one of the antecedents of psychic distance, only affects the country dimension of psychic distance perception; the cooperation, institutionalization and international market experience affect both the country and individual dimensions of psychic distance perception. The country and individual dimensions of psychic distance were found to have an impact on the product, price, promotion and distribution dimensions of marketing mix adaptation. Only the product dimension of marketing mix adaption was found to affect export performance.

Practical implications
This study offers a comprehensive perspective for both theoretical and practical studies by discussing various aspects that would help improve the exporting activities of firms within the scope of antecedents of perceived psychic distance.

Originality/value
In this research, a scale was developed for measuring the antecedents of psychic distance, and the variables affecting export performance were analyzed holistically.
A meta-analysis of the effects of lifelong vocational education in South Korea
Authors: Kim Jhong Yun Joy , Kim EunBee , Lim Doo Hun 
Published: September 2023

Purpose
This study aims to conduct a quantitative meta-analysis of previous research on lifelong vocational education to generate generalized conclusions about its effects, set directions for future lifelong vocational education and identify implementation measures.

Design/methodology/approach
To conduct a meta-analysis on research results that have a heterogeneous distribution, it is important to specify the analysis category for examining the effects of research variables.

Findings
First, lifelong vocational education has an effect on dependent variables. And action appears to have the highest effect size on dependent variables. Next, when calculating the size of variables that had an effect on lifelong vocational education by educational type, the effect size of informal education was found to be larger than that of formal education. Finally, regarding the effect on the participants, office workers were influenced most, followed by university students, North Korean defectors, job seekers and foreigners.

Research limitations/implications
Although this study attempted to conduct an in-depth analysis of subcomponents, it was not possible to analyze variables at a more detailed level. Therefore, future studies should aim to conduct a more comprehensive analysis of different variables based on a wider composition. Because lifelong vocational education is relevant to people’s daily lives, it should be investigated in the context of their personal characteristics and social backgrounds.

Practical implications
This research was designed to uncover general effects of lifelong vocational education and discover relevant variables affecting lifelong vocational education in South Korea. A meta-analysis of 15 studies with 67 subgroups examining lifelong vocational education was conducted.

Social implications
In the current era of VUCA (Volatility, Uncertainty, Complexity and Ambiguity), lifelong vocational education needs to be organized systematically, unlike in the past. With the rapid advancements in technology influenced by artificial intelligence and the fourth industrial revolution, there is a surge in social demands for continued reeducation and redevelopment of employees to prepare for talent development paradigm innovation, increasing unemployment among unskilled workers and competence enhancement needs among job seekers and employed individuals.

Originality/value
This study aims to conduct a quantitative meta-analysis of previous research on lifelong vocational education to draw generalized conclusions on its effectiveness and discuss its implications for implementation measures. Specifically, this study will analyze the general effect size; differences in the effect size among different dependent variable groups; and the effect size based on lifelong vocational education participants.
Cigarette tax pass-through in Vietnam: evidence from retailers’ data
Authors: Vo Mai-Huong , Nguyen Ngoc-Anh , Dauchy Estelle , Nguyen Nuong 
Published: September 2023

PurposeThis study aims to estimate the pass-through rate of the increases in the excise tax and TCF tax on tobacco in Vietnam. This study seeks to shed light on how the tax burden is split between consumers and producers and inform policy discussions in the country. Using panel micro-level data collected from three waves of a nationwide retailer's survey, this study provides an evidence-based pass-through estimation for tobacco tax in Vietnam and contributes to the understanding of tax policy on smoking and smoking-related issues.Design/methodology/approachFollowing increases in the excise tax and TCF tax on tobacco in 2019, the differential effect of the tax hike on the “treatment group” (domestic cigarettes) versus the “control group” (illicit cigarettes) using a difference-in-difference (DID) analysis has been studied. The study utilized unique longitudinal retailers’ data on cigarettes prices in Vietnam from 2018 to 2019 to estimate the tax pass-through rate for some of the most popular factory-made cigarette brands.FindingsThis study found evidence of an over-shifting of cigarette taxes on smokers. Specifically, it discovered that the tax increase is absorbed more by low-priced brand smokers compared to premium brand users due to (1) the limited increase in prices under a pure ad valorem system and (2) the way the Vietnamese currency is denominated. Additionally, there is evidence of cushioning to mitigate price shock on consumers as the real prices increase gradually over the period of one year after the tax change.Originality/valueTo the best of the authors’ knowledge, this study is the first to collect and analyze a unique panel micro-level data from three waves of a nationwide retailers’ survey, which captures the changes in marketing and pricing strategies of the tobacco industry in Vietnam before and after an increase in excise tax in 2019. The results of this study could be used as a reference for future policymakers in considering increasing taxes on tobacco.