bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk for experiencing psychological and sexual abuse on- and offline: a comparison of bisexual, gay/lesbian, and heterosexual women and men
Authors: Chadwick Sara B , Woerner Jacqueline , Schrimshaw Eric W 
Published: June 2024

Abstract
Dating abuse research on lesbian, gay, and bisexual (LGB) populations tends to aggregate LGB participants for comparisons with heterosexuals and often excludes nonassaultive dating abuse and abuse that takes place on online dating applications. In the present study, we used the Pew Research Center’s 2019 American Trends Panel Wave 56 data set (n = 4712) to compare ever experiencing several types of nonassaultive on- and offline dating abuse between bisexual women (n = 402), lesbian women (n = 207), heterosexual women (n = 1802), bisexual men (n = 225), gay men (n = 575), and heterosexual men (n = 1501). We found that gay men and bisexual women generally had the greatest odds of experiencing online dating abuse. Bisexual and heterosexual women had the greatest odds of experiencing some offline abuse (eg, being touched in an uncomfortable way), but gay men, bisexual women, and bisexual men had the greatest odds of experiencing other offline abuse (eg, having their contact information or a sexual image of them shared nonconsensually). Findings highlight how assessments of nonassaultive dating abuse in on- and offline contexts via analyses of more specified gender/sex and sexual identity groups can broaden understandings of dating abuse victimization, especially among sexual minority populations.
Crosstalk between genomic variants and DNA methylation in FLT3 mutant acute myeloid leukemia
Authors: Dao Bac , Trinh Van Ngu , Nguyen Huy V , Nguyen Hoa L , Le Thuc Duy , Luu Phuc Loi 
Published: June 2024

Abstract
Acute myeloid leukemia (AML) is a type of blood cancer with diverse genetic variations and DNA methylation alterations. By studying the interaction of gene mutations, expression, and DNA methylation, we aimed to gain valuable insights into the processes that lead to block differentiation in AML. We analyzed TCGA-LAML data (173 samples) with RNA sequencing and DNA methylation arrays, comparing FLT3 mutant (48) and wild-type (125) cases. We conducted differential gene expression analysis using cBioPortal, identified DNA methylation differences with ChAMP tool, and correlated them with gene expression changes. Gene set enrichment analysis (g:Profiler) revealed significant biological processes and pathways. ShinyGo and GeneCards were used to find potential transcription factors and their binding sites among significant genes. We found significant differentially expressed genes (DEGs) negatively correlated with their most significant methylation probes (Pearson correlation coefficient of −0.49, P-value &lt;0.001) between FLT3 mutant and wild-type groups. Moreover, our exploration of 450 k CpG sites uncovered a global hypo-methylated status in 168 DEGs. Notably, these methylation changes were enriched in the promoter regions of Homebox superfamily gene, which are crucial in transcriptional-regulating pathways in blood cancer. Furthermore, in FLT3 mutant AML patient samples, we observed overexpress of WT1, a transcription factor known to bind homeobox gene family. This finding suggests a potential mechanism by which WT1 recruits TET2 to demethylate specific genomic regions. Integrating gene expression and DNA methylation analyses shed light on the impact of FLT3 mutations on cancer cell development and differentiation, supporting a two-hit model in AML. This research advances understanding of AML and fosters targeted therapeutic strategy development.
BAllC and BAllCools: efficient formatting and operating for single-cell DNA methylation data
Authors: Tian Wei , Ding Wubin , Shen Jiawei , Li Daofeng , Wang Ting , Ecker Joseph R 
Published: June 2024

Abstract

Motivation
With single-cell DNA methylation studies yielding vast datasets, existing data formats struggle with the unique challenges of storage and efficient operations, highlighting a need for improved solutions.

Results
BAllC (Binary All Cytosines) emerges as a tailored format for methylation data, addressing these challenges. BAllCools, its complementary software toolkit, enhances parsing, indexing, and querying capabilities, promising superior operational speeds and reduced storage needs.

Availability and implementation
https://github.com/jksr/ballcools
Reflections Upon Heterodox Economics: Legacy and Prospects
Authors: Fleetwood Steve 
Published: June 2024

Abstract
In this review article, I take three themes from Lynne Chester and Tae-Hee Jo’s edited collection Heterodox Economics: Legacy and Prospects. The first is Geoff Hodgson’s critique which I summarise thus: heterodox economics lacks consensus, coordination, and organizational coherence because it lacks a definition of heterodoxy. The second and third themes are pluralism and interdisciplinarity. But pluralism has a shortcoming: even a sophisticated structured pluralism would remain within the disciplinary boundary of (heterodox) economics and, therefore, lack valuable insights found in other social science disciplines. Whilst interdisciplinarity appears to offer a solution, it too has a shortcoming: it connects disciplines, whilst leaving the boundaries between them in place. Moreover, the majority of heterodox economists know that economic phenomena are not separate from, but are entangled with, myriad social phenomena, and if so, investigation might require going beyond interdisciplinarity, perhaps to transdisciplinarity. The conclusion draws all these strands together, to consider their implications for the future prospect of heterodox economics.
Returns to Labour Mobility
Authors: Baley Isaac , Ljungqvist Lars , Sargent Thomas J 
Published: June 2024

Abstract
Returns to labour mobility have too often escaped the attention they deserve as conduits of important forces in macro-labour models. These returns are shaped by calibrations of productivity processes that use theoretical perspectives and data sources from (i) labour economics and (ii) industrial organisation. By investigating earlier prominent studies, we conclude that the focus on firm size dynamics and shocks intermediated through neo-classical production functions in (ii) yields large returns to labour mobility that are robust to parameter perturbations. In contrast, the reliance on statistics in labour economics to calibrate per-worker productivity processes in (i) can give rise to fragilities in the sense that parameter perturbations that generate similar targeted statistics can have very different implications for returns to labour mobility.
Can managers successfully deceive investors? Media attention and market manipulation during the Panama scandal
Authors: Ortiz-Serrano Miguel Ángel , Forero-Laverde Germán 
Published: June 2024

Abstract
This paper explores how the Panama Company stock price incorporated fake positive news planted by company managers in French newspapers during the spring of 1888 to bait investors into an upcoming securities issue. The results show that news about the Panama Company only had firm-specific effects, making the firm’s main stock more volatile while keeping constant expected returns. This suggests that investors considered the new debt issue a risky operation. Finally, we find a non-contemporaneous positive effect of future news on present stock returns, suggesting an unlawful exploitation of asymmetric information by investors privy to the publication of fake news.
Postmortem Analysis of Dolutegravir, Tenofovir, Lamivudine, and Efavirenz Penetration in Multiple Central Nervous System Compartments
Authors: Wang Fan , Rademeyer Kara , Namuju Olivie C , Abdusalaamu Kizito , Fisher James , Meya David B , McRae MaryPeace , Boulware David R , Lukande Robert , Nicol Melanie R 
Published: June 2024

Abstract

Background
Central nervous system (CNS) compartmentalization provides opportunity for human immunodeficiency virus (HIV) persistence and resistance development. Differences between cerebrospinal fluid (CSF) and cerebral matter regarding HIV persistence are well described. However, CSF is often used as surrogate for CNS drug exposure, and knowledge from solid brain tissue is rare.

Methods
Dolutegravir, tenofovir, lamivudine, and efavirenz concentrations were measured across 13 CNS regions plus plasma in samples collected during autopsy in 49 Ugandan decedents. Median time from death to autopsy was 8 hours (interquartile range, 5–15 hours). To evaluate postmortem redistribution, a time course study was performed in a mouse model.

Results
Regions with the highest penetration ratios were choroid plexus/arachnoid (dolutegravir and tenofovir), CSF (lamivudine), and cervical spinal cord/meninges (efavirenz); the lowest were corpus callosum (dolutegravir and tenofovir), frontal lobe (lamivudine), and parietal lobe (efavirenz). On average, brain concentrations were 84%, 87%, and 76% of CSF for dolutegravir, tenofovir, and lamivudine, respectively. Postmortem redistribution was observed in the mouse model, with tenofovir and lamivudine concentration increased by 350% and efavirenz concentration decreased by 24% at 24 hours postmortem.

Conclusions
Analysis of postmortem tissue provides a unique opportunity to investigate CNS antiretroviral penetration. Regional differences were observed paving the way to identify mechanisms of viral compartmentalization and/or neurotoxicity.
A multilayer microfluidic system for studies of the dynamic responses of cellular proteins to oxygen switches at the single-cell level
Authors: Fu Wei , Wang Shujing , Ouyang Qi , Luo Chunxiong 
Published: June 2024

Abstract
Oxygen levels vary in the environment. Oxygen availability has a major effect on almost all organisms, and oxygen is far more than a substrate for energy production. However, less is known about related biological processes under hypoxic conditions and about the adaptations to changing oxygen concentrations. The yeast Saccharomyces cerevisiae can adapt its metabolism for growth under different oxygen concentrations and can grow even under anaerobic conditions. Therefore, we developed a microfluidic device that can generate serial, accurately controlled oxygen concentrations for single-cell studies of multiple yeast strains. This device can construct a broad range of oxygen concentrations, [O2] through on-chip gas-mixing channels from two gases fed to the inlets. Gas diffusion through thin polydimethylsiloxane (PDMS) can lead to the equilibration of [O2] in the medium in the cell culture layer under gas cover regions within 2 min. Here, we established six different and stable [O2] varying between ~0.1 and 20.9% in the corresponding layers of the device designed for multiple parallel single-cell culture of four different yeast strains. Using this device, the dynamic responses of different yeast transcription factors and metabolism-related proteins were studied when the [O2] decreased from 20.9% to serial hypoxic concentrations. We showed that different hypoxic conditions induced varying degrees of transcription factor responses and changes in respiratory metabolism levels. This device can also be used in studies of the aging and physiology of yeast under different oxygen conditions and can provide new insights into the relationship between oxygen and organisms.
Integration, innovation and insight: Most living cells are sensitive to the oxygen concentration because they depend on oxygen for survival and proper cellular functions. Here, a composite microfluidic device was designed for yeast single-cell studies at a series of accurately controlled oxygen concentrations. Using this device, we studied the dynamic responses of various transcription factors and proteins to changes in the oxygen concentration. This study is the first to examine protein dynamics and temporal behaviors under different hypoxic conditions at the single yeast cell level, which may provide insights into the processes involved in yeast and even mammalian cells. This device also provides a base model that can be extended to oxygen-related biology and can acquire more information about the complex networks of organisms.
Multikingdom oral microbiome interactions in early-onset cryptogenic ischemic stroke
Authors: Manzoor Muhammed , Leskelä Jaakko , Pietiäinen Milla , Martinez-Majander Nicolas , Ylikotila Pauli , Könönen Eija , Niiranen Teemu , Lahti Leo , Sinisalo Juha , Putaala Jukka , Pussinen Pirkko J , Paju Susanna 
Published: June 2024

Abstract
Although knowledge of the role of the oral microbiome in ischemic stroke is steadily increasing, little is known about the multikingdom microbiota interactions and their consequences. We enrolled participants from a prospective multicentre case–control study and investigated multikingdom microbiome differences using saliva metagenomic datasets (n = 308) from young patients diagnosed with cryptogenic ischemic stroke (CIS) and age- and sex-matched stroke-free controls. Differentially abundant taxa were identified using Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC2). Functional potential was inferred using HUMANn3. Our findings revealed significant differences in the composition and functional capacity of the oral microbiota associated with CIS. We identified 51 microbial species, including 47 bacterial, 3 viral, and one fungal species associated with CIS in the adjusted model. Co-abundance network analysis highlighted a more intricate microbial network in CIS patients, indicating potential interactions and co-occurrence patterns among microbial species across kingdoms. The results of our metagenomic analysis reflect the complexity of the oral microbiome, with high diversity and multikingdom interactions, which may play a role in health and disease.
Computational simulation of the potential improvement in clinical outcomes of cardiovascular diseases with the use of a personalized predictive medicine approach
Authors: Jacquemyn Xander , Van den Eynde Jef , Chinni Bhargava K , Danford David M , Kutty Shelby , Manlhiot Cedric 
Published: June 2024

Abstract

Importance and objectives
The current medical paradigm of evidence-based medicine relies on clinical guidelines derived from randomized clinical trials (RCTs), but these guidelines often overlook individual variations in treatment effects. Approaches have been proposed to develop models predicting the effects of individualized management, such as predictive allocation, individualizing treatment allocation. It is currently unknown whether widespread implementation of predictive allocation could result in better population-level outcomes over guideline-based therapy. We sought to simulate the potential effect of predictive allocation using data from previously conducted RCTs.

Methods and results
Data from 3 RCTs (positive trial, negative trial, trial stopped for futility) in pediatric cardiology were used in a computational simulation study to quantify the potential benefits of a personalized approach based on predictive allocation. Outcomes were compared when using a universal approach vs predictive allocation where each patient was allocated to the treatment associated with the lowest predicted probability of negative outcome. Compared to results from RCTs, predictive allocation yielded absolute risk reductions of 13.8% (95% confidence interval [CI] −1.9 to 29.5), 13.9% (95% CI 4.5-23.2), and 15.6% (95% CI 1.5-29.6), respectively, corresponding to a number needed to treat of 7.3, 7.2, and 6.4. The net benefit of predictive allocation was directly proportional to the performance of the prediction models and disappeared as model performance degraded below an area under the curve of 0.55.

Discussion
These findings highlight that predictive allocation could result in improved group-level outcomes, particularly when highly predictive models are available. These findings will need to be confirmed in simulations of other trials with varying conditions and eventually in RCTs of predictive vs guideline-based treatment allocation.
A novel hyperparameter search approach for accuracy and simplicity in disease prediction risk scoring
Authors: Lu Yajun , Duong Thanh , Miao Zhuqi , Thieu Thanh , Lamichhane Jivan , Ahmed Abdulaziz , Delen Dursun 
Published: June 2024

AbstractObjectiveDevelop a novel technique to identify an optimal number of regression units corresponding to a single risk point, while creating risk scoring systems from logistic regression-based disease predictive models. The optimal value of this hyperparameter balances simplicity and accuracy, yielding risk scores of small scale and high accuracy for patient risk stratification.Materials and MethodsThe proposed technique applies an adapted line search across all potential hyperparameter values. Additionally, DeLong test is integrated to ensure the selected value produces an accuracy insignificantly different from the best achievable risk score accuracy. We assessed the approach through two case studies predicting diabetic retinopathy (DR) within six months and hip fracture readmissions (HFR) within 30 days, involving cohorts of 90 400 diabetic patients and 18 065 hip fracture patients.ResultsOur scores achieve accuracies insignificantly different from those obtained by existing approaches, reaching AUROCs of 0.803 and 0.645 for DR and HFR predictions, respectively. Regarding the scale, our scores ranged 0-53 for DR and 0-15 for HFR, while scores produced by existing methods frequently spanned hundreds or thousands.DiscussionAccording to the assessment, our risk scores offer simple and accurate predictions for diseases. Furthermore, our new DR score provides a competitive alternative to state-of-the-art risk scores for DR, while our HFR case study presents the first risk score for this condition.ConclusionOur technique offers a generalizable framework for crafting precise risk scores of compact scales, addressing the demand for user-friendly and effective risk stratification tool in healthcare.
A comparative study of large language model-based zero-shot inference and task-specific supervised classification of breast cancer pathology reports
Authors: Sushil Madhumita , Zack Travis , Mandair Divneet , Zheng Zhiwei , Wali Ahmed , Yu Yan-Ning , Quan Yuwei , Lituiev Dmytro , Butte Atul J 
Published: June 2024

Abstract

Objective
Although supervised machine learning is popular for information extraction from clinical notes, creating large annotated datasets requires extensive domain expertise and is time-consuming. Meanwhile, large language models (LLMs) have demonstrated promising transfer learning capability. In this study, we explored whether recent LLMs could reduce the need for large-scale data annotations.

Materials and Methods
We curated a dataset of 769 breast cancer pathology reports, manually labeled with 12 categories, to compare zero-shot classification capability of the following LLMs: GPT-4, GPT-3.5, Starling, and ClinicalCamel, with task-specific supervised classification performance of 3 models: random forests, long short-term memory networks with attention (LSTM-Att), and the UCSF-BERT model.

Results
Across all 12 tasks, the GPT-4 model performed either significantly better than or as well as the best supervised model, LSTM-Att (average macro F1-score of 0.86 vs 0.75), with advantage on tasks with high label imbalance. Other LLMs demonstrated poor performance. Frequent GPT-4 error categories included incorrect inferences from multiple samples and from history, and complex task design, and several LSTM-Att errors were related to poor generalization to the test set.

Discussion
On tasks where large annotated datasets cannot be easily collected, LLMs can reduce the burden of data labeling. However, if the use of LLMs is prohibitive, the use of simpler models with large annotated datasets can provide comparable results.

Conclusions
GPT-4 demonstrated the potential to speed up the execution of clinical NLP studies by reducing the need for large annotated datasets. This may increase the utilization of NLP-based variables and outcomes in clinical studies.
Ensiled diet improved the growth performance of Tibetan sheep by regulating the rumen microbial community and rumen epithelial morphology
Authors: Zhao Jian , Zhao Xinsheng , Gao Jian , Bai Binqiang , Niu Jianzhang , Yang Yingkui , Zhao Guojun , Wang Zuojiang , Xu Zhenhua , Wang Jilong , Cheng Yanfen , Hao Lizhuang 
Published: June 2024

Abstract
The aim of this study was to investigate the effects of ensiled agricultural byproducts from Qinghai-Tibet plateau on growth performance, rumen microbiota, ruminal epithelium morphology, and nutrient transport-related gene expression in Tibetan sheep. Fourteen male Tibetan sheep were randomly assigned to one of two diets: an untreated diet (without silage inoculum, CON, n = 7) or an ensiled diet (with silage inoculum, ESD, n = 7). The total experimental period lasted for 84 d, including early 14 d as adaption period and remaining 70 d for data collection. The ESD increased average daily gain (P = 0.046), dry matter intake (P &lt; 0.001), ammonia nitrogen (P = 0.045), microbial crude protein (P = 0.034), and total volatile fatty acids concentration (P &lt; 0.001), and decreased ruminal pH value (P = 0.014). The proportion of propionate (P = 0.006) and the copy numbers of bacteria (P = 0.01) and protozoa (P = 0.002) were higher, while the proportion of acetate (P = 0.028) was lower in the sheep fed ESD compared to CON. Pyrosequencing of the 16S ribosomal RNA gene revealed that ESD increased the relative abundance of Firmicutes, Ruminococcus, Lachnospiraceae_AC2044_group, Lachnospiraceae_XPB1014_group, and Christensenellaceae_R-7_group in the rumen (P &lt; 0.05), while decreased the relative abundance of Bacteroidota, Prevotellaceae_UCG-003, and Veillonellaceae_UCG-001 (P &lt; 0.05). Analyses with PICRUSt2 and STAMP indicated that the propionate metabolism pathway was enriched in the sheep fed ESD (P = 0.026). The ESD increased the rumen papillae height (P = 0.012), density (P = 0.036), and surface area (P = 0.001), and improved the thickness of the total epithelia (P = 0.018), stratum corneum (P = 0.040), stratum granulosum (P = 0.042), and stratum spinosum and basale (P = 0.004). The relative mRNA expression of cyclin-dependent Kinase 2, CyclinA2, CyclinD2, zonula occludens-1, Occludin, monocarboxylate transporter isoform 1 (MCT1), MCT4, sodium/potassium pump, and sodium/hydrogen antiporter 3 were higher in the rumen epithelial of sheep fed ESD than CON (P &lt; 0.05). Conversely, the relative mRNA expressions of Caspase 3 and B-cell lymphoma-2 were lower in the sheep fed ESD than CON (P &lt; 0.05). In conclusion, compared with an untreated diet, feeding an ensiled diet altered the rumen microbial community, enhanced nutrient transport through rumen epithelium, and improved the growth performance of Tibetan sheep.