bluuebunny/crossref_metadata_2025_split huggingface dataset:
Religious service attendance is protective against the diseases of despair: evidence from regression, sibling-fixed effects, and instrumental variables analyses
Authors: Lebenbaum Michael , Fletcher Jason 
Published: February 2025

Abstract
It is unclear whether the large secular decline in religiosity has contributed to the dramatic rise in the “deaths of despair.” We contribute to the recent epidemiologic literature estimating more rigorous effects of religiosity on health by examining the association between religiosity and the diseases of despair via regression, sibling fixed effects (SFE) analyses, instrumental variable (IV), and cross-lag analyses. We used the US Add Health sample when respondents were in Waves (W) 3-5 (ages: 18-43). We measured religious service attendance and a composite outcome consisting of painkiller abuse, past-year suicidal ideation, and weekly binge drinking. We estimated linear probability models, SFE, IV, and cross-lag models. Confounders included parental socio-demographics, community/school characteristics, and individual socio-demographics. Greater religious service attendance was negatively associated with the composite outcome in the pooled sample (β =-0.031; p &lt; .5) and at each wave (W3 β=-0.025; W4 β=-0.040; W5 β=-0.028; all p &lt; .5). Conclusions were similar in SFE models (W3-5 pooled β=-0.013), IV models (W4 β=-0.081; W3-5 pooled β=-0.064, all p &lt; .5, F&gt;100, and overidentification p &gt; .10) and cross-lag models (W3-5 pooled β=-0.023, p &lt; .5). The consistent results across models suggests that the large decline in religious service attendance likely contributed to the rise in the deaths of despair.
Montefiore Einstein Robust Geriatric Normative Project: Robust Age- and Regression-Based Demographic Norms for the Repeatable Battery for Neuropsychological Status and Select Neuropsychological Tests in Older Adults
Authors: Freilich Bryan M , Scharaga Elyssa , Holtzer Roee 
Published: February 2025

Abstract

Objective
This study introduces the Montefiore Einstein Robust Geriatric Normative Project (MERGER-NP), which provides robust normative data for older adults on the Repeatable Battery for Neuropsychological Status (RBANS) and other select neuropsychological tests.

Method
Age-stratified and regression-based demographic norms were derived from a robust sample of older adults (n = 420, mean age = 75.55, 68% female). The study included assessments using the RBANS, Trail Making Test, Digit-Symbol Coding, a 15-item version of the Boston Naming Test, and verbal fluency tests, along with word reading measures. Regression-based norms were generated by analyzing predictors of test performance, integrating demographic variables and measurable social determinants of health (SDOH), specifically word reading ability and occupational attainment.

Results
Normative data include convenient look-up tables for the RBANS and other tests. Findings indicate that word reading measures significantly predict neuropsychological performance, accounting for up to 41% of the variance when included with demographic variables. Notably, our analyses revealed that race often did not contribute unique variance when controlling for reading ability. Additionally, occupation was identified as a significant predictor of test performance, with Job Zone scores retained in approximately 60% of regression models.

Conclusions
The MERGER-NP enhances existing normative data by integrating robust norms with regression-based methods, facilitating more precise assessments for older adults. The findings underscore the utility of including SDOH such as reading ability and occupation into normative approaches, with important implications for improving diagnostic accuracy and patient care in clinical settings. Future research should explore the generalizability of these norms to more diverse populations.
The DNA binding of plant-specific GROWTH-REGULATING FACTOR transcription factors is stabilized by GRF-INTERACTING FACTOR coactivators
Authors: Nosaki Shohei , Ohtsuka Masae 
Published: February 2025

Abstract
The plant-specific GROWTH-REGULATING FACTOR (GRF) transcription factor family proteins play crucial role in regulating diverse aspects of plant life. The transcriptional activity of GRFs is known to be enhanced through direct interaction with the GRF-INTERACTING FACTOR (GIF) coactivators. However, it remains unclear how the binding to GIF affects the biochemical ability of GRFs. Herein, we present evidence that GIFs also stabilize the DNA binding of GRFs. A combination of biochemical experiments and AlphaFold-predicted structural models suggests that the GIF-binding domain in GRFs may partially restrict their own DNA binding through direct interaction with the DNA-binding domain. These findings deepen our understanding of the GRF:GIF module in plant regulation and provide a basis for strategies to manipulate this module for agricultural and biotechnological applications.
DeepPFP: a multi-task-aware architecture for protein function prediction
Authors: Wang Han , Ren Zilin , Sun Jinghong , Chen Yongbing , Bo Xiaochen , Xue JiGuo , Gao Jingyang , Ni Ming 
Published: February 2025

Abstract
Deriving protein function from protein sequences poses a significant challenge due to the intricate relationship between sequence and function. Deep learning has made remarkable strides in predicting sequence-function relationships. However, models tailored for specific tasks or protein types encounter difficulties when using transfer learning across domains. This is attributed to the fact that protein function relies heavily on structural characteristics rather than mere sequence information. Consequently, there is a pressing need for a model capable of capturing shared features among diverse sequence-function mapping tasks to address the generalization issue. In this study, we explore the potential of Model-Agnostic Meta-Learning combined with a protein language model called Evolutionary Scale Modeling to tackle this challenge. Our approach involves training the architecture on five out-domain deep mutational scanning (DMS) datasets and evaluating its performance across four key dimensions. Our findings demonstrate that the proposed architecture exhibits satisfactory performance in terms of generalization and employs an effective few-shot learning strategy. To explain further, Compared to the best results, the Pearson’s correlation coefficient (PCC) in the final stage increased by ~0.31%. Furthermore, we leverage the trained architecture to predict binding affinity scores of the DMS dataset of SARS-CoV-2 using transfer learning. Notably, training on a subset of the Ube4b dataset with 500 samples resulted in a notable improvement of 0.11 in the PCC. These results underscore the potential of our conceptual architecture as a promising methodology for multi-task protein function prediction.
Fever and Rash in a Traveler
Authors: Reddy Maithri , Curtin John 
Published: February 2025

Abstract
This Photo Quiz article presents a case of acute dengue fever in an American traveler returning from Puerto Rico. In addition to the relevant epidemiologic and medical history, a key finding that allowed clinical diagnosis of the infection was the characteristic rash (“isles of white in a sea of red”) that our patient manifested. This physical exam finding was documented and is featured prominently in the article. Despite the fact that initial testing for dengue virus infection was negative, the characteristic exposures, incubation period, and clinical syndrome our patient presented with allowed us to provide directed care for the most likely illness. Our clinical diagnosis was later confirmed on convalescent serologic testing. We use this case to illustrate and discuss highlights of diagnosis, treatment, and prevention of both non-severe and severe dengue virus infection.
Risk of Neurodevelopmental Disorders in Children Exposed to Human Immunodeficiency Virus and Antiretrovirals In Utero: A National Cohort Study in France
Authors: Collier Mathis , Chouchana Laurent , Frange Pierre , Sibiude Jeanne , Munnich Arnold , Treluyer Jean Marc , Blanche Stéphane 
Published: February 2025

Abstract

Background
The health of children exposed but uninfected by human immunodeficiency virus (HIV) requires long-term assessment, in particular in terms of neurological and cognitive development. Numerous confounding factors have hampered such assessment, and published data are contradictory.

Methods
Using data from the French National Health Data System from 2012 to 2022, we conducted a population-based matched cohort study on all live-born single children, including those born to mothers living with HIV, all prenatally exposed to antiretrovirals (ARVs). The primary outcome was the diagnosis of neurodevelopmental disorders according to the International Classification of Diseases, 10th Revision. The recourse to specialized consultations likely to indirectly reflect neurodevelopmental symptoms was also evaluated. Incidence was assessed using the Cox survival model.

Results
Of 6 667 363 live-born singletons, 9035 were born to mothers with HIV, all exposed to ARVs during pregnancy. Children were followed for up to 11 years (average, 5.5 years). Overall, the incidence of neurodevelopmental disorders among exposed children was higher than in the general population, even after matching for 5 sociodemographic criteria and gestational age (hazard ratio, 1.24 [95% confidence interval, 1.04–1.47]). It was not possible to dissect the respective role of maternal infection from that of maternal treatment, as all children were coexposed to HIV and ARVs. However, among those exposed to tenofovir-emtricitabine, the ritonavir-boosted darunavir–based combination was significantly associated with a higher combined incidence of neurodevelopmental disorders and related specialized consultations than other protease inhibitors (log-rank P &lt; .001).

Conclusions
Children exposed to HIV and ARVs in utero have a higher risk of developing neurodevelopmental disorders of multifactorial origin.
Advancing periodontal diagnosis: Harnessing advanced artificial intelligence for patterns of periodontal bone loss in cone beam computed tomography
Authors: Kurt-Bayrakdar Sevda , Bayrakdar İbrahim Şevki , Kuran Alican , Çelik Özer , Orhan Kaan , Jagtap Rohan 
Published: February 2025

Abstract

Objectives
The current study aimed to automatically detect tooth presence, tooth numbering, and types of periodontal bone defects from CBCT images using a segmentation method with an advanced artificial intelligence (AI) algorithm.

Methods
This study utilized a dataset of CBCT volumes collected from 502 individual subjects. Initially, 250 CBCT volumes were used for automatic tooth segmentation and numbering. Subsequently, CBCT volumes from 251 patients diagnosed with periodontal disease were employed to train an AI system to identify various periodontal bone defects using a segmentation method in web-based labeling software. In the third stage, CBCT images from 251 periodontally healthy subjects were combined with images from 251 periodontally diseased subjects to develop an AI model capable of automatically classifying patients as either periodontally healthy or periodontally diseased. Statistical evaluation included ROC curve analysis and confusion matrix model.

Results
The AUC values for the models developed to segment teeth, total alveolar bone loss, supra-bony defects, infra-bony defects, perio-endo lesions, buccal defects, and furcation defects were 0.9594, 0.8499, 0.5052, 0.5613 (with cropping, AUC: 0.7488), 0.8893, 0.6780 (with cropping, AUC: 0.7592), and 0.6332 (with cropping, AUC: 0.8087), respectively. Additionally, the classification CNN model achieved an accuracy of 80% for healthy individuals and 76% for unhealthy individuals.

Conclusions
This study employed AI models on CBCT images to automatically detect tooth presence, numbering, and various periodontal bone defects, achieving high accuracy and demonstrating potential for enhancing dental diagnostics and patient care.
Characteristics analyses and tumor staging proposal for primary malignant melanoma of the esophagus: a retrospective study
Authors: Ye Weijie , Leng Changsen , Chen Junying , Mai Zihang , Liu Nianjin , Zhang Shuishen , Fu Jianhua , Liu Qianwen 
Published: February 2025

Summary
Primary malignant melanoma of the esophagus (PMME) is a malignant tumor with a poor prognosis. This study aimed to conduct survival analysis for patients with PMME and propose a staging system for PMME. Data from 179 patients were compiled for survival analysis and to propose a staging system for PMME. Survival analysis was conducted using the Kaplan–Meier method, log-rank test, and Cox proportional hazards model. The median OS of the 179 patients with PMME was 20.0 months. The 1-, 3-, and 5-year survival rates were 67.0%, 35.0%, and 17.0%. In the pooled analysis of 179 patients, significant differences in OS were observed between patients with tumors invading the lamina propria or muscularis mucosae (T1a) and deeper layers (T1b, T2, T3, T4) (P &lt; 0.001). Significant differences in OS were observed between patients with no regional lymph node metastasis and those with one or more regional lymph node metastases (P &lt; 0.001). PD-1 inhibitors significantly improved 3-year OS for patients with the pT1b-4 N+ stage (P = 0.020). The proposed staging system for PMME is as follows: (1) Stage I: T1aN0M0 (2) Stage II: T1b-4N0M0 and T1N1M0; Stage III: T2-4N1M0 and TxNxM1(P &lt; 0.001). The lower T-stage and no lymph node metastasis indicated better prognosis. Surgery could be considered an effective treatment for patients with early-stage PMME. The effectiveness of surgery as a treatment for advanced-stage patients remained unclear and required further research. However, PD-1 inhibitors might improve the 3-year OS for advanced-stage patients. Furthermore, the tumor, node, metastasis staging system for PMME was proposed, and could be valuable in guiding prognostic predictions.
A rare case of dual left anterior descending artery type 4 in inferior myocardial infarction patient: a case report
Authors: Isa W Yus Haniff W , Yusof Zurkurnai , Aziz Mohamad Fadini Abdul , Othman Mohd Khairi , Suliman Ayman 
Published: February 2025

Abstract

Background
This case highlights a type 4 dual left anterior descending coronary artery anomaly, identified incidentally during coronary angiography.

Case summary
A 51-year-old male patient presented with acute myocardial infarction, which was successfully treated with thrombolysis and percutaneous coronary intervention. Angiography revealed an anomalous origin of the left anterior descending artery (LAD) from the right coronary artery. Stenting was performed on the right coronary artery and the right posterior descending artery branch.

Discussion
Type 4 dual LAD is a rare coronary anomaly with potential clinical risks, including sudden cardiac death due to its course between major arteries. Variations in the structure of coronary arteries can present challenges for interventional cardiologists when conducting percutaneous coronary interventions. Accurate coronary anatomy assessment via angiography and computed tomography coronary angiography is crucial for successful percutaneous coronary intervention and surgical planning. Although uncommon, the dual LAD type 4 anomaly is a significant coronary artery variation that interventional cardiologists must consider due to its impact on prognosis and long-term treatment strategies.
Valve Thrombosis and Antithrombotic Therapy After Bioprosthetic Mitral Valve Replacement: A Systematic Review And Meta-Analysis
Authors: Zorman Mark J , Vibhishanan Jonathan , Dangas Katerina , Castle James , Li Ka Hou Christien , Coronelli Marco , Eastwick-Jones Kate , Swan Alexander , Johnson Nicky , Choksey Anurag , Yan Helen , Scott Sam G C , Henry Matthew , Cassar Mark Philip , Barnes Cara , Ferreira-Martins Joao , Newton James , Dawkins Sam , Alkhouli Mohamad , Rihal Charanjit , Eleid Mackram F , Pislaru Sorin V , Guerrero Mayra E , Ordonez-Mena Jose , Cahill Thomas J 
Published: February 2025

Abstract

Aims
Transcatheter mitral valve replacement (TMVR) has become a feasible alternative to surgical mitral valve replacement (SMVR) in selected patients at high surgical risk. The risk of valve thrombosis following SMVR and TMVR, and the optimal antithrombotic therapy following these procedures, remains uncertain. We aimed to compare the incidence of bioprosthetic mitral valve thrombosis (bMVT) after SMVR and TMVR, and the incidence of bMVT between patients on different antithrombotic regimens.

Methods and Results
A literature search of Medline, Embase and Cochrane Library was performed between January 2000 and August 2024. Random-effects models were used to derive pooled estimates of the incidence of bMVT in the absence of prior or active endocarditis and valve thrombosis. 47 studies (6170 patients, total follow-up 9541.8 patient-years) were eligible for inclusion. The overall incidence of bMVT was 5.05 (95%CI 3.18–8.01, I2 = 82%) per 100-patient-years. Subclinical bMVT was more common than clinically significant bMVT: incidence 19.11 vs 7.91 per 100-patient-years, adjusted incidence rate ratio (aIRR) 4.62 (95%CI 1.39–15.36), p = 0.012. bMVT was numerically more common after TMVR than SMVR, but the comparison was not statistically significant: incidence 7.03 vs 0.58 per 100-patient-years, aIRR 2.19 (95%CI 0.72–6.72), p = 0.170. Patients on vitamin-K antagonists (VKA) had a lower incidence of bMVT than patients on direct oral anticoagulants (DOAC; incidence 5.72 vs 17.08, aIRR 0.31, 95%CI 0.13–0.73, p = 0.007).

Conclusions
bMVT is not uncommon, with numerically higher incidence in transcatheter compared to surgical valves, but the comparison was not statistically significant. VKAs are associated with a lower incidence of bMVT compared to DOACs.
Application of omics technology in ecotoxicology of arthropod in farmland
Authors: Li Zhongyuan , Gao Cuimei , Wang Zhuoman , Huang Siqi , Jiang Zijian , Liu Jing , Yang Huilin 
Published: February 2025

Abstract
Arthropods, abundant in farmland, have unique biological traits that make them valuable for studying the ecotoxicological impacts of pollutants. Recent advancements in multi-omics technologies have enhanced their use in assessing pollution risks and understanding toxicity mechanisms. This paper reviews recent developments in applying omics technologies—genomics, transcriptomics, proteomics, metabolomics and meta-omics to ecotoxicological research on farmland arthropods. Agricultural arthropods manage genes and proteins like metallothioneins (MTs), antioxidant enzyme systems, heat shock proteins, cytochrome P450 (CYP450), carboxylesterases (CarEs), and glutathione S-transferases (GSTs), for detoxification and antioxidant purposes. They adjust amino acid, sugar, and lipid metabolism to counteract pollutant-induced energy drain and modify gut microbiota to aid in detoxification. This study advocates for enhanced analysis of compound pollution and emerging pollutants using multi-omics, especially meta-omics, to clarify the toxicological mechanisms underlying arthropod responses to these pollutants. Furthermore, it underscores the urgent need for subsequent gene function mining and validation to support biological control strategies and promote sustainable agricultural practices. The findings of this research provide significant insights into the toxicological impacts and mechanisms of pollutants within farmland ecosystems, thereby contributing to the preservation of arthropod diversity.
Prognostic relevance of baseline exercise stress test in RYR2-related CPVT
Authors: Kukavica Deni , Pili Gianluca , Trancuccio Alessandro , Giannini Gala , Pergola Valerio , Memmi Mirella , Gambelli Patrick , Marino Maira , Morini Massimo , Bloise Raffaella , Napolitano Carlo , Mazzanti Andrea , Priori Silvia G 
Published: February 2025

Abstract

Aims
Exercise stress test (EST) represents the gold standard for diagnosis of catecholaminergic polymorphic ventricular tachycardia (CPVT). We aimed to determine the relevance of exercise induced VT for the occurrence of LAE at follow-up.

Methods and results
In RYR2-related CPVT patients who underwent a baseline EST, we assessed the incidence and severity of ventricular arrhythmias (VA). Data were analysed using logistic regression models and Cox proportional hazards models. The primary outcome was the occurrence of life-threatening arrhythmic event (LAE; composite of sudden cardiac death, aborted cardiac arrest, or hemodynamically non-tolerated VT) at follow-up. In 102 RYR2-related CPVT patients (65 females; median age 16 years, IQR: 11–36 years), exercise-induced VT (bidirectional in 64% of cases) was elicited in 56% patients. VT could not be induced in pre-school children. Lower basal heart rate, early onset VA (within the first step of EST) and heart rate at the first minute of recovery were associated with exercise-induced VT. Cox analyses showed that early onset VA (HR 6.0, 95% CI: 1.3–27.9, P = 0.022) and exercise-induced VT (HR 6.6, 95% CI: 1.5–29.1, P = 0.012) at baseline EST were significantly associated with the occurrence of LAE at follow-up, and remained associated even after correction for symptoms.

Conclusion
Early onset VA and exercise-induced VT at baseline EST was associated with LAE at follow-up, allowing to identify a sub-set of patients at higher risk already at diagnosis.
Interactions within higher-order antibiotic combinations do not influence the rate of adaptation in bacteria
Authors: Lozano-Huntelman Natalie Ann , Cook Emoni , Bullivant Austin , Ida Nick , Zhou April , Boyd Sada , Yeh Pamela J 
Published: February 2025

Abstract
The prevalence and strength of antibiotic resistance has led to an ongoing battle between the development of new treatments and the evolution of resistance. Combining multiple drugs simultaneously is a potential solution for combating antibiotic resistance. However, this approach introduces new factors that must be considered, including the influence of drug interactions on the rate of resistance evolution. When antibiotics are used in combination, their effects can be additive, synergistic, or antagonistic. In this study, we investigated the effect of higher-order interactions involving three drugs on resistance evolution in Staphylococcus epidermidis. Previous studies have shown that synergistic interactions can increase the adaptation rate. However, the effects of higher-order interactions on rates of adaptation are unclear. We investigated the adaptation of Staphylococcus epidermidis to single-, two-, and three-drug environments to assess how interactions within drug combinations influence the rate of adaptation. We analyzed both the overall interaction and emergent interaction, the latter being a unique interaction that occurs in three-drug combinations due to the presence of all three drugs, rather than simply strong pairwise interactions. Our results show that neither the overall interactions nor the emergent interactions affect adaptation rates.