bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linking household members and defining relational networks using routine health data
Authors: Campbell Jeffrey I. , Poblacion Ana , Sheward Richard 
Published: November 2024

Purpose of review
The growth of rich electronic health record (EHR) data and large health databases has introduced new opportunities to link individuals together into households and relational networks. These ‘linked relational networks’ hold promise for providing family-level care and studying intergenerational epidemiology and clinical outcomes. However, as linked relational networks become more commonly available in EHRs and research databases, it is critical to understand their challenges and limitations.

Recent findings
Matching algorithms are being used to create linked relational networks in EHR and health databases. Clinically, these algorithms have been most useful to provide dyadic maternal–newborn care. In research, studies using these algorithms investigate topics ranging from the pharmacoepidemiology of parental drug exposure on childhood health outcomes, to heritability of chronic conditions, to associations between parental and child healthcare access and service delivery. However, ethical and technical challenges continue to limit use of these algorithms. There is also a critical research gap in the external validity of these matching algorithms.

Summary
Linked relational networks are in widespread use in pediatric clinical care and research. More research is needed to understand the scope, limitations, and biases inherent in existing matching strategies.
Exploring ChatGPT in clinical inquiry: a scoping review of characteristics, applications, challenges, and evaluation
Authors: Abhari Shahabeddin , Afshari Yasna , Fatehi Farhad , Salmani Hosna , Garavand Ali , Chumachenko Dmytro , Zakerabasali Somayyeh , Morita Plinio P. 
Published: November 2024

Introduction:
Recent advancements in generative AI, exemplified by ChatGPT, hold promise for healthcare applications such as decision-making support, education, and patient engagement. However, rigorous evaluation is crucial to ensure reliability and safety in clinical contexts. This scoping review explores ChatGPT’s role in clinical inquiry, focusing on its characteristics, applications, challenges, and evaluation.

Methods:
This review, conducted in 2023, followed PRISMA-ScR guidelines (Supplemental Digital Content 1, http://links.lww.com/MS9/A636). Searches were performed across PubMed, Scopus, IEEE, Web of Science, Cochrane, and Google Scholar using relevant keywords. The review explored ChatGPT’s effectiveness in various medical domains, evaluation methods, target users, and comparisons with other AI models. Data synthesis and analysis incorporated both quantitative and qualitative approaches.

Results:
Analysis of 41 academic studies highlights ChatGPT’s potential in medical education, patient care, and decision support, though performance varies by medical specialty and linguistic context. GPT-3.5, frequently referenced in 26 studies, demonstrated adaptability across diverse scenarios. Challenges include limited access to official answer keys and inconsistent performance, underscoring the need for ongoing refinement. Evaluation methods, including expert comparisons and statistical analyses, provided significant insights into ChatGPT’s efficacy. The identification of target users, such as medical educators and nonexpert clinicians, illustrates its broad applicability.

Conclusion:
ChatGPT shows significant potential in enhancing clinical practice and medical education. Nevertheless, continuous refinement is essential for its successful integration into healthcare, aiming to improve patient care outcomes, and address the evolving needs of the medical community.
Positivity and Follow-Up Testing of Chlamydia trachomatis and Neisseria gonorrhoeae Infections in Universally Screened Female Basic Military Trainees
Authors: Townsend Lisa C. , Stahlman Shauna L. , Escobar James D. , Osuna Angela B. , Casey Theresa M. , Winkler Erin L. , Kieffer John W. , Okulicz Jason F. , Yun Heather C. , Marcus Joseph E. 
Published: November 2024

Introduction
Follow-up testing is recommended 3 months after patients initially test positive with Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC). Follow-up testing adherence in the United States has been reported below one-third of women, even in universally insured populations. We assessed both the positivity of CT and GC infections in female basic military trainees and the rates of follow-up testing for those who tested positive.

Methods
Between January 1, 2006, and December 31, 2021, female Air Force Basic Military Trainees were universally screened with urinary nucleic acid amplification testing for CT and GC. Those who tested positive were evaluated to determine demographic information as well as follow-up testing rates. Patients who were evaluated with a repeat CT/GC nucleic acid amplification test within 12 months after a positive CT/GC test result were considered to have received appropriate follow-up.

Results
A total of 5022 (5.2%) of 97,168 trainees tested positive for only CT (4749 [4.8%]), only GC (138 [0.1%]), or both CT/GC (135 [0.1%]) during the study period. Those at increased risk of infection were those <24 years of age, Hispanic and Black individuals, those with high school education level, and single women. Of the 4687 still in the military at 3 months after diagnosis, 3268 (69.7%) had repeat testing within 12 months. There was no significant difference in follow-up testing by age, race, educational level, marital status, or organism causing original infection.

Conclusions
Follow-up testing among female United States Air Force basic military trainees is higher than in other universally insured populations. This study demonstrates remaining barriers to adherence to recommended guidelines.
Non-liver Malignancies as Main Cause of Mortality After HCV Eradication Among People Living With HIV
Authors: Alessia Siribelli , Sara Diotallevi , Laura Galli , Camilla Muccini , Giulia Morsica , Riccardo Lolatto , Costanza Bertoni , Emanuela Messina , Simona Bossolasco , Benedetta Trentacapilli , Caterina Uberti-Foppa , Antonella Castagna , Hamid Hasson 
Published: November 2024

Background:
In people living with HIV (PLWH) with hepatitis C virus (HCV) infection, liver and nonliver-related mortality significantly decreased after receiving direct acting antivirals (DAAs). We aimed to assess main causes and predictors of mortality after sustained virologic response induced by DAAs.

Methods:
Retrospective study in antiretroviral treatment-experienced PLWH with HCV infection, followed at San Raffaele Hospital, Milan, Italy, who achieved sustained virologic response after DAAs. Kaplan–Meier analysis and log-rank test were used to estimate cumulative probability of death for any cause. Cox proportional hazards model was used to estimate adjusted hazard ratio (aHR) of death and the corresponding 95% confidence interval (95% CI); baseline variables included in the model were age, diabetes, hepatocellular carcinoma (HCC), α-fetoprotein (AFP), and albumin–bilirubin (ALBI) grade.

Results:
Among 663 people included with a median follow-up of 4.4 years (interquartile range = 3.5–5.5), 49 died. Overall 5-year cumulative probability of death was 8.0% (95% CI: 5.5% to 0.4%); 63.2% (n = 31/49) died from nonliver-related events [mainly nonliver malignancies (18/49) and cardiovascular events (7/49)]. At multivariate analysis, death was more likely in older people [aHR (5-year older) = 1.46, 95% CI: 1.16 to 1.83, P = 0.0009], and in people with diabetes (aHR = 2.98, 95% CI: 1.55 to 5.71, P = 0.001), ALBI grade ≥2 (aHR = 2.13, 95% CI: 1.17 to 3.90, P = 0.014), and AFP ≥3.4 ng/mL (aHR = 1.96, 95% CI: 1.01; 3.84, P = 0.049).

Conclusions:
In our cohort, nonliver-related events and malignancies were the most common cause of death after HCV eradication. Diabetes, ALBI grade ≥2, and AFP ≥3.4 ng/L were associated with higher risk of death. In PLWH after HCV eradication, regardless of liver disease stage, surveillance of nonliver events, particularly malignancies, should be recommended.
Simultaneous Implantation of Maxillary Fibroskeletal Lesions: A Case Report and Literature Review
Authors: Chen Duo , Shen Yufeng , Qian Yi , Chen Shiman , Li Luoxin , Zhou Zheng 
Published: November 2024

Objective:
To investigate a clinical case of simultaneous implantation therapy for a patient with fibroskeletal disease of the jaw, and to provide a clinical basis for the treatment of such patients by clinical prosthetists.

Methods:
The clinical data of a patient with fibroskeletal disease of the jaw undergoing implant treatment were collected, and the clinical repair plan for this patient was discussed by reviewing the literature.

Results:
The patient, a female, 49 years old, right upper posterior tooth missing for 1 year, through the maxillofacial surgery consultation, according to the imaging data, the maxillary fibroskeletal lesions were considered. The tumor was removed, bone regeneration was guided, and microimplants were implanted at the same time. Cone Beam Computed Tomography was performed at 3, 9, and 20 months postoperatively, and according to clinical evaluation, the patient did not show any signs of recurrence. At the same time, a literature search was conducted to summarize the data on simultaneous implantation therapy for fibroskeletal lesions of the jaw.

Conclusion:
The treatment plan of tumor removal → guided bone regeneration → simultaneous implantation of microimplants can effectively achieve implant repair and reduce the failure rate of implants in patients with jaw fibroskeletal lesions.
The MangLE score: A novel simple tool to identify patients who are unlikely to require amputation following severe lower extremity injury
Authors: Forssten Maximilian Peter , Coimbra Bruno , Matecki Mary , Godshall Saundra , Cao Yang , Mohseni Shahin , Sarani Babak 
Published: November 2024

BACKGROUND
There are no validated and sensitive models that can guide the decision regarding amputation in patients with mangled lower extremities. We sought to describe a simple scoring model, the Mangled Lower Extremity (MangLE) score, which can predict those who are highly unlikely to need an amputation as a means to direct resources to this cohort.

METHODS
This is a retrospective study using the 2013–2021 American College of Surgeons Trauma Quality Improvement Program data set. Adult patients with a mangled lower extremity, defined as a crush injury or a fracture of the femur or tibia combined with severe soft tissue injury, arterial injury, or nerve injury, were included. Patients who suffered a traumatic lower extremity amputation, underwent amputation within 24 hours of admission, or who died within 24 hours of admission were excluded. Patients were divided into those who did/did not undergo amputation during their hospital stay. Demographics, injury mechanism, Injury Severity Score, and Abbreviated Injury Scale score, initial vital signs, and comorbid conditions were abstracted. A logistic regression model was constructed and the top five most important variables were used to create the score.

RESULTS
The study includes 107,620 patients, of whom 2,711 (2.5%) underwent amputation. The five variables with the highest predictive value for amputation were arterial injury, lower-extremity Abbreviated Injury Scale score of ≥3, crush injury, blunt mechanism, and shock index. The lowest possible MangLE score was 0, and the highest was 15. The model demonstrated an excellent predictive ability for lower extremity amputation in both the development and validation data set with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval, 0.80–0.82) and 0.82 (95% confidence interval, 0.81–0.84), respectively. The negative predictive value for a score of <8 is 99%.

CONCLUSION
The MangLE score is able to identify patients who are unlikely to require amputation. Resources for limb salvage can be directed to this cohort.

LEVEL OF EVIDENCE
Prognostic and Epidemiological; Level IV.
Current trend in air pollution exposure and stroke
Authors: Gabet Stephan , Puy Laurent 
Published: November 2024

Purpose of review
Stroke is the second leading cause of death worldwide, and exposure to particulate air pollution is now recognized as one of the major modifiable risk factors. However, air pollution can vary in terms of physicochemical composition and exposition specificities. Therefore, its relationships with stroke outcomes remain under intense investigation.

Recent findings
This review highlights, alongside particles, that short-term and long-term exposure to nitrogen dioxide (NO2) and ozone is likely to be also linked to stroke-related morbidity and mortality. Moreover, air pollution may increase the risk of transitioning from a healthy status to incident stroke and morbimortality after stroke. Additionally, relationships may vary depending on the air pollution mixture (e.g., particle-related components, pollutant interactions), pollutant sources (e.g., traffic-related or not), stroke etiology (ischemic or hemorrhagic), or exposed individual's characteristics (e.g., age, sex, genetic predisposition, weight status). Nonlinear dose-response functions and short-term effect lags have been reported, but these features need further refinement.

Summary
The relationship between stroke and air pollution is now well established. Nonetheless, future research should further consider the physicochemical properties of air pollutants, multiple exposures, and individual vulnerabilities. Moreover, advanced statistical methods should be more commonly used to better describe the relationship shapes.
Lymphopenia drives T cell exhaustion in immunodeficient STING gain-of-function mice
Authors: Freytag Damien , Giorgiutti Stéphane , Wadier Nadège , Depauw Sabine , Hopsomer Grégoire , Mertz Philippe , Augé Fabrice , Carapito Raphaël , Couillin Isabelle , Korganow Anne-Sophie , Pala Francesca , Bosticardo Marita , Notarangelo Luigi D. , Rieux-Laucat Frédéric , Riteau Nicolas , Kirstetter Peggy , Soulas-Sprauel Pauline 
Published: November 2024

AbstractSTING gain-of-function (GOF) mutations are associated with the severe autoinflammatory disease designated STING Associated Vasculopathy with onset in Infancy (SAVI). Mice with the STING GOF V154M mutation develop profound T cell lymphopenia, partly due to a blockage of T cell development in the thymus. To better characterize the mechanisms of peripheral T cell dysfunctions, we conducted a transcriptomic and phenotypic analysis on sorted splenic CD4+ and CD8+ mature T cells from STING GOF V154M mice. We identify a T cell exhaustion phenotype that manifests at a terminal stage, acquired early in life but only after reaching the peripheral environment. This phenotype is independent of type I interferons and does not rely on intrinsic STING activation in either T cells or stromal cells. Mechanistically, the limited number of mature T cells that reach the periphery appear to be quickly impacted by the lymphopenic environment, experiencing heightened stimulation of the IL-7 receptor and TCR pathways, including the NFAT pathway, a key factor in T cell exhaustion. By performing transplantation experiments with STING GOF long term-hematopoietic stem cells (LT-HSCs) along with supportive wild-type bone marrow (BM) cells, we were able to prevent the T cell exhaustion of STING GOF T cells in the resulting non-lymphopenic context, demonstrating that lymphopenia is a major driver of T cell exhaustion in STING GOF mice. T cell exhaustion, although less severe, was also observed in lymphopenic mice carryingRag1hypomorphic mutations. In conclusion, our results, which highlight T cell exhaustion induced by lymphopenia, could have important implications for the management of patients with severe immune deficiencies.HighlightsWe describe a phenotype of T cell exhaustion in STING GOF V154M mice, which is acquired early in life and in the periphery.STING GOF-associated T cell exhaustion is independent of type I IFNs, and STING GOF/activation in T cells or in stromal cells is not sufficient for T cell exhaustion.Lymphopenia is a major driver of T cell exhaustion in STING GOF mice, and increased antigenic/IL-7 stimulation of T cells in the lymphopenic context of STING GOF mice could be implicated in the induction of T cell exhaustion.
Visual Field Progression Rate and Laminar Depth and Curvature in the African Descent and Glaucoma Evaluation Study (ADAGES)
Authors: Murillo Karla , Jiravarnsirikul Anuwat , Walker Evan , Fazio Massimo A. , Gardiner Stuart , Weinreb Robert N , Liebmann Jeffrey M , Zangwill Linda M. , Girkin Christopher A. 
Published: November 2024

AbstractPurposeTo determine if lamina cribrosa (LC) depth and curvature predict visual field (VF) progression rate in the African Descent and Glaucoma Evaluation Study (ADAGES) cohort in patients with primary open angle glaucoma (POAG).SubjectsParticipants, and/or Controls. Three eyes from three research-consented brain-dead organ donors.MethodsAnterior laminar cribrosa surface depth (ALCSD) and LC curvature index (LCCI) were defined from 24 radial B-scan spectral domain optic coherence tomographic (SDOCT) images of each image. All scans were processed using a deep learning software to perform the segmentation and optic nerve health (ONH) layers. Univariable and multivariable linear mixed effects models were used to test associations between VF progression rate, ALCSD, and other demographic and clinical characteristics and known risk factors for progressive POAG. Additionally, the variable selection in the final multivariable model was reached using the Akaike information criterion index (AICc) and clinical utility.MeasuresIOP change with exposure to NP.MainOutcomeThe associations between ALCSD and LCCI with the rate of VF progression.ResultsThere was a statistically significant relationship between faster VF progression rates, and a deeper ALCSD (−0.02 dB/year/50 microns, p<0.001) and LCCI (−0.01unit/dB/year, p<0.001). There was also increasing progression seen in both models for with increasing age (−0.025dB/year/10 years, p<0.007), intraocular pressure (IOP) (−0.011dB/year per 2 mmHg, p=0.021), and disease severity (0.017dB/year per dB, p<0.001). The rate of progression was faster in the ED cohort (−0.056 dB/year, p=0.006) following propensity matching for disease severity and age.ConclusionsIn the ADAGES cohort, there is a statistically significant association between VF progression rate and ALCSD and curvature (LCCI). A 50 um deeper LC at baseline had a similar effect of VF progression as being 10 years of age older. These data suggest that morphologic change in the ONH due to glaucomatous and age-related remodeling may induce greater vulnerability to develop progressive disease. Thus, LC depth and curvature may inform the likelihood and rate of glaucoma progression and are promising candidates for mechanistic biomarkers.
Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems biology approach
Authors: De Silva M.R.P. , Weeraman J.W.J.K. , Fernando P.C. 
Published: November 2024

AbstractBackgroundRice is a critical global food source, but it faces challenges due to nutritional deficiencies and the pressures of a growing population. Understanding the molecular mechanisms and protein functions in rice seed development is essential to improve yield and grain quality. However, there is still a significant knowledge gap regarding the key proteins and their interactions that govern rice seed development. Protein-protein interaction (PPI) analysis is a powerful tool for studying developmental processes like seed development, though its potential in rice research is yet to be fully realized. With the aim of unravelling the protein interaction landscape associated with rice seed development, this systems biology study conducted a PPI network-based analysis. Using a list of known seed development proteins from the Gene Ontology (GO) knowledgebase and literature, novel candidate proteins for seed development were predicted using an ensemble of network-based algorithms, including majority voting (MV), Hishigaki, Functional flow, and Random Walk with Restart (RWR). The predictions were validated using enrichment analysis, and the rice seed development subnetwork was further analyzed for community and hub detection.ResultsThe study predicted 196 new proteins linked to rice seed development and identified 14 sub-modules within the network, each representing different developmental pathways such as endosperm development and seed growth regulation. Of these, 17 proteins were identified as intra-modular hubs and 6 as inter-modular hubs. Notably, the protein SDH1 emerged as a dual hub, acting as both an intra-modular and inter-modular hub, highlighting its crucial role in coordinating interactions during rice seed development.ConclusionsThese findings, including the identified hub proteins and sub-modules, provide a better understanding of the PPI interaction landscape governing seed development in rice. This information is useful for improving rice cultivars for better yield and quality through genetic engineering and breeding. This study implements an ensemble of algorithms for the analysis and showcases how systems biology techniques can be applied in developmental biology.
Benchmarking Self-Supervised Learning for Single-Cell Data
Authors: Toma Philip , Ovcharenko Olga , Daunhawer Imant , Vogt Julia , Barkmann Florian , Boeva Valentina 
Published: November 2024

AbstractSelf-supervised learning (SSL) has emerged as a powerful approach for learning biologically meaningful representations of single-cell data. To establish best practices in this domain, we present a comprehensive benchmark evaluating eight SSL methods across three downstream tasks and eight datasets, with various data augmentation strategies. Our results demonstrate that SimCLR and VICReg consistently outperform other methods across different tasks. Furthermore, we identify random masking as the most effective augmentation technique. This benchmark provides valuable insights into the application of SSL to single-cell data analysis, bridging the gap between SSL and single-cell biology.
Automated cell tracking using 3D nnUnet and Light Sheet Microscopy to quantify regional deformation in zebrafish
Authors: Teranikar Tanveer , Saeed Saad , Le The Van , Kang Yoonsuk , Hernandez Gilberto , Nguyen Phuc , iing Yichen , Chuong Cheng-Jen , Lee Jin Young , Ko Hyunsuk , Lee Juhyun 
Published: November 2024

ABSTRACTLight Sheet Microscopy (LSM) in conjunction with embryonic zebrafish, is rapidly advancing three-dimensional,in vivocharacterization of myocardial contractility. Preclinical cardiac deformation imaging is predominantly restricted to a low-order dimensionality image space (2i) or suffers from poor reproducibility. In this regard, LSM has enabled high throughput, non-invasive 4i (3d+time) characterization of dynamic organogenesis within the transparent zebrafish model. More importantly, LSM offers cellular resolution across large imaging Field-of-Views at millisecond camera frame rates, enabling single cell localization for global cardiac deformation analysis. However, manual labeling of cells within multilayered tissue is a time-consuming task and requires substantial expertise. In this study, we applied the 3i nnU-Net with Linear Assignment Problem (LAP) framework for automated segmentation and tracking of myocardial cells. Using binarized labels from the neural network, we quantified myocardial deformation of the zebrafish ventricle across 4-6 days post fertilization (dpf). Our study offers tremendous promise for developing highly scalable and disease-specific biomechanical quantification of myocardial microstructures.