bluuebunny/crossref_metadata_2025_split huggingface dataset:
Path model explaining the association between fear of falling and health-related quality of life in (pre-)frail older adults
Authors: Sattler Tjard , Gottschalk Sophie , König Hans-Helmut , Braun Tobias , Büchele Gisela , Denkinger Michael , Fleiner Tim , Nerz Corinna , Rapp Kilian , Schäufele Martina , Werner Christian , Dams Judith 
Published: February 2025

Abstract

Background
Fear of falling (FoF) is estimated to be prevalent in over 50% of older adults and several studies suggest that it negatively affects health-related quality of life (HrQoL). Unlike previous studies that examined only few mediating variables, this study aimed to develop a more comprehensive path model explaining the association between FoF and HrQoL.

Methods
A theoretical path model was developed based on existing evidence and expert feedback and fitted to cross-sectional baseline data on 385 community-dwelling (pre-)frail older adults from the PromeTheus randomized controlled trial using robust weighted least squares estimation. FoF and HrQoL were operationalized by the Short Falls Efficacy Scale International and EQ-5D Index, respectively. The model included potential explanatory pathways through physical activity (German Physical Activity Questionnaire for middle-aged and older adults), physical capacity (Short Physical Performance Battery), physical performance (Late-Life Function and Disability Instrument [LLFDI] function component), disability (LLFDI disability component – short form), and affect (visual analogue scales on ‘happiness’, ‘sadness’, ‘calmness’ and ‘tension’). Age, sex, education, and previous falls were considered as covariates.

Results
The model demonstrated good fit to the data and the remaining direct effect of FoF on HrQoL was small (β=-0.05). Physical capacity and physical performance were the most important mediators (combined indirect effect of β=-0.17, accounting for > 50% of the total effect). Pathways of minor individual relevance (e.g. through disability or affect) contributed considerably to the total indirect effect when combined. Controlling for sociodemographic data and previous falls only had minor effects on model fit and path coefficients.

Conclusion
Physical capacity and physical performance are particularly important levers for reducing the impact of FoF on HrQoL through interventions. However, the other pathways also had a considerable influence when taken together. Hence, research on the association of FoF and HrQol should acknowledge the complexity of causal pathways that may explain this association and not neglect minor pathways. The proposed model should be tested on an alternative sample, using longitudinal data, and extended to include additional explanatory factors (e.g. activity avoidance).

Trial registration
German Clinical Trials Register, ID: DRKS00024638, https://drks.de/search/en/trial/DRKS00024638, date of registration: March 11th 2021.
Key tips to shift student perspectives through transformative learning in medical education
Authors: Hart Efraim J. , de Heer-Koster Merel H. , van der Harst Maria , Browne Joyce L. , Scheele Fedde 
Published: February 2025

Abstract
Healthcare systems are increasingly complex, facing challenges such as rising costs, aging populations, and persistent health inequities. These challenges demand that medical education adapts, to equip health professionals with the competencies required to navigate and transform complex systems. This is where transformative learning theory can play a crucial role. This article offers twelve practical tips to integrate transformative learning in medical education, emphasizing the need for a shift from traditional educational approaches to more transformative methods. These tips focus on educating learners on the principles of transformative learning, encouraging critical reflection, fostering interdisciplinary collaboration, addressing the hidden curriculum, and creating a supportive learning environment. By implementing these tips, medical education can better prepare healthcare professionals to act as change agents, contributing to the long-term sustainability and effectiveness of healthcare systems. The potential impact of these tips on medical education is substantial, as they provide a pathway toward a more responsive, ethical, and sustainable future of healthcare. Clinical trial number: Not applicable.
Disparities in well-being outcomes among medical students: a comparative study between medical students with and without disability
Authors: Seaborne Henry J. , Chehab Lara Z. , Rajapuram Nikhil , Sammann Amanda 
Published: February 2025

Abstract

Background
The strenuous demands of medical education often lead to adverse mental health outcomes among students. Despite extensive research on medical student distress, the unique challenges faced by students with disabilities remain understudied. This study aims to investigate the well-being of medical students with and without disabilities, by comparing levels of distress, risk and protective factors, and modifiable variables’ impact on distress.

Methods
From September 2019 to February 2020, we implemented an exploratory observational study to survey medical students across the US, US territories, and Caribbean. Participants completed the Medical Student Wellbeing Survey (MSWS), which was used to assess well-being and capture extensive demographic data on these students. We retrospectively sorted participant data into cohorts based on disability status, then compared them using rates of well-being outcomes, logistic regression, and interaction analyses. We conducted logistic regression analyses to identify significant predictors of severe distress, burnout, and depression.

Results
Of the 3162 medical student participants, 277 identified as having a disability. Respondents with disabilities reported significantly higher rates of severe distress (65%) compared to their non-disabled peers (51.3%). Additionally, burnout and depression rates were higher among disabled students, with 80.41% experiencing burnout and 54.84% experiencing depression. Logistic regression revealed that certain identities, as well as high debt and tuition costs, were significant predictors of severe distress across cohorts. Uniquely, marital status emerged as a protective factor specifically for students with disabilities.

Conclusion
Medical students with disabilities exhibit higher levels of severe distress, burnout, and depression than their non-disabled counterparts. Current interventions and modifiable factors are insufficient in lessening severe distress for these students. These findings highlight the necessity for tailored support strategies and structural interventions to improve the well-being of medical students with disabilities, especially for those with intersecting vulnerable identities.

Trial registration
This study does not report the results of a health care intervention on human participants, so trial registration is not required.
High risk for life-threatening adverse events of fluoroquinolones in young adults: a large German population-based cohort study
Authors: Wicherski Julia , Peltner Jonas , Becker Cornelia , Schüssel Katrin , Brückner Gabriela , Schlotmann Andreas , Schröder Helmut , Kern Winfried V. , Haenisch Britta 
Published: February 2025

Abstract

Background
Fluoroquinolone antibiotics have a high potential for serious adverse drug reactions, but real-world evidence in European patient cohorts is lacking. Therefore, we aim to examine the association between fluoroquinolone exposure and potentially life-threatening adverse events stratified by age and gender in Germany.

Methods
We conducted an administrative cohort study using the active comparator new user design with a risk window up to 365 days between January 2013 and December 2019. Population-based longitudinal data from one of the largest German statutory health insurances were used. Episodes of newly dispensed fluoroquinolones (ciprofloxacin, levofloxacin, ofloxacin, moxifloxacin, norfloxacin, and enoxacin) were compared to other antibiotics (amoxicillin, amoxicillin clavulanic acid, azithromycin, cefuroxime, cephalexin, clindamycin, sulfamethoxazole-trimethoprim, and doxycycline). Endpoints were defined by incident diagnoses of aortic aneurysm/dissection, cardiac arrhythmia, hepatotoxicity, and all-cause mortality. Adjusted hazard ratios were estimated from piece-wise exponential additive mixed models with smooth non-linear effects for person-time and age and adjusted for comorbidities, year and quarter at index.

Results
The cohorts comprised 15,139,840; 11,760,159; 11,027,175; and 15,305,757 antibiotic episodes. Patients during fluoroquinolone episodes were older (59 versus 51 years) and more often female (58% versus 54%). We counted 46,502; 446,727; 19,125; and 474,411 incident endpoints. Relative risk for all-cause mortality and hepatotoxicity was high for < 40-year- and 40–69-year-old females (aHR = 1.77, 95% CI 1.55–2.03 and aHR = 1.42, 95% CI 1.32–1.53), respectively. For aortic aneurysm/dissection a nominally increased relative risk for < 40-year-old females was found (aHR = 1.42, 95% CI 0.96–2.11), although 95% CI indicates that a small relative risk reduction is also supported by the data. Relative risk for cardiac arrhythmia was increased for men aged < 40 years (aHR = 1.14, 95% CI 1.08–1.20). High relative risks for each endpoint were also identified depending on choice of active comparator, and risks increased with higher defined daily doses and shorter follow-up.

Conclusions
This study contributes real-world evidence to endpoint-specific differences of risks in patient subgroups which need to be considered to improve fluoroquinolone drug safety.
Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence
Authors: Chen Yi-Ming , Hsiao Tzu-Hung , Lin Ching-Heng , Fann Yang C. 
Published: February 2025

Abstract
Artificial intelligence (AI) has emerged as a transformative force in precision medicine, revolutionizing the integration and analysis of health records, genetics, and immunology data. This comprehensive review explores the clinical applications of AI-driven analytics in unlocking personalized insights for patients with autoimmune rheumatic diseases. Through the synergistic approach of integrating AI across diverse data sets, clinicians gain a holistic view of patient health and potential risks. Machine learning models excel at identifying high-risk patients, predicting disease activity, and optimizing therapeutic strategies based on clinical, genomic, and immunological profiles. Deep learning techniques have significantly advanced variant calling, pathogenicity prediction, splicing analysis, and MHC-peptide binding predictions in genetics. AI-enabled immunology data analysis, including dimensionality reduction, cell population identification, and sample classification, provides unprecedented insights into complex immune responses. The review highlights real-world examples of AI-driven precision medicine platforms and clinical decision support tools in rheumatology. Evaluation of outcomes demonstrates the clinical benefits and impact of these approaches in revolutionizing patient care. However, challenges such as data quality, privacy, and clinician trust must be navigated for successful implementation. The future of precision medicine lies in the continued research, development, and clinical integration of AI-driven strategies to unlock personalized patient care and drive innovation in rheumatology.
Baseline atherogenic index of plasma and its trajectory predict onset of type 2 diabetes in a health screened adult population: a large longitudinal study
Authors: Sun Yongbing , Lin Xinbei , Zou Zhi , Zhao Caiwen , Liu Ao , Zhou Jing , Li Zhonglin , Wu Xiaoling , Dou Shewei , Zhu Jiadong , Li Tao , Lv Xue , Wang Yong , Li Yongli 
Published: February 2025

Abstract

Background
The Atherogenic Index of Plasma (AIP) is a novel biomarker for assessing the severity of atherosclerosis and has been shown to be closely associated with the risk of Type 2 Diabetes Mellitus (T2DM). However, no prospective cohort study has comprehensively evaluated both the immediate risk stratification through baseline AIP and the long-term risk assessment through multi-time point AIP trajectories in health screened adults in relation to T2DM risk.

Methods
This longitudinal study included data from 42,850 participants who underwent health check-ups at Henan Provincial People’s Hospital between January 2018 and August 2024. AIP was calculated as the logarithm of the ratio of triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C). The Kaplan-Meier method was employed to analyze the incidence of T2DM across different AIP groups. A Cox model with restricted cubic splines assessed the dose-response relationship between AIP and T2DM risk, while latent class trajectory models (LCTM) evaluated the trends of AIP over multiple time points. Cox proportional hazards models were used to examine the relationship between baseline AIP quartiles, AIP trajectories, and T2DM risk.

Results
During an average follow-up of 47.95 months, 3,228 participants developed T2DM. Stratifying by baseline AIP quartiles revealed that higher AIP levels were associated with an increased risk of T2DM. Compared to the lowest quartile, the highest quartile had a hazard ratio (HR) of 2.10 (95% CI: 1.74, 2.53). The LCTM identified three trajectory patterns for AIP: with the low-stable group as the reference, the medium-stable and high-stable groups had HRs of 1.72 (95% CI: 1.50, 1.96) and 2.50 (95% CI: 2.06, 3.03), respectively, indicating a significantly elevated risk of T2DM (P < 0.05).

Conclusion
Elevated baseline AIP levels, medium stable trajectories and high stable trajectories are associated with an increased risk of T2DM in health screened adults.
Biogenesis, characterization, and applications of Spirulina selenium nanoparticles
Authors: Yassein Asmaa S. , Elamary Rokaia B. , Alwaleed Eman A. 
Published: February 2025

Abstract

Background
Nowadays, researchers are attracted to the phyco-synthesis of selenium nanoparticles (SeNPs) for biotechnological and medical applications as they possess many advantages such as safety, nutritional value, and easy biodegradation than gold, copper, and silver nanoparticles. Spirulina platensis is the preferred microalgae for SeNPs synthesis because it contains many compounds that increase their stability making them fit for biomedical treatments.

Results
The biosynthesized Spirulina platensis selenium nanoparticles (SP-SeNPs) were spherical and crystalline, with a diameter of 65 nm and a net charge of -16.7 mV. Furthermore, they were surrounded by active groups responsible for stability. The DPPH radical scavenging test assessed the antioxidant efficacy of SP-SeNPs and exposed scavenging inhibition of 79.234% at a 100 µM dosage. ABTS and H2O2 radical scavenging assay is dose-dependent recording IC50 of 50.69 and 116.18 µg/ml, respectively. The antibacterial efficacy was investigated against 13 G-negative & G-positive bacteria. The study demonstrated that SP-SeNPs had antibacterial and antibiofilm efficiencies against the tested strains with MBC of 286–333 µg/ml. The highest percentages of biofilm inhibition were recorded for Bacillus subtilis and Klebsiella pneumoniae, with ratios of 78.8 and 69.9%, respectively. The prepared SP-SeNPS efficiently suppressed the tested fungi growth with MIC (350 µg/ml) and MFCs (480–950 µg/ml). Most notably, biogenic SeNPs effectively extended the clot formation period recording 170.4 S for prothrombin time (PT) and 195.6 S for the activated partial thromboplastin time (aPTT). SP-SeNPs reduced the cell viability of breast adenocarcinoma (MCF-7) and ovarian cancer (SKOV-3) cell lines with a percentage of 17.6009% and 14.9484% at a concentration of 100 ug/ml, respectively. Moreover, SP-SeNPs could effectively alleviate the inflammation in RAW 264.7 macrophages with a reduction percentage of 8.82% in Nitric oxide concentration.

Conclusion
The investigation findings reveal that SP-SeNPs are a hopeful antimicrobial, anti-tumor, anticoagulant, antioxidant, and anti-inflammatory factor that can be applied in medical cures.
Promoting ER stress in a plasmacytoid dendritic cell line drives fibroblast activation
Authors: Ferreira Beatriz H. , Silva Inês S. , Mendes Andreia , Leite-Pinheiro Fátima , Paton Adrienne W. , Paton James C. , Duarte Iola F. , Pierre Philippe , Almeida Catarina R. 
Published: February 2025

Abstract

Background
Fibrosis remains a major complication in several chronic diseases, including systemic sclerosis (SSc). Plasmacytoid dendritic cells (pDCs) are innate immune cells that play a key role in the development of fibrosis in SSc patients, through still poorly defined mechanisms. Interestingly, endoplasmic reticulum (ER) stress signaling pathways are dysregulated in pDCs from patients with SSc, but their contribution to fibrosis remains unclear. Thus, this study aimed to unravel the mechanisms behind the involvement of pDCs and ER stress in fibrosis.

Methods
To address this question, we established an in vitro model designed to study the interactions between pDCs and fibroblasts. More specifically, IMR-90 fibroblasts were co-cultured with CAL-1, a pDC cell line. ER stress was then induced by the bacterial toxin SubAB. Extracellular matrix (ECM) production was assessed using immunoblotting, qPCR and confocal microscopy. The importance of cell-to-cell contact was investigated using conditioned media (CM) and transwell assays.

Results
Direct contact of CAL-1 and IMR-90 cells under ER stress conditions led to increased expression of fibronectin and alpha-smooth muscle actin (α-SMA). This effect required expression of the ER stress signaling sensor protein kinase R-like ER kinase (PERK) in pDCs and was observed only upon direct contact between both cell types.

Conclusions
Overall, our data suggest that ER stress induction in pDCs promotes fibroblast activation, which may contribute to the development of fibrosis in SSc.
Inhibition of tumour necrosis factor alpha by Etanercept attenuates Shiga toxin-induced brain pathology
Authors: Christ Robin , Siemes Devon , Zhao Shuo , Widera Lars , Spangenberg Philippa , Lill Julia , Thiebes Stephanie , Bottek Jenny , Borgards Lars , Pinho Andreia G. , Silva Nuno A. , Monteiro Susana , Jorch Selina K. , Gunzer Matthias , Siebels Bente , Voss Hannah , Schlüter Hartmut , Shevchuk Olga , Chen Jianxu , Engel Daniel R. 
Published: February 2025

Abstract
Infection with enterohemorrhagic E. coli (EHEC) causes severe changes in the brain leading to angiopathy, encephalopathy and microglial activation. In this study, we investigated the role of tumour necrosis factor alpha (TNF-α) for microglial activation and brain pathology using a preclinical mouse model of EHEC infection. LC–MS/MS proteomics of mice injected with a combination of Shiga toxin (Stx) and lipopolysaccharide (LPS) revealed extensive alterations of the brain proteome, in particular enrichment of pathways involved in complement activation and coagulation cascades. Inhibition of TNF-α by the drug Etanercept strongly mitigated these changes, particularly within the complement pathway, suggesting TNF-α-dependent vasodilation and endothelial injury. Analysis of microglial populations using a novel human-in-the-loop deep learning algorithm for the segmentation of microscopic imaging data indicated specific morphological changes, which were reduced to healthy condition after inhibition of TNF-α. Moreover, the Stx/LPS-mediated angiopathy was significantly attenuated by inhibition of TNF-α. Overall, our findings elucidate the critical role of TNF-α in EHEC-induced brain pathology and highlight a potential therapeutic target for mitigating neuroinflammation, microglial activation and injury associated with EHEC infection.

Graphical Abstract
Incidence and predictors of respiratory tract infections among birth cohorts in Ethiopia, 2023
Authors: Bayou Fekade Demeke , Arefaynie Mastewal , Mohammed Anissa , Tareke Abiyu Abadi , Keleb Awoke , Kebede Natnael , Tsega Yawkal , Mersha Bayu Hailemariam , Endawkie Abel , Kebede Shimels Derso , Abera Kaleab Mesfin , Abeje Eyob Tilahun , Enyew Ermias Bekele , Daba Chala , Asmare Lakew 
Published: February 2025

Abstract

Background
Respiratory tract infection (RTI) has been a predominant health problem worldwide, including Ethiopia. It is one of the major causes of under-five mortality in Ethiopia, accountable for 18% of total deaths. Nationwide studies on the incidence of respiratory infections and maternal risk factors are limited. Hence, this study was aimed to determine the incidence and predictors of respiratory infections among infants aged less than six months in Ethiopia, 2023.

Methods
This was a retrospective follow up study using data from Performance Monitoring for Action Ethiopia (PMA Ethiopia). A two-stage cluster sampling technique was used to select a total 2,246 eligible study participants from 206 enumeration areas. A Cox proportional hazards regression model was used to identify independent predictors of respiratory tract infection incidence. Hazard ratios with 95% confidence intervals and p value < 0.05 were used to declare statically significant associations between variables.

Results
The incidence rate of respiratory tract infections among birth cohorts was 22.99 per 1000 infant weeks of observation. Infants born from mothers who sustained convulsion during labor had nearly doubled [AHR = 1.65, 95%CI (1.20, 2.28)] hazard or risk of developing respiratory tract infections than their counterparts. Similarly, infants born from mothers having prolonged labor (more than 12 h) had one and half times [AHR = 1.48, 95%CI (1.13, 1.93)] increased risk of developing respiratory tract infections as compared to their counterparts.

Conclusion
The incidence of respiratory tract infections is a significant public health concern in Ethiopia. Infants born to mothers with prolonged labor and convulsions need closer monitoring for early signs of respiratory tract infections.
Drug response is related to NR3C1 and FAAH polymorphism in Chinese pediatric epilepsy patients
Authors: Wang Hongli , Li Chu , Li Qian , Li Ning , Qin Huiling 
Published: February 2025

Abstract

Background
Childhood epilepsy is a common neurological syndrome with complex etiology and recurrent seizures. It seriously affects the growth and development of child patients.

Methods
NR3C1 rs41423247 and FAAH rs324420 polymorphisms were detected by the polymerase chain reaction in 105 pediatric epilepsy patients. Patients were divided into the good response group and the poor response group after anti-seizure medications (ASMs) treatment. According to the results of the liver function test (LFT), patients were divided into the no LFT disturbance group and the LFT disturbance group. Hardy–Weinberg balance was applied to analyze the population representation. The correlations were calculated by logistic regression analysis.

Results
NR3C1 rs41423247 genotype and allele frequencies differed significantly between good response and poor response groups, while FAAH rs324420 did not. The CG genotype and C allele of NR3C1 rs41423247 were associated with good drug response, and the association was also detected in the dominant model. In addition, polymorphisms in NR3C1 and FAAH were not associated with liver damage induced by epilepsy medication.

Conclusion
The polymorphism of NR3C1 rs41423247 might influence the drug response of epilepsy children.