bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidence of optic neuritis among Afro-descendant, a cohort study
Authors: Bobelna Benoit , Lobjois Quentin , Croitoru Stefana , Jalkh Edmond , Ventura Eric , Merle Harold 
Published: February 2025

Background: Optic neuritis (ON) is a multifactorial condition with a strong association with ethnicity. Objectives: We conducted a retrospective cohort study in a Caribbean Island, Martinique, French West Indies to assess the incidence and characteristics of ON among an Afro-descendant (AD) population. Methods: We reviewed medical records of all patients presenting ON at the Fort de France University Hospital, Martinique between 2018 and 2022. We analysed clinical, paraclinical, and biological examinations at onset and during follow-up (6 months, 1, 2 and 3 years). ON was confirmed after a neuro-ophthalmological evaluation according to the latest criteria defined in the Lancet, 2022. Results: Overall, 44 patients with a condition suggestive of ON were evaluated, out of which 29 fulfilled the criteria for ON. The overall incidence was 1.61 (95% CI: 1.12–2.08) per 100,000 person-years. The final diagnosis was distributed as follows: neuromyelitis optica spectrum disorder (NMOSD) (10%), myelin oligodendrocyte glycoprotein (MOG) ON (20%), multiple sclerosis (35%), single isolated ON (24%), relapsing isolated ON (7%) and (4%) unclassified diagnosis. Conclusion: This is the first cohort study assessing the incidence of ON and its characteristics among AD. We found a high proportion of severe disease, such as NMOSD and MOG-associated disease.
Inhibitors of soluble epoxide hydrolase and cGAS/STING repair defects in amyloid-β clearance underlying vascular complications of Alzheimer's disease
Authors: Fiala Milan , Hammock Bruce D , Hwang Sung Hee , Whitelegge Julian , Paul Ketema , Kaczor-Urbanowicz Karolina Elżbieta , Urbanowicz Andrzej , Kesari Santosh 
Published: February 2025

Background Alzheimer's disease (AD) and its monoclonal antibody therapies are associated with brain vasculitis and amyloid-related imaging abnormalities. The naturally-formed epoxides (EpFAs) of polyunsaturated fatty acids (PUFAs), such as 11,12-epoxyeicosatetraenoic acid (EEQ), are anti-inflammatory and pro-resolution mediators, which are increased by dietary supplementation with ω-3 PUFAs. EpFAs are, however, enzymatically hydrolyzed by soluble epoxide hydrolase (sEH) in AD patients' macrophages in vivo and in vitro . Objective To repair amyloid-β 1-42 (Aβ) degradation by AD macrophages using the inhibitors of a) soluble epoxide hydrolase (sEHIs), termed TPPU and EC5026, together with EpFAs, or b) STING pathway termed H-151. Methods Immunobiology, immunochemistry, RNA sequencing, and confocal microscopy were used. Results In AD brain (examined postmortem), monocyte/macrophages upload Aβ in plaques and transfer it without degradation into brain microvessels, suffer apoptotis, and release Aβ, inducing vasculitis. The EpFAs of epoxyeicosatetraenoic acid (EEQ), along with the inhibitors TPPU and H-151, decrease inflammatory cytokines and regulate macrophage unfolded protein response to endoplasmic reticulum stress. Treatment of AD macrophages by TPPU with EEQ or by STING inhibitor H-151 increased uploading of Aβ after 2 hours and increased degradation of Aβ after 24 hours. Conclusions The sEHI inhibitor EC5026 and the STING inhibitor H-151 increased macrophage uptake and degradation of Aβ. EC5026 administration was safe in normal volunteers. EC5026 together with ω-3 PUFA supplementation are indicated for in a clinical trial in patients with mild cognitive impairment.
Controlled growth of citrate-stabilized gold nanoparticles using a semi-continuous seed-mediated route
Authors: Bilal Muhammad , Bandyopadhyay Sulalit 
Published: February 2025

Abstract
Gold nanoparticles (Au NPs) hold unique optical and electronic properties due to their surface plasmon resonance. The size, shape, and surface chemistry of Au NPs are key parameters for altering their optical properties to fine-tune Au NPs for specific applications. We report a size-controlled synthesis of citrate-stabilized Au NPs via the Turkevich method, followed by their growth through a semi-continuous seed-mediated approach. Au NPs of up to 53 nm were synthesized by controlled addition of chloroauric acid (HAuCl₄) to pre-prepared citrate stabilized Au NP seeds. Our approach leverages the residual sodium citrate from the Turkevich reaction to reduce HAuCl₄ during seed-mediated growth of Au NPs. Notably, we observed that a boiling temperature, as opposed to 70 °C, provided better control over nanoparticle size and morphology. Our method addresses several challenges associated with seed-mediated growth by yielding relatively spherical, monodisperse, citrate-stabilized, water-dispersible Au NPs in a single growth step, without sacrificing yield. Furthermore, a kinetics study revealed a continuous increase in particle diameter over the reaction period, hinting at the continuous and uniform growth of Au NPs.
Impact of glucose and propionic acid on even and odd chain fatty acid profiles of oleaginous yeasts
Authors: Bonzanini Veronica , Haddad Momeni Majid , Olofsson Kim , Olsson Lisbeth , Geijer Cecilia 
Published: February 2025

Abstract

Background
Odd chain fatty acids (OCFAs) are gaining attention for their valuable medical and nutritional applications. Microbial fermentation offers a sustainable and environmentally friendly alternative for OCFA production compared to traditional extraction or chemical synthesis methods. To achieve an economically feasible OCFA production process, it is essential to identify and develop microbial cell factories capable of producing OCFAs with high titers and yields.

Results
We selected 19 yeast species, including both oleaginous yeasts and representatives from the Ascomycota and Basidiomycota phyla, based on their known or potential ability to produce OCFAs. These species were screened under various growth conditions to evaluate their OCFA production potential. In glucose-based, nitrogen-limited media, the strains produced fatty acids to varying extents, with OCFAs comprising 0.5–5% of the total fatty acids. When using the OCFAs precursor propionic acid as the sole carbon source, only eight strains exhibited growth, with tolerance to propionic acid concentrations between 5 and 29 g/L. The strains also displayed varying efficiencies in converting propionic acid into fatty acids, yielding between 0.16 and 1.22 g/L of fatty acids, with OCFAs constituting 37–89% of total fatty acids. Among the top performing strains, Cutaneotrichosporon oleaginosus produced the highest OCFA titers and yields (0.94 g/L, 0.07 g/g), Yarrowia lipolytica demonstrated superior growth rates even at elevated propionic acid concentrations, and Rhodotorula toruloides achieved the highest proportion of OCFAs relative to total fatty acids (89%).

Conclusions
Our findings highlight the diverse capacities of the selected yeast species for OCFA production, identifying several promising strains for further optimization as microbial cell factories in sustainable OCFA production processes.

Graphical Abstract
Unveiling the impact: understanding long-term care workers’ experiences and their perceptions of resident challenges amidst the COVID-19 pandemic
Authors: Halperin Donna M. , Whitfield Krista , Bettinger Julie A. , Orhierhor Marian , Salter Katherine L. , Selig Bailey M. , Mack Anna , Condran Brian R. , Davis Alexa , Salyzyn Camryn , Parsons Janet A. , Kervin Melissa , Halperin Scott A. 
Published: February 2025

Abstract

Background
During the COVID-19 pandemic, long-term care (LTC) facilities in Canada were confronted with many rapidly changing public health safety guidelines. Based on the guidelines, LTC facilities had to implement a series of virus containment and mitigation measures, presenting significant challenges for both workers and residents. This research aims to provide insights that could be used to guide improvements in the experiences of LTC workers, and of residents, in future pandemic crises.

Methods
A qualitative multi-case study was used to explore the pandemic experiences of a demographically diverse group of LTC workers in Canada, focusing on how public health safety guidelines impacted them, and their perceptions of challenges faced by residents. Fourteen workers were engaged from facilities in Nova Scotia and British Columbia, which are regions distinct geographically and with differences in safety guidelines and implementation. Semi-structured interviews were conducted between April to October 2021. Using thematic analysis, we identified patterns within and across the interview transcripts.

Results
The thematic analysis provided an understanding of the experiences and perspectives of LTC workers. There were four key themes: (1) Tangling with Uncertainty, that describes the effects of ambiguous messaging and shifting COVID-19 safety guidance on workers; (2) Finding Voice, that highlights how workers coped with feelings of helplessness during the healthcare crisis; (3) Ripple Effects, of pandemic pressures on workers beyond resident care, that included strengthening of inter-colleague support as well as financial challenges, and; (4) Loss of Home, where workers perceived that protection of residents led to a loss of the residents’ home environment, personal freedom, and autonomy.

Conclusions
The findings suggest that LTC workers’ experiences during future pandemics may be improved by their inclusion in the development of public health safety guidelines, facilitating inter-colleague support systems, and ensuring worker financial stability. A balance should be found between preventing infection in LTC facilities and retaining the principles of holistic and resident-centered care for workers’ and residents’ mental health benefits.
Association between triglyceride glucose-body mass index and gestational diabetes mellitus: a prospective cohort study
Authors: Liang Xiaomin , Lai Kai , Li Xiaohong , Ren Di , Gui Shuiqing , Li Ying , Xing Zemao 
Published: February 2025

Abstract

Background
Limited research has examined the potential association between triglyceride glucose-body mass index (TyG-BMI) and gestational diabetes mellitus (GDM). The objective of this investigation was to analyze this linkage and evaluate TyG-BMI’s capability to predict GDM.

Methods
This research employed secondary data derived from a prospective cohort in South Korea, which included 588 pregnant women with singleton gestations, collected between November 2014 and July 2016. To investigate the connection between TyG-BMI and GDM, logistic regression and sensitivity analyses were performed. Furthermore, an analysis of receiver operating characteristics (ROC) was conducted to assess the prognostic accuracy of TyG-BMI in relation to GDM.

Results
The cohort exhibited a mean age of 32.07 ± 3.80 years, with 36 individuals (6.12%) manifesting GDM during the interval of 24 to 28 weeks of gestation. Following the adjustment for possible confounding variables, an increased TyG-BMI was associated with an elevated risk of GDM, as indicated by an odds ratio (OR) of 1.02 (95% CI: 1.01–1.04). Additionally, the area under the curve (AUC) for TyG-BMI’s predictive performance was recorded at 0.7979 (0.7143–0.8814), with an optimal threshold established at 211.03, which resulted in a specificity of 86.23% and a sensitivity of 66.67%.

Conclusions
In this South Korean cohort, increased TyG-BMI during early pregnancy (10–14 weeks) was significantly associated with the onset of GDM (during pregnancy 24–28 weeks). TyG-BMI could be integrated into clinical practice as a complementary preliminary screening tool for detecting women who are at increased risk of GDM.
Using student-staff partnership to teach early years medical students about quality improvement: an evaluation
Authors: Goldwater Breheny Cate , O’Connell Eve , Edwards Lisa-Jayne , Ryan Noreen 
Published: February 2025

Abstract

Background
Quality Improvement (QI) skills are recognized as a key outcome for medical students but are still rarely taught at the undergraduate level. Whilst there is evidence that preclinical students enjoy learning about QI, there is limited practical work exploring the best way to teach QI to this cohort. There are gaps in the literature around the evaluation of student-staff partnership approaches in the context of teaching QI, especially in line with the sustainable QI (susQI) framework. Our study evaluates a worksheet-based interactive session developed through student-staff partnership. The session was delivered to year one medical students in January 2024 at Imperial College School of Medicine (ICSM).

Methods
An inductive approach to thematic analysis was used to review worksheet content submitted by students during the teaching session. This method was employed to determine the session’s effectiveness and ascertain common themes of interest and application. 16 groups comprising 69 total students submitted worksheets for analysis.

Results
Three themes were identified: Making QI personal: learners chose to focus on improving their university experience over clinical projects, which affected how they identified stakeholders and designed their QI interventions; Misinterpretation of technical language: learners used their everyday understanding of QI terminology in the worksheets, evidencing some misconceptions; Understanding QI as a process: learners reported understanding and engaging with QI as a process and set of skills. Overall, students demonstrated both their understanding and application of QI methodology through engagement with the worksheet-based tasks.

Conclusions
Student-staff partnership is a feasible tool to develop and deliver an engaging and effective teaching session on QI, in line with susQI principles, for students with limited clinical experience. Further evaluation and use of partnership approaches in developing QI teaching and curricula are welcome and will likely deliver positive outcomes for learners.
Do we have a lost generation of junior doctors: Effects of the COVID-19 pandemic on junior doctors’ resilience status, medical knowledge and medical skills
Authors: Kolb Nicola Katharina , Keil Stephanie , Huber Johanna 
Published: February 2025

Abstract

Background
At the onset of the COVID-19 pandemic, strict measures suspended face-to-face teaching at German universities, posing significant challenges for medical education. Practical, patient-centered training couldn’t be fully replaced by online formats, leading to skill deficits and increased stress among students. To date, no study has examined the impact of COVID-19 on the resilience and the competence of medical graduates so far. This study aims to address this knowledge gap by investigating the pandemic impact on resilience, medical competence, communication skills, and research competence of medical graduates.

Methods
The study employed data from the “Bavarian Graduate Study of Medicine” (MediBAS), a cross-sectional evaluation survey conducted in cooperation with Bavarian universities and the Bavarian Institute for higher education research and planning. It targeted medical, dental, and veterinary graduates. The data were collected in two waves (2018/19 and 2022/23), with 1.114 human medicine graduates participating. The questionnaire assessed among others resilience, medical expertise, communication skills, and research competence. Statistical analysis involved descriptive statistics, correlation analysis, and Mann-Whitney-U tests due to non-normal data distribution.

Results
The study analyzed self-assessed resilience, medical expertise, communication, and research skills of medical graduates from two waves. The findings demonstrated through descriptive statistics a decline in all competencies except research skills, which exhibited an increase. Correlation analysis revealed significant relationships between variables. Mann-Whitney-U tests revealed no significant differences between the waves in resilience (p =.079, r =.06), medical expertise (p =.117, r =.05), communication skills (p =.053, r =.07), or research competence (p =.106, r =.05).

Conclusion
The study examined the impact of COVID-19 on medical graduates’ resilience, medical expertise, communication skills, and research competence. While there was a slight decline in resilience, medical expertise, and communication skills between the waves, there was an improvement in research competence. None of these changes were statistically significant. The findings suggest that the pandemic may have contributed to these trends by limiting practical experiences. No major negative impacts were found, suggesting no “lost generation” of doctors. The long-term effects of the changes remain uncertain due to the cross-sectional design and require further research.
An analysis of telehealth in a post-pandemic rural, Midwestern community: increased comfort and a preference for primary care
Authors: Salmon Chase , Bell Kameron , Reyes Eric , Ireland Ellen , Danek Robin 
Published: February 2025

Abstract

Background
The COVID-19 pandemic accelerated the adoption of telemedicine, integrating it into mainstream healthcare, especially in underserved and rural areas. This study examines the implementation and perceptions of telehealth in a rural Midwestern community in the post-pandemic period. Rural populations often face unique healthcare challenges. Telehealth has the potential to mitigate these issues by improving healthcare accessibility and patient satisfaction, thus being a vital topic for research.

Methods
A survey was created and conducted from September to October 2023 to evaluate Internet access, telehealth usage, and perceptions among residents of a rural Midwestern county. The county received fiberoptic Internet in November 2021, offering a valuable glimpse at the impact of advanced internet. The survey, distributed both online and in person, garnered 253 valid responses. Statistical analyses, including chi-square tests, were performed using IBM SPSS to explore the relationships between survey responses.

Results
Among the 253 participants, the majority were female (81.4%) with a median age of 50 years. Internet access varied, with 22% of paper survey respondents lacking home Internet compared to 1.3% of online respondents. Telehealth usage for participants increased from 5% pre-pandemic to 42.1% during the pandemic, with 21.8% continuing to use telehealth post-pandemic. Primary care visits were the most common telehealth appointments. Key concerns included a preference for in-person care and perceived lower quality of telehealth services. Despite these concerns, 59.7% of respondents were willing to use telehealth, rising to 67.5% if recommended by a healthcare provider. Comfort with telehealth was significantly linked to perceptions of Internet speed and stability.

Conclusions
While broadband and fiberoptic Internet are associated with better telehealth experiences, other types of Internet also facilitated telehealth usage in our study, indicating that factors beyond access influence patient comfort and willingness to use telehealth. Our findings also reveal significant interest in telehealth for primary care, suggesting rural patients prefer familiar providers for telehealth interactions. Despite increased telehealth interest and usage during the pandemic, a decline post-pandemic indicates potential barriers exist, such as limited availability of healthcare providers. Exploring and addressing these barriers remains crucial for sustaining telehealth adoption and improving healthcare access in rural communities.
Development and validation of prediction models for stroke and myocardial infarction in type 2 diabetes based on health insurance claims: does machine learning outperform traditional regression approaches?
Authors: Stephan Anna-Janina , Hanselmann Michael , Bajramovic Medina , Schosser Simon , Laxy Michael 
Published: February 2025

Abstract

Background
Digitalization and big health system data open new avenues for targeted prevention and treatment strategies. We aimed to develop and validate prediction models for stroke and myocardial infarction (MI) in patients with type 2 diabetes based on routinely collected high-dimensional health insurance claims and compared predictive performance of traditional regression with state-of-the-art machine learning including deep learning methods.

Methods
We used German health insurance claims from 2014 to 2019 with 287 potentially relevant literature-derived variables to predict 3-year risk of MI and stroke. Following a train-test split approach, we compared the performance of logistic methods with and without forward selection, LASSO-regularization, random forests (RF), gradient boosting (GB), multi-layer-perceptrons (MLP) and feature-tokenizer transformers (FTT). We assessed discrimination (Areas Under the Precision-Recall and Receiver-Operator Curves, AUPRC and AUROC) and calibration.

Results
Among n = 371,006 patients with type 2 diabetes (mean age: 67.2 years), 3.5% (n = 13,030) had MIs and 3.4% (n = 12,701) strokes. AUPRCs were 0.035 (MI) and 0.034 (stroke) for a null model, between 0.082 (MLP) and 0.092 (GB) for MI, and between 0.061 (MLP) and 0.073 (GB) for stoke. AUROCs were 0.5 for null models, between 0.70 (RF, MLP, FTT) and 0.71 (all other models) for MI, and between 0.66 (MLP) and 0.69 (GB) for stroke. All models were well calibrated.

Conclusions
Discrimination performance of claims-based models reached a ceiling at around 0.09 AUPRC and 0.7 AUROC. While for AUROC this performance was comparable to existing epidemiological models incorporating clinical information, comparison of other, potentially more relevant metrics, such as AUPRC, sensitivity and Positive Predictive Value was hampered by lack of reporting in the literature. The fact that machine learning including deep learning methods did not outperform more traditional approaches may suggest that feature richness and complexity were exploited before the choice of algorithm could become critical to maximize performance. Future research might focus on the impact of different feature derivation approaches on performance ceilings. In the absence of other more powerful screening alternatives, applying transparent regression-based models in routine claims, though certainly imperfect, remains a promising scalable low-cost approach for population-based cardiovascular risk prediction and stratification.

Graphical abstract