bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Case of Meibomian Gland Dysfunction in a Young Boy With Allgrove Syndrome
Authors: Sharda Shipra , Koli Omeshwer , Bharti Nisha 
Published: January 2025

Purpose:
This report presents a case of Triple-A syndrome (Allgrove syndrome), a rare autosomal recessive disorder, and emphasizes the importance of early diagnosis through ocular manifestations, particularly dry eye. The goal is to highlight that the dry eye demonstrated in Allgrove syndrome could be considered as part of dysfunctional main lacrimal gland and meibomian gland because of defective innervation.

Methods:
A 5-year-old male patient with a history of dry eyes since birth and dysphagia for 3 months was evaluated. Ophthalmic assessment included Schirmer test, tear meniscus measurement, and meibography. Laboratory tests assessed serum cortisol and electrolytes. The diagnosis was confirmed through clinical presentation, ophthalmic findings, and laboratory results. The patient was treated with topical lubrication, glucocorticoids for adrenal insufficiency, and surgical correction of achalasia.

Results:
The patient exhibited alacrima (Schirmer test: 2 mm right, 4 mm left), meibomian gland dysfunction (increased tear osmolarity, meibographic abnormalities, low tear break-up time), and low serum cortisol levels, confirming adrenal insufficiency. Management entailed warm compresses to melt thickened oils in the glands, daily lid hygiene to remove debris and bacteria, and topical lubricants (preservative-free artificial tears) to relieve dryness.

Conclusions:
Our patient displayed markedly reduced tear production as evidenced by Schirmer test, coupled with elevated tear osmolarity and shortened break-up time. This suggests that meibomian gland dysfunction in our patient is intricately linked to autonomic disturbance. Thus, the dry eye observed in Allgrove syndrome could be attributed to dysfunction in both main lacrimal gland and meibomian gland because of defective innervation.
Surgical Management of Gestational Gigantomastia: A Case Report Highlighting Therapeutic Intervention
Authors: Lemma Misha A. , Debodina Yisihak S. , Gebremedhin Martha F. , Aman Meki K. , Lucero-Prisno Don Eliseo III 
Published: January 2025

Summary:
Gigantomastia is an exceedingly rare condition characterized by extraordinary growth of breasts during pregnancy, and its underlying etiology remains elusive. Although surgical intervention is the primary treatment modality, there have been emerging prospects for utilizing adjunctive medical therapies, such as bromocriptine, to address this challenging condition. Herein, we report the case of a 26-year-old woman who experienced abrupt and asymmetric bilateral breast enlargement commencing in the second month of her pregnancy. Remarkably, this enlargement persisted for an extended duration of 3 years. Despite the absence of prior medical therapy involving bromocriptine or other interventions, the patient ultimately underwent a simple mastectomy coupled with nipple-areola complex reconstruction. Although bromocriptine treatment holds potential benefits, its availability may vary in different healthcare settings. Therefore, the consideration of surgical management as an alternative approach becomes crucial, particularly when bromocriptine is not accessible or proves ineffective. This approach ensures the appropriate management of gestational gigantomastia, with the choice of treatment tailored to the individual patient’s needs and resource availability.
Routine HIV Testing for People Who Inject Drugs Hospitalized With Infective Endocarditis in the United States: A Commentary
Authors: Dippel Kathryn , Tomlinson Starr , McCauley Paula , Jackson Kristopher 
Published: January 2025

Abstract
HIV screening is not routinely offered to acutely ill, hospitalized patients. For some patients a hospitalization represents a crucial opportunity to identify undiagnosed HIV infection and interrupt HIV transmission chains. Among people who inject drugs, a hospitalization for infective endocarditis may be one of the only touchpoints they have with a health care provider. Nurse-led HIV screening initiatives in the acute care and emergency medicine settings are being trialed across the United States. Nurses and nurse practitioners are uniquely poised to establish universal, comprehensive HIV testing protocols for people who inject drugs hospitalized for the management of infective endocarditis.
Tunable porosity in a hydrogel with extreme vibration damping properties
Authors: Day Graham J. , Zhang Qicheng , Remillat Chrystel D. L. , Comandini Gianni , Perriman Adam W. , Scarpa Fabrizio 
Published: January 2025

AbstractWe have developed hydrogel systems with tunable porosity through dialysis casting by varying alginate and poloxamer compositions from 0% to 10%. These gels feature diverse porosity topologies, yielding loss factors between 16% and 29% in the 50 Hz to 300 Hz frequency range. The dynamic modulus shows a remarkable increase of over an order of magnitude, reaching approximately 3 MPa compared to the static modulus. Vibration transmissibility tests and dynamic mechanical analysis reveal that the poroelastic and pneumatic-like effects from the tunable porous structures contribute significantly to this damping effect. Furthermore, these hydrogels are biosourced and biodegradable, providing a sustainable alternative to conventional fossil-based damping materials.
Efficient count-based models improve power and robustness for large-scale single-cell eQTL mapping
Authors: Zhang Zixuan Eleanor , Kim Artem , Suboc Noah , Mancuso Nicholas , Gazal Steven 
Published: January 2025

AbstractPopulation-scale single-cell transcriptomic technologies (scRNA-seq) enable characterizing variant effects on gene regulation at the cellular level (e.g., single-cell eQTLs; sc-eQTLs). However, existing sc-eQTL mapping approaches are either not designed for analyzing sparse counts in scRNA-seq data or can become intractable in extremely large datasets. Here, we propose jaxQTL, a flexible and efficient sc-eQTL mapping framework using highly efficient count-based models given pseudo-bulk data. Using extensive simulations, we demonstrated that jaxQTL with a negative binomial model outperformed other models in identifying sc-eQTLs, while maintaining a calibrated type I error. We applied jaxQTL across 14 cell types of OneK1K scRNA-seq data (N=982), and identified 11-16% more eGenes compared with existing approaches, primarily driven by jaxQTL ability to identify lowly expressed eGenes. We observed that fine-mapped sc-eQTLs were further from transcription starting site (TSS) than fine-mapped eQTLs identified in all cells (bulk-eQTLs;P=1×10-4) and more enriched in cell-type-specific enhancers (P=3×10-10), suggesting that sc-eQTLs improve our ability to identify distal eQTLs that are missed in bulk tissues. Overall, the genetic effect of fine-mapped sc-eQTLs were largely shared across cell types, with cell-type-specificity increasing with distance to TSS. Lastly, we observed that sc-eQTLs explain more SNP-heritability (h2) than bulk-eQTLs (9.90 ± 0.88% vs. 6.10 ± 0.76% when meta-analyzed across 16 blood and immune-related traits), improving but not closing the missing link between GWAS and eQTLs. As an example, we highlight that sc-eQTLs in T cells (unlike bulk-eQTLs) can successfully nominateIL6STas a candidate gene for rheumatoid arthritis. Overall, jaxQTL provides an efficient and powerful approach using count-based models to identify missing disease-associated eQTLs.
Keep the hospital clean: diagnostic performance of ten different molecular and culture-based methods to detectCandidozyma auris
Authors: Korsten Koos , Gerrits van den Ende Bert , Pique Rick D. , Hagen Ferry , van Dijk Karin 
Published: January 2025

AbstractRationaleCandidozyma auris(formerlyCandida auris) is a globally emerging potentially multi-drug resistant human pathogenic yeast. To detectC. auriswe aimed to compare different culture-, and molecular-based methods.MethodsRectal swabs routinely collected in clinical care were spiked with different concentrations ofC. auris. Co-infection/colonization was mimicked by spiking part of these samples with other pathogenicCandidaspecies. Spiked materials were cultured at 37°C or 42°C using CHROMagar Candida and CHROMagar CandidaPlus plates. In parallel, samples were incubated in a dulcitol salt enrichment broth. Additionally, we compared seven in-house and commercial molecular tests on the direct material and from the broth one day after inoculation.ResultsCulture-based methods showed sensitivities up to 100% within 48 hours of incubation, although sensitivity decreased as low as 44% at lower concentrations (≤50 CFU per inoculum), in the presence of an abundance of other species and at higher temperature (42°C). Incubation at 42°C made visual identification possible since other species with similar colony morphologies did not grow at this temperature. No added value of using the dulcitol salt enrichment broth was found. qPCR on direct materials was highly sensitive and specific (both up to 100%) but major differences between various molecular tests were observed.ConclusionWe showed that both culture-based and molecular methods are sensitive for diagnosingC. auris. The clinical setting (routine screening versus an outbreak), local prevalence and the load in those that carry or are infected byC. aurisare important factors to consider when determining which diagnostic tests should be employed.
Machine learning models for tuberculous pleural effusion diagnosis in Africa setting
Authors: Pefura-Yone Eric Walter , Balkissou Adamou Dodo , Endale-Mangamba Laurent-Mireille , Bane Jodie , Massongo Massongo , Ngah Komo Marie Elisabeth , Poka-Mayap Virginie , Kuaban Alain , Nsounfon Abdou Wouliyou , Amadou Djenabou , Ntyo’o’ Nkoumou Arnaud Laurel , Tendap-Ndam Paul Ledoux , Ntsama-Essomba Marie Josiane , Ekongolo Marie Christine , Mbobara-Yapele Christian , Ama-Moor Vicky Jocelyne 
Published: January 2025

ABSTRACTBackgroundTraditional diagnostic methods for Tuberculous pleural effusion (TPE) are often limited by their invasiveness, low sensitivity, and lack of accessibility. This study aims to develop and evaluate ML models for diagnosing TPE in African contexts, using readily available clinical and laboratory data.MethodsA cross-sectional study carried out in Yaoundé, Cameroon (2018-2023), included patients with non-purulent exudative pleural effusion. Pleural fluid was analysed for total protein, lactate dehydrogenase (LDH), glucose, C-reactive protein (CRP) and cytology. TPE diagnosis relied on detection of tuberculous bacilli or tuberculous granuloma . Five ML models namely Random Forest (RF), XGBOOST, Logistic Regression (LR), Support Vector Machine (SVM), and Multilayer Perceptron (MLP) were tested using binary classification (TPE vs non-TPE) in Python software. The performance of models was evaluated using the area under the receiver operating characteristic curve (AUC), F1 score, accuracy, sensitivity, and precision.ResultsOf the 302 participants included, 175 (57.9%) were male and their median age (interquartile range) was 46 (34-61) years. Overall, 58.9% of participants had TPE, 15.9% had pleural metastasis and 25.2% had other causes of pleural effusion. Patients with TPE were younger, more often male and had a higher prevalence of HIV-infection. They also had higher pleural protein and CRP levels. The RF model showed the best performance with an AUC of 0.846 and an F1 score of 0.811 in the testing sample. Sensitivity was higher for MLP (0,944) and precision was higher for LR (0.806). Key predictors identified by the RF model were pleural CRP levels, age, pleural LDH levels, body mass index, and pleural protein levels.ConclusionThe RF model had the best performance. MLP and LR had the best sensitivity and precision respectively. The models can be used to improve diagnosis of TPE in Africa settings.KEY MESSAGESWhat is already known on this topicTuberculous pleural effusion (TPE) diagnosis is invasive and lacks sensitivity in resource-limited African settings, with limited ML models available.What this study addsThis study developed and evaluated five ML models for TPE diagnosis using clinical and pleural fluid data from Africa setting. The Random Forest model outperformed others in diagnosing TPE, using pleural CRP levels, age, pleural LDH levels, body mass index, and pleural protein levels as key predictors.How this study might affect research, practice, or policyMachine learning models can enhance TPE diagnosis in Africa using accessible and reliable biomarkers.
Psychosocial Risk Factors for Injury in Performing Artists: A Scoping Review of Screening and Predictive Tools
Authors: Cahalan Róisín , Walsh Caoimhe Barry , Ni Bhriain Orfhlaith , de Gallaí Breandán , Fahey de Brún Hannah , Pye Michele , Schmieg Rose 
Published: January 2025

ABSTRACTThe performing arts are a broad church and include artists from various ﬁelds including dance, music and circus. Despite obvious differences in disciplines, much is shared in terms of an elevated risk of injury, and a common identity as a performer and artist. Injury screening protocols are imperative to mitigate injury risk. However, current programmes focus overwhelmingly on physical risks for injury and fail to appropriately consider psychosocial drivers injury affecting this cohort. This scoping review will synthesize the information on tools used to evaluate psychosocial factors related to injury in non-recreational performing artists, to identify robust instruments for use in future screening protocols. The scoping review will conform to Joanna Briggs Institute (JBI) Evidence Synthesis guidelines. Multiple databases relating to health, medicine, kinesiology, sport and dance will be searched for relevant articles. Two independent reviewers will conduct title and abstract screening followed by full-text screening. Data charting will be completing using a modiﬁed standardised form. Descriptive results will be reported using tabular and graphical media. The published scoping review will be disseminated to relevant stakeholders in the performing arts as well as to clinicians working with these artists. The resulting outputs will be in the form of both peer-reviewed and non-peer reviewed publications (e.g. blog posts, academic publications and conference presentations to reach key stakeholders such as performing artists and their support teams). An infographic of key ﬁndings will be developed and shared on social media platforms as appropriate. Ethical approval was not required for this study.What is already known on this topic– Although injury in the performing arts is extremely prevalent with implications for the biopsychological and ﬁnancial wellbeing of the artists, there are few screening instruments which consider drivers of injury apart from physical factors.What this study adds– this study will identify psychosocial screening and predictive tools used to identify injury in performing artists, and the psychometric properties and utility of each.How this study might affect research, practice or policy– the outputs of this scoping review will raise stakeholder awareness of the psychosocial drivers of injury in performing artists. It will also identify a range of robust instruments that will aid in the holistic identiﬁcation of those artists at risk of injury.
Summarizing Clinical Notes using LLMs for ICU Bounceback and Length-of-Stay Prediction
Authors: Choudhuri Akash , Polgreen Philip , Segre Alberto , Adhikari Bijaya 
Published: January 2025

AbstractRecent advances in the Large Language Models (LLMs) provide a promising avenue for retrieving relevant information from clinical notes for accurate risk estimation of adverse patient outcomes. In this empirical study, we quantify the gain in predictive performance obtained by prompting LLMs to study the clinical notes and summarize potential risks for downstream tasks. Specifically, we prompt LLMs to generate a summary of progress notes and state potential complications that may arise. We then learn representations of the generated notes in sequential order and estimate the risks of patients in the ICU getting readmitted in ICU after discharge (ICU bouncebacks) and predict the overall length of stay in the ICU. Our analysis in the real-world MIMIC III dataset shows performance gains of 7.17% in terms of AUC-ROC and 14.16% in terms of AUPRC for the ICU bounceback task and 2.84% in terms of F-1 score and 7.12% in terms of AUPRC for the ICU LOS Prediction task. This demonstrates that the LLM-infused models outperform the approaches that only directly rely on clinical notes and other EHR data.
Bat-Human Interactions and associated factors among communities in Bundibugyo District, Uganda: A Cross-sectional Study
Authors: Baguma James Natweta , Namusisi Shamilah , Ninsiima Lesley Rose , Musiitwa Rogers , Tamale Bridget Nagawa , Amperiize Mathius , Bulafu Douglas , Muleme James , Musoke David , Kankya Clovice , Kato Charles Drago 
Published: January 2025

AbstractBackgroundMore than 70% of new, emerging, and reemerging infectious diseases are from animal origin. Human interaction with bats has been associated as a driver for various fetal zoonoses, including numerous viral diseases of bat-origin. A lot of serological evidence has been gathered around human-bat interaction, yet very little is known regarding the underlying risk factors at community level. This study was aimed at understanding the human-bat interactions and associated factors among communities in Bundibugyo District in Uganda.MethodsA cross-sectional study was conducted using both qualitative and quantitative data collection methods in Harugale, Burondo and Ntandi Subcounties in Bundibugyo District between November 2022 and March 2023. A total of 344 participants were interviewed using a semi structured questionnaire installed on the Kobo Collect Software. Key Informant interviews were also conducted among purposively selected individuals who have vast knowledge on human-bat interaction. Proportional piling and focus group discussions were conducted among groups of men, women, and youths to get their insights into human-bat interaction. Quantitative data was cleaned using Microsoft Excel and exported to Stata 15 for analysis. Qualitative data was analyzed using Atlas. ti (version 8.0). Our study was limited by response and recall bias during data collection.ResultsThe study revealed that 54.1% of the respondents were males, 42.1% were aged above 40 years. Households headed by males (APR=1.31, 95% CI:1.07-1.62, Batwa communities (APR=3.03, 95% CI:1.87-3.94), residing in urban areas (APR=1.72, 95 CI%:1.35-2.20), trading of food and animal products (APR=0.6, 95 CI%:0.36-0.99), no occupation (APR=0.27, 95 CI%:0.12-0.57) and residing in incomplete houses (APR=1.57, 95 CI%:1.25-1.98) were significantly associated with exposure of humans to bats. There was high exposure of humans to bats in Ntandi compared to Burondo and Harugale. Women groups highlighted use of bat repellants and killing of bats using sticks as the measures to reduce human bat interaction during the Focus Group Discussions.ConclusionGenerally, there is high exposure to bats among human communities in Bundibugyo district which increases the risk of zoonotic disease transmission at human-bat interface. Findings from this study aim to enable the one health interventions to reduce bat-human interaction potential risks in both urban and rural areas and support design of feasible interventions for Bundibugyo district and Uganda at large.
Causes And MEchanisms foR non-atopic Asthma in Children (CAMERA) Study: rationale and protocol
Authors: Njoroge Mary , Pinheiro Gabriela Pimentel , Santana Cinthia Vila Nova , Ali Hajar , Hobbs Stephanie , Mena-Bucheli Santiago , Romero-Sandoval Natalia , Robertson Steven , Rutter Charlotte E , Davoren Donna , Brooks Collin , Douwes Jeroen , Cooper Philip J , Mpairwe Harriet , Figueiredo Camila A , Cruz Alvaro A , Barreto Mauricio L , Pearce Neil , Pembrey Lucy ,   the CAMERA study group
Published: January 2025

AbstractThe Causes And MEchanisms foR non-atopic Asthma in children (CAMERA) study was designed to investigate risk factors and mechanisms of non-atopic asthma in children and young adults in Brazil, Ecuador, Uganda, and New Zealand. Initial epidemiological analyses using existing datasets identified and compared risk factors for both atopic and non-atopic asthma. The focus of this paper is the protocol for sample collection and analysis of clinical data on possible non-atopic mechanisms.In each of the four centres, the CAMERA study will enroll 160 participants aged 10 – 28 years, equally distributed among atopic asthmatics (AA), non-atopic asthmatics (NAA), atopic non-asthmatics and non-atopic non-asthmatics. Participants will be new recruits or returning World ASthma Phenotypes (WASP) study participants.Phase I consists of skin prick tests to define atopy, a general CAMERA questionnaire that covers respiratory and general health to identify asthma cases, followed by an asthma control questionnaire for asthmatics only. Phase II consists of a stress questionnaire and the following clinical assessments: lung function, nasal cytology, blood sampling,in vitrowhole blood stimulation to assess IFN-γ production, hair cortisol concentration, dry air and capsaicin challenges, plus in a subset, cold air challenges. Analyses will compare inflammatory, physiological and clinical parameters across the four groups overall and by country.Here, we present the protocol for the CAMERA study, to provide relevant methodological details for CAMERA publications and to allow other centres globally to conduct similar analyses. The findings of this mechanistic multi-centre study will inform new and phenotype-specific prevention and treatment approaches.
Trends and Disparities in Newer GLP1 Receptor Agonist Initiation among Real-World Adult Patients Eligible for Obesity Treatment
Authors: Radwan Rotana M. , Lee Yao An , Kotecha Pareeta , Wright Davene R. , Hernandez Inmaculada , Ramon Ronald , Donahoo William T. , Chen Yong , Allen John M. , Bian Jiang , Guo Jingchuan 
Published: January 2025

AbstractAimsTo characterize trends in the initiation of newer anti-obesity medications (AOMs) and determine factors associated with their use among obese/overweight populations.Materials and methodsThis retrospective study utilized electronic health record data from OneFlorida+ (2015–2024). Adults eligible for AOMs were included, defined as having a BMI ≥30 kg/m² or a BMI of 27–29.9 kg/m² with at least one obesity-related comorbidity. The primary outcome was the initiation of newer AOMs, specifically glucagon-like peptide-1 receptor agonists (GLP-1 RAs) including liraglutide, semaglutide, and tirzepatide. Trends across years were examined, and a multivariable logistic regression identified sociodemographic, clinical, and healthcare utilization factors associated with AOM initiation.ResultsOf 319,949 adults, 1.8% initiated newer AOMs. Semaglutide accounted for 77.9% of initiations, tirzepatide 19.7%, and liraglutide 17.8%. Initiation trends showed liraglutide uptake peaked at 5% in 2018 but declined afterward, while semaglutide and tirzepatide uptake increased exponentially since 2022. Odds of initiation were lower for Black (aOR (95% CI): 0.87 [0.80– 0.94]) and Hispanic (0.84 [0.78–0.91]) groups vs. Whites, and for Medicaid (0.69 [0.63–0.76]) and uninsured (0.81 [0.74–0.87]) patients vs. privately insured. Higher odds were associated with being female, middle-aged, having more outpatient visits, and visiting endocrinologists.ConclusionsThe initiation of newer AOMs among overweight and obese populations remains low, but uptake has increased exponentially since 2022. Our findings reveal significant disparities in obesity care, highlighting the importance of addressing inequities in AOM access to improve obesity outcomes.