bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-Wide Identification of Stable RNA Secondary Structures Across Multiple Organisms Using Chemical Probing Data: Insights into Short Structural Motifs and RNA-Targeting Therapeutics
Authors: Wang Jingxin 
Published: October 2024

ABSTRACTSmall molecules targeting specific RNA binding sites, including stable and transient RNA structures, are emerging as effective pharmacological approaches for modulating gene expression. However, little is understood about how stable RNA secondary structures are shared across organisms, an important factor in controlling drug selectivity. In this study, I provide an analytical pipeline named RNA Secondary Structure Finder (R2S-Finder) to discover short, stable RNA structural motifs for humans,Escherichia coli(E. coli), SARS-CoV-2, and Zika virus by leveraging existing in vivo and in vitro genome-wide chemical RNA-probing datasets. I found several common features across organisms. For example, apart from the well-documented tetraloops, AU-rich tetraloops are widely present in different organisms. I also found that the 5’ untranslated region (UTR) contains a higher proportion of stable structures than the coding sequences in humans, SARS-CoV-2, and Zika virus. In general, stable structures predicted from in vitro (protein-free) and in vivo datasets are consistent in humans,E. coli, and SARS-CoV-2, indicating that most stable structure formation were driven by RNA folding alone, while a larger variation was found between in vitro and in vivo data with certain RNA types, such as human long intergenic non-coding RNAs (lincRNAs). Finally, I predicted stable three- and four-way RNA junctions that exist both in vivo and in vitro conditions, which can potentially serve as drug targets. All results of stable sequences, stem-loops, internal loops, bulges, and three- and four-way junctions have been collated in the R2S-Finder database (https://github.com/JingxinWangLab/R2S-Finder), which is coded in hyperlinked HTML pages and tabulated in CSV files.
Navigating the Privacy-Accuracy Tradeoff: Federated Survival Analysis with Binning and Differential Privacy
Authors: Gouthamchand Varsha , van Soest Johan , Arcuri Giovanni , Dekker Andre , Damiani Andrea , Wee Leonard 
Published: October 2024

AbstractFederated learning (FL) offers a decentralized approach to model training, allowing for data-driven insights while safeguarding patient privacy across institutions. In the Personal Health Train (PHT) paradigm, it is local model gradients from each institution, aggregated over a sample size of its own patients that are transmitted to a central server to be globally merged, rather than transmitting the patient data itself. However, certain attacks on a PHT infrastructure may risk compromising sensitive data. This study delves into the privacy-accuracy tradeoff in federated Cox Proportional Hazards (CoxPH) models for survival analysis by assessing two Privacy-Enhancing Techniques (PETs) added on top of the PHT approach. In one, we implemented a Discretized Cox model by grouping event times into finite bins to hide individual time-to-event data points. In another, we explored Local Differential Privacy by introducing noise to local model gradients. Our results demonstrate that both strategies can effectively mitigate privacy risks without significantly compromising numerical accuracy, reflected in only small variations of hazard ratios and cumulative baseline hazard curves. Our findings highlight the potential for enhancing privacy-preserving survival analysis within a PHT implementation and suggest practical solutions for multi-institutional research while mitigating the risk of re-identification attacks.
Prevalence and patient characteristics associated with cardiovascular disease risk factor screening in UK primary care for people with severe mental illness: An electronic healthcare record study
Authors: N Launders , CA Jackson , JF Hayes , A John , R Stewart , MH Iveson , E Bramon , B Guthrie , SW Mercer , DPJ Osborn 
Published: October 2024

AbstractBackgroundPeople with severe mental illness (SMI) are at increased risk of cardiovascular disease (CVD), and initiatives for CVD risk factor screening in the UK have not reduced disparities.ObjectivesTo describe the annual screening prevalence for CVD risk factors in people with SMI from April 2000 to March 2018, and to identify factors associated with receiving no screening and regular screening.MethodsWe identified adults with a diagnosis of SMI (schizophrenia, bipolar disorder or ‘other psychosis’) from UK primary care records in Clinical Practice Research Datalink (CPRD). We calculated the annual prevalence of screening for blood pressure, cholesterol, glucose, body mass index, alcohol consumption and smoking status, using multinomial logistic regression to identify factors associated with receiving no screening and complete screening.ResultsOf 216,136 patients with SMI, 55% received screening for all six CVD risk factors at least once follow-up and 35% received all six within a one-month period. Changes in screening prevalence coincided with changes in incentivisation of screening. In 2014-2018, men, people with a diagnosis of ‘other psychoses’, or with missing ethnicity were more likely to have received no screening.ConclusionsThe low proportion of people with SMI receiving regular comprehensive CVD risk factor screening is concerning. Screening needs to be embedded as part of broad physical health checks to ensure the health needs of people with SMI are being met. If we are to improve cardiovascular health, interventions are needed where risk of receiving no screening or not receiving regular screening is highest.What is already known on this topicThe prevalence of CVD risk factor screening in primary care increased with the introduction of an incentivisation scheme and when incentivisation for screening for specific CVD risk factors is removed the screening decreases.What does this study add?Few patients received regular screening for all six CVD risk factors considered, and both screening prevalence and risk of receiving no screening varied depending on patient characteristics.Only 35% of patients ever received screening for all six CVD risk factors considered in a one-month period, suggesting that screening is not often being done as part of a physical health check.How this study might affect research, practice or policyClinicians should be aware that some sub-groups of patients with SMI are less likely to receive screening, and the importance of providing screening as part of a regular, comprehensive physical health check.
Nurses’ and doctors’ perspectives on emergency and critical care at primary health care facilities in Kilimanjaro, Tanzania
Authors: Isack Manji N , Mkoka Dickson A. , Mwilike Beatrice E. 
Published: October 2024

AbstractBackgroundIn Tanzania, primary health care faces the worst challenges in delivering emergency and critical care with purposeful improvement strategies alarming from multiple stakeholders. This study described nurses’ and doctors’ perspectives on emergency and critical care at primary healthcare facilities in Kilimanjaro, Tanzania.MethodsA descriptive qualitative design was used. Twelve participants; 6 nurses and 6 doctors from three primary healthcare facilities in Moshi Municipal were purposively recruited for the audio-recorded, face-to-face individualized, in-depth interviews. Themes were generated through thematic analysis of the data.ResultsThe analysis resulted in five (5) major themes: unconducive environment, disparity and disconnection of the continuum of care along the health care system, routines for emergency and critical care, raised needs for emergency and critical care, and strategies for improvement.ConclusionNurses and doctors in primary healthcare severely face many challenges that limit their ability to manage critical illnesses adequately associated with the absence of favorable infrastructures, guidelines, trained personnel, on-job training, and expert support from higher-level hospitals, and the shortage of staff, lack of essential drugs and equipment, and lack of staff and managerial prioritization thereby tilting the balance of survival in these settings to the worst side.
BREATH TEST TO DETECT WOMEN AT LOW RISK FOR BREAST CANCER: POTENTIAL CLINICAL AND ECONOMIC BENEFITS
Authors: Phillips Michael , Bevers Therese B , Larsen Linda Hovanessian , Pappas Nadine , Pathak Sonali 
Published: October 2024

ABSTRACTBackgroundA breath test for volatile organic compounds has identified biomarkers associated with breast cancer. We evaluated the potential clinical and economic benefits of a breath test to detect women at low risk for breast cancer by comparing its negative predictive value (NPV) to the NPV of screening mammography.MethodsSensitivity and specificity values for screening mammography were obtained from the Food & Drug Administration Mammography Quality Standards Act; Amendments to Part 900 Regulations Docket No. FDA-2013-N-0134. The high values were sensitivity = 79.0%, specificity = 88.9% and the low values were sensitivity = 66.0%, specificity = 88.9%. In two previous studies of 771 women undergoing mammography, breath testing identified breast cancer with sensitivity=84% and specificity = 68.6% in 178 asymptomatic women, and sensitivity=82% and specificity = 77% in 593 who were symptomatic. These values were projected to a hypothetical screening population of 100,000 asymptomatic women with average breast cancer prevalence of 450/100,000, in order to estimate the NPV and PPV (positive predictive value) for breath testing and screening mammography respectively.ResultsBreath test in asymptomatic women: NPV = 99.895% and PPV = 1.19%; in symptomatic women: NPV = 99.895% and PPV = 1.59%. For screening mammography, NPV = 99.83% and PPV = 2.82% (low values), increasing to NPV= 99.89% and PPV = 3.12% (high values). A negative breath test identified 68.3% of the screening population as having low risk of breast cancer, with NPV similar to mammography. Based on Medicare reimbursement rates, elimination of mammography in women with a negative breath test could reduce the annual cost of breast cancer screening by 38.9%ConclusionsIn a hypothetical screening population, a negative breath test ruled out breast cancer with the same accuracy as a negative mammogram. A screening breath test could potentially eliminate the need for two thirds of all mammograms and reduce the costs of screening without increasing the risk of false-negative findings. If applied in clinical practice, this approach could potentially reduce the costs and burdens of breast cancer screening services, and benefit women by lessening the discomfort, anxiety, radiation exposure, and costs associated with mammography.
Echo-Vision-FM: A Pre-training and Fine-tuning Framework for Echocardiogram Video Vision Foundation Model
Authors: Zhang Ziyang , Wu Qinxin , Ding Sirui , Wang Xiaolong , Ye Jiancheng 
Published: October 2024

ABSTRACTBackgroundEchocardiograms provide essential insights into cardiac health, yet their complex, multidimensional data poses significant challenges for analysis and interpretation. Existing deep learning models for echocardiogram analysis often rely heavily on supervised training, which limits their generalizability and robustness across different datasets and clinical environments.ObjectiveTo develop and evaluateEcho-Vision-FM(Echocardiogram videoVision FoundationModel), a self-supervised video learning framework designed to pre-train a video encoder on large-scale, unlabeled echocardiogram data. Echo-Vision-FM aims to produce robust and transferable video representations, improving downstream performance across diverse echocardiogram datasets and clinical conditions.MethodsThe proposed framework employs advanced self-supervised video learning through a masked auto-encoding technique, which compresses segments of video data and reconstructs the full video by masking non-overlapping video patches. An asymmetric encoder-decoder architecture underpins this approach. To further enhance the learned representations, we introduceSTF-Net, aSpatial-TemporalFusionNet, which integrates spatial and temporal correlations from the video representations. We pre-trained Echo-Vision-FM using the MIMIC-IV-ECHO dataset and fine-tuned it across multiple downstream datasets for specific clinical tasks, including morphological value estimation and the diagnosis of heart function and diseases.ResultsEcho-Vision-FM achieved superior performance in classifying left ventricular ejection fraction (LVEF), with an accuracy of 0.905, an F1 score of 0.941, and an AUC of 0.931. In regression tasks, Echo-Vision-FM outperformed state-of-the-art models, achieving a mean absolute error (MAE) of 3.87% and anr2of 0.825 forLVEFprediction. The model also demonstrated significant improvements in estimating end-systolic and end-diastolic volumes, withr2values of 0.782 and 0.742, respectively. Incorporating STF-Net further enhanced performance across all tasks.ConclusionOur results demonstrate that large-scale self-supervised video learning on echocardiogram data enables the extraction of transferable and clinically relevant features, surpassing existing methods. The Echo-Vision-FM framework, particularly with the inclusion of STF-Net, significantly improves the extraction of spatiotemporal features, resulting in enhanced predictive accuracy for a range of cardiac parameters. Echo-Vision-FM offers a scalable and effective solution for echocardiogram analysis, with promising applications in clinical diagnostics and research.
Diffuse optical tomography system for acute traumatic brain injury in the intensive care unit: a prospective study on healthy volunteers
Authors: Forcione Mario , Chiarelli Antonio Maria , Perpetuini David , Perkins Guy A. , Stevens Andrew R. , Davies David J. , Belli Antonio 
Published: October 2024

AbstractSignificanceCurrent systems for diffuse optical tomography (DOT) are unsuitable for clinical applications on acute traumatic brain injury (TBI) patients while in the intensive care unit (ICU).AimTo develop and test a method for DOT recordings suitable for TBI patients in the ICU. This method is based on measurements and co-registration using 3-D optical scans, and the acquisition of optical data using a custom-made helmet which would enable a multimodal (invasive and non-invasive) neuromonitoring.ApproachProbe displacements compared to electromagnetic digitization co-registrations were assessed. The capacity to isolate and monitor, using functional near-infrared spectroscopy (fNIRS), the optical signal in the intracranial (ICT) and extracranial tissues (ECT) was tested on 23 healthy volunteers. Participants were scanned with a frequency-domain NIRS device (690 and 830 nm) during 5 Valsalva maneuvers (VM) in a simulated ICU environment.ResultsThe results showed an average error in probe displacement of 5.5 mm, a sufficient capacity to isolate oxyhemoglobin O2Hb (p=6.4·10-6) and total hemoglobin HbT (p=2.8·10-5) in the ICT from the ECT, and to follow the changes of hemoglobin in the ICT during the VM (O2Hb, p=9.2·10-4; HbT, p=1.0·10-3).ConclusionsThe developed approach appears to be suitable for use on TBI patients in the ICU.
Evaluating the performance and potential bias of predictive models for the detection of transthyretin cardiac amyloidosis
Authors: Hourmozdi Jonathan , Easton Nicholas , Benigeri Simon , Thomas James D. , Narang Akhil , Ouyang David , Duffy Grant , Okwuosa Ike , Kline Adrienne , Kho Abel N. , Luo Yuan , Shah Sanjiv J. , Ahmad Faraz S. 
Published: October 2024

AbstractBackgroundDelays in the diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM) contribute to the significant morbidity of the condition, especially in the era of novel disease-modifying therapies. Screening for ATTR-CM with AI and other algorithms may improve timely diagnosis, but these algorithms have not been directly compared with each other.MethodsWe identified patients treated at an integrated health system from 2010-2022 with biopsy or PYP scan-confirmed ATTR-CM and age -and sex-matched them to controls with HF in a 19:1 ratio to target 5% prevalence. We compared the performance of three publicly available algorithms: a random forest model of claims data, the regression-based Mayo ATTR-CM Score, and a deep-learning echo model (EchoNet-LVH). Bias was measured in the best performing models using standard fairness metrics.ResultsWe identified 198 confirmed cases of ATTR-CM from 3924 patients in the analytic cohort that had the necessary structured and imaging data for all three models. In this cohort, 78.9% of the cohort self-identified as White, 8.7% Black, 4.0% Hispanic and 8.4% Other. ATTR-CM prevalence was highest in individuals who identified as Black. The claims-based model performed poorly with an AUC of 0.48. EchoNet-LVH had higher AUC (0.88 vs 0.78, DeLong Test p < 0.0001) and average precision (0.61 vs 0.15) compared to the Mayo score. Bias auditing of the top two performing models demonstrated that both models satisfied our fairness criteria forequal opportunity(1.05 for EchoNet-LVH and 0.91 for ATTR-CM Score) among patients who identified as Black.ConclusionsIn external validation using a large, diverse cohort of patients with heart failure, a deep-learning echo-based model to detect ATTR-CM demonstrated best overall performance compared to two other publicly available models. The results of a bias audit suggest that the regression- and echo-based models are unlikely to exacerbate existing health disparities through inequitable distribution of error with respect to self-identified Black race.
Microscopic Phage Adsorption Assay: High-throughput quantification of virus particle attachment to host bacterial cells
Authors: Antani Jyot D. , Ward Timothy , Emonet Thierry , Turner Paul E. 
Published: October 2024

AbstractPhages, viruses of bacteria, play a pivotal role in Earth’s biosphere and hold great promise as therapeutic and diagnostic tools in combating infectious diseases. Attachment of phages to bacterial cells is a crucial initial step of the interaction. The classic assay to quantify the dynamics of phage attachment involves co-culturing and enumeration of bacteria and phages, which is laborious, lengthy, hence low-throughput, and only provides ensemble estimates of model-based adsorption rate constants. Here, we utilized fluorescence microscopy and particle tracking to obtain trajectories of individual virus particles interacting with cells. The trajectory durations quantified the heterogeneity in dwell time, the time that each phage spends interacting with a bacterium. The average dwell time strongly correlated with the classically-measured adsorption rate constant. We successfully applied this technique to quantify host-attachment dynamics of several phages including those targeting key bacterial pathogens. This approach should benefit the field of phage biology by providing highly quantitative, model-free readouts at single-virus resolution, helping to uncover single-virus phenomena missed by traditional measurements. Owing to significant reduction in manual effort, our method should enable rapid, high-throughput screening of a phage library against a target bacterial strain for applications such as therapy or diagnosis.
TRIM37 employs peptide motif recognition and substrate-dependent oligomerization to prevent ectopic spindle pole assembly
Authors: Bellaart Andrew , Brambila Amanda , Xu Jiawei , Diaz Francisco Mendez , Deep Amar , Anzola John , Meitinger Franz , Ohta Midori , Corbett Kevin D. , Desai Arshad , Oegema Karen 
Published: October 2024

ABSTRACTTightly controlled duplication of centrosomes, the major microtubule-organizing centers of animal cells, ensures bipolarity of the mitotic spindle and accurate chromosome segregation. The RBCC (RING-B-box-coiled coil) ubiquitin ligase TRIM37, whose loss is associated with elevated chromosome missegregation and the tumor-prone developmental human disorder Mulibrey nanism, prevents the formation of ectopic spindle poles that assemble around structured condensates containing the centrosomal protein centrobin. Here, we show that TRIM37’s TRAF domain, unique in the extended TRIM family, engages peptide motifs in centrobin to suppress condensate formation. TRIM proteins form anti-parallel coiled-coil dimers with RING–B-box domains on each end. Oligomerization due to RING–RING interactions and conformational regulation by B-box-2–B-box-2 interfaces are critical for TRIM37 to suppress centrobin condensate formation. These results indicate that, analogous to anti-viral TRIM ligases, TRIM37 activation is linked to the detection of oligomerized substrates. Thus, TRIM37 couples peptide motif recognition and substrate-dependent oligomerization to effect ubiquitination-mediated clearance of ectopic centrosomal protein assemblies.
Public Perceptions and Engagement in mHealth: A European Survey on Attitudes towards Health Apps Use and Data Sharing
Authors: Causio Francesco Andrea , Beccia Flavia , Tona Diego Maria , Verduchi Alessandra , Cristiano Antonio , Calabrò Giovanna Elisa , Pastorino Roberta , van El Carla , Boccia Stefania 
Published: October 2024

AbstractThis study explores public perceptions and engagement in mobile health (mHealth) across eight European countries: Italy, the Netherlands, France, Germany, Spain, Poland, Romania, and Hungary. The focus is on the public’s attitudes toward health app usage and data sharing examined through a cross-sectional survey involving 6,581 participants. The survey revealed that 21.87% of respondents currently use health apps, with 42.71% expressing interest in future use. Regarding data sharing, 52.82% are willing to share health data with healthcare providers, and 25.48% would share data with public and private research institutions. However, concerns about data privacy and security are prevalent, with 63.68% fearing hacking of their data and 72.34% afraid that their data might be used for inappropriate purposes. However, prevalent concerns about data privacy and security emerged, with 72.34% expressing worry about data misuse and 63.68% fearing data hacking.The study highlights significant generational and geographical differences in mHealth engagement, with older generations displaying a lower adoption level of health apps. Education level emerged as a crucial factor influencing attitudes toward mHealth, with those having tertiary education more likely to use health apps and demand transparency. These findings underscore the need for targeted strategies to enhance digital literacy, ensure data privacy, and promote equitable access to mHealth technologies across Europe.