bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved correction ofB0inhomogeneity-induced distortions in diffusion-weighted images of the prostate
Authors: Conlin Christopher C , Bagrodia Aditya , Barrett Tristan , Baxter Madison T , Do Deondre D , Hahn Michael E , Harisinghani Mukesh G , Javier-DesLoges Juan F , Kallis Karoline , Kane Christopher J , Kuperman Joshua M , Liss Michael A , Margolis Daniel JA , Murphy Paul M , Ohliger Michael , Ollison Courtney , Rakow-Penner Rebecca , Domingo Mariluz Rojo , Song Yuze , Wehrli Natasha , Woolen Sean , Seibert Tyler M , Dale Anders M 
Published: March 2024

AbstractBackgroundConventional distortion correction techniques include the Reversed Polarity Gradient (RPG) method and FSL-topup, which estimate tissue displacement from EPI images of opposite phase-encoding polarity, and scale image intensity by the Jacobian of the estimated displacement.PurposeTo demonstrate that Jacobian intensity correction (JIC) can cause misleading improvement of EPI image distortion. We propose an alternative distortion correction approach (multi-bRPG; mRPG) that eliminates the JIC factor by normalizing opposite-polarity EPI images across multipleb-values.Study typeRetrospective.Population163 prostate cancer patients without metallic implants.Fieldstrength/Sequence3T diffusion-weighted sequence with EPI readout, using multipleb-values.AssessmentMaps of spatial shift (distortion) were estimated from opposite-polarity EPI volumes using RPG, topup, and mRPG. The estimated spatial shifts from each method were then applied to correct theb=0s/mm2images (both with and without JIC) and ADC maps (for which JIC is meaningless).Distortion was quantified by the Pearson correlation between opposite-polarity volumes. The distribution of correlation coefficients across all patients was examined forb=0s/mm2images and ADC maps, before and after distortion correction by each method. The mean, median, and 10thpercentile were reported for each distribution.Statistical testsWilcoxon signed-rank tests (α=0.05) were used to assess whether correlation increased significantly after distortion correction by each method, and whether mRPG yielded a larger increase versus RPG or topup.ResultsMedian improvement in the correlation betweenb=0s/mm2volumes was significantly smaller without JIC (p<0.001): 0.04 vs 0.16 (RPG), 0.06 vs 0.18 (topup). mRPG yielded significantly larger improvements compared to RPG or topup (p<0.001).b=0s/mm2: 0.09 vs 0.04 (RPG) and 0.06 (topup). ADC: 0.09 vs 0.02 (RPG) and 0.03 (topup).Data conclusionDisparity in the distortion-correction performance of conventional methods with and without JIC suggests underestimation of tissue displacement. mRPG shows improved correction of distortion artifacts compared to conventional methods.
Trends of heart failure associated mortality in premenopausal women in the United states 1999-2020
Authors: Mannumbeth Renjithlal Sarath Lal , Magdi Mohamed Eid , Renjith Keerthi , Cordeiro Nikhil , Lever Hazel , Alexis Jeffrey , Thomas Sabu 
Published: March 2024

AbstractBackgroundHeart Failure (HF)-related mortality has been showing an upward trend since 2012. In this study, we assessed nationwide trends in mortality related to HF among women and focused on women 15-55 years of age in the United States from 1999 to 2020.MethodsTrends in mortality related to HF were assessed through a cross-sectional analysis of the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research database. Age-adjusted mortality rates per 1,000,000 people and associated annual percent changes with 95% Confidence Intervals(CI) were determined. Joinpoint regression was used to assess the trends in the overall, demographic (sex, race and ethnicity, age), and regional groups.ResultsBetween 1999 and 2020, 1,035,383 women died of heart failure. The age-adjusted mortality rate remained stable from 1999-2005, saw a reduction till 2012 and then an increase till 2020. Higher mortality rates were observed for Black patients, and patients ≥55 years of age. Large metropolitan counties had lesser mortality burden compared to rural counterparts. In 15-55 age group,18,875 women died due to heart failure.The discrepancy in mortality rates was even more pronounced between races in 15-55 age group.ConclusionsFollowing an initial period of stability, HF-related mortality in women worsened from 2012 to 2020 in the United States. Black women had higher AAMR compared with White women, with a significant geographic variation. In the premenopausal group, black women had 4 times worse AAMR compared to their white counterparts. Focus towards preventative medicine, early diagnosis, and bridging the disparities, including socioeconomic, to promote healthcare equality should be upheld.
Analysis of gliomas DNA methylation: Assessment of pre-analytical variables
Authors: Bomsztyk Karol , Mar Daniel , Denisenko Oleg , Powell Suzanne , Vishnoi Monika , Delegard Jennifer , Patel Anoop , Ellenbogen Richard G , Ramakrishna Rohan , Rostomily Robert 
Published: March 2024

ABSTRACTPrecision oncology is driven by molecular biomarkers. For glioblastoma multiforme (GBM), the most common malignant adult primary brain tumor, O6-methylguanine-DNA methyltransferase (MGMT) gene DNA promoter methylation is an important prognostic and treatment clinical biomarker. Time consuming pre-analytical steps such as biospecimen storage before fixing, sampling, and processing are major sources of errors and batch effects, that are further confounded by intra-tumor heterogeneity ofMGMTpromoter methylation. To assess the effect of pre-analytical variables on GBM DNA methylation, tissue storage/sampling (CryoGrid), sample preparation multi-sonicator (PIXUL) and 5-methylcytosine (5mC) DNA immunoprecipitation (Matrix MeDIP-qPCR/seq) platforms were used.MGMTpromoter CpG methylation was examined in 173 surgical samples from 90 individuals, 50 of these were used for intra-tumor heterogeneity studies.MGMTpromoter methylation levels in paired frozen and formalin fixed paraffin embedded (FFPE) samples were very close, confirming suitability of FFPE forMGMTpromoter methylation analysis in clinical settings. Matrix MeDIP-qPCR yielded similar results to methylation specific PCR (MS-PCR). Warm ex-vivo ischemia (37°C up to 4hrs) and 3 cycles of repeated sample thawing and freezing did not alter 5mC levels atMGMTpromoter, exon and upstream enhancer regions, demonstrating the resistance of DNA methylation to the most common variations in sample processing conditions that might be encountered in research and clinical settings. 20-30% of specimens exhibited intratumor heterogeneity in theMGMTDNA promoter methylation. Collectively these data demonstrate that variations in sample fixation, ischemia duration and temperature, and DNA methylation assay technique do not have significant impact on assessment ofMGMTpromoter methylation status. However, intratumor methylation heterogeneity underscores the need for histologic verification and value of multiple biopsies at different GBM geographic tumor sites in assessment ofMGMTpromoter methylation. Matrix-MeDIP-seq analysis revealed thatMGMTpromoter methylation status clustered with other differentially methylated genomic loci (e.g. HOXA and lncRNAs), that are likewise resilient to variation in above post-resection pre-analytical conditions. TheseMGMT-associated global DNA methylation patterns offer new opportunities to validate more granular data-based epigenetic GBM clinical biomarkers where the CryoGrid-PIXUL-Matrix toolbox could prove to be useful.
Conserved Lysine in transmembrane helix 5 is key for the inner gating of the LAT transporter BasC
Authors: Fort Joana , Nicolàs-Aragó Adrià , Maggi Luca , Molledo Maria Martinez , Kapiki Despoina , Zijlstra Niels , Bodoy Susanna , Pardon Els , Steyaert Jan , Llorca Oscar , Orozco Modesto , Cordes Thorben , Palacín Manuel 
Published: March 2024

AbstractL-amino acid transporters (LATs) play a key role in a wide range of physiological processes. Defects in LATs can lead to neurological disorders and aminoacidurias, while the overexpression of these transporters is related to cancer. BasC is a bacterial LAT transporter with an APC fold. In this study, to monitor the cytoplasmic motion of BasC, we developed a smFRET assay that can characterize the conformational states of the intracellular gate in solution at room temperature. Based on combined biochemical and biophysical data and molecular dynamics simulations, we propose a model in which the conserved lysine residue in TM5 supports TM1a to explore both open and closed states within the cytoplasmic gate under apo conditions. This equilibrium can be altered by substrates, mutation of conserved lysine 154 in TM5, or transport-blocking nanobodies. Overall, these findings provide insights into the transport mechanism of BasC and highlight the significance of the lysine residue in TM5 in the cytoplasmic gating of LATs.
Clinical-Grade Validation of an Autofluorescence Virtual Staining System with Human Experts and a Deep Learning System for Prostate Cancer
Authors: Wong Pok Fai , McNeil Carson , Wang Yang , Paparian Jack , Santori Charles , Gutierrez Michael , Homyk Andrew , Nagpal Kunal , Jaroensri Tiam , Wulczyn Ellery , Steiner David F. , Chen Po-Hsuan Cameron , Restorick Luke , Roy Jonathan , Cimermancic Peter 
Published: March 2024

AbstractThe tissue diagnosis of adenocarcinoma and intraductal carcinoma of the prostate (IDC-P) includes Gleason grading of tumor morphology on the hematoxylin and eosin (H&E) stain, and immunohistochemistry (IHC) markers on the PIN-4 stain (CK5/6, P63, AMACR). In this work, we create an automated system for producing both virtual H&E and PIN-4 IHC stains from unstained prostate tissue using a high-throughput multispectral fluorescence microscope and artificial intelligence & machine learning. We demonstrate that the virtual stainer models can produce high-quality images suitable for diagnosis by genitourinary pathologists. Specifically, we validate our system through extensive human review and computational analysis, using a previously-validated Gleason scoring model, and an expert panel, on a large dataset of test slides. This study extends our previous work on virtual staining from autofluorescence, demonstrates the clinical utility of this technology for prostate cancer, and exemplifies a rigorous standard of qualitative and quantitative evaluation for digital pathology.
Highlighting Educational Gaps in Hairstyling Practices amongst Dermatologists and Trainees
Authors: Araoye Erinolaoluwa F. , Jamerson Taylor A. , Yin Lu , Lo Sicco Kristen , Aguh Crystal 
Published: March 2024

AbstractBackgroundHairstyling practices are associated with the development and/or exacerbation of various forms of alopecia. Exposure to various hairstyling practices ranges but is often insufficient in current dermatologic textbooks and training curricula. We therefore conducted a survey to establish dermatologists understanding of hairstyling practices, particularly those that have been implicated in alopecia.MethodsA 34-item anonymous, electronic survey was distributed by email to 291 board-certified dermatologists and dermatology residents across the US between August 2020 and February 2021. Responses were rated on a 10-point scale to identify physician confidence in various styling practicesResultsBlack providers were more confident in both the knowledge and counseling of all hair practices (chemical straightening, heat styling, braiding, weaving, and wigs) compared to non-Black providers (p <0.001), with the exception of counseling patients on hair dyes for which no significant difference was found (p=0.337). Female providers were only more likely to indicate confidence in knowledge regarding different heat styling methods and hair dyes, and counseling of heat styling methods compared to male providers (OR 15.72, p<0.001; OR 2.47, p=0.022; OR 3.78, p=0.001 respectively) across all hair practices surveyed. Overall, 63.8% of providers reported that the majority of their knowledge on hair practices was from personal experience as opposed to formal training.LimitationsThis survey is limited by its response rate and the inability to characterize non-responders due to anonymity.ConclusionOur study highlights educational gaps in dermatologic training on hair practices, especially those more common among Black patients. Interestingly, the majority of provider knowledge came from personal experience rather than dermatologic training emphasizing the need for formalized curricula to enhance understanding among all dermatology providers.
An adaptive weight ensemble approach to forecast influenza activity in the context of irregular seasonality
Authors: Tsang Tim K. , Du Qiurui , Cowling Benjamin J. , Viboud Cécile 
Published: March 2024

ABSTRACTForecasting of influenza activity in tropical and subtropical regions such as Hong Kong is challenging due to irregular seasonality with high variability in the onset of influenza epidemics, and potential summer activity. To overcome this challenge, we develop a diverse set of statistical, machine learning and deep learning approaches to forecast influenza activity in Hong Kong 0-to 8- week ahead, leveraging a unique multi-year surveillance record spanning 34 winter and summer epidemics from 1998-2019. We develop a simple average ensemble (SAE), which is the average of individual forecasts from the top three individual models. We also consider an adaptive weight blending ensemble (AWBE) that allows for dynamic updates of each model contribution based on LASSO regression and uses decaying weights in historical data to capture rapid change in influenza activity. Overall, across all 9 weeks of horizon, all models outperform the baseline constant incidence model, reducing the root mean square error (RMSE) by 23%-29% and weighted interval score (WIS) by 25%-31%. The SAE ensemble only slightly better than individual models, reducing RMSE and WIS by 29%. The AWBE ensemble reduce RMSE by 45% and WIS by 46%, and outperform individual models for forecasts of epidemic trends (growing, flat, descending), and during both winter and summer seasons. Using the post-COVID surveillance data in 2023-2024 as another test period, the AWBE ensemble still reduces RMSE by 32% and WIS by 36%. Our framework contributes to the ensemble forecasting of infectious diseases with irregular seasonality.Significance statementIn subtropical and tropical regions, irregular influenza seasonality makes accurate forecasting challenging. We test ensemble approaches using diverse statistical, machine learning, and deep learning models based on a unique multi-year surveillance record in Hong Kong. Performance of individual models varies by season and epidemic trend, but simple averaging ensemble cannot improve accuracy. Here we develop an adaptive weight ensemble approach, which updated individual model contributions dynamically. This approach halves the RMSE, outperforms all individual models in different settings and reducing RMSE by one-third even in post-COVID periods. Our method contributes to comparison and benchmarking of models in ensemble forecasts, enhancing the evidence base for synthesizing multiple models in disease forecasting in geographies with irregular influenza seasonality.
MRI assessment of adipose tissue fatty acid composition in the UK Biobank and its association with diet and disease
Authors: Thanaj Marjola , Basty Nicolas , Whitcher Brandon , Bell Jimmy D , Thomas E Louise 
Published: March 2024

AbstractObjectivesThis study aimed to assess the fatty acid (FA) composition of abdominal subcutaneous (ASAT) and visceral (VAT) adipose tissue in the UK Biobank imaging cohort (N = 33,823) using magnetic resonance imaging (MRI).MethodsWe measured the fractions of saturated (fSFA), monounsaturated (fMUFA), and polyunsaturated (fPUFA) in ASAT and VAT from multi-echo MRI scans. We selected a sub-cohort that followed a vegan and an omnivore diet (N=36) to validate the effect of diet on adipose tissue. In the wider imaging cohort, we examined the relationship between adipose tissue FA composition and various traits related to disease and body size.ResultsWe measured adipose tissue FA composition for over 33,000 participants, revealing higher fSFA and fPUFA and lower fMUFA in VAT (p < 0.00016). fMUFA and fPUFA were higher in ASAT and lower in VAT for women (p<0.00016). Vegans exhibited lower fSFA in both ASAT and VAT (p < 0.00016). VAT fSFA and fMUFA showed significant associations with disease as well as anthropometric variables.DiscussionThis extensive analysis revealed the relationships between adipose tissue FA composition and a range of factors in a diverse population, highlighting the importance of studying body adipose tissue beyond its quantity.Study importanceWhat is already known?The fatty acid (FA) composition of adipose tissue is an independent risk factor for hypertension, type-2 diabetes (T2D) and cardiovascular disease.There has yet to be a large-scale population study of adipose tissue FA composition, principally due to the invasive nature of available methods.What does the study add?We show that MRI-based methods can be readily applied across a large population (n=33,823) while confirming and expanding on the associations between dietary patterns and FA composition in both abdominal subcutaneous (ASAT) and visceral (VAT) adipose tissue.Models involving saturated and monounsaturated FA composition in VAT demonstrate significant association with disease outcomes, anthropometric variables, dietary macronutrient intake and physical activity.How might these results change the direction of research or the focus of clinical practice?Our findings highlight the importance of evaluating adipose tissue composition and its relationship with dietary and disease traits.These insights will contribute to formulating more informed lifestyle recommendations to alleviate or even reverse metabolic conditions associated with obesity.
Depression, Brain Structure and Socioeconomic Status: A UK Biobank Study
Authors: Johns Sasha , Lea-Carnall Caroline , Shryane Nick , Maharani Asri 
Published: March 2024

AbstractBackgroundDepression results from interactions between biological, social, and psychological factors. Literature shows that depression is associated with abnormal brain structure, and that socioeconomic status (SES) is associated with depression and brain structure. However, limited research considers the interaction between each of these factors.MethodsMultivariate regression analysis was conducted using UK Biobank data on 39,995 participants to examine the relationship between depression and brain volume in 23 cortical regions for the whole sample and then separated by sex. It then examined whether SES affected this relationship.ResultsEight out of 23 brain areas had significant negative associations with depression in the whole population. However, these relationships were diminished in seven areas when SES was included in the analysis. For females, three regions had significant negative associations with depression when SES was not included, but only one when it was. For males, lower volume in six regions was significantly associated with higher depression without SES, but this relationship was abolished in four regions when SES was included. The precentral gyrus was robustly associated with depression across all analyses.LimitationsParticipants with conditions that could affect the brain were not excluded. UK Biobank is not representative of the general population which may limit generalisability. SES was made up of education and income which were not considered separately.ConclusionsSES affects the relationship between depression and cortical brain volume. Health practitioners and researchers should consider this when working with imaging data in these populations.
A structural mean modelling Mendelian randomization approach to investigate the lifecourse effect of adiposity: applied and methodological considerations
Authors: Power Grace M. , Palmer Tom , Warrington Nicole , Heron Jon , Richardson Tom G. , Didelez Vanesa , Tilling Kate , Davey Smith George , Sanderson Eleanor 
Published: March 2024

AbstractThe application of a lifecourse approach to genetic epidemiology is key to better understanding causal effects of adversities on health outcomes over time. For some time-varying phenotypes, it has been shown that genetic effects may have differential importance in the development of an exposure at different periods in the lifecourse. Mendelian randomization (MR) is a technique that uses genetic variation to address causal questions about how modifiable exposures influence health. MR studies often employ conventional instrumental variable (IV) methods designed to estimate lifelong effects. Recently, several extensions of MR have been used to investigate time-varying effects, including structural mean models (SMMs). SMMs exploit IVs through g-estimation and circumvent some of the parametric assumptions of other MR methods.In this study, we apply g-estimation of SMMs to MR. We aim to estimate the period effects of adiposity measured at two different life stages on cardiovascular disease (CVD), type 2 diabetes (T2D) and breast cancer in later life. We found persistent period effects of higher adulthood adiposity on increased risk of CVD and T2D. Higher childhood adiposity had a protective period effect on breast cancer. We compare this method to an inverse variance weighted multivariable MR approach: a technique also using multiple IVs to assess time-varying effects, however, relying on a different set of assumptions and subsequent interpretations. We discuss the strengths and limitations of each approach and emphasise the importance of underlying methodological assumptions in the application of MR to lifecourse research questions.
An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer’s Disease Using UK Biobank
Authors: Meng Weimin , Inampudi Rohit , Zhang Xiang , Xu Jie , Huang Yu , Xie Mingyi , Bian Jiang , Yin Rui 
Published: March 2024

AbstractAlzheimer’s disease (AD) manifests with varying progression rates across individuals, necessitating the understanding of their intricate patterns of cognition decline that could contribute to effective strategies for risk monitoring. In this study, we propose an innovative interpretable population graph network framework for identifying rapid progressors of AD by utilizing patient information from electronic health-related records in the UK Biobank. To achieve this, we first created a patient similarity graph, in which each AD patient is represented as a node; and an edge is established by patient clinical characteristics distance. We used graph neural networks (GNNs) to predict rapid progressors of AD and created a GNN Explainer with SHAP analysis for interpretability. The proposed model demonstrates superior predictive performance over the existing benchmark approaches. We also revealed several clinical features significantly associated with the prediction, which can be used to aid in effective interventions for the progression of AD patients.