bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling the Risk of Airborne Transmission of Respiratory Viruses in Microgravity
Authors: Sararat Chayanin , Jiravejchakul Natnicha , Nawattanapaiboon Kawin , Modchang Charin 
Published: September 2024

AbstractAirborne transmission is the most efficient and widespread route of viral spread, posing a significant challenge in controlling major infectious diseases such as COVID-19 and influenza. In microgravity environment, such as the International Space Station (ISS), this mode of transmission requires heightened vigilance and preventive measures due to the prolonged suspension of virus-laden particles, which increases the risk of infection. Using the COVID Airborne Risk Assessment (CARA) tool, we assess the risk of airborne transmission of respiratory viruses in microgravity by simulating the emission, dispersion, and inhalation of virus-laden particles. Our findings show that the unique conditions of microgravity allow these particles to remain airborne for significantly longer periods compared to Earth, leading to a 286-fold increase in virus concentration in the air, resulting in nearly twice the probability of infection for a susceptible host. We also evaluated the effectiveness of preventive measures, and found that facemasks can reduce the risk by up to 23% while continuous HEPA filtration at five air changes per hour proves crucial for managing air quality and minimizing infection risks by reducing airborne virus concentration at 99.79%. However, when simulated the infection risk by accounting the spaceflight-induced immune suppression, we found that the infection probability increased by 12% in the condition that viral load in infected host increase for 8-fold and absence of protective measures. Although facemasks and air filtration help mitigate the risk, their effectiveness diminishes when the viral load carrying by host is high. Enhancing host immunity through vaccination or other interventions is vital, potentially reducing infection probability by up to 14.17% when combined with HEPA filtration. These findings highlight the need for robust mitigation strategies to safeguard the health of astronauts against airborne pathogens during future space missions.
Pesticides and lifestyle factors are associated with disease severity of Parkinson’s disease: a longitudinal study
Authors: Lüth Theresa , Caliebe Amke , Gabbert Carolin , Sendel Sebastian , Laabs Björn-Hergen , König Inke R. , Klein Christine , Trinh Joanne 
Published: September 2024

AbstractObjectiveTo longitudinally analyze the impact of the environment and lifestyle on PD motor sign severity in LRRK2 p. Gly2019Ser-related PD (LRRK2-PD) and idiopathic PD (iPD).BackgroundThere is increasing evidence that the environment impacts disease severity. Recent studies have shown that pesticide exposure is associated with a faster disease progression. However, the relationship between smoking, caffeine, and disease severity has not yet been investigated longitudinally.MethodsIn this longitudinal study, we included patients with iPD from the PPMI Online (N=2815) and Fox Insight (N=2319) cohorts, as well as patients withLRRK2-PD (N=81) from Fox Insight. Motor signs were assessed with the MDS-UPDRS Part II, and patients were assessed multiple times, followed up to 35 months or 60 months in the PPMI Online or Fox Insight cohort, respectively. The motor sign severity over time was analyzed by applying a linear mixed effects model. The outcome was the cumulative score of the MDS-UPDRS Part II questionnaire. Subsequently, we investigated the association between environmental exposure, lifestyle factors and motor signs. Pesticide exposure in a work setting, smoking, coffee, black tea, green tea, and caffeinated soda consumption were assessed using the validated PD-RFQ-U questionnaires. The mixed effects model included the environmental and lifestyle factors as binary (yes/no) variables.ResultsWhen comparingLRRK2-related PD and iPD, motor signs were less severe in patients withLRRK2-PD compared to iPD (β=-0.23,p=0.005). InLRRK2-PD, black tea consumption was associated with less severe motor signs (β=-0.51,p=0.028). In patients with iPD, we observed that pesticide exposure was associated with more severe motor signs over time in PPMI-Online (β=0.23,p=3.56×10-9). Smoking was associated with a higher motor signs score in PPMI-Online (β=0.13,p=0.001). Lastly, caffeinated soda was associated with more severe motor signs in patients with iPD from PPMI-Online (β=0.15,p=3.84×10-8) and Fox Insight (β=0.09,p=0.031).ConclusionsOur results provide further evidence of the importance of environment and lifestyle in PD, even after the disease onset. We suggest that pesticide exposure and lifestyle factors may affect disease severity in patients withLRRK2-PD and iPD; still, further validation is necessary.
Deep Learning based CT-scan Coronary Artery Segmentation and Calcium Scoring
Authors: Upadhyayula Sai Koundinya 
Published: September 2024

AbstractCoronary artery disease (CAD), primarily driven by atherosclerosis, poses significant health risks, contributing to a rising mortality rate globally. This study introduces a deep learning framework designed for the automated segmentation of coronary arteries and quantification of coronary artery calcium (CAC) from CT scans, facilitating improved risk stratification in patients. Leveraging data from the National Lung Screening Trial, we developed a three-step model that includes heart localization, coronary calcium segmentation, and calcium scoring. Various configurations of the UNet architecture were employed, with the Extended UNet utilizing an autoencoder achieving the highest validation performance, reflected by an Intersection over Union (IoU) score of 0.78 and an F1 score of 0.83.The model’s efficacy was validated against manually segmented masks, showcasing its potential for accurate risk assessment based on CAC scores. This automated approach significantly reduces the time and expertise required for traditional calcium scoring, enabling rapid and reliable assessments in clinical settings. Our findings indicate that the deep learning system can effectively classify patients into risk categories, underscoring its potential utility in enhancing the management of CAD and improving patient outcomes. This research highlights the feasibility of integrating advanced computational techniques into routine clinical practice, paving the way for more efficient cardiovascular risk stratification.
Exposome-wide gene-environment interaction study of psychotic experiences in the UK Biobank
Authors: Lin Bochao Danae , Pries Lotta-Katrin , Arias-Magnasco Angelo , Klingenberg Boris , Linden David E. J. , Blokland Gabriella A. M. , van der Meer Dennis , Luykx Jurjen J. , Rutten Bart P. F. , Guloksuz Sinan 
Published: September 2024

AbstractBackgroundA previous study successfully identified 148 out of 23,098 exposures associated with any psychotic experiences (PE) in the UK Biobank using an exposome-wide association study (XWAS). Research has shown that the polygenic risk score for schizophrenia (PRS-SCZ) is associated with PE. However, the interaction of these exposures and PRS-SCZ remains unknown.MethodTo systematically investigate gene-environment interaction underlying PE through data-driven agnostic analyses, we conducted 1) a conditional XWAS adjusting for PRS-SCZ to estimate the main effects of the exposures and PRS-SCZ, respectively; 2) exposome-wide interaction studies (XWIS) to estimate multiplicative and additive interactions between PRS-SCZ and exposures; and 3) the correlations between PRS-SCZ and exposures. The study included 148,502 participants from UK biobank.ResultsIn the conditional XWAS models, the significant effects of PRS-SCZ and 148 exposures on PE remained statistically significant. In the XWIS model, we found a significant multiplicative (Ms, 1.23, 95%CI, 1.10-1.37; P=4.0×10-4) and additive (RERI, 0.55; 95%CI, 0.32-0.77; SI, 0.22; 95%CI, 0.14-0.30; AP, 1.59; 95%CI, 1.30-1.91; all P < 0.05/148) interaction between PRS-SCZ and variable “serious medical conditions or disability” on PE. There were six additive gene-environment interactions identified for mental distress, help/treatment-seeking behaviors, vitamin D and sleep problems. In the correlation test focused on seven exposures with significant interaction with PRS-SCZ, no significant or small (r2< 0.04) gene-environment correlations were estimated.ConclusionThese findings reveal preliminary evidence for gene-environment interaction underlying PEs and suggest that genetic vulnerability and exposures might represent intertwined pathways leading to psychosis.
Uncertainty quantification in epigenetic clocks via conformalized quantile regression
Authors: Li Yanping , Goodrich Jaclyn M. , Peterson Karen E , Song Peter X-K , Luo Lan 
Published: September 2024

AbstractDNA methylation (DNAm) is a chemical modification of DNA that can be influenced by various factors, including age, the environment, and lifestyle. An epigenetic clock is a predictive tool that measures biological age based on DNAm levels. It can provide insights into an individual’s biological age, which may differ from their chronological age. This difference, known as the epigenetic age acceleration, may reflect health status and the risk for age-related diseases. Moreover, epigenetic clocks are used in studies of aging to assess the effectiveness of anti-aging interventions and to understand the underlying mechanisms of aging and disease. Various epigenetic clocks have been developed using samples from different populations, tissues, and cell types, typically by training high-dimensional linear regression models with an elastic net penalty. While these models can predict mean biological age based on DNAm with high precision, there is a lack of uncertainty quantification which is important for interpreting the precision of age estimations and for clinical decision-making. To understand the distribution of a biological age clock beyond its mean, we propose a general pipeline for training epigenetic clocks, based on an integration of high-dimensional quantile regression and conformal prediction, to effectively reveal population heterogeneity and construct prediction intervals. Our approach produces adaptive prediction intervals not only achieving nominal coverage but also accounting for the inherent variability across individuals. By using the data collected from 728 blood samples in 11 DNAm datasets from children, we find that our quantile regression-based prediction intervals are narrower than those derived from conventional mean regression-based epigenetic clocks. This observation demonstrates an improved statistical efficiency over the existing pipeline for training epigenetic clocks. In addition, the resulting intervals have a synchronized varying pattern to age acceleration, effectively revealing cellular evolutionary heterogeneity in age patterns in different developmental stages during individual childhoods and adolescent cohort. Our findings suggest that conformalized high-dimensional quantile regression can produce valid prediction intervals and uncover underlying population heterogeneity. Although our methodology focuses on the distribution of measures of biological aging in children, it is applicable to a broader range of age groups to improve understanding of epigenetic age beyond the mean. This inference-based toolbox could provide valuable insights for future applications of epigenetic interventions for age-related diseases.
Evidence that extracellular HSPB1 contributes to inflammation in alcohol-associated hepatitis
Authors: Overstreet Anne-Marie C , Burge McKenzie , Bellar Annette , McMullen Megan , Czarnecki Douglas , Huang Emily , Pathak Vai , Finney Chelsea , Vij Raveena , Dasarathy Srinivasan , Dasarathy Jaividhya , Streem David , Welch Nicole , Rotroff Daniel , Schmitt Adam M , Nagy Laura E , Messer Jeannette S 
Published: September 2024

ABSTRACTBackground and aimsAlcohol-associated hepatitis (AH) is the most life-threatening form of alcohol-associated liver disease (ALD). AH is characterized by severe inflammation attributed to increased levels of ethanol, microbes or microbial components, and damage-associated molecular pattern (DAMP) molecules in the liver. HSPB1 (Heat Shock Protein Family B (Small) Member 1; also known as Hsp25/27) is a DAMP that is rapidly increased in and released from cells experiencing stress, including hepatocytes. The goal of this study was to define the role of HSPB1 in AH pathophysiology.MethodsSerum HSPB1 was measured in a retrospective study of 184 heathy controls (HC), heavy alcohol consumers (HA), patients with alcohol-associated cirrhosis (AC), and patients with AH recruited from major hospital centers. HSPB1 was also retrospectively evaluated in liver tissue from 10 HC and AH patients and an existing liver RNA-seq dataset. Finally, HSPB1 was investigated in a murine Lieber-DeCarli diet model of early ALD as well as cellular models of ethanol stress in hepatocytes and hepatocyte-macrophage communication during ethanol stress.ResultsCirculating HSPB1 was significantly increased in AH patients and levels positively correlated with disease-severity scores. Likewise, HSPB1 was increased in the liver of patients with severe AH and in the liver of ethanol-fed mice.In vitro, ethanol-stressed hepatocytes released HSPB1, which then triggered TNFα-mediated inflammation in macrophages. Anti-HSPB1 antibody prevented TNFα release from macrophages exposed to media conditioned by ethanol-stressed hepatocytes.ConclusionsOur findings support investigation of HSPB1 as both a biomarker and therapeutic target in ALD. Furthermore, this work demonstrates that anti-HSPB1 antibody is a rational approach to targeting HSPB1 with the potential to block inflammation and protect hepatocytes, without inactivating host defense.GRAPHICAL ABSTRACTHIGHLIGHTSHSPB1 is significantly increased in serum and liver of patients with alcohol-associated hepatitis.Ethanol consumption leads to early increases in HSPB1 in the mouse liver.Hepatocytes subjected to ethanol stress release HSPB1 into the extracellular environment where it activates TNFα-mediated inflammation in macrophages.Anti-HSPB1 antibody blocks hepatocyte-triggered TNFα in a model of hepatocyte-macrophage communication during ethanol stress.
Associations between accurate measures of adiposity and fitness, blood proteins, and insulin sensitivity among South Asians and Europeans
Authors: Kho Pik Fang , Stell Laurel , Jimenez Shirin , Zanetti Daniela , Panyard Daniel J , Watson Kathleen L , Sarraju Ashish , Chen Ming-Li , Lind Lars , Petrie John R , Chan Khin N , Fonda Holly , Kent Kyla , Myers Jonathan N , Palaniappan Latha , Abbasi Fahim , Assimes Themistocles L. 
Published: September 2024

AbstractObjectiveSouth Asians (SAs) may possess a unique predisposition to insulin resistance (IR). We explored this possibility by investigating the relationship between ‘gold standard’ measures of adiposity, fitness, selected proteomic biomarkers, and insulin sensitivity among a cohort of SAs and Europeans (EURs).MethodsA total of 46 SAs and 41 EURs completed ‘conventional’ (lifestyle questionnaires, standard physical exam) as well as ‘gold standard’ (dual energy X-ray absorptiometry scan, cardiopulmonary exercise test, and insulin suppression test) assessments of adiposity, fitness, and insulin sensitivity. In a subset of 28 SAs and 36 EURs, we also measured the blood-levels of eleven IR-related proteins. We conducted Spearman correlation to identify correlates of steady-state plasma glucose (SSPG) derived from the insulin suppression test, followed by multivariable linear regression analyses of SSPG, adjusting for age, sex and ancestral group.ResultsSixteen of 30 measures significantly associated with SSPG, including one conventional and eight gold standard measures of adiposity, one conventional and one gold standard measure of fitness, and five proteins. Multivariable regressions revealed that gold standard measures and plasma proteins attenuated ancestral group differences in IR, suggesting their potential utility in assessing IR, especially among SAs.ConclusionAncestral group differences in IR may be explained by accurate measures of adiposity and fitness, with specific proteins possibly serving as useful surrogates for these measures, particularly for SAs.
A multicenter study to assess the performance of the point-of-care RT-PCR Cobas SARS-CoV-2 & Influenza A/B nucleic acid test for use on the Cobas Liat system in comparison with centralized assays across healthcare facilities in the United States
Authors: Robbins Elissa M. , Bertuzis Rasa , Chiu Ho-Chen , Miller Lupe , Noutsios Christopher 
Published: September 2024

Non-structured abstractRespiratory diseases can share many of the same symptoms, highlighting the need for timely and accurate differentiation to facilitate effective clinical management and reduce transmission. Compared with centralized testing, molecular point-of-care tests (POCT) can provide a faster time to result.We evaluated the RT-PCR POCT Cobas®SARS-CoV-2 & Influenza A/B qualitative assay for use on the Cobas Liat®system (the POC SARS-CoV-2 & Influenza A/B test) in nasal and nasopharyngeal swab samples from 10 diverse healthcare facilities in the US. A composite comparator design consisting of three centralized tests was used to analyze SARS-CoV-2, whilst performance versus a single centralized test was used for analysis of influenza A and B. Evaluations included performance stratified by sample type (prospective/retrospective and nasal/nasopharyngeal [paired by subject]), collection method (self/healthcare worker-collected [alternated and approximately balanced], symptom status (symptomatic/asymptomatic), and SARS-CoV-2 vaccination status, as well as assay inclusivity and system ease of use.A total of 2,247 samples were tested. For SARS-CoV-2, the overall percent agreement (OPA) was 98.8% (95% CI: 97.9, 99.3) in nasal swab samples and 99.0% (95% CI: 98.2, 99.4) in nasopharyngeal swab samples. Regression analysis showed that Ct values from paired nasal and nasopharyngeal swab samples were highly correlated (correlation coefficient 0.83). The OPA was ≥99.5% (sample type dependent) and 100.0% for influenza A and B, respectively. The POC SARS-CoV-2 & Influenza A/B test was easy to use.These results support the use of the POCT in various sample types and by various operators in the intended-use setting.Summary statement/importanceThis study highlights the benefits of RT-PCR POCT, namely comparable performance to centralized testing in multiple sample types and ease of use. Utilizing assays such as the POC SARS-CoV-2 & Influenza A/B test may improve timely differentiation of respiratory diseases that share similar symptoms.
Phenotypic presentation of family members of ATTRv probands and subsequent disease penetrance
Authors: Fazzini Luca , Castrichini Matteo , Li Yan , De Melo Jose , Figueiral Marta , Cao Jenny J. , Klee Eric W. , Dessalvi Christian Cadeddu , Grogan Martha , Dispenzieri Angela , Pereira Naveen L. 
Published: September 2024

AbstractBACKGROUNDHereditary transthyretin amyloid cardiomyopathy (ATTRv-CM) is being increasingly diagnosed due to enhanced awareness and availability of newer therapeutics. MultipleTTRvariants have been described worldwide, but with uncertain disease penetrance. The characteristics and outcomes of “previously undiagnosed” pathogenic-likely pathogenic (P/LP)TTRvariant (genotype or G+; cardiac phenotype or P-) carriers are unknown which has important prognostic and therapeutic implications, especially for affected family members. This descriptive study aimed to delineate phenotype and cardiac penetrance in “previously undiagnosed” G+P-family members of ATTRv probands.METHODSDemographic, electrocardiographic (ECG), genetic, and imaging (echocardiography, cardiac technetium-99m pyrophosphate (PYP) and magnetic resonance imaging) data were analyzed. The prediction effect of selected baseline characteristics for ATTRv-CM development was evaluated. Kaplan-Meier and Cox regression methods were used to describe risk and predictors of ATTRv-CM development in family members.RESULTSThere were 85 G+P-family members identified. Mean age was 48.5±11.7 years, 39% were male, 18% had a diagnosis of peripheral neuropathy, 15% with a history of carpal tunnel syndrome, and 4% had atrioventricular block at baseline. Of these, 55 patients had follow-up imaging studies. After a median 6.8-year follow-up, 22% developed ATTR-CM with a 10-year estimated risk of 29.5% (95% CI 7.9-46.0). Cardiac penetrance increased with increasing family member’s age. Proband’s diagnosis age (p=0.0096) and artificial intelligence (AI)-ECG prediction (p=0.0091) were promising baseline predictors of time to ATTRv-CM development.CONCLUSIONIn previously undiagnosed G+P-ATTRv family members, the incidence of subsequent CM is high. Predictors for CM development such as proband’s diagnosis age and AI-determined ECG probability of ATTR-CM require further investigation.
SYNE1gene novel variant is associated with myocardial infarction in young people with a family history of premature atherosclerosis
Authors: Ambroziak Michał , Franke Jakub , Wójcicka Anna , Kolanowska Monika , Budaj Andrzej 
Published: September 2024

AbstractAimThe aim of the study was to investigate the role of genetic variants in young patients (aged <50 years) with myocardial infarction (MI) and a family history of premature atherosclerosis.Methods and ResultsThe studied group consisted of 70 patients aged 26-49 (mean 43.1, SD ±4.3), 17 women and 53 men, with MI and with a family history of premature atherosclerosis, defined as MI or ischaemic stroke in first-degree relatives at age <65 years in women or <55 years in men. The total DNA was extracted from the peripheral blood samples. The targeted enrichment library was prepared and analyzed using the Next-Generation Sequencing method. Statistical analyses were performed using the R software package (http://www.r-project.org/). The results of sequencing were compared to data from the reference control population consisting of 597 people with no history of MI (418 women, 179 men) aged 18-83 (mean 40.5, SD ± 12.4) as a whole and after matching with a studied group by age and gender in a proportion 1:3 (210 people, 51 women, 159 men, aged 18-77, mean 42.1, SD ±10.6) using Propensity Score Matching. Risks associated with detected variants were evaluated using Fisher’s exact test based on the allelic frequencies of variants in both groups.SYNE1gene variant rs36215567 (NM_182961.4: c.20396+22A>G) occurs with a significantly higher incidence in the studied group when compared to the control population with OR 4.80 95%CI 1.43-14.45 (p=0.005) as well as when compared to the control population matched by age and gender OR 9.31 95%CI 1.64-95.41 (p=0.004). There were no statistically significant differences in the incidence of variants related to familial hypercholesterolemia such asLDLRc.667G>A,PCSK9c.658-36G>A, andAPOBc.12382G>A between both cohorts.ConclusionA novel variant of theSYNE1gene is associated with myocardial infarction in young patients with a family history of premature atherosclerosis.Lay summaryThe wide use of genetic information to predict coronary artery disease (CAD) development and incidence, particularly important in young people, still requires investigation before clinical implementation.A novel variant of theSYNE1gene is associated with myocardial infarction (MI) in young patients with a family history of premature atherosclerosis.Although, the role of SYNE1 in the maintenance of proper function of the cardiac muscles and coronary arteries remains still under examination the result of this study open a new opportunity to use theSYNE1gene variant in genetic risks MI scores.