bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning-based Clinical Decision Support for Infection Risk Prediction
Authors: Feng Ting , Noren David , Kulkarni Chaitanya , Mariani Sara , Zhao Claire , Ghosh Erina , Swearingen Dennis , Frassica Joseph , McFarlane Daniel , Conroy Bryan 
Published: May 2023

ABSTRACTBackgroundHealthcare-associated infection (HAI) remains a significant risk for hospitalized patients and a challenging burden for the healthcare system. This study presents a clinical decision support tool that can be used in clinical workflows to proactively engage secondary assessments of pre-symptomatic and at-risk infection patients, thereby enabling earlier diagnosis and treatment.MethodsThis study applies machine learning, specifically ensemble-based boosted decision trees, on large retrospective hospital datasets to develop an infection risk score that predicts infection before obvious symptoms present. We extracted a stratified machine learning dataset of 36,782 healthcare-associated infection patients. The model leveraged vital signs, laboratory measurements and demographics to predict HAI before clinical suspicion, which is defined as the order of a microbiology test or administration of antibiotics.ResultsWe find that our best performing infection risk model achieves a cross-validated AUC of 0.88 at 1-hour before clinical suspicion and maintains an AUC>0.85 for 48-hours before suspicion by aggregating information across demographics and a set of 163 vital signs and laboratory measurements. A second model trained on a reduced feature space comprising demographics and the 36 most frequently measured vital signs and laboratory measurements can still achieve an AUC of 0.86 at 1-hour before clinical suspicion. These results compare favorably against using temperature alone and clinical rules such as the quick Sequential Organ Failure Assessment (qSOFA) score. Along with the performance results, we also provide an analysis on model interpretability via feature importance rankings.ConclusionsThe predictive model aggregates information from multiple physiological parameters such as vital signs and laboratory measurements to provide a continuous risk score of infection that can be deployed in hospitals to provide advance warning of patient deterioration.
DLST—a Cuproptosis-related Gene—is a Potential Diagnostic and Prognostic Factor for Clear Cell Renal Cell Carcinoma
Authors: Wang Haoyuan , Ma Xiaopeng , Li Sijie , Ni Xiaochen 
Published: May 2023

AbstractClear cell renal cell carcinoma (ccRCC) accounts for the highest number of renal malignancies and 3% of all adult cancers. The incidence of ccRCC is increasing worldwide, and its prognosis is poor. Approximately 30% of the patients are diagnosed at a late stage and are frequently asymptomatic. Cuproptosis is a new type of cell death that is regulated by Cu ions. As cuproptosis is associated with cancer development, we hypothesized that changes in the expression of cuproptosis-related genes (CRGs) are associated with the prognosis of ccRCC, and that CRGs can serve as biomarkers for the diagnosis and prognosis of ccRCC. In the present study, we explored the correlation between CRGs and ccRCC prognosis by analyzing publicly available data. We analyzed the clinical information and RNA-sequencing data in The Cancer Genome Atlas using bioinformatics tools. Dihydrolipoamide S-succinyltransferase (DLST) was identified as a novel gene with predictive and diagnostic potential. CRGs were under-expressed in ccRCC samples, and downregulation ofDLSTwas highly associated with poor prognosis. Cox univariate and multivariate regression analyses revealed thatDLSTcould serve as an independent prognostic factor for ccRCC. Further, functional enrichment analysis indicated that low expression ofDLSTmay affect immune function. Our results strongly indicate thatDLSTplays an important role in ccRCC progression and may serve as an independent diagnostic and prognostic biomarker for ccRCC. Therefore,DLSTis a potential therapeutic target for patients with ccRCC.
Multi-sector stakeholder consensus on tackling the complex health and social needs of the growing population of people leaving prison in older age
Authors: Hwang Ye In (Jane) , Withall Adrienne , Hampton Stephen , Snoyman Phillip , Forsyth Katrina , Butler Tony 
Published: May 2023

AbstractAs populations age globally, cooperation across multi-sector stakeholders is increasingly important to service older persons, particularly those with high and complex health and social needs. One such population is older people entering society after a period of incarceration in prison. The ‘ageing epidemic’ in prisons worldwide has caught the attention of researchers, governments and community organisations, who identify challenges in servicing this group as they re-enter the community. Challenges lie across multiple sectors, with inadequate support leading to dire consequences for public health, social welfare and recidivism. This is the first study to bring together multi-sector stakeholders from Australia to form recommendations for improving health and social outcomes for older people re-entering community after imprisonment. A modified nominal group technique was used to produce recommendations from N=15 key stakeholders across prison health, corrections, research, advocacy, aged care, community services, via online workshops. The importance and priority of these recommendations was validated by a broader sample of N=44 stakeholders, using an online survey. Thirty-six recommendations for improving outcomes for this population were strongly supported. These recommendations entail two important findings about this population: (1) They are a high-needs, unique, and underserved group at risk of significant health and social inequity in the community, (2) Multi-sector stakeholder cooperation will be crucial to service this growing group.
ARF1 prevents aberrant type I IFN induction by regulating STING activation and recycling
Authors: Hirschenberger Maximilian , Lepelley Alice , Rupp Ulrich , Klute Susanne , Hunszinger Victoria , Koepke Lennart , Merold Veronika , Didry-Barca Blaise , Wondany Fanny , Bergner Tim , Wiese Sebastian , Volpi Stefano , Gattorno Marco , Papa Riccardo , Lynch Sally-Ann , Haug Marte G. , Houge Gunnar , Wigby Kristen M. , Sprague Jessica , Lenberg Jerica , Read Clarissa , Walther Paul , Michaelis Jens , Kirchhoff Frank , de Oliveira Mann Carina C. , Crow Yanick J. , Sparrer Konstantin M.J. 
Published: May 2023

ABSTRACTType I interferon (IFN) signalling is tightly controlled. Upon recognition of DNA by cyclic GMP AMP synthase (cGAS), stimulator of interferon genes (STING) translocates along the endoplasmic reticulum (ER)-Golgi axis to induce IFN signalling. Termination is achieved through autophagic degradation or recycling of STING by retrograde Golgi-to-ER transport. Here, we identify the GTPase ARF1 as a crucial negative regulator of cGAS-STING signaling. Heterozygous ARF1 missense mutations cause a novel type I interferonopathy associated with enhanced IFN stimulated gene expression. Disease-associated, GTPase-defective, ARF1 results in increased cGAS-STING dependent type I IFN signalling in cell lines and primary patient cells. Mechanistically, mutated ARF1 perturbs mitochondrial fusion causing cGAS activation by aberrant mitochondrial DNA, and promotes accumulation of active STING at the Golgi/ERGIC due to defective retrograde transport. Our data show that ARF1 has an unexpected dual role in maintaining cGAS-STING homeostasis, through the promotion of mitochondrial fusion and STING recycling.
Interaction between risk SNPs of Developmental Dyslexia and Parental Education on Reading Ability: Evidence for Differential-Susceptibility Theory
Authors: Yang Qing , Cheng Chen , Wang Zhengjun , Belsky Jay , Zhao Jingjing 
Published: May 2023

AbstractWhile genetic and environmental factors have been shown as predictors of children’s reading ability, the interaction effects of identified genetic risk susceptibility and specified environmental for reading ability have rarely been investigated. The current study assessed potential gene-environmental (G×E) interactions on reading ability in 1477 school-aged children. The gene-environment interactions on character recognition were investigated by an exploration analysis between the risk single-nucleotide polymorphisms (SNPs) which were discovered by previous genome-wide association studies of developmental dyslexia (DD), and parental education (PE). The re-parameterized regression analysis suggested that this G×E interaction conformed to the strong differential-susceptibility model. Results showed that rs281238 exhibits a significant interaction with PE on character recognition. Children with “T” genotype profited from high PE, whereas they performed worse in low PE environment, but “CC” genotype children were not malleable in different PE environments.Research HighlightsWe calculated the Cumulative Genetic Score (CGS) of 9 SNPs related to developmental dyslexia, and found that the interaction between CGS and parental education on reading ability. The G×E comforted to the differential-susceptibility model that those individuals carrying more plasticity alleles were affected more than those carrying more fewer.The interaction between rs281238 and parental education conformed to the strong differential-susceptibility model that children with “T” allele would have highest reading ability in positive environment and lowest reading ability in adversity environment, whereas children without “T” allele would not be affected by parental education.
Maternal diabetes influences neonatal obesity-adiposity but not in later life Offspring obesity in diabetic pregnancy
Authors: Deshpande-Joshi Sayali S. , Wagle Sonali S. , Deshmukh Madhura K. , Damle Hemant S. , Otiv Suhas R. , Phatak Sanat B. , Dhadge Smita N. , Ambardekar Shubha S. , Bhat Dattatray S. , Raut Deepa A. , Kamat Rajashree P. , Wadke Sayali G. , Kumaran Kalyanaraman , Chandak Giriraj R. , Yajnik Chittaranjan S. 
Published: May 2023

AbstractBackgroundBased on studies in overweight-obese populations, it is tacitly assumed that maternal hyperglycemia is responsible for obesity-adiposity at birth and in later life.Study designTwo hospital based case control studies: 1) Neonatal outcomes, 2) Later life outcomes.MethodsWe studied associations of neonatal and later life obesity-adiposity [age and sex-adjusted BMI, waist circumference, skinfolds, and body fat percent by Dual energy X-ray Absorptiometry (DXA)] in offspring of mothers with diabetes (ODM) and those of mothers without diabetes (ONDM). Exposures were parental hyperglycemia and overweight-obesity.ResultsNeonatal study included 372 non-diabetic and 816 diabetic pregnancies [74 type 1 diabetes, 102 type 2 diabetes, 640 gestational diabetes (GDM)]. Mothers with type 1 diabetes were the youngest, thinnest, and with highest HbA1c. Maternal glycemia but not BMI was associated with neonatal obesity-adiposity. Thus, neonates of mothers with type 1 diabetes had highest ponderal index, abdominal circumference, and skinfolds.Later life study included 200 ODM (25 type 1 diabetes, 22 type 2 diabetes, 153 GDM) and 177 age, sex and socio-economic matched ONDM (2 to 26 y). Their obesity-adiposity was associated with bi-parental overweight-obesity in an additive manner, but not with parental diabetes. Offspring birth weight was also positively associated. Offspring of mothers with type 1 diabetes had the lowest and offspring of mothers with type 2 diabetes the highest obesity-adiposity.ConclusionNeonatal obesity-adiposity is driven by maternal glycemia while later life obesity-adiposity by bi-parental obesity. Our results provide a clear insight into pathogenesis of obesity-adiposity in the offspring.Article HighlightsIt is tacitly assumed that maternal diabetes is responsible for offspring obesity-adiposity.We examined the determinants of obesity-adiposity in intrauterine and in later life in children born to mothers with type 1, type 2 and GDM. Paternal influence was also investigated.Mothers with type 1 diabetes were the thinnest and most hyperglycemic. Their children were the most obese-adipose at birth but thinnest in later life. Later life obesity-adiposity was driven by bi-parental overweight-obesity, not by diabetes.Our findings suggest that strict maternal metabolic control during pregnancy will reduce macrosomia while targeting obesogenic family environment may reduce later life offspring obesity-adiposity.
Urinary peptides predict future death
Authors: Keller Felix , Beige Joachim , Siwy Justyna , Mebazaa Alexandre , An Dewei , Mischak Harald , Schanstra Joost P. , Mokou Marika , Perco Paul , Staessen Jan A. , Vlahou Antonia , Latosinska Agnieszka 
Published: May 2023

AbstractBackgroundThere is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, though the mechanisms that cause this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to already present vulnerabilities. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides.MethodsUrinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated.ResultsIn the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death (adj. HR 1·2 [95% CI 1·17-1·24]). The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% (adj. HR 1·61 [95% CI 1·47-1·76]), in line with adjusted meta-analytic HR estimate of 1·55. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I(I).ConclusionThe COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. Prediction is based mainly on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as basis for proteomics guided intervention aiming towards manipulating/improving collagen turnover, thereby reducing the risk of death.
Mediators of monocyte chemotaxis and matrix remodeling are associated with the development of fibrosis in patients with COVID-19
Authors: Holton Sarah E. , Mitchem Mallorie , Pipavath Sudhakar , Morrell Eric D. , Bhatraju Pavan K. , Hamerman Jessica A. , Speake Cate , Malhotra Uma , Wurfel Mark M. , Ziegler Steven , Mikacenic Carmen 
Published: May 2023

AbstractAcute respiratory distress syndrome (ARDS) has a fibroproliferative phase that may be followed by pulmonary fibrosis. This has been described in patients with COVID-19 pneumonia, but the underlying mechanisms have not been completely defined. We hypothesized that protein mediators of tissue remodeling and monocyte chemotaxis are elevated in the plasma and endotracheal aspirates of critically ill patients with COVID-19 who subsequently develop radiographic fibrosis.We enrolled COVID-19 patients admitted to the ICU who had hypoxemic respiratory failure, were hospitalized and alive for at least 10 days, and had chest imaging done during hospitalization (n= 119). Plasma was collected within 24h of ICU admission and at 7d. In mechanically ventilated patients, endotracheal aspirates (ETA) were collected at 24h and 48-96h. Protein concentrations were measured by immunoassay. We tested for associations between protein concentrations and radiographic evidence of fibrosis using logistic regression adjusting for age, sex, and APACHE score.We identified 39 patients (33%) with features of fibrosis. Within 24h of ICU admission, plasma proteins related to tissue remodeling (MMP-9, Amphiregulin) and monocyte chemotaxis (CCL-2/MCP-1, CCL-13/MCP-4) were associated with the subsequent development of fibrosis whereas markers of inflammation (IL-6, TNF-α) were not. After 1 week, plasma MMP-9 increased in patients without fibrosis. In ETAs, only CCL-2/MCP-1 was associated with fibrosis at the later timepoint.This cohort study identifies proteins of tissue remodeling and monocyte recruitment that may identify early fibrotic remodeling following COVID-19. Measuring changes in these proteins over time may allow for early detection of fibrosis in patients with COVID-19.
Neighborhood air pollution is negatively associated with neurocognitive maturation in early adolescence
Authors: Kardan Omid , Sereeyothin Chacriya , Schertz Kathryn E. , Angstadt Mike , Weigard Alexander S. , Berman Marc G. , Heitzeg Mary M. , Rosenberg Monica D. 
Published: May 2023

AbstractThe ability to maintain focus and process task-relevant information continues developing during adolescence, but the specific physical environmental factors that influence this development remain poorly characterized. One candidate factor is air pollution. Evidence suggests that small particulate matter and NO2 concentrations in the air may negatively impact cognitive development in childhood. We assessed the relationship between neighborhood air pollution and the changes in performance on then-back task, a test of attention and working memory, in the Adolescent Brain Cognitive Development (ABCD) Study’s baseline (ages 9-10) and two-year-follow-up releases (Y2, ages 11-12; n = 5,256). In thebehavioraldomain, multiple linear regression showed that developmental change in n-back task performance was negatively associated with neighborhood air pollution (β = -.044, t = -3.11, p = .002), adjusted for covariates capturing baseline cognitive performance of the child, their parental income and education, family conflicts, and their neighborhood’s population density, crime rate, perceived safety, and Area Deprivation Index (ADI). The strength of the adjusted association for air pollution was similar to parental income, family conflict, and neighborhood ADI. In theneuroimagingdomain, we evaluated a previously published youthcognitivecomposite Connectome-based Predictive Model (ccCPM), and again found that decreased developmental change in the strength of the ccCPM from pre-to early adolescence was associated with neighborhood air pollution (β = -.110, t = -2.69, p = .007), adjusted for the covariates mentioned above and head motion. Finally, we found that the developmental change in ccCPM strength was predictive of the developmental change in n-back performance (r= .157, p < .001), and there was an indirect-only mediation where the effect of air pollution on change in n-back performance was mediated by the change in the ccCPM strength (βindirecteffect= -.013, p = .029). In conclusion, neighborhood air pollution is associated with lags in the maturation of youth cognitive performance and decreased strengthening of the brain networks supporting cognitive abilities over time.
Assessment of valvular function in over 47,000 people using deep learning-based flow measurements
Authors: Kany Shinwan , Rämö Joel T. , Hou Cody , Jurgens Sean J. , Nauffal Victor , Cunningham Jon , Lau Emily S. , Butte Atul J. , Ho Jennifer E. , Olgin Jeffrey E. , Elmariah Sammy , Lindsay Mark E. , Ellinor Patrick T. , Pirruccello James P. 
Published: May 2023

AbstractValvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale.We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants. We calculated eight traits, including peak velocity, mean gradient, aortic valve area, forward stroke volume, mitral and aortic regurgitant volume, greatest average velocity, and ascending aortic diameter. We then computed sex-stratified reference ranges for these phenotypes in up to 31,909 healthy individuals. In healthy individuals, we found an annual decrement of 0.03cm2in the aortic valve area. Participants with mitral valve prolapse had a 1 standard deviation [SD] higher mitral regurgitant volume (P=9.6 × 10−12), and those with aortic stenosis had a 4.5 SD-higher mean gradient (P=1.5 × 10−431), validating the derived phenotypes’ associations with clinical disease. Greater levels of ApoB, triglycerides, and Lp(a) assayed nearly 10 years prior to imaging were associated with higher gradients across the aortic valve. Metabolomic profiles revealed that increased glycoprotein acetyls were also associated with an increased aortic valve mean gradient (0.92 SD, P=2.1 x 10−22). Finally, velocity-derived phenotypes were risk markers for aortic and mitral valve surgery even at thresholds below what is considered relevant disease currently.Using machine learning to quantify the rich phenotypic data of the UK Biobank, we report the largest assessment of valvular function and cardiovascular disease in the general population.
Y-chromosomal microsatellites and expansion from Africa
Authors: Cenac Zarus 
Published: May 2023

AbstractResearch has suggested that Africa is the continent from which modern humans dispersed around the world. Some diversities are thought to trace this expansion; they decline as distance from Africa accumulates, and they suggest that the expansion originated within a range of locations in Africa. Previously, a decline was found regarding Y-chromosomal microsatellite heterozygosity. However, this diversity has been noted to suggest a non-African origin and, consequently, not look like it indicates expansion from Africa. Declines have appeared in other variables which are derived from Y-chromosomal microsatellites. These variables include effective population size, expansion time, and time to the most recent common ancestor. The present research inferred if these variables, and some Y-chromosomal diversities, indicate expansion from Africa. Variables which indicate the expansion could help with identifying which area of Africa the expansion started in. This research used variables previously derived from Y-chromosomal microsatellites. These variables were for populations from across the world (effective population size, expansion time, and time to the most recent common ancestor) or only in Africa (haplotype and repeat unit diversities). Regarding populations across the world, San were very high in each variable when considering distance from (southern) Africa. Without San, effective population size and time to the most recent common ancestor did not squarely indicate an African origin, and expansion time placed the origin wholly outside of Africa. When using San, each area was only in Africa. Amongst African populations, whilst both haplotype diversity and repeat unit diversity showed a geographical pattern of declining, only haplotype diversity suggested a completely African area of origin. A southern African origin was broadly indicated when a general estimate of the origin was produced from Y-chromosomal haplotype diversity alongside some other genetic diversities.