bluuebunny/crossref_metadata_2025_split huggingface dataset:
RAAS blockers and region-specific variations in COVID-19 outcomes: findings from a systematic review and meta-analysis
Authors: Kaur Upinder , Chakrabarti Sankha Shubhra , Patel Tejas Kumar 
Published: September 2020

AbstractBackgroundCoronavirus disease 2019 (COVID-19) has evolved as a global crisis with high mortality seen in elderly and people with cardiometabolic diseases. The use of renin angiotensin aldosterone system (RAAS) blockers in these patients is known to enhance the expression of ACE-2, the chief binding receptor of SARS-CoV-2 and may potentially enhance infectivity.ObjectiveTo provide a pooled estimate of the effect of RAAS blocker usage on COVID-19 outcomes.Data SourcesAn electronic literature search was performed for published (using MEDLINE/PubMed and Google Scholar) and preprint (using bioRxiv and medRxiv) studies of interest. The last search was conducted on 9th July 2020.Study SelectionStudies reporting data on RAAS blocker use and COVID-19 mortality and severity were included in the review.Data Extraction and SynthesisMortality data and severity data including hospitalization, intensive care unit (ICU) admission, invasive ventilation, steroid use and acute kidney injury (AKI) were recorded. Pooled Odds ratio (OR) estimates were reported with 95% CIs and level of heterogeneity (I2).Main Outcomes and MeasuresOdds of mortality in users of RAAS blockers with respect to non-users was the primary outcome. Odds of severity, hospitalization, ICU admission, mechanical ventilation, steroid use, and AKI in users with respect to non-users of RAAS blockers were the secondary outcomes.ResultsOf 1348 articles identified, 48 published studies were included in the final analysis, with a total of 26432 patients from 31 studies included in mortality analysis and 20127 patients from 23 studies included in severity analysis. Majority of the studies (41.6%) were from China. No increased risk of mortality (Pooled OR 0.91 (0.65-1.26), I2=89%) or severity (Pooled OR 1.08 (0.79-1.46), I2=88%) was seen with RAAS blockers. The drug class was protective in hypertension (pooled OR 0.63 (0.46-0.86), I2=58%). Severity of COVID-19 outcomes was found to be high for Europeans (Pooled OR 2.08 (1.52-2.85), I2=77%) and US patients (Pooled OR 1.87 (1.62-2.17) in users of RAAS-blockers. A nearly 4 times higher risk of hospitalization, two times higher risk of ICU admission and mechanical ventilation was observed in US patients on RAAS blockers. No net effect on mortality and severity outcomes was seen in Chinese patients. RAAS blocker usage did not have any effect on corticosteroid use and AKI in Chinese patients.Conclusions and RelevanceUse of RAAS blockers is not associated with increased risk of mortality in COVID-19 patients. Reduced mortality is seen in hypertensive patients with COVID-19 and therefore the drugs should be continued in this subset. US and European patients are at higher risk of severe outcomes. Pharmacogenomic differences may explain the ethnicity related variations.
Disrupting upstream translation in mRNAs leads to loss-of-function associated with human disease
Authors: Lee David S.M. , Park Joseph , Kromer Andrew ,   Regeneron Genetics Center, Rader Daniel J. , Ritchie Marylyn D. , Ghanem Louis R. , Barash Yoseph 
Published: September 2020

ABSTRACTRibosome-profiling has uncovered pervasive translation in 5’UTRs, however the biological significance of this phenomenon remains unclear. Using genetic variation from 71,702 human genomes, we assess patterns of selection in translated upstream open reading frames (uORFs) in 5’UTRs. We show that uORF variants introducing new stop codons, or strengthening existing stop codons, are under strong negative selection comparable to protein-coding missense variants. Using these variants, we map and validate new gene-disease associations in two independent biobanks containing exome sequencing from 10,900 and 32,268 individuals respectively, and demonstrate their impact on gene expression in human cells. Our results establish new mechanisms relating uORF variation to loss-of-function of downstream genes, and demonstrate that translated uORFs are genetically constrained regulatory elements in 40% of human genes.
Automated analysis of lexical features in Frontotemporal Degeneration
Authors: Cho Sunghye , Nevler Naomi , Ash Sharon , Shellikeri Sanjana , Irwin David J. , Massimo Lauren , Rascovsky Katya , Olm Christopher , Grossman Murray , Liberman Mark 
Published: September 2020

AbstractWe implemented an automated analysis of lexical aspects of semi-structured speech produced by three patient groups with Frontotemporal degeneration (FTD): behavioral variant FTD (n=74), semantic variant Primary Progressive Aphasia (svPPA, n=42), and nonfluent/agrammatic PPA (naPPA, n=22). With a natural language processing program, we automatically tagged part-of-speech categories of all words and rated nouns for lexical measures, and computed the cross-entropy estimation, which is a measure of word predictability. Our automated analysis was a valid reflection of manual scoring. For svPPA patients, we found fewer unique nouns and more pronouns and wh-words than in the other patient groups and the controls; high abstractness, ambiguity, frequency, and familiarity for nouns they produced; and the lowest cross-entropy estimation among the groups. These measures were associated with cortical thinning in the left temporal lobe. In naPPA patients, we found increased speech errors, which were associated with cortical thinning in the left middle frontal gyrus. bvFTD patients were similar to the controls. Our results underline distinct word use profiles in subgroups of PPA patients and validate our automated method of analyzing FTD patients’ speech.
Improved mTBI outcomes with a BCI Amplified CRT Training: A retrospective chart review
Authors: Cripe C.T. , Mikulecky P. , Cooper Rebecca , Eagan T. 
Published: September 2020

AbstractThis study is a retrospective chart review of 200 clients who participated in a non-verbal restorative Cognitive Remediation Training (rCRT) program. The program was applied to effect proper neural functional remodeling needed to support resilient, flexible and adaptable behaviors after encountering a mild to medium closed head traumatic brain injury (mTBI). The r CRT training program focused on improving functional performance in executive cognitive control networks as defined by fMRI studies. All rCRT training activities were delivered in a semi-game-like manner, incorporating a Brain Computer Interface (BCI) that provided in-the-moment neural network performance integrity metrics (nPIMs) used to adjust the level of play required to properly engage long-term potentiation (LTP) and long term depreciation (LTD) network learning rules.This study reports on t-test and Reliable Change Index (RCI) changes found within cognitive abilities’ performance metrics derived from the Woodcock Johnson Cognitive Abilities III Test. We compared pre and post scores from seven cognitive abilities considered dependent on executive cognitive control networks against seven non-executive control abilities. We observed significant improvements (p values 10 to 10-22) with large Cohen’s d effect sizes (0.78-1.20) across thirteen cognitive ability domains with a medium effect size (.49) on the remaining. The mean percent change for pooled trained domain was double that observed for pooled untrained domain, at 17.2% versus 8.3%, respectively. To further adjust for practice effects, practice effect RCI values were computed and further supported the effectiveness of the rCRT training (RCI-trained 1.4 - 4.8; untrained RCI 0.08-0.75).
GWAS reveal a role for the central nervous system in regulating weight and weight change in response to exercise
Authors: Watanabe Louis P. , Riddle Nicole C. 
Published: September 2020

ABSTRACTBody size and weight show considerable variation both within and between species. This variation is controlled in part by genetics, but also strongly influenced by environmental factors including diet and the level of activity experienced by the individual. Due to the increasing obesity epidemic in much of the world, there is considerable interest in the genetic factors that control body weight and how weight changes in response to exercise treatments. Here, we use GWAS in Drosophila to identify the molecular pathways that control weight and exercise-induced weight changes. We find that there is a complex set of molecular pathways controlling weight, with many genes linked to the central nervous system (CNS). Weight was strongly impacted by animal size and body composition. While the CNS appears to be important for weight and exercise-induced weight change, signaling pathways are particularly important for determining how exercise impacts weight.
Combined protein and transcript single cell RNA sequencing in human peripheral blood mononuclear cells
Authors: Vallejo Jenifer , Saigusa Ryosuke , Gulati Rishab , Ghosheh Yanal , Durant Christopher P. , Roy Payel , Ehinger Erik , Suryawanshi Vasantika , Pattarabanjird Tanyaporn , Padgett Lindsey E. , Olingy Claire E. , Hanna David B. , Landay Alan L. , Tracy Russell P. , Lazar Jason M. , Mack Wendy J. , Weber Kathleen M. , Adimora Adaora A. , Hodis Howard N. , Tien Phyllis C. , Ofotokun Igho , Heath Sonya L. , Blanco-Dominguez Rafael , Dinh Huy Q. , Shemesh Avishai , McNamara Coleen A. , Lanier Lewis L. , Hedrick Catherine C. , Kaplan Robert C. , Ley Klaus 
Published: September 2020

AbstractCryopreserved peripheral blood mononuclear cells (PBMCs) are frequently collected and provide disease- and treatment-relevant data in clinical studies. Here, we developed combined protein (40 antibodies) and transcript single cell (sc)RNA sequencing in PBMCs. Among 31 participants in the WIHS Study, we sequenced 41,611 cells. Using Boolean gating followed by Seurat UMAPs and Louvain clustering, we identified 58 subsets among CD4 T, CD8 T, B, NK cells and monocytes. This resolution was superior to flow cytometry, mass cytometry or scRNA-sequencing without antibodies. Since the transcriptome was not needed for cell identification, combined protein and transcript scRNA-Seq allowed for the assessment of disease-related changes in transcriptomes and cell type proportion. As a proof-of-concept, we showed such differences between healthy and matched individuals living with HIV with and without cardiovascular disease. In conclusion, combined protein and transcript scRNA sequencing is a suitable and powerful method for clinical investigations using PBMCs.
Modular barcode beads for microfluidic single cell genomics
Authors: Delley Cyrille L. , Abate Adam R. 
Published: September 2020

AbstractBarcode beads allow efficient nucleic acid tagging in single cell genomics. Current barcode designs, however, are fabricated with a particular application in mind. Repurposing to novel targets, or altering to add additional targets as information is obtained is possible but the result is suboptimal. Here, we describe a modular framework that simplifies generation of multifunctional beads and allows their easy extension to new targets.One Sentence SummaryWe describe an optimized design for barcoding beads which are useful for single cell RNA and DNA sequencing.
Molecular characterization of non-small cell lung cancer tumors in Latin American patients from Brazil, Chile and Peru uncovers novel potentially driver mutations
Authors: Sepúlveda-Hermosilla Gonzalo , Blanco Alejandro , Freire Matías , Lizana Rodrigo , Cáceres-Molima Javier , Ampuero Diego , Pérez Paola , Ramos Liliana , Aren Osvaldo , Chernilo Sara , Spencer María Loreto , Flores Jacqueline , Bernal Giuliano , Olea Mónica Ahumada , Rasse Germán , Sánchez Carolina , Marcelain Katherine , Rivas Solange , Amorim Maria Galli de , Branco Gabriela , Nunes Diana Noronha , Dias-Neto Emmanuel , Freitas Helano C. , Fernández Cristina ,   NIRVANA Team, Assar Rodrigo , Armisén Ricardo 
Published: September 2020

AbstractIntroductionTherapies that target activatingEgfr, Alk, Ros1and other mutations have become first-line treatments that improve NSCLC patient’s life expectancy. Latin-American patients are poorly represented in clinical trials and in genomic databases, thus little is known about the prevalence of actionable mutations in this population. This study characterizes, for the first time, the somatic mutations found in 52 actionable genes, and describe a novel set of potentially actionable mutations, in NSCLC patients from Chile, Brazil and Peru, while correlating these genomic occurrences with relevant clinical, demographic and pathology aspects.Methods1732 subjects diagnosed with NSCLC were analyzed. DNA and RNA were sequenced using a 52 genes NGS panel. Mutations were annotated using the Variant Effect Predictor, COSMIC, OncoKB and the Cancer Genome Interpreter to categorize somatic mutations.ResultsWe found a total of 1713 mutations with 626 (36.5%) novel, potentially driver mutations. 66.1% of these novel mutations were predicted as Tier 1 driver mutations. Actionable mutations forRet and Alkwere more prevalent in Brazil than in Chile, whereasMetexon-14 skipping was significantly enriched in Chile. In Peru,Egfris higher whileKrasis lower. A high number of novels potentially driver mutations in know NSCLC actionable genes, such asAlk, Erbb2, Ret, Met, andRos1, was found.ConclusionsThe analysis of many Latin America subjects revealed a significant number of clinically actionable but also novel somatic mutations in cancer genes highlighting the importance of including less-represented populations in clinical trials and molecular studies.
On Machine Learning-Based Short-Term Adjustment of Epidemiological Projections of COVID-19 in US
Authors: Kefayati Sarah , Roberts Fred , Pethe Sayali , Liu Xuan , Huang Hu , Gopalakrishnan Vishrawas , Madan Piyush , Hu Jianying , Chakraborty Prithwish , Srinivasan Raman , Deshpande Ajay , Jackson Gretchen 
Published: September 2020

ABSTRACTEpidemiological models have provided valuable information for the outlook of COVID-19 pandemic and relative impact of different mitigation scenarios. However, more accurate forecasts are often needed at near term for planning and staffing. We present our early results from a systemic analysis of short-term adjustment of epidemiological modeling of COVID 19 pandemic in US during March-April 2020. Our analysis includes the importance of various types of features for short term adjustment of the predictions. In addition, we explore the potential of data augmentation to address the data limitation for an emerging pandemic. Following published literature, we employ data augmentation via clustering of regions and evaluate a number of clustering strategies to identify early patterns from the data.From our early analysis, we used CovidActNow as our underlying epidemiological model and found that the most impactful features for the one-day prediction horizon are population density, workers in commuting flow, number of deaths in the day prior to prediction date, and the autoregressive features of new COVID-19 cases from three previous dates of the prediction. Interestingly, we also found that counties clustered with New York County resulted in best preforming model with maximum of R2= 0.90 and minimum of R2=0.85 for state-based and COVID-based clustering strategy, respectively.
Whole-Exome sequencing identifies a Type 2 Diabetes candidate mutation inPTPRF
Authors: Toonen Erik J.M. , Kwint Michael , Hoischen Alexander , Tack Cees J. 
Published: September 2020

AbstractObjectivesIdentification of genetic factors involved in Type 2 diabetes mellitus (T2DM) has been challenging. While genome-wide association studies (GWAS) have identified over 60 loci associated with T2DM, these variants only explain a small proportion of the total heritability of the disease. Whole-exome sequencing has become a powerful approach to identify genetic variants that are not captured by GWAS. We applied exome sequencing to identify causal genetic variants in a family with a 2-generation history of T2DM characterized by substantial insulin resistance, hypertension and isolated hypertriglyceridemia. Methods: Exome sequencing was performed on genomic DNA of two affected family members. Twenty-four identified variants that were present in both family members were further tested for segregation in all other family members by Sanger sequencing. Results: Three rare missense variants, located in the genesPTPRF, FUCA1andFBXO30, were present in all affected family members but also in one unaffected family member. Protein-protein interaction analysis showed thatPTPRFstrongly interacts with several members of the insulin signaling pathway. Conclusions: Our results suggest that the variant in thePTPRFgene might be causal for an unusual T2DM subtype that is characterized by a severe insulin resistance and isolated hypertriglyceridemia.
Spatial and temporal invasion dynamics of the 2014-2017 Zika and chikungunya epidemics in Colombia
Authors: Charniga Kelly , Cucunubá Zulma M. , Mercado Marcela , Prieto Franklyn , Ospina Martha , Nouvellet Pierre , Donnelly Christl A. 
Published: September 2020

AbstractZika virus (ZIKV) and chikungunya virus (CHIKV) were recently introduced into the Americas resulting in significant disease burdens. Understanding their spatial and temporal dynamics at the subnational level is key to informing surveillance and preparedness for future epidemics. We analyzed anonymized line list data on approximately 105,000 Zika virus disease and 412,000 chikungunya fever suspected and laboratory-confirmed cases during the 2014-2017 epidemics. We first determined the week of invasion in each city. Out of 1,122, 288 cities met criteria for epidemic invasion by ZIKA and 338 cities by CHIKV. We estimated that the geographic origin of both epidemics was located in Barranquilla, north Colombia. Using gravity models, we assessed the spatial and temporal invasion dynamics of both viruses to analyze transmission between cities. Invasion risk was best captured when accounting for geographic distance and intermediate levels of density dependence. Although a few long-distance invasion events occurred at the beginning of the epidemics, an estimated distance power of 1.7 (95% CrI: 1.5-2.0) suggests that spatial spread was primarily driven by short-distance transmission. Cities with large populations were more likely to spread disease than cities with smaller populations. Similarities between the epidemics included having the same estimated geographic origin and having the same five parameters estimated in the best-fitting models. ZIKV spread considerably faster than CHIKV.Author summaryUnderstanding the spread of infectious diseases across space and time is critical for preparedness, designing interventions, and elucidating mechanisms underlying transmission. We analyzed human case data from over 500,000 reported cases to investigate the spread of the recent Zika virus (ZIKV) and chikungunya virus (CHIKV) epidemics in Colombia. Both viruses were introduced into northern Colombia. We found that intermediate levels of density dependence best described transmission and that transmission mainly occurred over short distances. Our results highlight similarities and key differences between the ZIKV and CHIKV epidemics in Colombia, which can be used to anticipate future epidemic waves and prioritize cities for active surveillance and targeted interventions.
SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19
Authors: Dashti Hesam , Roche Elise C. , Bates David William , Mora Samia , Demler Olga 
Published: September 2020

AbstractAlthough models have been developed for predicting severity of COVID-19 based on the medical history of patients, simplified risk prediction models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic health records were queried from 02/26/2020 to 07/14/2020 to construct derivation and validation cohorts. The derivation cohort was used to fit a generalized linear model for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. On the validation cohort, the model resulted in c-statistics of 0.77 [95% CI: 0.73-0.80] for hospitalization outcome, and 0.72 [95% CI: 0.69-0.74] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, black ethnicity, lower socioeconomic status, and current/past smoking status. The model can be applied to predict risk of hospitalization and mortality, and could aid decision making when detailed medical history of patients is not easily available.
Diagnosing Community-Acquired Pneumonia: diagnostic accuracy study of a cough-centred algorithm for use in primary and acute-care consultations
Authors: Porter Paul , Brisbane Joanna , Abeyratne Udantha , Bear Natasha , Wood Javan , Peltonen Vesa , Della Phillip , Smith Claire , Claxton Scott 
Published: September 2020

ABSTRACTBackgroundCommunity-acquired pneumonia (CAP) is an essential consideration in patients presenting to primary care with respiratory symptoms; however, accurate diagnosis is difficult when clinical and radiologic examinations are not possible, such as during telehealth consultations.AimTo develop and test a smartphone-based algorithm for diagnosing CAP without need for clinical examination or radiology inputs.Design and SettingA prospective cohort study using data from subjects aged over 12 years presenting with acute respiratory symptoms to a hospital in Western Australia.MethodFive cough audio-segments were recorded and four patient-reported symptoms (fever, acute cough, productive cough, age) were analysed by the smartphone-based algorithm to generate an immediate diagnostic output for CAP. We recruited independent cohorts to train and test the accuracy of the algorithm.Diagnostic agreement was calculated against the confirmed discharge diagnosis of CAP by specialist physicians. Specialist radiologists reported medical imaging.ResultsThe algorithm had high percent agreement (PA) with the clinical diagnosis of CAP in the total cohort (n=322, Positive PA=86%, Negative PA=86%, AUC=0.95); in subjects 22-65 years (n=192, PPA=86%, NPA=87%, AUC=0.94) and in subjects >65 years (n=86, PPA=86%, NPA=87.5%, AUC=0.94). Agreement was preserved across CAP severity: 85% (80/94) of subjects with CRB-65 scores 1-2, and 87% (57/65) with a score of 0, were correctly diagnosed by the algorithm.ConclusionThe algorithm provides rapid and accurate diagnosis of CAP. It offers improved accuracy over current protocols when clinical evaluation is difficult. It provides increased capabilities for primary and acute care, including telehealth services, required during the COVID-19 pandemic.How this fits in?Diagnosis of community-acquired pneumonia (CAP) in the primary care setting relies upon the identification of clinical features or abnormal vital signs during a clinical examination. We have developed a smartphone-based algorithm which removes the requirement for in-person consultation and provides high-diagnostic agreement with specialist diagnosis of CAP. The algorithm requires the input of five cough-sound segments and four patient-reported symptoms and provides a result in less than one minute. With increasing momentum towards digital-first care under the NHS, tools such as this which allow remote deployment are likely to find increased merit.