bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Computational Model to Predict Brain Trauma Outcome in the Intensive Care Unit
Authors: Palepu Anil K. , Murali Aditya , Ballard Jenna L. , Li Robert , Ramesh Samiksha , Nguyen Hieu , Kim Hanbiehn , Sarma Sridevi , Suarez Jose I. , Stevens Robert D. 
Published: November 2020

AbstractObjectivesTo predict short-term outcomes of critically ill patients with traumatic brain injury (TBI) by training machine learning classifiers on two large intensive care databasesDesignRetrospective analysis of observational data.PatientsPatients in the multicenter Philips eICU and single-center Medical Information Mart for Intensive Care–III (MIMIC-III) databases with a primary admission diagnosis of TBI, who were in intensive care for over 24 hours.InterventionsNone.Measurements and Main ResultsWe identified 1,689 and 126 qualifying TBI patients in eICU and MIMIC-III, respectively. Generalized Linear Models were used to predict mortality and neurological function at ICU discharge using features derived from clinical, laboratory, medication and physiological time series data obtained in the first 24 hours after ICU admission. Models were trained, tested and validated in eICU then validated externally in MIMIC-III. Model discrimination determined by area under the receiver operating characteristic curve (AUROC) analysis was 0.903 and 0.874 for mortality and neurological function, respectively. Performance was maintained when the models were tested in the independent MIMIC-III dataset (AUROC 0.958 and 0.878 for mortality and neurological function, respectively).ConclusionsComputational models trained with data available in the first 24 h after admission accurately predict discharge outcomes in ICU stratum TBI patients.
Loneliness among older adults in the community during COVID-19
Authors: Savage Rachel D. , Wu Wei , Li Joyce , Lawson Andrea , Bronskill Susan E. , Chamberlain Stephanie A. , Grieve Jim , Gruneir Andrea , Reppas-Rindlisbacher Christina , Stall Nathan M. , Rochon Paula A. 
Published: November 2020

AbstractObjectivePhysical distancing and stay-at-home measures implemented to slow transmission of novel coronavirus disease (COVID-19) may intensify feelings of loneliness in older adults, especially those living alone. Our aim was to characterize the extent of loneliness in a sample of older adults living in the community and assess characteristics associated with loneliness.DesignOnline cross-sectional survey between May 6 and May 19, 2020SettingOntario, CanadaParticipantsConvenience sample of the members of a national retired educators’ organization.Primary outcome measuresSelf-reported loneliness, including differences between women and men.Results4879 respondents (71.0% women; 67.4% 65-79 years) reported that in the preceding week, 43.1% felt lonely at least some of the time, including 8.3% that felt lonely always or often. Women had increased odds of loneliness compared to men, whether living alone (adjusted Odds Ratio (aOR) 1.52 [95% Confidence Interval (CI) 1.13-2.04]) or with others (2.44 [95% CI 2.04-2.92]). Increasing age group decreased the odds of loneliness (aOR 0.69 [95% CI 0.59-0.81] 65-79 years and 0.50 [95% CI 0.39-0.65] 80+ years compared to <65 years). Living alone was associated with loneliness, with a greater association in men (aOR 4.26 [95% CI 3.15-5.76]) than women (aOR 2.65 [95% CI 2.26-3.11]). Other factors associated with loneliness included: fair or poor health (aOR 1.93 [95% CI 1.54-2.41]), being a caregiver (aOR 1.18 [95% CI 1.02-1.37]), receiving care (aOR 1.47 [95% CI 1.19-1.81]), high concern for the pandemic (aOR 1.55 [95% CI 1.31-1.84]), not experiencing positive effects of pandemic distancing measures (aOR 1.94 [95% CI 1.62-2.32]), and changes to daily routine (aOR 2.81 [95% CI 1.96-4.03]).ConclusionsWhile many older adults reported feeling lonely during COVID-19, several characteristics – such as being female and living alone – increased the odds of loneliness. These characteristics may help identify priorities for targeting interventions to reduce loneliness.Strengths and limitations of this studyThis survey study leveraged a strong community-based partnership to obtain timely data from a large sample of older Canadians on the impacts of COVID-19.This study identified several characteristics that increased the odds of loneliness, which may help to identify priorities for targeted interventions to reduce loneliness.The data were based on a convenience sample of retired, educational staff, who are not fully representative of the Canadian population. The perspectives of vulnerable groups who may be at greater risk for loneliness (e.g. those with severe mental health illness, low income, no home internet access, etc.) are likely underrepresented in this sample.
Reducing travel-related SARS-CoV-2 transmission with layered mitigation measures: Symptom monitoring, quarantine, and testing
Authors: Johansson Michael A. , Wolford Hannah , Paul Prabasaj , Diaz Pamela S. , Chen Tai-Ho , Brown Clive M. , Cetron Martin S. , Alvarado-Ramy Francisco 
Published: November 2020

AbstractBalancing the control of SARS-CoV-2 transmission with the resumption of travel is a global priority. Current recommendations include mitigation measures before, during, and after travel. Pre- and post-travel strategies including symptom monitoring, testing, and quarantine can be combined in multiple ways considering different trade-offs in feasibility, adherence, effectiveness, cost and adverse consequences. Here we use a mathematical model to analyze the expected effectiveness of symptom monitoring, testing, and quarantine under different estimates of the infectious period, test-positivity relative to time of infection, and test sensitivity to reduce the risk of transmission from infected travelers during and after travel. If infection occurs 0-7 days prior to travel, immediate isolation following symptom onset prior to or during travel reduces risk of transmission while traveling by 26-30%. Pre-departure testing can further reduce risk if testing is close to the time of departure. For example, testing on the day of departure can reduce risk while traveling by 37-61%. For transmission risk after travel with infection time up to 7 days prior to arrival at the destination, isolation based on symptom monitoring reduced introduction risk at the destination by 42-56%. A 14-day quarantine after arrival, without symptom monitoring or testing, can reduce risk by 97-100% on its own. However, a shorter quarantine of 7 days combined with symptom monitoring and a test on day 3-4 after arrival is also effective (95-99%) at reducing introduction risk and is less burdensome, which may improve adherence. To reduce the risk of introduction without quarantine, optimal test timing after arrival is close to the time of arrival; with effective quarantine after arrival, testing a few days later optimizes sensitivity to detect those infected immediately before or while traveling. These measures can complement recommendations such as social distancing, using masks, and hand hygiene, to further reduce risk during and after travel.
Evolution of Human Respiratory Virus Epidemics
Authors: Rochman Nash D. , Wolf Yuri I. , Koonin Eugene V. 
Published: November 2020

AbstractBackgroundWhile pathogens often evolve towards reduced virulence, many counterexamples are evident. When faced with a new pathogen, such as SARS-CoV-2, it is highly desirable to be able to forecast the case fatality rate (CFR) into the future. Considerable effort has been invested towards the development of a mathematical framework for predicting virulence evolution. Although these approaches accurately recapitulate some complex outcomes, most rely on an assumed trade-off between mortality and infectivity. It is often impractical to empirically validate this constraint for human pathogens.ResultsUsing a compartment model with parameters tuning the degree to which symptomatic individuals are isolated and the duration of immunity, we reveal kinetic constraints where the variation of multiple parameters in concert leads to decreased virulence and increased pathogen fitness, whereas independent variation of the parameters decreases pathogen fitness. Smallpox, SARS-CoV-2, and Influenza are analyzed as diverse representatives of human respiratory viruses. We show that highly virulent viruses, such as Smallpox, are likely often constrained by host behavior, whereas moderately virulent viruses, such as SARS-CoV-2, appear to be typically constrained by the relationship between the duration of immunity and CFR.ConclusionsThe evolution of human respiratory epidemics appears to be often kinetically constrained and a reduction in virulence should not be assumed. Our findings imply that, without continued public health intervention, SARS-CoV-2 is likely to continue presenting a substantial disease burden. The existence of a parameter regime admitting endemic equilibrium suggests that herd immunity is unachievable. However, we demonstrate that even partial isolation of symptomatic individuals can have a major effect not only by reducing the number of fatalities in the short term but also by potentially changing the evolutionary trajectory of the virus towards reduced virulence.
Predicting heterogeneity in clone-specific therapeutic vulnerabilities using single-cell transcriptomic signatures
Authors: Suphavilai Chayaporn , Chia Shumei , Sharma Ankur , Tu Lorna , Da Silva Rafael Peres , Mongia Aanchal , DasGupta Ramanuj , Nagarajan Niranjan 
Published: November 2020

SummaryWhile understanding heterogeneity in molecular signatures across patients underpins precision oncology, there is increasing appreciation for taking intra-tumor heterogeneity into account. Single-cell RNA-seq (scRNA-seq) technologies have facilitated investigations into the role of intra-tumor transcriptomic heterogeneity (ITTH) in tumor biology and evolution, but their application toin silicomodels of drug response has not been explored. Based on large-scale analysis of cancer omics datasets, we highlight the utility of ITTH for predicting clinical outcomes. We then show that heterogeneous gene expression signatures obtained from scRNA-seq data can be accurately analyzed (80%) in a recommender system framework (CaDRReS-Sc) forin silicodrug response prediction. Patient-derived cell lines capturing transcriptomic heterogeneity from primary and metastatic tumors were used asin vitroproxies for validating monotherapy predictions (Pearson r>0.6), as well as optimal drug combinations to target different subclonal populations (>10% improvement). Applying CaDRReS-Sc to the increasing number of publicly available tumor scRNA-seq datasets can serve as anin silicoscreen for furtherin vitroandin vivodrug repurposing studies.Graphical abstractHighlightsLarge-scale analysis to establish the impact of transcriptomic heterogeneity within tumors on clinical outcomesCalibrated recommender system for drug response prediction based on single-cell RNA-seq data (CaDRReS-Sc)Prediction of drug response in patient-derived cell lines with transcriptomic heterogeneityIn silicoidentification of drug combinations that work based on clonal vulnerabilities
LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2
Authors: Li Sizhen , Zhang He , Zhang Liang , Liu Kaibo , Liu Boxiang , Mathews David H. , Huang Liang 
Published: November 2020

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length, and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scaleslinearlywith sequence length, enabling unprecedentedglobalstructural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurbo-Fold’s purelyin silicoprediction not only is close to experimentally-guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5’ and 3’ UTRs (∼29,800ntapart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies novel conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, siRNAs, CRISPR-Cas13 guide RNAs and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies, and will be a useful tool in fighting the current and future pandemics.Significance StatementConserved RNA structures are critical for designing diagnostic and therapeutic tools for many diseases including COVID-19. However, existing algorithms are much too slow to model the global structures of full-length RNA viral genomes. We present LinearTurboFold, a linear-time algorithm that is orders of magnitude faster, making it the first method to simultaneously fold and align whole genomes of SARS-CoV-2 variants, the longest known RNA virus (∼30 kilobases). Our work enables unprecedented global structural analysis and captures long-range interactions that are out of reach for existing algorithms but crucial for RNA functions. LinearTurboFold is a general technique for full-length genome studies and can help fight the current and future pandemics.
The anti-inflammatory peptide Catestatin blocks chemotaxis
Authors: Muntjewerff Elke M. , Parv Kristel , Mahata Sushil K. , Phillipson Mia , Christoffersson Gustaf , van den Bogaart Geert 
Published: November 2020

AbstractIncreased levels of the anti-inflammatory peptide catestatin (CST), a cleavage product of the pro-hormone chromogranin A, correlates with less severe outcomes in hypertension, colitis and diabetes. However, it is unknown how CST reduces the infiltration of monocytes and macrophages in inflamed tissues. Here, we report that CST blocks leukocyte migration towards inflammatory chemokines. Byin vitroandin vivomigration assays, we show that although CST itself is weakly chemotactic, it blocks migration of monocytes and granulocytes to inflammatory attracting factor CC-chemokine ligand 2 (CCL2) and macrophage inflammatory protein 2 (MIP-2). Moreover, it directs CX3CR1+macrophages away from pancreatic islets. These findings support the emerging notion that CST is a key anti-inflammatory modulator.
Beauty That Moves: Dance for Parkinson’s Effects on Affect, Self-Efficacy, Gait Symmetry and Dual Task Performance
Authors: Fontanesi Cecilia , DeSouza Joseph FX 
Published: November 2020

AbstractBackgroundPrevious studies have investigated the effects of dance interventions on Parkinson’s motor and non-motor symptoms in an effort to develop an integrated view of dance as a therapeutic intervention. This within-subject study questions whether dance can be simply considered a form of exercise by comparing a Dance for Parkinson’s class with a matched-intensity exercise session lacking dance elements like music, metaphorical language, and social reality of grace and beauty.MethodsIn this repeated-measure design, 7 adults with Parkinson’s were tested four times; (i) before and (ii) after a Dance for Parkinson’s class, as well as (iii) before and (iv) after a matched-intensity exercise session. Physiological measures included heart rate and electrodermal activity. Self-reported affect and body self-efficacy were collected. Gait symmetry and dual task cost were analyzed using the 6-minutes walking test (6MWT) and Timed-Up-and-Go test (TUG), respectively.ResultsAverage heart rate was the same for both conditions, while electrodermal activity was higher during Dance for Parkinson’s. Significant differences were found in body self-efficacy, beauty subscale, symmetry of gait, and dual task performance.ConclusionsDance, compared to an exercise intervention of matched intensity, yields different outcomes through the means of intrinsic artistic elements, which may influence affective responses, the experience of beauty, self-efficacy, and gait performance.
Rapid shift in microbial community structure in a neutral hydrothermal hot spring from Costa Rica
Authors: Rojas-Gätjens Diego , Arce-Rodríguez Alejandro , Puente-Sánchez Fernando , Avendaño Roberto , Libby Eduardo , Conejo-Barboza Geraldine , Mora-Amador Raul , Rojas Keilor , Pieper Dietmar H. , Chavarría Max 
Published: November 2020

AbstractIn this work, we characterize the geochemistry and microbial community of Bajo las Peñas, a neutral (pH 6.5-7.4), hot spring (T = 62.0-68.0°C) located near Turrialba Volcano, Costa Rica. The microbiota at its two sources belongs mainly to the family Aquificae, comprising OTUs closely related to the generaSulfurihydrogenibium,Thermosulfidibacter,ThermodesulfovibrioandThermocriniswhich is consistent with the presence of moderate levels of sulfate (243-284 mg/L) along the stream. We determined a dramatic shift in the microbial community just a few meters downstream of the sources of the hot spring (15-20 meters), with a change from sulfur related chemoautotrophic (e.g.Sulfurihydrogenibiumand an OTU closely related toThermodesulfovibrio) to chemoheterotrophic prokaryotes (e.g.Meiothermus,Nitrososphaera,Thermoflexus,Thermus). Thus, in this neutral hot spring, the first level of the trophic chain is associated with photosynthesis as well other anaerobic CO2fixing bacteria. Then, thermotolerant chemoheterotrophic bacteria colonize the environment to degrade organic matter and use fermentative products from the first level of the trophic chain. Our data demonstrate how quickly the microbial community of an ecosystem can change in response to environmental variables and sheds light on the microbial ecology of less common circumneutral pH hot springs.
Composition and acquisition of the microbiome in solitary, ground-nesting alkali bees
Authors: Kapheim Karen M. , Johnson Makenna M. , Jolley Maggi 
Published: November 2020

ABSTRACTIncreasing evidence suggests the microbiome plays an important role in bee ecology and health. However, the relationship between bees and their bacterial symbionts has only been explored in a handful of species. We characterized the microbiome across the life cycle of solitary, ground-nesting alkali bees (Nomia melanderi). We find that feeding status is a major determinant of microbiome composition. The microbiome of feeding larvae was similar to that of pollen provisions, but the microbiome of post-feeding larvae (pre-pupae) was similar to that of the brood cell walls and newly-emerged females. Feeding larvae and pollen provisions had the lowest beta diversity, suggesting the composition of larval diet is highly uniform. Comparisons between lab-reared, newly-emerged, and nesting adult females suggest that the hindgut bacterial community is largely shaped by the external environment. However, we also identified taxa that are likely acquired in the nest or which increase or decrease in relative abundance with age. Although Lactobacillus micheneri was highly prevalent in pollen provisions, it was only detected in one lab-reared female, suggesting it is primarily acquired from environmental sources. These results provide the foundation for future research on metagenomic function and development of probiotics for these native pollinators.
Clonal dynamics in early human embryogenesis inferred from somatic mutation
Authors: Park Seongyeol , Mali Nanda Maya , Kim Ryul , Choi Jeong-Woo , Lee Junehawk , Lim Joonoh , Park Jung Min , Park Jung Woo , Kim Donghyun , Kim Taewoo , Yi Kijong , Choi June Hyug , Kwon Seong Gyu , Hong Joo Hee , Youk Jeonghwan , An Yohan , Kim Su Yeon , Kim Moonkyu , Kim Dong Sun , Park Ji Young , Oh Ji Won , Ju Young Seok 
Published: November 2020

SummaryThe trillions of cells that constitute the human body are developed from a fertilized egg through embryogenesis. However, cellular dynamics and developmental outcomes of embryonic cells in humans remain to be largely unknown due to the technical and ethical challenges. Here, we explored whole-genomes of 334 single-cell expanded clones and targeted deep-sequences of 379 bulk tissues obtained from various anatomical locations from seven individuals. Using the discovered 1,688,652 somatic mutations as an intrinsic barcode, we reconstructed cellular phylogenetic trees that provide novel insights into early human embryogenesis. Our findings suggest (1) endogenous mutational rate that is higher in the first cell division of life but decreases to ~1 per cell per cell division later in life, (2) universal unequal contribution of early cells into embryo proper resulting from early cellular bottlenecks that stochastically separate epiblasts from embryonic cells (3) uneven differential outcomes of early cells into three germ layers, left-right and cranio-caudal tissues, (4) emergence of a few ancestral cells that will contribute to the substantial fraction of adult blood cells, and (5) presence of mitochondrial DNA heteroplasmy in the fertilized egg. Our approach additionally provides insights into the age-related mutational processes including UV-mediated mutagenesis and loss of chromosome X or Y in normal somatic cells. Taken together, this study scrutinized somatic mosaicism, clonal architecture, and cellular dynamics in human embryogenesis at an unprecedented level and provides a foundation for future studies to complete cellular phylogenies in human embryogenesis.