bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Impact of Donor Asphyxiation or Drowning on Pediatric Lung Transplant Recipients
Authors: Seese Laura , Kilic Arman , Turbendian Harma K. , Sanchez Pablo G. , Diaz-Castrillon Carlos E. , Morell Victor O. 
Published: April 2020

Background.
Donors with drowning or asphyxiation (DA) as a mechanism of death (MOD) are considered high risk in pediatric lung transplantation. We sought to evaluate whether recipients of DA donors had negatively impacted outcomes.

Methods.
Pediatric recipients recorded in the United Network for Organ Sharing registry between 2000 and 2019 were included. Primary stratification was donor MOD. Propensity matching with a 1:1 ratio was performed to balance the DA and non-DA MOD donor cohorts. Cox multivariable regression was used to determine the risk-adjusted impact of donor MOD. A subanalysis of the effect of lung allocation score was also evaluated.

Results.
A total of 1016 patients underwent bilateral lung transplantation during the study period, including 888 (85.6%) from non-DA donors and 128 (14.4%) from DA donors. Survival at 90 days, 1 year, and 2 years were similar in the matched and unmatched cohorts regardless of the donor MOD. Moreover, separate risk-adjusted analysis of drowning and asphyxiated donors was similar to other MOD donors at 30 days, 1 year, and 5 years. Similar survival findings persisted regardless of pretransplant lung allocation score. Although the rates of posttransplant stroke (1.0% versus 3.1%, P = 0.04) and the length of hospital stay (19 versus 22 d, P = 0.004) were elevated in the unmatched DA MOD recipients, these differences were mitigated after propensity matching.

Conclusions.
This study evaluated the impact of DA MOD donors in pediatric lung transplant recipients and found similar rates of complications and survival in a propensity-matched cohort. These data collectively support the consideration of DA MOD donors for use in pediatric lung transplantation.
A Practical Risk-Score for Early Prediction of Neurological Outcome after Out-of-Hospital Cardiac Arrest –MIRA2CLE2
Authors: Pareek Nilesh , Kordis Peter , Beckley-Hoelscher Nicholas , Pimenta Dominic , Kocjancic Spela Tadel , Jazbec Anja , Nevett Joanne , Fothergill Rachael , Kalra Sundeep , Lockie Tim , Shah Ajay M. , Byrne Jonathan , Noc Marko , MacCarthy Philip 
Published: April 2020

AimsThe purpose of this study was to develop a practical risk−score to predict poor neurological outcome after out−of−hospital cardiac arrest (OOHCA) for use on arrival to a Heart Attack Centre.Methods and ResultsBetween May 2012 and December 2017, 1055 patients had OOHCA in our region, of whom 373 patients were included in the King's Out of Hospital Cardiac Arrest Registry (KOCAR). We performed prediction modelling with multi-variable logistic regression to identify factors independently predictive of the primary outcome in order to derive a risk score. This was externally validated in two independent cohorts comprising 474 patients. The primary outcome was poor neurological function at 6−month follow−up (Cerebral Performance Category 3-−). Seven independent variables for prediction of outcome were identified: Missed (Unwitnessed) arrest, Initial non-shockable rhythm, non-Reactivity of pupils, Age, Changing intra-arrest rhythms, Low pH<;7.20 and Epinephrine administration. From these variables, the MIRA2CLE2 score was developed which had an AUC of 0.90 in the development and 0.85 and 0.89 in the validation cohorts. 3 risk groups of the MIRA2CLE2 were defined − Low risk (≤2−5.6% risk of poor outcome; Intermediate risk (3−4−55.4% of poor outcome) and high risk (≥5−92.3% risk of poor outcome). The risk-score performance was equivalent in a sub-group of patients referred for early angiography and revascularisation where appropriate.ConclusionsThe MIRA2CLE2 score is a practical risk score for early accurate prediction of poor neurological outcome after OOHCA, which has been developed for simplicity of use on admission to a Heart Attack Centre.
Epidemiological characteristics of an outbreak of Coronavirus Disease 2019 in the Philippines
Authors: Alipio Mark M. , Pregoner Joseph Dave M. 
Published: April 2020

AbstractThe outbreak of Coronavirus disease 2019 (Covid-2019) is a source of great concern in the Philippines. In this paper, we described the epidemiological characteristics of the laboratory-confirmed patients with Covid-2019 in the Philippines as of April 3, 2020 and provided recommendations on how to limit the spread of the disease. Data from the DOH NCOV tracker and University of the Philippines’ Covid-2019 tracker were extracted, from its initiation (January 30, 2020) until the most recent situation report (April 3, 2020). The total number of cases and deaths were stratified by sex, age, and region of the Philippines. Descriptive statistics were used to analyze the demographic profile of the confirmed cases. Case fatality rate, in percent, was calculated by dividing the total number of deaths to the total number of confirmed cases. Results revealed that a total of 3,018 cases of Covid-2019 spread were confirmed across 17 regions in the Philippines. These cases occurred over the course of 73 days through person-to-person transmission, highlighting an extremely high infectivity rate. The 144 deaths accounted for, equate to 4.51 case fatality rate, seemingly lower compared to its predecessors, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), but higher compared to that of United States of America, Germany, mainland China, and neighboring Southeast Asian countries such as Malaysia, Singapore, Brunei, and Thailand. Of the 3,018 confirmed cases, majority were male, elderly, and diagnosed in Metro Manila region. Case fatality rates were higher in male and highest among elderly and Filipinos in the Ilocos region. With the surge on the number of cases, precautionary measures should remain a responsibility, and protocols for prevention need to be set. Adherence to infection control guidelines such as but not limited to frequently handwashing for at least 20 seconds, observing coughing etiquette, wearing of masks, and social distancing should be maintained in order to contain the disease.
Characteristics and outcomes of a cohort of SARS-CoV-2 patients in the Province of Reggio Emilia, Italy
Authors: Rossi Paolo Giorgi , Marino Massimiliano , Formisano Debora , Venturelli Francesco , Vicentini Massimo , Grilli Roberto ,   the Reggio Emilia COVID-19 Working Group
Published: April 2020

AbstractObjectivesTo describe the age- and sex-specific prevalence of SARS-CoV-2 disease (COVID-19) and its prognostic factors.DesignPopulation-based prospective cohort study on archive data.SettingPreventive services and hospital care in the province of Reggio Emilia, Northern Italy.ParticipantsAll 2653 symptomatic patients who tested positive for SARS-CoV-2 from February 27 to April 2, 2020 in the province of Reggio Emilia.Main outcome measuresHospitalization and death up to April 2, 2020.ResultsFemales had higher prevalence of infection than males below age 50 (2.61 vs. 1.84 ‰), but lower in older ages (16.49 vs. 20.86 ‰ over age 80). Case fatality rate reached 20.7% (22/106) in cases with more than 4 weeks follow up. After adjusting for age and comorbidities, men had a higher risk of hospitalization (hazard ratio (HR) 1.4 95% confidence interval (95% CI) 1.2 to 1.6) and of death (HR 1.6, 95% CI 1.2 to 2.1). Patients over age 80 compared to < age 50 had HR 7.1 (95% CI 5.4 to 9.3) and HR 27.8 (95% CI 12.5 to 61.7) for hospitalization and death, respectively. Immigrants had a higher risk of hospitalization (HR 1.3, 95% CI 0.99 to 1.81) than Italians and a similar risk of death. Risk of hospitalization and of death were higher in patients with heart failure (HR 1.6, 95% CI 1.2 to 2.1and HR 2.3, 95% CI 1.6 to 3.2, respectively), arrhythmia (HR 1.5, 95% CI 1.2 to 1.9 and HR 1.8, 95% CI 1.3 to 2.5, respectively), dementia (HR 1.2, 95% CI 0.9 to 1.8 and HR 1.8, 95% CI 1.1 to 2.8, respectively), ischemic heart disease (HR 1.3, 95% CI 1.0 to 1.7 and HR 1.7, 95% CI 1.2 to 2.5, respectively), diabetes (HR 1.5, 95% CI 1.3 to 1.9 and HR 1.6, 95% CI 1.1 to 2.2, respectively), and hypertensions(HR 1.4, 95% CI 1.2 to 2.6 and HR 1.6, 95% CI 1.2 to 2.1, respectively), while COPD increased the risk of hospitalization (HR 1.9, 95% CI 1.4 to 2.5) but not of death (HR 1.1, 95% CI 0.7 to 1.7). Previous use of ACE inhibitors has no effect on risk of death (HR 0.97, 95% CI 0.69 to 1.34)ConclusionsThe mechanisms underlying these associations are mostly unknown. A deeper understanding of the causal chain from infection, disease onset, and immune response to outcomes may explain how these prognostic factors act.
Smoking is Associated with COVID-19 Progression: A Meta-Analysis
Authors: Patanavanich Roengrudee , Glantz Stanton A. 
Published: April 2020

ABSTRACTObjectiveTo determine the association between smoking and progression of COVID-19.DesignA meta-analysis of 12 published papers.Data SourcePubMed database was searched on April 6, 2020.Eligibility criteria and data analysisWe included studies reporting smoking behavior of COVID-19 patients and progression of disease. Search terms included “smoking”, “smoker*”, “characteristics”, “risk factors”, “outcomes”, and “COVID-19”, “COVID”, “coronavirus”, “sar cov-2”, “sar cov 2”. There were no language limitations. One author extracted information for each study, screened the abstract or the full text, with questions resolved through discussion among both authors. A random effects meta-analysis was applied.Main Outcome MeasuresThe study outcome was progression of COVID-19 among people who already had the disease.ResultsWe identified 12 papers with a total of 9,025 COVID-19 patients, 878 (9.7%) with severe disease and 495 with a history of smoking (5.5%). The meta-analysis showed a significant association between smoking and progression of COVID-19 (OR 2.25, 95% CI 1.49-3.39, p=0.001). Limitations in the 12 papers suggest that the actual risk of smoking may be higher.ConclusionsSmoking is a risk factor for progression of COVID-19, with smokers having higher odds of COVID-19 progression than never smokers. Physicians and public health professionals should collect data on smoking as part of clinical management and add smoking cessation to the list of practices to blunt the COVID-19 pandemic.What is already known on this topicSmoking increases risk and severity of pulmonary infections because of damage to upper airways and a decrease in pulmonary immune function.What this study addsSmoking is associated with COVID-19 severity.Smoking history should be part of clinical management of COVID-19 patients and cessation should be added to the list of practices to blunt the COVID-19 pandemic.
The Conceptualization and Preliminary Evaluation of a Dynamic, Mechanistic Mathematical Model to Assess the Water Footprint of Beef Cattle Production
Authors: Menendez Hector M. , Atzori Alberto S. , Tedeschi Luis O. 
Published: April 2020

AbstractThe water footprint assessment method has helped to bring livestock water use to the forefront of research to address water challenges under the ecological footprint perspective. The current assessment methods of water use make a meaningful assessment of livestock water use difficult as they are mainly static, thus poorly adaptable to understand future scenarios of water use and requirements. They lack the integration of fundamental ruminant nutrition and growth equations within a dynamic context that accounts for short and long-term behavior and time delays associated with economically important beef producing areas. This study utilized the System Dynamics methodology to conceptualize a water footprint for ruminants within a dynamic and mechanistic modeling framework. The problem of beef cattle livestock water footprint assessment was articulated, and a dynamic hypothesis was formed to represent the Texas livestock water use system as the initial step in developing the Texas Beef Water Footprint model (TXWFB). The fulfillment of the dynamic hypothesis required the development of three causal loop diagrams (CLD): cattle population, growth and nutrition, and the livestock water footprint. The CLD provided a framework that captured the daily water footprint of beef (WFB) of the cow-calf, stocker, and feedlot phases and the entire beef supply chain. Preliminary simulations captured the oscillatory behavior of the Texas cattle population and overshoot and collapse behavior, under conditions when regional livestock water resources became scarce. Sensitivity analysis from the hypothesized CLD structures indicated that forage quality was less of an impact on the daily WFBof each cattle phase compared to the use of high concentrate feeds. This study provided a framework concept for the development of a dynamic water footprint model for Texan’s beef cattle production and water sustainability.
Flexible open-source automation for robotic bioengineering
Authors: Chory Emma J , Gretton Dana W , DeBenedictis Erika A , Esvelt Kevin M 
Published: April 2020

INTRODUCTIONLiquid handling robots have become a biotechnology staple1,2, allowing laborious or repetitive protocols to be executed in high-throughput. However, software narrowly designed to automate traditional hand-pipetting protocols often struggles to harness the full capabilities of robotic manipulation. Here we present Pyhamilton, an open-source Python package that eliminates these constraints, enabling experiments that could never be done by hand. We used Pyhamilton to double the speed of automated bacterial assays over current software and execute complex pipetting patterns to simulate population dynamics. Next, we incorporated feedback-control to maintain hundreds of remotely monitored bacterial cultures in log-phase growth without user intervention. Finally, we applied these capabilities to comprehensively optimize bioreactor protein production by maintaining and monitoring fluorescent protein expression of nearly 500 different continuous cultures to explore the carbon, nitrogen, and phosphorus fitness landscape. Our results demonstrate Pyhamilton’s empowerment of existing hardware to new applications ranging from biomanufacturing to fundamental biology.
From Value to Saliency: Neural Computations of Subjective Value under Uncertainty in PTSD
Authors: Jia Ruonan , Ruderman Lital , Gordon Charles , Ehrlich Daniel , Horvath Mark , Mirchandani Serena , DeFontes Clara , Southwick Steven , Krystal John H. , Harpaz-Rotem Ilan , Levy Ifat 
Published: April 2020

AbstractMilitary personnel engaged in combat are vulnerable to Posttraumatic Stress Disorder (PTSD), following traumatic experiences in the battlefield. Prior research has mostly employed fear-related paradigms to unravel neural underpinnings of fear dysregulation in individuals with PTSD. The ability to acquire and update fear responses depends critically on the individual’s ability to cope with uncertainty, yet the role of individual uncertainty attitudes in the development of trauma-related psychopathology has hardly been examined. Here, we investigated the association between PTSD-related alterations and the subjective valuation of uncertain outcomes during decision-making. We used a monetary gambling paradigm inspired by behavioral economics in conjunction with fMRI and explored neural markers of both vulnerability and resilience to PTSD in a group of combat veterans. Behaviorally, PTSD symptom severity was associated with increased aversion to uncertainty. Neurally, activity in the ventromedial prefrontal cortex (vmPFC) during valuation of uncertain options was associated with PTSD symptoms, an effect which was specifically driven by numbing symptoms. Moreover, the neural encoding of the subjective value of those uncertain options was markedly different in the brains of veterans diagnosed with PTSD, compared to veterans who experienced trauma but did not develop PTSD. Most notably, veterans with PTSD exhibited enhanced representations of the saliency of rewards and punishments in the neural valuation system, especially in ventral striatum, compared with trauma-exposed controls. Our results point to a link between the function of the valuation system under uncertainty and the development and maintenance of PTSD symptoms, and stress the significance of studying reward processes in PTSD.
Interactive dynamics of matrix adhesion and reaction-diffusion predict diverse multiscale strategies of cancer cell invasion
Authors: Pramanik Durjay , Jolly Mohit Kumar , Bhat Ramray 
Published: April 2020

AbstractThe metastasis of malignant epithelial tumors begins with the egress of transformed cells from the confines of their basement membrane to their surrounding collagenous stroma. Invasion can be morphologically diverse, ranging from dispersed mesenchymal cells to multicellular collectives. When breast cancer cells are cultured within basement membrane-like matrix (BM), or Type 1 collagen, or a combination of both, they exhibit collective-, dispersed mesenchymal-, and hybrid collective-dispersed (multiscale) invasion, respectively. In this paper, we asked how distinct these invasive modes are with respect to the cellular and microenvironmental cues that drive them. A rigorous computational exploration of invasion was performed within an experimentally motivated Cellular Potts-based modeling environment. The model comprises of adhesive interactions between cancer cells, BM- and collagen-like extracellular matrix (ECM), and reaction-diffusion-based remodeling of ECM. The model outputs were parameters cognate to dispersed- and collective- invasion. Input sweeps gave rise to a spatial output distribution that consisted of dispersed-, collective- and multiscale- invasion. K-means clustering of the output distribution followed by silhouette analysis revealed three optimal clusters: one signifying indolent invasion and two representing multiscale invasions, which we call collective-multiscale (CMI), and dispersed multiscale invasion (DMI), respectively. Constructing input-output mapped phenotypic spaces suggested that adhesion to BM- and collagen- matrix specify CMI and DMI respectively. Parameter perturbations confirmed these associations and revealed how the cellular phenotype may transition between the three states. Our systems-level analysis provides quantitative insights into how the diversity in matrix microenvironments may steer invasion into distinct phenotypic modes during metastasis.
A pharmacological interactome platform for discovery of pain mechanisms and targets
Authors: Wangzhou Andi , Paige Candler , Neerukonda Sanjay V , Dussor Gregory , Ray Pradipta R , Price Theodore J 
Published: April 2020

AbstractCells communicate with each other through ligand and receptor interactions. In the case of the peripheral nervous system, these ligand-receptor interactions shape sensory experience. In disease states, such as chronic pain, these ligand-receptor interactions can change the excitability of target neurons augmenting nociceptive input to the CNS. While the importance of these cell to neuron interactions are widely acknowledged, they have not been thoroughly characterized. We sought to address this by cataloging how peripheral cell types interact with sensory neurons in the dorsal root ganglion (DRG) using RNA sequencing datasets. Using single cell sequencing datasets from mouse we created a comprehensive interactome map for how mammalian sensory neurons interact with 42 peripheral cell types. We used this knowledge base to understand how specific cell types and sensory neurons interact in disease states. In mouse datasets, we created an interactome of colonic enteric glial cells in the naïve and inflamed state with sensory neurons that specifically innervate this tissue. In human datasets, we created interactomes of knee joint macrophages from rheumatoid arthritis patients and pancreatic cancer samples with human DRG. Collectively, these interactomes highlight ligand-receptor interactions in mouse models and human disease states that reflect the complexity of cell to neuron signaling in chronic pain states. These interactomes also highlight therapeutic targets, such as the epidermal growth factor receptor (EGFR), which was a common interaction point emerging from our studies.
Toxoplasma gondiico-opts the unfolded protein response to enhance migration and dissemination of infected host cells
Authors: Augusto Leonardo , Martynowicz Jennifer , Amin Parth H. , Alakhras Nada S. , Kaplan Mark H. , Wek Ronald C. , Sullivan William J. 
Published: April 2020

AbstractToxoplasma gondiiis an intracellular parasite that reconfigures its host cell to promote pathogenesis. One consequence ofToxoplasmaparasitism is increased migratory activity of host cells, which facilitates dissemination. Here we show thatToxoplasmatriggers the unfolded protein response (UPR) in host cells through calcium release from the endoplasmic reticulum (ER). We further found that host IRE1, an ER stress sensor protein activated duringToxoplasmainfection, also plays a noncanonical role in actin remodeling by binding filamin A in infected cells. By inducing cytoskeletal remodeling via IRE1 oligomerization in host cells,Toxoplasmaenhances host cell migrationin vitroand dissemination of the parasite to host organsin vivo. Our study identifies novel mechanisms used byToxoplasmato induce dissemination of infected cells, providing new insights into strategies for treatment of toxoplasmosis.ImportanceCells that are infected with the parasiteToxoplasma gondiiexhibit heightened migratory activity, which facilitates dissemination of the infection throughout the body. In this study, we identify a new mechanism used byToxoplasmato hijack its host cell and increase its mobility. We further show that the ability ofToxoplasmato increase host cell migration does not involve the enzymatic activity of IRE1, but rather IRE1 engagement with actin cytoskeletal remodeling. Depletion of IRE1 from infected host cells reduces their migration in vitro and significantly hinders dissemination ofToxoplasmain vivo. Our findings reveal a new mechanism underlying host-pathogen interactions, demonstrating how host cells are co-opted to spread a persistent infection around the body.