bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oxygenation Strategy During Acute Respiratory Failure in Critically-Ill Immunocompromised Patients
Authors: Lemiale Virginie , De Jong Audrey , Dumas Guillaume , Demoule Alexandre , Mokart Djamel , Pène Frederic , Kouatchet Achille , Bisbal Magali , Bruneel Fabrice , Lebert Christine , Vinatier Isabelle , Benoit Dominique , Meert Anne-Pascale , Jaber Samir , Darmon Michael , Azoulay Elie 
Published: July 2020

Objectives:
To assess the response to initial oxygenation strategy according to clinical variables available at admission.

Design:
Multicenter cohort study.

Setting:
Thirty French and Belgium medical ICU.

Subjects:
Immunocompromised patients with hypoxemic acute respiratory failure.

Interventions:
None.

Measurements and Main Results:
Data were extracted from the Groupe de Recherche en Reanimation Respiratoire du patient d'Onco-Hématologie database. Need for invasive mechanical ventilation was the primary endpoint. Secondary endpoint was day-28 mortality. Six-hundred forty-nine patients were included. First oxygenation strategies included standard oxygen (n = 245, 38%), noninvasive ventilation (n = 285; 44%), high-flow nasal cannula oxygen (n = 55; 8%), and noninvasive ventilation + high-flow nasal cannula oxygen (n = 64; 10%). Bilateral alveolar pattern (odds ratio = 1.67 [1.03–2.69]; p = 0.04), bacterial (odds ratio = 1.98 [1.07–3.65]; p = 0.03) or opportunistic infection (odds ratio = 4.75 [2.23–10.1]; p < 0.001), noninvasive ventilation use (odds ratio = 2.85 [1.73–4.70]; p < 0.001), Sequential Organ Failure Assessment score (odds ratio = 1.19 [1.10–1.28]; p < 0.001), and ratio of Pao
2 and Fio
2 less than 100 at ICU admission (odds ratio = 1.96 [1.27–3.02]; p = 0.0002) were independently associated with intubation rate. Day-28 mortality was independently associated with bacterial (odds ratio = 2.34 [1.10–4.97]; p = 0.03) or opportunistic infection (odds ratio = 4.96 [2.11–11.6]; p < 0.001), noninvasive ventilation use (odds ratio = 2.35 [1.35–4.09]; p = 0.003), Sequential Organ Failure Assessment score (odds ratio = 1.19 [1.10–1.28]; p < 0.001), and ratio of Pao
2 and Fio
2 less than 100 at ICU admission (odds ratio = 1.97 [1.26–3.09]; p = 0.003). High-flow nasal cannula oxygen use was neither associated with intubation nor mortality rates.

Conclusions:
Some clinical characteristics at ICU admission including etiology and severity of acute respiratory failure enable to identify patients at high risk for intubation.
Rise in Angiopoietin-2 Following Neonatal Cardiac Surgery Is Associated With Adverse Clinical Outcomes
Authors: Watkins Kimberly J. , Geisler Sarah , Doman Tammy , Orringer Matthew J. , Tracy Paloma , Yu Sunkyung , Wilder Nicole S. , Russell Mark W. 
Published: July 2020

Objectives:
Neonatal cardiac surgery for congenital cardiac defects is associated with significant morbidity and mortality, and there is a need for early identification of patients at highest risk of adverse outcomes. Because vascular endothelial injury mediates damage across organ systems, we measured serum biomarkers of endothelial injury in neonates following cardiopulmonary bypass and examined their associations with short-term outcomes.

Design:
Prospective cohort study.

Setting:
Pediatric cardiac ICU.

Patients:
Thirty neonates less than 2 weeks old undergoing repair of congenital cardiac defects with cardiopulmonary bypass.

Interventions:
None.

Measurements and Main Results:
Biomarkers of endothelial integrity, angiopoietin-1 and angiopoietin-2, were measured preoperatively and at 24 hours postoperatively. A composite adverse outcome was defined as any of the following: stroke, need for renal replacement therapy, extracorporeal membrane oxygenation support, cardiac arrest, or death. Associations of biomarkers with adverse outcomes were examined using Wilcoxon rank-sum test. There was an increase in angiopoietin-2 from preoperatively to 24 hours postoperatively (p < 0.0001) and a decrease in angiopoietin-1 from preoperatively to 24 hours postoperatively (p < 0.0001). Patients with greater rise in angiopoietin-2 from preoperatively to 24 hours postoperatively had greater risk of composite adverse outcome (p = 0.04). They had a trend toward higher Vasoactive-Inotropic Score (p = 0.06) and a higher prevalence of low cardiac output syndrome (p = 0.06). Twenty-four hour postoperative angiopoietin-2 level was associated with the composite adverse outcome (p = 0.03). The rise in angiopoietin-2 level from preoperatively to 24 hours postoperatively directly correlated with cardiopulmonary bypass duration (r = 0.47; p = 0.01).

Conclusions:
In neonatal cardiac surgery, longer duration of cardiopulmonary bypass is directly associated with greater endothelial injury as measured by increased serum levels of angiopoietin-2. Angiopoietin-2 levels 24 hours postoperatively were significantly associated with a composite adverse outcome. Postoperative angiopoietin-2 level may serve as an early indicator of patients in need of closer monitoring and protective intervention. Further research into endothelial protective strategies is warranted.
Conditioning open-label placebo: a pilot pharmacobehavioral approach for opioid dose reduction and pain control
Authors: Morales-Quezada Leon , Mesia-Toledo Ines , Estudillo-Guerra Anayali , O'Connor Kevin C. , Schneider Jeffrey C. , Sohn Douglas J. , Crandell David M. , Kaptchuk Ted , Zafonte Ross 
Published: July 2020

Introduction:
Opioid consumption for those in comprehensive inpatient rehabilitation units is high because of the complexity of their injuries. Notably, pain in rehabilitation leads to worsened clinical outcomes because of maladaptive behaviors and poor engagement during therapies. It is critical to developing evidence-based pharmacobehavioral interventions. Based on principles of classical conditioning, conditioning open-label placebo (COLP) is a promising approach for reducing opioid use in comprehensive inpatient rehabilitation, and this technique takes advantage of the possibility of association learning and opioid pharmacology to promote evoked placebo-driven analgesia.

Objectives:
In this brief report, we evaluate the feasibility of COLP as a pharmacobehavioral intervention to decrease total opioid consumption in patients with pain hospitalized at Spaulding Rehabilitation Hospital.

Methods:
Inpatients with spinal cord injury and polytrauma (n = 20) with moderate to severe pain were randomized to receive COLP (n = 10) or treatment-as-usual for 6 consecutive days. Opioid utilization was measured by morphine equivalents using the morphine equivalent dose conversion; pain severity was assessed using the numerical visual analog scale.

Results:
Conditioning open-label placebo significantly reduced total opioid consumption by the end of the intervention period (P ≤ 0.001). Pain reduction was also significant for the COLP group (P = 0.005), whereas the treatment-as-usual group demonstrated a trend towards pain reduction (P = 0.05).

Conclusions:
This study presents the first data in the use of a pharmacobehavioral intervention that capitalize on the benefits of open-label placebo and classical drug conditioning for opioid dose reduction in a population with moderate to severe pain exposed to intensive inpatient rehabilitation.
Hymenobacter ginkgonis sp. nov., isolated from bark of Ginkgo biloba
Authors: Cha Inseong , Kang Heeyoung , Kim Haneul , Bae Seokhyeon , Joh Kiseong 
Published: July 2020

Strain HMF4947T, isolated from the bark of a ginkgo tree, was a pale-pink coloured, Gram-stain-negative, non-motile, strictly aerobic and rod-shaped bacterium. The isolate grew optimally on Reasoner's 2A agar at 30 °C, pH 7.0 and with 0 % NaCl. Phylogenetic analysis based on 16S rRNA gene sequences showed that strain HMF4947T belonged to the genus

Hymenobacter

and was most closely related to

Hymenobacter metalli

A2-91T (96.9 % sequence similarity) and

Hymenobacter pomorum

9-2-1-1T (96.5 %). The average nucleotide identity and estimated DNA–DNA hybridization values between strain HMF4947T and

Hymenobacter arizonensis

DSM 17870T were 74.3 and 20.5 %, respectively. The major fatty acids were summed feature 3 (C16 : 1
ω7c and/or C16 : 1
ω6c), iso-C15 : 0 and C16 : 1
ω5c. The predominant isoprenoid quinone was menaquinone-7. The polar lipids comprised phosphatidylethanolamine, one unidentified aminoglycolipid, three unidentified aminophospholipids, one unidentified phospholipid, three unidentified aminolipids, two unidentified glycolipids and three unidentified polar lipids. The genomic DNA G+C content was 59.3 mol%. Thus, based on phylogenetic, phenotypic and chemotaxonomic data, strain HMF4947T represents a novel species of the genus

Hymenobacter

, for which the name Hymenobacter ginkgonis sp. nov. is proposed. The type strain of the species is strain HMF4947T (=KCTC 72780T=NBRC 114271T).
Dynamic causal modeling of layered magnetoencephalographic event-related responses
Authors: Ihle Stephan J. , Bonaiuto James J. , Bestmann Sven , Stephan Klaas Enno , Barnes Gareth R. , Heinzle Jakob 
Published: July 2020

AbstractThe layered architecture of cortex is thought to play a fundamental role in shaping cortical computations. However, direct electrophysiological measurements of layered activity are not possible non-invasively in humans. Recent advances have shown that a distinction of two layers can be achieved using magnetoencephalography in combination with head casts and advanced spatial modeling. In this technical note, we present a dynamic causal model of a single cortical microcircuit that models event related potentials. The model captures the average dynamics of a detailed two layered circuit. It combines a temporal model of neural dynamics with a spatial model of a layer specific lead field to facilitate layer separation. In simulations we show that the spatial arrangement of the two layers can be successfully recovered using Bayesian inference. The layered model can also be distinguished from a single dipole model. We conclude that precision magnetoencephalography in combination with detailed dynamical system modeling can be used to study non-invasively the fast dynamics of layered computations.
BDdb: a comprehensive platform for exploration and utilization of birth defect multi-omics data
Authors: Zhang Dengwei , Sun Hai-Xi , Zhou Ziheng , Jiang Xiaosen , Chen Dongsheng , Zhou Si , Huang Jie , Qu Shoufang , Gu Ying , Zhang Xiuqing , Jin Xin , Gao Ya , Shen Yue , Chen Fang 
Published: July 2020

ABSTRACTBirth defect, not only poses a major challenge for infant health but also attracts the attention of countless people in the world. Chromosome abnormality directly results in diverse birth defects which are generally deleterious and even lethal. Therefore, gaining molecular regulatory insights into these diseases is important and necessary for effective prenatal screening. Recently, with the advance of next-generation sequencing (NGS) techniques, a myriad of treatises and data associated with these diseases are now constantly produced from different laboratories across the world. To meet the increasing requirements for birth-related data resources, we developed a birth defect multi-omics database (BDdb), freely accessible at http://t21omics.cngb.org and consisting of multi-omics data, circulating free DNA (cfDNA) data, as well as diseases biomarkers. Omics data sets from 138 GSE samples, 5271 GSM samples and 328 entries, and more than 2000 biomarkers of 22 birth-defect diseases in 5 different species were integrated into BDdb, which provides a user-friendly interface for searching, browsing and downloading selected data. Additionally, we re-analyzed and normalized the raw data so that users can also customize the analysis using the data generated from different sources or different High-Throughput Sequencing (HTS) methods. To our knowledge, BDdb is the first comprehensive database associated with birth-defect-related diseases. which would benefit the diagnosis and prevention of birth defects.
A phosphoproteomic approach reveals that PKD3 controls phenylalanine and tyrosine metabolism
Authors: Mayer Alexander E. , Loza-Valdes Angel , Schmitz Werner , Viera Jonathan Trujillo , Leitges Michael , Schlosser Andreas , Sumara Grzegorz 
Published: July 2020

SummaryMembers of the Protein Kinase D (PKD) family (PKD1, 2, and 3) integrate hormonal and nutritional inputs to regulate complex cellular metabolism. Despite the fact that a number of functions have been annotated to particular PKDs, their molecular targets are relatively poorly explored. PKD3 promotes insulin sensitivity and suppresses lipogenesis in the liver. However, its substrates are largely unknown. Here we applied proteomic approaches to determine PKD3 targets. We identified over three-hundred putative targets of PKD3. Among them phenylalanine hydroxylase (PAH). PAH catalyses the conversion of phenylalanine to tyrosine and its activity is regulated by, phenylalanine concentration and glucagon-induced signaling. Consistently, we showed that PKD3 is activated by glucagon and promotes tyrosine levels in primary hepatocytes and liver of mice.Taken together, our comprehensive proteomic approach established that PKD3 determine the rate of phenylalanine to tyrosine conversion in the liver. Therefore, our data indicate that PKD3 might play a role in development of diseases related to the defective tyrosine and phenylalanine metabolism.
Natural selection and circular pathways to seasonal migration in birds
Authors: Halley Matthew R. 
Published: July 2020

AbstractThe “migratory revolutions” (MR) model is a synthetic theory of bird migration that seeks to explain the full range of the functional phenotype, from sedentary residents of non-seasonal (tropical) habitats to obligate long-distance migrants, as a cumulative evolutionary response to shifting distributions of adult extrinsic mortality across the annual cycle. At macroevolutionary scales, the general model predicts that migration evolves in circular patterns, reframing classic debates about the effects of migration on speciation and extinction rates. Here, I describe and apply the MR model to a well-known system, the passerine genusCatharus(Turdidae), to illustrate its broad implications for reconstructing evolutionary history.
Maternal age alters recombination rate inDrosophila pseudoobscura
Authors: Pownall Keeley A. , Taylor Hannah N. , Altindag Ulku H. , Stevison Laurie S. 
Published: July 2020

AbstractAs individuals senesce, factors correlated with fitness, such as fecundity and longevity, decline. Increased age also alters recombination rates in a variety of taxa. Changes in individual recombination rate, or ‘recombination rate plasticity’, can increase meiotic errors. InDrosophila melanogaster, multiple studies on maternal age and recombination rate have found a characteristic pattern where rates initially increase, then decrease, then increase again relative to controls. Here, this phenomenon was investigated inD. pseudoobscura. First, fecundity and survivorship were investigated to guide the choice of treatment age. Then, a large-scale recombination analysis (N=23,559) was set up using three X-linked phenotypic markers. Recombination rate differences in two genomic intervals were measured in females aged to 7 days (control) and 35 days (selected treatment age) prior to mating, with progeny collection continuing for 12 days post-mating in 72 hour timepoints. Results revealed a 3.39% increase in recombination rate due to maternal age (p=0.025), for the first 72 hour time point in one of the two marker intervals. For both genomic intervals, recombination rates were higher in the age treatment for the first time point and lower in later time points of the experiment. Next, these data were used to investigate crossover interference, which decreased with maternal age in the first time point and increased in the last time point. Overall, these results suggest that the mechanisms responsible for recombination rate plasticity may differ between maternal age and stressors, such as temperature.
Deep learning detection of informative features in tau PET for Alzheimer’s disease classification
Authors: Jo Taeho , Nho Kwangsik , Risacher Shannon L. , Saykin Andrew J. ,   for the Alzheimer’s Neuroimaging Initiative
Published: July 2020

AbstractBackgroundAlzheimer’s disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and there is currently no approved disease-modifying treatment. Biomarkers for early detection and mechanistic understanding of disease course are critical for drug development and clinical trials. Amyloid has been the focus of most biomarker research. Here, we developed a deep learning-based framework to identify informative features for AD classification using tau positron emission tomography (PET) scans.MethodsWe analysed [18F]flortaucipir PET image data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. We first developed an image classifier to distinguish AD from cognitively normal (CN) older adults by training a 3D convolutional neural network (CNN)-based deep learning model on tau PET images (N=132; 66 CN and 66 AD), then applied the classifier to images from individuals with mild cognitive impairment (MCI; N=168). In addition, we applied a layer-wise relevance propagation (LRP)-based model to identify informative features and to visualize classification results. We compared these results with those from whole brain voxel-wise between-group analysis using conventional Statistical Parametric Mapping (SPM12).ResultsThe 3D CNN-based classification model of AD from CN yielded an average accuracy of 90.8% based on five-fold cross-validation. The LRP model identified the brain regions in tau PET images that contributed most to the AD classification from CN. The top identified regions included the hippocampus, parahippocampus, thalamus, and fusiform. The LRP results were consistent with those from the voxel-wise analysis in SPM12, showing significant focal AD associated regional tau deposition in the bilateral temporal lobes including the entorhinal cortex. The AD probability scores calculated by the classifier were correlated with brain tau deposition in the medial temporal lobe in MCI participants (r=0.43 for early MCI and r=0.49 for late MCI).ConclusionA deep learning framework combining 3D CNN and LRP algorithms can be used with tau PET images to identify informative features for AD classification and may have application for early detection during prodromal stages of AD.
EEG-Beats: Automated analysis of heart rate variability (HVR) from EEG-EKG
Authors: Thanapaisal Supakjeera , Mosher Sabrina , Trejo Brenda , Robbins Kay 
Published: July 2020

AbstractHeart rate variability (HRV), the variation of the period between consecutive heartbeats, is an established tool for assessing physiological indicators such as stress and fatigue. In non-clinical settings, HRV is often computed from signals acquired using wearable devices that are susceptible to strong artifacts. In EEG (electroencephalography) experiments, these devices must be synchronized with the EEG and typically provide intermittent interbeat interval information based on proprietary artifact-removal algorithms. This paper describes an automated algorithm that uses the output of an EEG sensor mounted on a subject’s chest to accurately detect interbeat intervals and to calculate time-varying metrics. The algorithm is designed for raw signals and is robust to artifacts, resulting in fine-grained capture of HRV that is synchronized with the EEG. An open-source MATLAB toolbox (EEG-Beats) is available to calculate interbeat intervals and many standard HRV time and frequency indicators. EEG-Beats is designed to run in a completely automated fashion on an entire study without manual intervention. The paper applies EEG-Beats to EKG signals measured with an EEG sensor in a large longitudinal study (17 subjects, 6 tasks, 854 datasets). The toolbox is available athttps://github.com/VisLab/EEG-Beats.
Phylogenetic Analysis Of SARS-CoV-2 In The First Months Since Its Emergence
Authors: Pereson Matías J. , Mojsiejczuk Laura , Martínez Alfredo P. , Flichman Diego M. , Garcia Gabriel H. , Di Lello Federico A. 
Published: July 2020

ABSTRACTDuring the first months of SARS-CoV-2 evolution in a new host, contrasting hypotheses have been proposed about the way the virus has evolved and diversified worldwide. The aim of this study was to perform a comprehensive evolutionary analysis to describe the human outbreak and the evolutionary rate of different genomic regions of SARS-CoV-2.The molecular evolution in nine genomic regions of SARS-CoV-2 was analyzed using three different approaches: phylogenetic signal assessment, emergence of amino acid substitutions, and Bayesian evolutionary rate estimation in eight successive fortnights since the virus emergence.All observed phylogenetic signals were very low and trees topologies were in agreement with those signals. However, after four months of evolution, it was possible to identify regions revealing an incipient viral lineages formation despite the low phylogenetic signal, since fortnight 3. Finally, the SARS-CoV-2 evolutionary rate for regions nsp3 and S, the ones presenting greater variability, was estimated to values of 1.37 × 10−3and 2.19 × 10−3substitution/site/year, respectively.In conclusion, results obtained in this work about the variable diversity of crucial viral regions and the determination of the evolutionary rate are consequently decisive to understand essential feature of viral emergence. In turn, findings may allow characterizing for the first time, the evolutionary rate of S protein that is crucial for vaccines development.
What’s the Temperature in Tropical Caves?
Authors: Mejía-Ortíz Luis , Christman Mary C , Pipan Tanja , Culver David C 
Published: July 2020

AbstractHourly temperature was measured for approximately one year at 17 stations in three caves in Quintana Roo, Mexico. Thirteen of these stations were in the extensive twilight zones of all three caves. All seventeen stations showed seasonality in temperature with a 3 °C drop during the Nortes season. Two of the caves, Muévelo Sabrosito and Muévelo Rico, showed greater variability during the winter months while in Rio Secreto variability was greatest during the rainy season. Río Secreto is less open to the surface than the other two. All sites also showed a daily temperature cycle, although it was very faint in some Rio Secreto sites. While temperature variability is diminished relative to surface variation, its temporal pattern is worthy of further study.
Deep neural network models of sound localization reveal how perception is adapted to real-world environments
Authors: Francl Andrew , McDermott Josh H. 
Published: July 2020

AbstractMammals localize sounds using information from their two ears. Localization in real-world conditions is challenging, as echoes provide erroneous information, and noises mask parts of target sounds. To better understand real-world localization we equipped a deep neural network with human ears and trained it to localize sounds in a virtual environment. The resulting model localized accurately in realistic conditions with noise and reverberation, outperforming alternative systems that lacked human ears. In simulated experiments, the network exhibited many features of human spatial hearing: sensitivity to monaural spectral cues and interaural time and level differences, integration across frequency, and biases for sound onsets. But when trained in unnatural environments without either reverberation, noise, or natural sounds, these performance characteristics deviated from those of humans. The results show how biological hearing is adapted to the challenges of real-world environments and illustrate how artificial neural networks can extend traditional ideal observer models to real-world domains.