bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of Total Parenteral Nutrition administration among Intensive Care Unit patients at Omdurman Military Hospital, Sudan
Authors: Khalafallah Bashir Bothina Essameldin , Ahmed Abdallah Mudawi Mohammed , Abd El-Raheem Ghada Omer Hamad , Ali Nassir Elkhansaa Hamad 
Published: October 2020

AbstractTotal parenteral nutrition is one of the important types of nutrition among patients with intestinal failure. This research was intended to assess total parenteral nutrition administration of the intensive care unit patients at the Military hospital, Sudan. A cross-sectional hospital-based study assessed the patients records in the period between April 2014-November 2015, data were analyzed through chi-square test, it was considered significant when p≤ 0.05. Twenty patients who received total parenteral nutrition were assessed, 60% were males, while 40% were females. The most frequent indication for total parenteral nutrition was laparotomy (35% of patients). The duration of total parenteral nutrition was assessed, 70% of patients had duration between 1-20 days. Regarding total parenteral nutrition complications, the most frequent complication was hypokalemia (45% of patients), refeeding syndrome occurred in 10 % of patients. A statistically significant association was found between total parenteral nutrition duration when assessed with age and indication (p= 0.005 and 0.000 respectively). Patients suffering from electrolytes imbalance need more care to avoid the development of refeeding syndrome, as well as high level of hygiene is strictly required to overcome septic complications. There is a need to consider specialized care team composed of nurses, clinical pharmacists and nutritionists.
Evaluation of Eye-tracking for a Decision Support Application
Authors: Visweswaran Shyam , King Andrew J , Tajgardoon Mohammadamin , Calzoni Luca , Clermont Gilles , Hochheiser Harry , Cooper Gregory F 
Published: October 2020

ABSTRACTEye-tracking is used widely to investigate attention and cognitive processes while performing tasks in electronic medical record (EMR) systems. We explored a novel application of eye tracking to collect training data for a machine learning-based clinical decision support tool that predicts which patient data are likely to be relevant for a clinical task. Specifically, we investigated in a laboratory setting the accuracy of eye tracking compared to manual annotation for inferring which patient data in the EMR are judged to be relevant by physicians. We evaluated several methods for processing gaze points that were recorded using a low-cost eye tracking device. Our results show that eye-tracking achieves accuracy and precision of 69% and 53% respectively compared to manual annotation and are promising for machine learning. The methods for processing gaze points and scripts that we developed offer a first step in developing novel uses for eye-tracking for clinical decision support.LAY SUMMARYIn the context of electronic medical record systems, eye-tracking is used extensively to explore attention and cognitive processes. We investigated a novel application of eye tracking to collect training data for machine learning-based clinical decision support. We evaluated several methods for processing gaze points that were recorded using a low-cost eye tracking device. The methods for processing gaze points and scripts that we developed offer a first step in developing novel uses for eye-tracking for clinical decision support.
Use of dried blood spot samples for SARS-CoV-2 antibody detection using the Roche Elecsys ® high throughput immunoassay
Authors: Mulchandani Ranya , Brown Ben , Brooks Tim , Semper Amanda , Machin Nicholas , Linley Ezra , Borrow Ray ,   EDSAB-HOME Study Investigators, Wyllie David 
Published: October 2020

AbstractBackgroundDried blood spot samples (DBS) provide an alternative sample type to venous blood samples for antibody testing. DBS are used by NHS for diagnosing HCV and by PHE for large scale HIV and Hepatitis C serosurveillance; the applicability of DBS based approaches to SARS-CoV-2 antibody detection is uncertain.ObjectiveTo compare antibody detection in dried blood spot eluates using the Roche Elecsys ® immunoassay (index test) with antibody detection in paired plasma samples, using the same assay (reference test).SettingOne Police and one Fire & Rescue facility in England.Participants195 participants within a larger sample COVID-19 serodiagnostics study of keyworkers, EDSAB-HOME.Outcome MeasuresSensitivity and specificity of DBS (the index test) relative to plasma (the reference test), at an experimental cut-off; quality of DBS sample collected; estimates of relative sensitivity of DBS vs. plasma immunoassay in a larger population.Results18/195 (9.2%) participants tested positive using plasma samples. DBS sample quality varied markedly by phlebotomist, and low sample volume significantly reduced immunoassay signals. Using a cut-off of ten median absolute deviations above the immunoassay result with negative samples, sensitivity and specificity of DBS were 89.0% (95% CI 67.2, 96.9%) and 100.0% (95% CI 97.9, 100%) respectively compared with using plasma. The limit of detection for DBS is about 30 times higher than for plasma.ConclusionDBS use for SARS-CoV-2 serology, though feasible, is insensitive relative to immunoassays on plasma. Sample quality impacts on assay performance. Alternatives, including the collection of capillary blood samples, should be considered for screening programs.
City-level SARS-CoV-2 sewage surveillance
Authors: Yaniv Karin , Shagan Marilou , Kramarsky-Winter Esti , Weil Merav , Indenbaum Victoria , Elul Michal , Erster Oran , Brown Alin Sela , Mendelson Ella , Mannasse Batya , Shirazi Rachel , Lakkakula Satish , Miron Oren , Rinott Ehud , Baibich Ricardo Gilead , Bigler Iris , Malul Matan , Rishti Rotem , Brenner Asher , Lewis Yair E. , Friedler Eran , Gilboa Yael , Sabach Sara , Alfiya Yuval , Cheruti Uta , Davidovitch Nadav , Bilenko Natalya , Moran-Gilad Jacob , Berchenko Yakir , Bar-Or Itay , Kushmaro Ariel 
Published: October 2020

AbstractThe COVID-19 pandemic created a global crisis impacting not only healthcare systems, but also world economies and society. Recent data have indicated that fecal shedding of SARS-CoV-2 is common, and that viral RNA can be detected in wastewater. This suggests that wastewater monitoring is a potentially efficient tool for both epidemiological surveillance, and early warning for SARS-CoV-2 circulation at the population level. In this study we sampled an urban wastewater infrastructure in the city of Ashkelon, Israel, during the end of the first COVID-19 wave in May 2020 when the number of infections seemed to be waning. We were able to show varying presence of SARS-CoV-2 RNA in wastewater from several locations in the city during two sampling periods. This was expressed as a new index, Normalized Viral Load (NVL), which can be used in different area scales to define levels of virus activity such as red (high) or green (no), and to follow morbidity in the population at tested area. Our index showed the rise in viral load between the two sampling periods (one week apart) and indicated an increase in morbidity that was evident a month later in the population. Thus, this methodology may provide an early indication for SARS-CoV-2 infection outbreak in a population before an outbreak is clinically apparent.HIGHLIGHTSDetecting the presence of SARS-CoV-2 virus RNA in urban wastewaterThe city sewer system may provide an early indication for SARS-CoV-2 infection and may be used as early warning for SARS-CoV-2 outbreaksNVL index defines various infected urban zones from red (high) to green (low)Graphical abstract
What predicts adherence to COVID-19 government guidelines? Longitudinal analyses of 51,000 UK adults
Authors: Wright Liam , Steptoe Andrew , Fancourt Daisy 
Published: October 2020

AbstractIn the absence of a vaccine, governments have focused on social distancing, self-isolation, and increased hygiene procedures to reduce the transmission of SARS-CoV-2 (COVID-19). Compliance with these measures requires voluntary cooperation from citizens. Yet, compliance is not complete, and existing studies provide limited understanding of what factors influence compliance; in particular modifiable factors. We use weekly panel data from 51,000 adults across the first three months of lockdown in the UK to identify factors that are related to compliance with COVID-19 guidelines. We find evidence that increased confidence in government to tackle the pandemic is longitudinally related to higher compliance, but little evidence that factors such as mental health and wellbeing, worries about future adversities, and social isolation and loneliness are related to changes in compliance. Our results suggest that to effectively manage the pandemic, governments should ensure that confidence is maintained, something which has not occurred in all countries.
Basrah experience among 6404 patients with COVID-19
Authors: Hamadi Al-Taher Saad S. , AlKanan Abbas K , Fares Mohammad N. , Mohammed Nihad Q. , Al-Jabery Ali Raheem , Habeeb Awatif A. , Mansour Abbas Ali 
Published: October 2020

AbstractsBackgroundThe first case of COVID-19 report in Basrah was in early March 2020. This study aimed to assess some of the characteristics of patients with COVID-19 in Basrah for the period from March, 4th to September, 8th 2020.MethodsRetrospective database analysis of the University of Basrah database. All RT-PCR positive patients during the study period were enrolled.ResultsOf 6404 patients included, male constituted 54.8%. Healthcare workers constituted 11.4% of the infected people. Of health care workers 16.1% were physicians. The mean age for the whole cohort was 39±16.7 years; adolescents and children younger than 20 years constituted 12.4%. The peak age was 31-40 years, those aged 61 years or more constituted 9.8% only. The case fatality rate was 3% (males 55.2% and females 44.8%). No death was reported in adolescents or children. The highest death rate was among those age 61 years or more.ConclusionThe situation of COVID-19 infection in Basrah, Iraq is evolving like other countries. Furthers studies are needed to assess associated comorbidities, treatment lines, outcomes and variables associated with mortality.
The ANTsX ecosystem for quantitative biological and medical imaging
Authors: Tustison Nicholas J. , Cook Philip A. , Holbrook Andrew J. , Johnson Hans J. , Muschelli John , Devenyi Gabriel A. , Duda Jeffrey T. , Das Sandhitsu R. , Cullen Nicholas C. , Gillen Daniel L. , Yassa Michael A. , Stone James R. , Gee James C. , Avants Brian B. ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: October 2020

AbstractThe Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis.
Early prognostication of COVID-19 to guide hospitalisation versus outpatient monitoring using a point-of-test risk prediction score
Authors: Chua Felix , Vancheeswaran Rama , Draper Adrian , Vaghela Tejal , Knight Matthew , Mogal Rahul , Singh Jaswinder , Spencer Lisa G , Thwaite Erica , Mitchell Harry , Calmonson Sam , Mahdi Noor , Assadullah Shershah , Leung Matthew , O’Neill Aisling , Popat Chayya , Kumar Radhika , Humphries Thomas J , Talbutt Rebecca , Raghunath Sarika , Molyneaux Philip L , Schechter Miriam , Lowe Jeremy , Barlow Andrew 
Published: October 2020

ABSTRACTIntroductionRisk factors of adverse outcomes in COVID-19 are defined but stratification of mortality using non-laboratory measured scores, particularly at the time of pre-hospital SARS-CoV-2 testing, is lacking.MethodsMultivariate regression with bootstrapping was used to identify independent mortality predictors in a derivation cohort of COVID-19 patients. Predictions were externally validated in a large random sample of the ISARIC cohort (N=14,231) and a smaller cohort from Aintree (N=290).Results983 patients (median age 70, IQR 53-83; in-hospital mortality 29.9%) were recruited over an 11-week study period. Through sequential modelling, a 5-predictor score termed SOARS (SpO2, Obesity, Age, Respiratory rate, Stroke history) was developed to correlate COVID-19 severity across low, moderate and high strata of mortality risk. The score discriminated well for in-hospital death, with area under the receiver operating characteristic values of 0.82, 0.80 and 0.74 in the derivation, Aintree and ISARIC validation cohorts respectively. Its predictive accuracy (calibration) in both external cohorts was consistently higher in patients with milder disease (SOARS 0-1), the same individuals who could be identified for safe outpatient monitoring. Prediction of a non-fatal outcome in this group was accompanied by high score sensitivity (99.2%) and negative predictive value (95.9%).ConclusionThe SOARS score uses constitutive and readily assessed individual characteristics to predict the risk of COVID-19 death. Deployment of the score could potentially inform clinical triage in pre-admission settings where expedient and reliable decision-making is key. The resurgence of SARS-CoV-2 transmission provides an opportunity to further validate and update its performance.
Cortical Spikes use Analog Sparse Coding
Authors: Ballard Dana H. , Zhang Ruohan 
Published: October 2020

Quantifying the message communicated by neurons in the cortex by averaging action potentials over repeated trials of a given stimulus can reveal neuronal tuning features. For example, simple cells in the visual cortex have been characterized by reverse correlation based on the detailed structure of their oriented receptive fields. This structure, in turn, has been modeled using large libraries of such receptive fields to allow the simultaneous coding of visual stimuli with small numbers of appropriate combinations of cells selected from the library. This strategy, known assparse coding, has been shown to produce excellent approximations for natural visual inputs. In concert with this mathematical development has been the discovery of cells’ use of oscillations in the gamma frequency range for general coding tasks, such as a mechanism for synchronizing distal networks of neurons. More recently, spikes timed with oscillations have been shown to exhibit local phase delays within a single gamma cycle, but such delays have resisted a behavioral functional interpretation. We show here that a specific coordinate system for the gamma cycle allows resultant phase delays to be interpreted quantitatively in classical terms. Specifically, extracted phase delays from mice viewing oriented sinusoidal grating images are shown to have the same distributions as those from a computer sparse coding model using natural images, suggesting for the first time a direct link between experimentally measured phase delays and model receptive fields.Significance StatementNetworks of pyramidal cells in the cortex exhibit action potentials (spikes) that are characterized by randomness and low firing rates. Spike averaging methods have been ordinarily useful in dealing with these features to reveal behavioral task structure, but the randomness and slowness so far prevented the specification of a satisfactory generative spike model. We show that a spike can be analyzed using the context of a specific phase of the gamma component of its membrane potential. The result is each spike can be can be assigned a scalar, which makes it immediately useful for network models.
Hierarchical Bayesian Models of Reinforcement Learning: Introduction and comparison to alternative methods
Authors: van Geen Camilla , Gerraty Raphael T. 
Published: October 2020

AbstractReinforcement learning models have been used extensively to capture learning and decision-making processes in humans and other organisms. One essential goal of these computational models is the generalization to new sets of observations. Extracting parameters that can reliably predict out-of-sample data can be difficult, however. The use of prior distributions to regularize parameter estimates has been shown to help remedy this issue. While previous research has suggested that empirical priors estimated from a separate dataset improve predictive accuracy, this paper outlines an alternate method for the derivation of empirical priors: hierarchical Bayesian modeling. We provide a detailed introduction to this method, and show that using hierarchical models to simultaneously extract and impose empirical priors leads to better out-of-sample prediction while being more data efficient.
Self-Organized Amphiphiles are Poor Hydroxyl Radical Scavengers in Fast Photochemical Oxidation of Proteins Experiments
Authors: Cheng Zhi , Mobley Charles , Misra Sandeep K. , Sharp Joshua S. 
Published: October 2020

ABSTRACTThe analysis of membrane protein topography using fast photochemical oxidation of protein (FPOP) has been reported in recent years, but still underrepresented in literature. Based on the hydroxyl radical reactivity of lipids and other amphiphiles, it is believed that the membrane environment acts as a hydroxyl radical scavenger decreasing effective hydroxyl radical doses and resulting in less observed oxidation of proteins. Here, we investigated the effect of bulk hydroxyl radical scavenging in FPOP using both isolated cellular membranes as well as detergent micelles. We found no significant change in radical scavenging activity upon the addition of disrupted cellular membranes with the membrane concentration in the range of 0-25600 cell/μL using an inline radical dosimeter. We confirmed the non-scavenging nature of the membrane with the FPOP results of a soluble model protein in the presence of cell membranes, which showed no significant difference in oxidation with or without membranes. The use of detergents revealed that, while soluble detergent below the critical micelle concentration acts as a potent hydroxyl radical scavenger as expected, additional detergent has little to no hydroxyl radical scavenging effect once the critical micelle concentration is reached. These results suggest that any scavenging effect of membranes or organized amphiphilic membrane mimetics in FPOP experiments are not due to bulk hydroxyl radical scavenging, but may be due to a localized scavenging phenomenon.
Hypothalamic NMDA receptors stabilize NREM sleep and are essential for REM sleep
Authors: Miracca Giulia , Soto Berta Anuncibay , Tossell Kyoko , Yustos Raquel , Vyssotski Alexei L. , Franks Nicholas P. , Wisden William 
Published: October 2020

SUMMARYThe preoptic hypothalamus regulates both NREM and REM sleep. We found that calcium levels in mouse lateral preoptic (LPO) neurons were highest during REM. Deleting the core GluN1 subunit of NMDA receptors from LPO neurons abolished calcium signals during all vigilance states, and the excitatory drive onto LPO neurons was reduced. Mice had less NREM sleep and were incapable of generating conventionally classified REM sleep episodes: cortical theta oscillations were greatly reduced but muscle atonia was maintained. Additionally, mice lacking NMDA receptors in LPO neurons had highly fragmented sleep-wake patterns. The fragmentation persisted even under high sleep pressure produced by sleep deprivation. Nevertheless, the sleep homeostasis process remained intact, with an increase in EEG delta power. The sedative dexmedetomidine and sleeping medication zolpidem could transiently restore consolidated sleep. High sleep-wake fragmentation, but not sleep loss, was also produced by selective GluN1 knock-down in GABAergic LPO neurons. We suggest that NMDA glutamate receptor signalling stabilizes the firing of “GABAergic NREM sleep-on” neurons and is also essential for the theta rhythm in REM sleep.
Single-cell analysis of cell fate bifurcation in the chordateCiona
Authors: Winkley Konner M. , Reeves Wendy M. , Veeman Michael T. 
Published: October 2020

AbstractInductive signaling interactions between different cell types are a major mechanism for the further diversification of embryonic cell fates. Most blastomeres in the model chordateCiona robustabecome restricted to a single predominant fate between the 64-cell and mid-gastrula stages. We used single-cell RNAseq spanning this period to identify 53 distinct cell states, 25 of which are dependent on a MAPK-mediated signal critical to earlyCionapatterning. Divergent gene expression between newly bifurcated sibling cell types is dominated by upregulation in the induced cell type. These upregulated genes typically include numerous transcription factors and not just one or two key regulators. The Ets family transcription factor Elk1/3/4 is upregulated in almost all the putatively direct inductions, indicating that it may act in an FGF-dependent feedback loop. We examine several bifurcations in detail and find support for a ‘broad-hourglass’ model of cell fate specification in which many genes are induced in parallel to key tissue-specific transcriptional regulators via the same set of transcriptional inputs.