bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of the Second Wave of the COVID-19 Pandemic in India: A Google Trends Analysis
Authors: Visaria Aayush , Polamarasetti Pooja , Reddy Shivani , Ali Alizah , Hameed Fariha R. , James Joel , Akhtar Moizz , Islam Sumaiya , Raju Priyanka , Thawani Rajat 
Published: May 2021

AbstractBackgroundThe second wave of the COVID-19 pandemic has led to considerable morbidity and mortality in India, in part due to lack of healthcare access, low health literacy, and poor disease surveillance. In this retrospective, descriptive ecological study, we utilized Google Trends (GT) to characterize the second COVID-19 wave and its association with official case counts based on search terms related to symptoms, testing, disease complications, medications, preventive behaviors, and healthcare utilization.MethodsGT is a publicly available, online tracking system of Google searches. Searches are presented as relative search volumes (RSV) from 0 (least) to 100 (most number of searches). We performed pre-defined Web searches in India from 2/12/2021 to 5/09/2021. We characterized the peak RSV, RSV doubling rates, and Spearman rank correlation of selected search terms with official case counts. We also used date-adjusted linear regression to estimate the association between highly correlated search terms and official case counts. We then qualitatively classified public search queries into thematic groups to better understand public awareness and needs related to COVID-19.ResultsWe observed that searches for symptoms (most searched terms in order: fever, cough, headache, fatigue, chest pain), disease states (infection, pneumonia), COVID-19-related medications (remdesivir, ivermectin, azithromycin, Fabiflu, dexamethasone), testing modalities (PCR, CT Scan, D-dimer, C-reactive protein, oxygen saturation), healthcare utilization (oxygen cylinders, hospital, physician), and preventive behaviors (lockdown, mask, pulse oximetry, hand sanitizer, quarantine) all demonstrated increases, in line with increases in official case counts. Symptoms, PCR testing, outpatient medications, and preventive behaviors peaked around April 24th, approximately two weeks prior to the peak RSV in official case counts. Contrarily, healthcare utilization factors, including searches for hospital, physicians, beds, disease states, and inpatient medications did not peak until the first week of May. There were highly significant correlations between ‘Coronavirus Disease 2019’ (r=0.959), ‘fever’ (r=0.935), ‘pulse oximetry’ (r=0.952), ‘oxygen saturation’ (r=0.944), ‘C-reactive protein’ (r=0.955), ‘D-Dimer’ (r=0.945), & ‘Fabiflu’ (r=0.943) and official case counts.ConclusionGT search terms related to symptoms, testing, and medications are highly correlated with official case counts in India, suggesting need for further studies examining GT’s potential use as a disease surveillance and public informant tool for public health officials.
Epidemiological characteristics of three SARS-CoV-2 variants of concern and implications for future COVID-19 pandemic outcomes
Authors: Yang Wan , Shaman Jeffrey 
Published: May 2021

AbstractThree SARS-CoV-2 variants classified as variants of concern – B.1.1.7, B.1.351, and P.1 – have spread globally. To characterize their viral and epidemiological properties in support of public health planning, we develop and apply a model-inference system to estimate the changes in transmissibility and immune escape for each variant, based on case and mortality data from the country where each variant emerged. Accounting for under-detection of infection, disease seasonality, concurrent non-pharmaceutical interventions, and mass-vaccination, we estimate that B.1.1.7 has a 46.6% (95% CI: 32.3 – 54.6%) increase in transmissibility but nominal immune escape from protection induced by prior wild-type infection; B.1.351 has a 32.4% (95% CI: 14.6 – 48.0%) increase in transmissibility and 61.3% (95% CI: 42.6 – 85.8%) immune escape; and P.1 has a 43.3% (95% CI: 30.3 – 65.3%) increase in transmissibility and 52.5% (95% CI: 0 – 75.8%) immune escape. Model simulations indicate that B.1.351 and P.1 could supplant B.1.1.7 dominance and lead to increased infections. Our findings highlight the importance of preventing the spread of B.1.351 and P.1, in addition to B.1.1.7, via continued preventive measures, prompt mass-vaccination of all populations, continued monitoring of vaccine efficacy, and possible updating of vaccine formulations to ensure high efficacy.
AnmO2l: An open-source pulse-dose oxygen conserving device for the COVID-19 crisis
Authors: Li Honquan , Krishnamurthy Deepak , Kothari Anesta , Li Ethan , Lipnick Michael , Gaba David , Fanning Ruth , Prakash Manu 
Published: May 2021

AbstractThe surge of COVID-19 cases in India and around the world has resulted in acute oxygen shortage. Oxygen therapy through nasal cannula with flow rates of 1-6 L/min is an effective treatment for many COVID-19 patients in non-critical conditions and may help prevent disease progression. The same treatment is also used in post-acute care for recovering COVID-19 patients. Here we describe a simple, open source, and rapidly manufacturable oxygen conservation device for use with dual-port nasal cannula that can extend the life of current oxygen supply by almost two to three times, which we hope will help towards coping with the ongoing crisis.
Demographic disparities in clinical outcomes of COVID-19: data from a statewide cohort in South Carolina
Authors: Yang Xueying , Zhang Jiajia , Chen Shujie , Olatosi Bankole , Bruner Larisa , Diedhiou Abdoulaye , Scott Cheryl , Mansaray Ali , Weissman Sharon , Li Xiaoming 
Published: May 2021

AbstractBackgroundCurrent literature examining the clinical characteristics of COVID-19 patients under-represent COVID-19 cases who were either asymptomatic or had a mild illness.ObjectiveTo generate a state-level description and examine the demographic disparities of clinical outcomes of COVID-19.DesignStatewide population-based cohort studySettingCOVID-19 surveillance facilities in South CarolinaPatientsAdults COVID-19 cases reported to the SC DHEC by Case Report Form during March 04–December 31, 2020MeasurementsThe primary predictors were socio-demographic characteristics. The outcomes were COVID-19 disease severity, hospitalization, and mortality, which collected from the standardized CRF.ResultsAmong a total of 280,177 COVID-19 cases, 5.2% (14,451) were hospitalized and 1.9% (5,308) died. Individuals who were older, male gender, Blacks, Hispanic or Latino, and residing in small towns had higher odds for hospitalization and death from COVID-19 (Ps<0.0001). Regarding disease severity, 144,157 (51.5%) were asymptomatic, while 34.4% and 14.2% had mild and moderate/severe symptoms, respectively. Older individuals (OR: 1.14, 95%CI: 1.11, 1.18), Hispanic or Latino (OR: 2.07; 95%CI: 1.96, 2.18), and people residing in small towns (OR: 1.15; 95%CI: 1.08, 1.23) had higher odds of experiencing moderate/severe symptoms, while male and Asian (vs Whites) patients had lower odds of experiencing moderate/severe symptoms.LimitationsPotential misclassification of outcomes due to missing data; other variables were not evaluated, such as comorbidities.ConclusionAs the first statewide population-based study using data from multiple healthcare systems with a long follow-up period in the US, we provide a more generalizable picture of COVID-19 symptoms and clinical outcomes. The findings from this study reinforce the fact that rural residence, racial and ethnic social determinants of health, unfortunately, remain predictors of poor health outcomes for COVID-19 patients.
Arousal state affects perceptual decision-making by modulating hierarchical sensory processing in a large-scale visual system model
Authors: Sörensen Lynn K. A. , Bohté Sander M. , Slagter Heleen A. , Scholte H. Steven 
Published: May 2021

AbstractArousal levels strongly affect task performance. Yet, what arousal level is optimal for a task depends on its difficulty. Easy task performance peaks at higher arousal levels, whereas performance on difficult tasks displays an inverted U-shape relationship with arousal, peaking at medium arousal levels, an observation first made by Yerkes and Dodson in 1908. It is commonly proposed that the noradrenergic locus coeruleus system regulates these effects on performance through a widespread release of noradrenaline resulting in changes of cortical gain. This account, however, does not explain why performance decays with high arousal levels only in difficult, but not in simple tasks. Here, we present a mechanistic model that revisits the Yerkes-Dodson effect from a sensory perspective: a deep convolutional neural network augmented with a global gain mechanism reproduced the same interaction between arousal state and task difficulty in its performance. Investigating this model revealed that global gain states differentially modulated sensory information encoding across the processing hierarchy, which explained their differential effects on performance on simple versus difficult tasks. These findings offer a novel hierarchical sensory processing account of how, and why, arousal state affects task performance.Author’s summaryOver a hundred years ago, it was first observed that the effect of arousal on performance depends on task difficulty: the Yerkes-Dodson effect. Difficult tasks are best solved at intermediate arousal levels, whereas easy tasks benefit from a high arousal state. Current theories on how arousal affects neural processing cannot explain this effect of task difficulty. Here, we implement a key effect of arousal on cortical processing, a change in neuronal gain, in a computational model of visual processing capable of object recognition. Across a series of experiments, we find that our model can reproduce the Yerkes-Dodson effect behaviorally and that this effect can be explained by where in the processing hierarchy different arousal states optimize sensory information encoding.
Genetic analysis of Caenorhabditis elegans pry-1/Axin suppressors identifies genes involved in reproductive structure development, stress response, and aging
Authors: Mallick Avijit , Jhaveri Nikita , Jeon Jihae , Chang Yvonne , Shah Krupali , Hosein Hannah , Gupta Bhagwati P. 
Published: May 2021

ABSTRACTThe Axin family of scaffolding proteins regulates a wide array of developmental and post-developmental processes in eukaryotes. Studies in the nematode, Caenorhabditis elegans, have shown that the Axin homolog, PRY-1, plays essential roles in multiple tissues. To understand the genetic network of pry-1, we focused on a set of genes that are differentially expressed in the pry-1-mutant transcriptome and are linked to reproductive structure development. Eight of the genes (ard-1, rpn-7, cpz-1, his-7, cdk-1, rnr-1, clsp-1, and spp-1), when knocked down by RNA interference, efficiently suppressed the plate-level multivulva phenotype of pry-1 mutants. In every case, other than clsp-1 and spp-1, the ectopic vulval precursor cell (VPC) induction was also inhibited. The suppressor genes are members of known gene families in eukaryotes and perform essential functions. Our genetic interaction experiments revealed that except for clsp-1, the genes participate in one or more pry-1-mediated biological events. While four of them (cpz-1, his-7, cdk-1, and rnr-1) function in VPC induction, stress response, and aging, the other three (spp-1, ard-1, and rpn-7) are specific to one or more of these processes. Further analysis of the genes involved in aging showed that his-7, cdk-1, and rnr-1 also interacted with daf-16/FOXO. The results of genetic epistasis experiments suggested that his-7 functions upstream of daf-16, whereas cdk-1 and rnr-1 act downstream of the pry-1-daf-16 pathway. Altogether, these findings demonstrate the important role of pry-1 suppressors in C. elegans. Given that all of the genes described in this study are conserved, future investigations of their interactions with Axin and their functional specificity promises to uncover the genetic network of Axin under normal and disease states.
Predicting T cell receptor antigen specificity from structural features derived from homology models of receptor-peptide-major histocompatibility complexes
Authors: Milighetti Martina , Shawe-Taylor John , Chain Benjamin M 
Published: May 2021

1AbstractThe physical interaction between the T cell receptor (TCR) and its cognate antigen causes T cells to activate and participate in the immune response. Understanding this physical interaction is important in predicting TCR binding to a target epitope, as well as potential cross-reactivity. Here, we propose a way of collecting informative features of the binding interface from homology models of T cell receptor-peptide-major histocompatibility complex (TCR-pMHC) complexes. The information collected from these structures is sufficient to discriminate binding from non-binding TCR-pMHC pairs in multiple independent datasets. The classifier is limited by the number of crystal structures available for the homology modelling and by the size of the training set. However, the classifier shows comparable performance to sequence-based classifiers requiring much larger training sets.
Neuroimaging Measures of Iron and Gliosis Explain Memory Performance in Aging
Authors: Venkatesh Anu , Daugherty Ana M. , Bennett Ilana J. 
Published: May 2021

AbstractEvidence from animal and histological studies have indicated that accumulation of iron in the brain results in reactive gliosis that contributes to cognitive deficits. The current study extends these findings to human cognitive aging and suggests that magnetic resonance imaging (MRI) techniques like quantitative relaxometry can be used to study iron and its effects in vivo. The effects of iron on microstructure and memory performance were examined using a combination of quantitative relaxometry and multi-compartment diffusion imaging in 35 young (21.06 ± 2.18 years) and 28 older (72.58 ± 6.47 years) adults, who also completed a memory task. Replicating past work, results revealed age-related increases in iron content (R2 *) and diffusion, and decreases in memory performance. Independent of age group, iron content was significantly related to restricted (intracellular) diffusion in regions with low-moderate iron (hippocampus, caudate) and to all diffusion metrics in regions with moderate-high iron (putamen, globus pallidus). This pattern is consistent with different stages of iron-related gliosis, ranging from astrogliosis that may influence intracellular diffusion to microglial proliferation and increased vascular permeability that may influence all sources of diffusion. Further, hippocampal restricted diffusion was significantly related to memory performance, with a third of this effect related to iron content; consistent with the hypothesis that higher iron-related astrogliosis in the hippocampus is associated with poorer memory performance. These results demonstrate the sensitivity of MRI to iron-related gliosis and extends our understanding of its impact on cognition by showing that this relationship also explains individual differences in memory performance.
Diel light cycles affect phytoplankton competition in the global ocean
Authors: Tsakalakis Ioannis , Follows Michael J. , Dutkiewicz Stephanie , Follett Christopher L. , Vallino Joseph J. 
Published: May 2021

AbstractLight, essential for photosynthesis, is present in two periodic cycles in nature: seasonal and diel. Although seasonality of light is typically resolved in ocean ecosystem and biogeochemistry models because of its significance for seasonal succession and biogeography of phytoplankton, the diel light cycle is generally not resolved. Here we use a three-dimensional global ocean model and compare high temporal resolution simulations with and without diel light cycles. The model simulates 15 phytoplankton types of different cell size, encompassing two broad ecological strategies: small cells with high nutrient affinity (gleaners) and larger cells with high maximal growth rate (opportunists). Both are grazed by zooplankton and limited by nitrogen, phosphorus and iron. Simulations show that diel cycles of light induce diel cycles in phytoplankton populations and limiting nutrients in the global ocean. Diel nutrient cycles are associated with higher concentration of limiting nutrients by up to 200% at low latitudes (-40° to 40°), a process that increases opportunists’ biomass by up to 50%. Size classes with the highest maximal growth rates from both gleaner and opportunist groups are favored the most by diel light cycles. This mechanism weakens as latitude increases because the effects of the seasonal cycle dominate over those of the diel cycle. The present work shows that resource competition under diel light cycles has a significant impact on phytoplankton biogeography, indicating the necessity of resolving diel processes in global ocean models.
Identification of Actin Filament Interactors in Giardia lamblia
Authors: Steele-Ogus Melissa C. , Johnson Richard , MacCoss Michael , Paredez Alexander R. 
Published: May 2021

AbstractThe deep-branching protozoan parasite Giardia lamblia is the causative agent of the intestinal disease giardiasis. Consistent with its proposed evolutionary position, many pathways are minimalistic or divergent, including its actin cytoskeleton. Giardia is the only eukaryote known to lack all canonical actin-binding proteins. Previously, our lab identified a number of non-canonical Giardia lamblia actin (GlActin) interactors; however, these proteins appeared to interact only with monomeric or globular actin (G-actin), rather than filamentous actin (F-actin). To identify interactors, we used a chemical crosslinker to preserve native interactions, followed by an anti-GlActin antibody, Protein A affinity chromatography, and liquid chromatography coupled to mass spectrometry. We found 46 putative actin interactors enriched in the conditions favoring F-actin. Data are available via ProteomeXchange with identifier PXD026067. None of the proteins identified contain known actin-interacting motifs, and many lacked conserved domains. Each potential interactor was then tagged with the fluorescent protein mNeonGreen and visualized in live cells. We categorized the proteins based on their primary localization; localizations included ventral disc, marginal plate, nuclei, flagella, plasma membrane, and internal membranes. One protein from each category was co-localized with GlActin using immunofluorescence microscopy. We also co-immunoprecipitated one protein from each category and confirmed three interactions. Most of the localization patterns are consistent with previously demonstrated GlActin functions, but the ventral disc represents a new category of actin interactor localization. These results suggest a role for GlActin in ventral disc function, which has previously been controversial.ImportanceThe single-celled eukaryote Giardia lamblia is an intestinal parasite that colonizes the small intestine and causes diarrhea and vomiting, which can lead to dehydration and malnutrition. Giardia actin (GlActin) has a conserved role in Giardia cells, despite being a highly divergent protein with none of the conserved regulators found in model organisms. Here we identify and localize 46 interactors of polymerized actin. These putative interactors localize to a number of places in the cell, underlining GlActin’s importance in multiple cellular processes. Surprisingly, eight of these proteins localize to the ventral disc, Giardia’s host attachment organelle. Since host attachment is required for infection, proteins involved in this process are an appealing target for new drugs. While treatments for Giardia exist, drug resistance is becoming more common, resulting in a need for new treatments. Giardia and human systems are highly dissimilar, thus drugs specifically tailored to Giardia proteins would be unlikely to have side effects.
Analyzing Supply and Demand on a General Internal Medicine Ward: A Cross-Sectional Study
Authors: Fralick Michael , Kaw Neal , Wang Mingkun , Mamdani Muhammad , Mourad Ophyr 
Published: May 2021

ABSTRACTBackgroundThe capacity of the general internal medicine clinical teaching units has been strained by decreasing resident supply and increasing patient demand. The objective of our study was to quantitatively compare the number of residents (supply) with the volume and duration of patient care activities (demand) to identify inefficiency.MethodsUsing the most recently available data from an academic teaching hospital, we identified each occurrence of a set of patient care activities that took place on the clinical teaching unit. We completed a descriptive analysis of the frequencies of these activities and how the frequencies varied by hour, day, week, month, and year. Patient care activities included admissions, rounds, responding to pages, meeting with patients and their families, patient transfers, discharges, and responding to cardiac arrests. The estimated time to complete each task was based on the available data in our electronic healthcare system and interviews with general internal medicine physicians or trainees. To calculate resident utilization, the person-hours of patient care tasks was divided by the person-hours of resident supply. Resident utilization was computed for three scenarios corresponding to varying levels of resident absenteeism.ResultsBetween 2015 and 2019 there were 14,581 consultations to general internal medicine from the emergency department. Patient volumes tended to be highest during January and lowest during May and June; and highest on Monday morning and lowest on Friday night. Daily admissions into hospital from the emergency department were higher on weekdays than on weekends, and hourly admissions peaked at 8:00 AM and between 3:00 PM and 1:00 AM. Weekday resident utilization was generally highest between 8:00 AM and 2:00 PM and lowest between 1:00 AM and 8:00 AM. In a scenario where all residents were present apart from those who were post-call, resident utilization generally never exceeded 100%; in scenarios where at least one resident was absent due to illness and/or vacation, it was common for resident utilization to approach or exceed 100%, particularly during daytime working hours.InterpretationAnalyzing supply and demand on a general internal medicine ward has allowed us to identify periods where supply and demand are not aligned and to empirically demonstrate the vulnerability of current staffing models. These data have the potential to inform and optimize scheduling on an internal medicine ward.