bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evidence that non-pathogenic microorganisms drive sea star wasting disease through boundary layer oxygen diffusion limitation
Authors: Aquino Citlalli A. , Besemer Ryan M. , DeRito Christopher M. , Kocian Jan , Porter Ian R. , Raimondi Peter , Rede Jordan E. , Schiebelhut Lauren M. , Sparks Jed P. , Wares John P. , Hewson Ian 
Published: August 2020

ABSTRACTSea star wasting disease describes a condition affecting asteroids that resulted in significant Northeastern Pacific population decline following a mass mortality event in 2013. The etiology of sea star wasting is unresolved. We hypothesized that asteroid wasting is a sequela of microbial organic matter remineralization near respiratory surfaces which leads to boundary layer oxygen diffusion limitation (BLODL). Wasting lesions were induced inPisaster ochraceusby enrichment with a variety of organic matter (OM) sources and by experimentally reduced oxygen conditions. Microbial assemblages inhabiting tissues and at the asteroid-water interface bore signatures of copiotroph proliferation before wasting onset, followed by the proliferation of putatively facultative and strictly anaerobic taxa. These results together illustrate that suboxic conditions at the animal-water interface may be established by heterotrophic bacterial activity in response to organic matter loading. Wasting susceptibility was significantly and positively correlated with rugosity, a key determinant of boundary layer thickness. At a semi-continuously monitored field site (Langley Harbor), wasting predictably occurred at annual peak or decline in phytoplankton biomass over 5 years, suggesting that primary production-derived OM may contribute to BLODL. Finally, wasting individuals from 2013 – 2014 bore stable isotopic signatures reflecting anaerobic processes which suggests that this phenomenon may have affected asteroids during mass mortality. The impacts of BLODL may be more pronounced under higher temperatures due to lower O2solubility, in more rugose asteroid species due to restricted hydrodynamic flow, and in larger specimens due to their lower surface area to volume ratios which affects diffusive respiratory potential. Moreover, our results demonstrate that marine invertebrate disease may result from heterotrophic microbial activity that occurs adjacent to respiratory tissues, which raises important questions about the etiology of marine diseases in other benthic taxa.
Cardiac Cell-Derived Matrices Impart Age-Specific Functional Properties to Human Cardiomyocytes
Authors: Kauss M. A. , Rockwood S. J. , Silva A. C. , Joy D. A. , Mendoza-Camacho N. , Whittaker M. N. , Stevenson Erica , Krogan N. J. , Swaney D. L. , McDevitt T. C. 
Published: August 2020

AbstractCell-derived matrices (CDMs) isolated from cultured cells provide complex and tissue-specific biochemical and physical cues derived from the extracellular matrix (ECM) that are lacking in typical tissue culture environments. However, current methods enhance ECM adhesion and thickness via introduction and promotion of singular matrix proteins, skewing the matrix composition, and confounding comparisons between CDMs. Here we developed a protocol that enhances CDM stability and deposition, respectively, by combining an L-polydopamine surface coating with Ficoll macromolecular crowing prior to hypotonic decellularization. This methodology was applied to the study of age-dependent phenotypic and functional changes observed in cardiac ECM by comparing the morphologic, electrophysiological and metabolic response of cardiomyocytes in response to CDMs produced by fetal and adult cardiac fibroblasts. Furthermore, mass spectrometry proteomics identified the enrichment of collagen VI in fetal CDMs, which we determined via siRNA-mediated silencing during CDM production to be necessary for maximal oxidative respiration in cardiomyocytes.
GridFree: A Python Package of Image Analysis for Interactive Grain Counting and Measuring
Authors: Hu Yang , Zhang Zhiwu 
Published: August 2020

AbstractGrain characteristics, including kernel length, kernel width, and thousand kernel weight, are critical component traits for grain yield. Manual measurements and counting are expensive, forming the bottleneck for dissecting the genetic architecture of these traits toward ultimate yield improvement. High-throughput phenotyping methods have been developed by analyzing images of kernels. However, segmenting kernels from the image background and noise artifacts or from other kernels positioned in close proximity remain challenges. In this study, we developed a software package, named GridFree, to overcome these challenges. GridFree uses an unsupervised machine learning approach, K-Means, to segment kernels from the background by using principal component analysis on both raw image channels and their color indices. GridFree incorporates users’ experiences as a dynamic criterion to set thresholds for a divide-and-combine strategy that effectively segments adjacent kernels. When adjacent multiple kernels are incorrectly segmented as a single object, they form an outlier on the distribution plot of kernel area, length, and width. GridFree uses the dynamic threshold settings for splitting and merging. In addition to counting, GridFree measures kernel length, width, and area with the option of scaling with a reference object. Evaluations against existing software programs demonstrated that GridFree had the smallest error on counting seeds for multiple crops, including alfalfa, canola, lentil, wheat, chickpea, and soybean. GridFree was implemented in Python with a friendly graphical user interface to allow users to easily visualize the outcomes and make decisions, which ultimately eliminates time-consuming and repetitive manual labor. GridFree is freely available at the GridFree website (https://zzlab.net/GridFree).
The association between COVID-19-imposed lockdowns and online searches for toothache using Google Trends
Authors: Sofi-Mahmudi Ahmad , Shamsoddin Erfan , Ghasemi Peyman , Nasser Mona , Mesgarpour Bita 
Published: August 2020

AbstractObjectiveTo assess the association between the lockdowns due to COVID-19 and global online searches for toothache using Google Trends (GT).MethodsWe investigated GT online searches for the search terms “toothache” and “tooth pain”, within the past five years. The time frame for data gathering was considered as the initiation and end dates of national/regional lockdowns in each country. Relative search volumes (RSVs) for online Google Search queries in 2019 was considered as the control. We analysed data after normalising based on the Internet penetration rate. We used one-way ANOVA to identify statistical difference for RSVs between 2020 and 2016-2019 for each country. A linear regression model was used to assess whether there is a correlation between RSVs in 2020 and gross domestic production, COVID-19 deaths, dentists’ density, YLDs of oral conditions, Internet access, lockdown duration, Education Index, and dental expenditure per capita.ResultsThe results of worldwide RSVs for toothache and tooth pain also showed significantly higher values in 2020 compared to the previous four years. Of 23 included countries in our study, 16 showed significantly increased RSVs during the lockdown period compared to the same periods in the past four years. There was a statistically significant relationship between difference of RSVs means in 2020 and in 2016-2019 combined with percent of urban residency (B=-1.82; 95% CI: (-3.38, −0.26); p=0.026) and dental expenditure per capita (B=-0.42; 95% CI: (-0.80, −0.05); p=0.031) (R2=0.66).ConclusionGenerally, the interest in toothache and tooth pain has significantly increased in 2020 compared to the last four years. This could implicitly reinforce the importance of dental care, as urgent medical care worldwide. Governments’ expenditure on oral healthcare and the rate of urban residency, could be mentioned as important factors to direct general populations’ online care-seeking behaviour with regard to dental pain.
A Study on Survival Scenario of COVID-19 patients in India: An Application of Survival Analysis on patient demographics
Authors: Kundu Sampurna , Kirti  , Mandal Debarghya 
Published: August 2020

AbstractThe study of transmission dynamics of COVID-19, have depicted the rate, patterns and predictions of the pandemic cases. In order to combat the disease transmission in India, the Government had declared lockdown on the 25th of March. Even after a strict lockdown nationwide, the cases are increasing and have crossed 4.5 lakh positive cases. A positive point to be noted amongst all that the recovered cases are slowly exceeding the active cases. The survival of the patients, taking death as the event that varies over age groups and gender wise is noteworthy. This study aims in carrying out a survival analysis to establish the variability in survivorship among age groups and sex, at different levels, that is, national, state and district level. The open database of COVID-19 tracker (covid19india.org) of India has been utilized to fulfill the objectives of the study. The study period has been taken from the beginning of the first case which was on 30th Jan 2020 till 30th June. Due to the amount of under-reporting of data and dropping missing columns a total of 26,815 sample patients were considered. The entry point of each patient is different and event of interest is death in the study. Kaplan Meier survival estimation, Cox proportional hazard model and multilevel survival model has been used to perform survival analysis. Kaplan Meier survival function, shows that the probability of survival has been declining during the study period of five months. A significant variability has been observed in the age groups, as evident from all the survival estimates, with increasing age the risk of dying from COVID-19 increases. When Western and Central India show ever decreasing survival rate in the framed time period then Eastern, North Eastern and Southern India shows a slightly better picture in terms of survival. Maharashtra, Gujarat, Delhi, Rajasthan and West bengal showed alrmingly poor survival as well. This study has depicted a grave scenario of gradation of ever decreasing survival rates in various regions and shows the variability by age and gender.
Characteristics of 24,516 Patients Diagnosed with COVID-19 Illness in a National Clinical Research Network: Results from PCORnet®
Authors: Block Jason P. , Marsolo Keith A. , Nagavedu Kshema , Bailey L. Charles , Cruz Henry , Forrest Christopher B. , Haynes Kevin , Hernandez Adrian F. , Kaushal Rainu , Kho Abel , McTigue Kathleen M. , Nair Vinit P. , Platt Richard , Puro Jon , Rothman Russell L. , Shenkman Elizabeth , Waitman Lemuel Russell , Weiner Mark G. , Williams Neely , Carton Thomas W. ,   Network Partners
Published: August 2020

AbstractBackgroundNational data from diverse institutions across the United States are critical for guiding policymakers as well as clinical and public health leaders. This study characterized a large national cohort of patients diagnosed with COVID-19 in the U.S., compared to patients diagnosed with viral pneumonia and influenza.Methods and FindingsWe captured cross-sectional information from 36 large healthcare systems in 29 U.S. states, participating in PCORnet®, the National Patient-Centered Clinical Research Network. Patients included were those diagnosed with COVID-19, viral pneumonia and influenza in any care setting, starting from January 1, 2020. Using distributed queries executed at each participating institution, we acquired information for patients on care setting (any, ambulatory, inpatient or emergency department, mechanical ventilator), age, sex, race, state, comorbidities (assessed with diagnostic codes), and medications used for treatment of COVID-19 (hydroxychloroquine with or without azithromycin; corticosteroids, anti-interleukin-6 agents).During this time period, 24,516 patients were diagnosed with COVID-19, with 42% in an emergency department or inpatient hospital setting; 79,639 were diagnosed with viral pneumonia (53% inpatient/ED) and 163,984 with influenza (41% inpatient/ED). Among COVID-19 patients, 68% were 20 to <65 years of age, with more of the hospitalized/ED patients in older age ranges (23% 65+ years vs. 12% for COVID-19 patients in the ambulatory setting). Patients with viral pneumonia were of a similar age, and patients with influenza were much younger. Comorbidities were common, especially for patients with COVID-19 and viral pneumonia, with hypertension (32% for COVID-19 and 46% for viral pneumonia), arrhythmias (20% and 35%), and pulmonary disease (19% and 40%) the most common. Hydroxychloroquine was used in treatment for 33% and tocilizumab for 11% of COVID-19 patients on mechanical ventilators (25% received azithromycin as well).Conclusion and RelevancePCORnet leverages existing data to capture information on one of the largest U.S. cohorts to date of patients diagnosed with COVID-19 compared to patients diagnosed with viral pneumonia and influenza.
Comparison of media and standards for SARS-CoV-2 RT-qPCR without prior RNA preparation
Authors: Ragan Katherine B. , Bhadra Sanchita , Choi Joon H. , Towers Dalton , Sullivan Christopher S. , Ellington Andrew D. 
Published: August 2020

AbstractSince the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, there have been demands on the testing infrastructure that have strained testing capacity. As a simplification of method, we confirm the efficacy of RNA extraction-free RT-qPCR and saline as an alternative patient sample storage buffer. In addition, amongst potential reagent shortages, it has sometimes been difficult to obtain inactivated viral particles. We have therefore also characterized armored SARS-CoV-2 RNA from Asuragen as an alternative diagnostic standard to ATCC genomic SARS-CoV-2 RNA and heat inactivated virions and provide guidelines for its use in RT-qPCR.
On the temporal spreading of the SARS-CoV-2
Authors: Bertacchini Francesca , Bilotta Eleonora , Pantano Pietro S. 
Published: August 2020

AbstractThe behaviour of SARS-CoV-2 virus is certainly one of the most challenging in contemporary world. Although the mathematical modelling of the virus has made relevant contributions, the unpredictable behaviour of the virus is still not fully understood. To identify some aspects of the virus elusive behaviour, we focused on the temporal characteristics of its course. We have analysed the latency trends the virus has realized worldwide, the outbreak of the hot spots, and the decreasing trends of the pandemic. We found that the spatio-temporal pandemic dynamics shows a power law distribution. As with physical systems, these changes in the pandemic’s course, which we have calledtransitional stages of contagion, highlight shared characteristics in many countries. The main results of this work is that the pandemic progression rhythms have been clearly identified for each country, providing the processes and the stages at which the virus develops, thus giving important information on the activation of containment and control measures.HighlightsTemporal spreading of the novel SARS-CoV-2 is analysed all over the world, and the distribution of infected people follows a power law.Latency, hot spots ignition, decreasing of the virus course all over the world are detected.As in physical systems, the virus behaviour showstransitional stagesin its evolution.Temporal rhythms of the virus behaviour have key biological significance from the theoretical point of view, disclosing the steps of the virus evolution.Predictions on the contagion dynamics, for each country, for all countries may be embodied into applications, for allowing forecasting about the contagion risk.
Limited Utility of Cardiovascular Risk Scores for People Living with HIV in Malawi
Authors: Goh Chia Y , Mwandumba Henry , Rapala Alicja , Tinago Willard , Sheha Irene , Chammudzi Mishek , Mallon Patrick , Klein Nigel , Khoo Saye , Kelly C 
Published: August 2020

AbstractHIV is associated with increased cardiovascular disease (CVD) risk. Despite the high prevalence of HIV in low income sub-Saharan Africa, there are few data on the assessment of CVD risk in the region. In this study, we aimed to compare the utility of existing CVD risk scores in a cohort of Malawian adults, and assess to what extent they correlate with established markers of endothelial damage: carotid intima-media thickness (IMT) and pulse wave velocity (PWV).WHO/ISH, SCORE, FRS, ASCVD, QRISK2 and D:A:D scores were calculated for 279 Malawian adults presenting with HIV and low CD4. Correlation of the calculated 10-year CVD risk score with IMT and PWV was assessed using Spearman’s rho.The median (IQR) age of patients was 37 (31 – 43) years and 122 (44%) were female. Median (IQR) blood pressure was 120/73mmHg (108/68 – 128/80) and 88 (32%) study participants had a new diagnosis of hypertension. The FRS and QRISK2 scores included the largest number of participants in this cohort (96% and 100% respectively). D:A:D, a risk score specific for people living with HIV, identified more patients in moderate and high-risk groups. Although all scores correlated well with physiological markers of endothelial damage, FRS and QRISK2 correlated most closely with both IMT [r2 0.51, p<0.0001 and r2 0.47, p<0.0001 respectively] and PWV [r2 0.47, p<0.0001 and r2 0.5, p<0.0001 respectively].Larger cohort studies are required to adapt and validate risk prediction scores in this region, so that limited healthcare resources can be effectively targeted.
Characteristics of COVID-19 fatality cases in East Kalimantan, Indonesia
Authors: Paramita Swandari , Isnuwardana Ronny , Duma Krispinus , Bakhtiar Rahmat , Nuryanto Muhammad Khairul , Pramulia Yudia Riries Choiru , Fitriany Evi , Aminyoto Meiliati 
Published: August 2020

AbstractIntroductionCoronavirus Disease (COVID-19) is caused by SARS-CoV-2 infection. On March 2, 2020, Indonesia announced the first confirmed cases of COVID-19 infection. East Kalimantan will play an important role as the new capital of Indonesia. There is attention to the preparedness of East Kalimantan to respond to COVID-19. We report the characteristics of COVID-19 fatality cases in here.MethodsWe retrospectively analyzed the fatality cases of COVID-19 patients from the East Kalimantan Health Office information system. All patients were confirmed COVID-19 by RT-PCR examination.ResultsBy July 31, 2020, 31 fatality cases of patients had been identified as having confirmed COVID-19 in East Kalimantan. The mean age of the patients was 55.1 ± 9.2 years. Most of the patients were men (22 [71.0%]) with age more than 60 years old (14 [45.2%]). Balikpapan has the highest number of COVID-19 fatality cases from all regencies. Hypertension was the most comorbidities in the fatality cases of COVID-19 patients in East Kalimantan.DiscussionOlder age and comorbidities still contributed to the fatality cases of COVID-19 patients in East Kalimantan, Indonesia. Hypertension, diabetes, cardiovascular disease, and cerebrovascular disease were underlying conditions for increasing the risk of COVID-19 getting into a serious condition.ConclusionActive surveillance for people older than 60 years old and having underlying diseases is needed for reducing the case fatality rate of COVID-19 in East Kalimantan.
Acute cognitive deficits after traumatic brain injury predict Alzheimer’s disease-like degradation of the human default mode network
Authors: Irimia Andrei , Maher Alexander S. , Chaudhari Nikhil N. , Chowdhury Nahian F. , Jacobs Elliot B. ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: August 2020

AbstractTraumatic brain injury (TBI) and Alzheimer’s disease (AD) are prominent neurological conditions whose neural and cognitive commonalities are poorly understood. The extent of TBI-related neurophysiological abnormalities has been hypothesized to reflect AD-like neurodegeneration because TBI can increase vulnerability to AD. However, it remains challenging to prognosticate AD risk partly because the functional relationship between acute post-traumatic sequelae and chronic AD-like degradation remains elusive. Here, functional magnetic resonance imaging (fMRI), network theory and machine learning (ML) are leveraged to study the extent to which geriatric mild TBI (mTBI) can lead to AD-like alteration of resting-state activity in the default mode network (DMN). This network is found to contain modules whose extent of AD-like, post-traumatic degradation can be accurately prognosticated based on the acute cognitive deficits of geriatric mTBI patients with cerebral microbleeds. Aside from establishing a predictive physiological association between geriatric mTBI, cognitive impairment and AD-like functional degradation, these findings advance the goal of acutely forecasting mTBI patients’ chronic deviations from normality along AD-like functional trajectories. The association of geriatric mTBI with AD-like changes in functional brain connectivity as early as ∼6 months post-injury carries substantial implications for public health because TBI has relatively high prevalence in the elderly.
Peripheral innate and adaptive immune cells during COVID-19: Functional neutrophils, pro-inflammatory monocytes and half-dead lymphocytes
Authors: Ekşioğlu-Demiralp Emel , Alan Servet , Sili Uluhan , Bakan Dilek , Ocak İlhan , Yürekli Rayfe , Alpay Nadir , Görçin Serpil , Yıldız Alaattin 
Published: August 2020

SUMMARYA better understanding of the innate and adaptive cells in the COVID-19 disease caused by the SARS-CoV-2 coronavirus is a necessity for the development of effective treatment methods and vaccines. We studied phenotypic features of innate and adaptive immune cells, oxidative burst, phagocytosis and apoptosis. One hundred and three patients with COVID-19 grouped according to their clinical features as mild (35%), moderate (40.8%), and severe (24.3%) were included in the study. Monocytes from all COVID-19 patients were CD16+ pro-inflammatory monocytes. Neutrophils were mature and functional. No defect has been found in ROS production of monocytes and neutrophils as well as no defect in their apoptosis. As bridging cells of the innate and adaptive immune system; the percentage of NK cells was in normal range whereas the percentages of CD3-CD8+CD56+ innate lymphoid and CD3+CD56+ NK like T cells were found to be high in the severe cases of COVID-19. Although absolute numbers of all lymphocyte subsets were low and showed a tendency for a gradual decrease in accord with the disease progression, in all COVID-19 patients, the lymphocyte subset with the most decreased absolute number was B lymphocytes, followed by CD4 + T cells in the severe cases. The percentages of suppressive, CD3+CD4-CD8-; HLA-DR+CD3+ and CD28-CD8+ cells were found to be significantly increased. Importantly, we demonstrated spontaneous caspase-3 activation and increased lymphocyte apoptosis. Altogether our data suggest that SARS-CoV-2 primarily affects lymphocytes not innate cells. So that, it may interrupt the cross-talk between adaptive and innate immune systems.