bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the auxiliary diagnosis value of antibodies assays for the detection of novel coronavirus (SARS-Cov-2)
Authors: Yong Gao , Yi Yuan , Tuantuan Li , Xiaowu Wang , Xiuyong Li , Ang Li , Mingfeng Han
Published: March 2020

Background

The spread of an novel coronavirus (SARS-CoV-2, previously named 2019-nCoV) has already taken on pandemic proportions, affecting over 100 countries in a matter of weeks. Elucidating the diagnostic value of different methods, especially the auxiliary diagnosis value of antibodies assays for SARS-CoV-2 infection is helpful for improving the sensitivities of pathogenic-diagnosis, providing timely treatment, and differentiating the infected cases from the healthy, thus preventing further epidemics.

Methods

Medical records from 38 patients with confirmed SARS-CoV-2 infection in the Second People’s Hospital of Fuyang from January 22, 2020 to February 28, 2020 were collected and retrospectively analyzed. Specimens including throat swabs, sputum and serum were collected during the hospitalization period, viral RNAs and serum IgM-IgG antibodies to SARS-CoV-2 were measured respectively. The detectability of different methods as well as the auxiliary diagnosis value of antibodies test for SARS-CoV-2 infection were analyzed.

Results

Among 38 patients, the total seropositive rate for IgM and IgG was 50.0% and 92.1%, respectively. Two patients remained seronegative throughout the course of illness. In the early phase of illness, the RNA test for sputum specimens possessed the highest detectability(92.3%), followed by the the RNA test for throat swabs (69.2%), and the antibodies assays presented lower positive rates(IgM, 23.0%, IgG, 53.8%). While, the sensitivity of antibodies assays overtook that of RNA test since day 8 after onset (IgM, 50.0%; IgG, 87.5%). Of note, the positive rate of throat swabs was only 13.0% for cases in later phase(≥15 d.a.o), and the sensitivities of IgM and IgG rose to 52.2% and 91.3%, respectively. Combined use of antibodies assay and qRT-PCR at the same time was able to improve the sensitivities of pathogenic-diagnosis, especially for the throat swabs group at the later stage of illness. Moreover, most of these cases with undetectable viral RNA in throat swabs specimens at the early stage of illness were able to be IgM/IgG seropositive after 7 days.

Conclusions

The antibodies detection against SARS-CoV-2 offers vital clinical information for physicians, and could be used as an effective supplementary indicator for suspected cases of negative viral nucleic acid detection or in conjunction with nucleic acid detection in the diagnosis of suspected cases.
Clinical and Paraclinical Characteristics of COVID-19 patients: A systematic review and meta-analysis
Authors: Heydari Keyvan , Rismantab Sahar , Shamshirian Amir , Lotfi Parisa , Shadmehri Nima , Houshmand Pouya , Zahedi Mohammad , Shamshirian Danial , Bathaeian Sahar , Alizadeh-Navaei Reza
Published: March 2020

Introduction

Recently, a new strain of coronaviruses, which originated from Wuhan City, Hubei Province, China has been identified. According to the high prevalence of new coronavirus, further investigation on the clinical and paraclinical features of this disease seems essential. Hence, we carried out this systematic review and meta-analysis to figure out the unknown features.

Methods

This study was performed using databases of Web of Science, Scopus and PubMed. We considered English cross-sectional and case-series papers which reported clinical, radiological, and laboratory characteristics of patients with COVID-19. We used STATA v.11 and random effect model for data analysis.

Results

In the present meta-analysis, 32 papers including 49504 COVID-19 patients were studied. The most common clinical symptoms were fever (84%), cough (65%) and fatigue (42%), respectively. The most common radiological and paraclinical features were bilateral pneumonia (61%), ground-glass opacity (50%), thrombocytopenia (36%) and lymphocytopenia (34%). The study also showed that the frequency of comorbidities and early symptoms was higher in critically severe patients. Moreover, we found the overall mortality rate of three percent.

Conclusion

According to that there are many cases without Computed Tomography Scan findings or clear clinical symptoms, it is recommended to use other confirming methods such RNA sequencing in order to identification of suspicious undiagnosed patients. Moreover, while there is no access to clinical and paraclinical facilities in in public places such as airports and border crossings, it is recommended to consider factors such as fever, cough, sputum and fatigue.
Extrapolation of Infection Data for the CoVid-19 Virus and Estimate of the Pandemic Time Scale
Authors: Langel Walter
Published: March 2020

Predictions about the further development of the Corona pandemic are widely diverging. Here, a simple yet powerful algorithm is introduced for extrapolating infection rate and number of total infections from available data. The calculation predicts that under present conditions the infection rate in Germany will culminate in a few weeks and decrease to low values by mid-June 2020. Total number of infections will reach several 100000 though. A refinement of the calculation is presented in the supplemental material and shows that the lock down in Germany has reduced the total number of infections from a target value of 338 000 to 184 000, corresponding to a decrease of about 45%.
Understand research hotspots surrounding COVID-19 and other coronavirus infections using topic modeling
Authors: Dong Mengying , Cao Xiaojun , Liang Mingbiao , Li Lijuan , Liu Guangjian , Liang Huiying
Published: March 2020

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that causes severe respiratory illness in humans, which results in global outbreak of novel coronavirus disease (COVID-19) currently. This study aimed to evaluate the characteristics of publications involving coronaviruses as well as COVID-19 by using topic modeling.

Methods

We extracted all abstracts and retained the most informative words from the COVID-19 Open Research Dataset, which contains 35,092 pieces of coronavirus related literature published up to March 20, 2020. Using Latent Dirichlet Allocation modeling, we trained a topic model from the corpus, analyzed the semantic relationships between topics and compared the topic distribution between COVID-19 and other CoV infections.

Results

Eight topics emerged overall: clinical characterization, pathogenesis research, therapeutics research, epidemiological study, virus transmission, vaccines research, virus diagnostics, and viral genomics. It was observed that current COVID-19 research puts more emphasis on clinical characterization, epidemiological study, and virus transmission. In contrast, topics about diagnostics, therapeutics, vaccines, genomics and pathogenesis only account for less than 10% or even 4% of all the COVID-19 publications, much lower than those of other CoV infections.

Conclusions

These results identified knowledge gaps in the area of COVID-19 and offered directions for future research.
No SARS-CoV-2 in expressed prostatic secretion of patients with coronavirus disease 2019: a descriptive multicentre study in China
Authors: Quan Weihe , Chen Jun , Liu Zhigang , Tian Jinfei , Chen Xiangqiu , Wu Tao , Ji Ziliang , Tang Jinqi , Chu Hao , Xu Haijia , Zhao Yong , Zheng Qingyou
Published: March 2020

Purpose

The aim of the present study was to assess whether SARS-CoV-2 can be detected in the expressed prostatic secretion (EPS) of patients with corona virus disease 2019 (COVID-19).

Methods

18 cases of COVID-19, and 5 suspected cases, were selected from three medical centers to detect the RNA expression of SARS-CoV-2 in their EPS with RT-PCR.

Results

Results were negative in all EPS samples for SARS-CoV-2 of suspected and confirmed patients.

Conclusions

No SARS-CoV-2 was expressed in EPS of patients with COVID-19.
Clinical characteristics of the recovered COVID-19 patients with re-detectable positive RNA test
Authors: An Jianghong , Liao Xuejiao , Xiao Tongyang , Qian Shen , Yuan Jing , Ye Haocheng , Qi Furong , Shen Chengguang , Liu Yang , Wang Lifei , Cheng Xiaoya , Li Na , Cai Qingxian , Wang Fang , Chen Jun , Liu Yingxia , Wang Yunfang , Zhang Feng , Fu Yang , Tan Xiaohua , Liu Lei , Zhang Zheng
Published: March 2020

Background

It has been reported that several cases recovered from COVID-19 tested positive for SARS-CoV-2 after discharge (re-detectable positive, RP), however the clinical characteristics, significance and potential cause of RP patients remained elusive.

Methods

A total of 262 COVID-19 patients were discharged from January 23 to February 25, 2020, and were enrolled for analysis of their clinical parameters. The RP and non-RP (NRP) patients were grouped according to the disease severity during their hospitalization period. The clinical characterization at re-admission to the hospital was analyzed. SARS-CoV-2 RNA and plasma antibody levels were detected using high-sensitive detection methods.

Findings

Up to March 10, 2020, all of patients were followed up for at least 14 days, and 38/262 of RP patients (14.5%) were present. The RP patients were characterized by being less than 14-years old and having mild and moderate conditions as compared to NRP patients, while no severe patients became RP. Retrospectively, the RP patients displayed fewer symptoms, more sustained remission of CT imaging and earlier RNA negative-conversion but similar plasma antibody levels during their hospitalization period as compared to those NRP patients. When re-admitted to the hospital, these RP patients showed no obvious clinical symptoms or disease progression indicated by normal or improving CT imaging and inflammatory cytokine levels. All 21 close contacts of RP patients were tested negative for SARS-CoV-2 RNA, and no suspicious clinical symptoms were reported. However, 18/24 of RNA-negative samples detected by the commercial kit were tested to be positive for virus RNA using a hyper-sensitive method, suggesting the carrier status of virus possibly existed in patients recovered from COVID-19.

Interpretation

Our results showed that young and mild COVID-19 patients seem to be RP patients after discharge, who show no obviously clinical symptoms and disease progression upon re-admission. More sensitive RNA detection methods are required to monitor these patients during follow-up. Our findings provide empirical information and evidence for the effective management of COVID-19 patients during their convalescent phase.
An Evaluation of the Vulnerable Physician Workforce in the United States During the Coronavirus Disease-19 Pandemic
Authors: Khera Rohan , Dhingra Lovedeep Singh , Jain Snigdha , Krumholz Harlan M
Published: March 2020

Background

The coronavirus disease-19 (COVID-19) pandemic threatens to overwhelm the healthcare resources of the country, but also poses a personal hazard to healthcare workers, including physicians. To address the potential impact of excluding physicians with a high risk of adverse outcomes based on age, we evaluated the current patterns of age of licensed physicians across the United States.

Methods

We compiled information from the 2018 database of actively licensed physicians in the Federation of State Medical Boards (FSMB) across the US. Both at a national- and the state-level, we assessed the number and proportion of physicians who would be at an elevated risk due to age over 60 years.

Results

Of the 985,026 licensed physicians in the US, 235857 or 23.9% were aged 25-40 years, 447052 or 45.4% are 40-60 years, 191794 or 19.5% were 60-70 years, and 106121 or 10.8% were 70 years or older. Age was not reported in 4202 or 0.4% of physicians. Overall, 297915 or 30.2% of physicians were 60 years of age or older, 246167 (25.0%) 65 years and older, and 106121 (10.8%) 70 years or older. States in the US reported that a median 5470 licensed physicians (interquartile range [IQR], 2394 to 10108) were 60 years of age or older. Notably, states of North Dakota (n=1180) and Vermont (n = 1215) had the lowest and California (n=50786) and New York (n=31582) the highest number of physicians over the age of 60 years (Figure 1). Across states, the median proportion of physicians aged 60 years and older was 28.9% (IQR, 27.2%, 31.4%), and ranged between 25.9% for Nebraska to 32.6% for New Mexico (Figure 2).

Discussion

Older physicians represent a large proportion of the US physician workforce, particularly in states with the worst COVID-19 outbreak. Therefore, their exclusion from patient care will be impractical. Optimizing care practices by limiting direct patient contact of physicians vulnerable to adverse outcomes from COVID-19, potentially by expanding their participation in telehealth may be a strategy to protect them.
Causal empirical estimates suggest COVID-19 transmission rates are highly seasonal
Authors: Carleton Tamma , Meng Kyle C.
Published: March 2020

Nearly every country is now combating the 2019 novel coronavirus (COVID-19). It has been hypothesized that if COVID-19 exhibits seasonality, changing temperatures in the coming months will shift transmission patterns around the world. Such projections, however, require an estimate of the relationship between COVID-19 and temperature at a global scale, and one that isolates the role of temperature from confounding factors, such as public health capacity. This paper provides the first plausibly causal estimates of the relationship between COVID-19 transmission and local temperature using a global sample comprising of 166,686 confirmed new COVID-19 cases from 134 countries from January 22, 2020 to March 15, 2020. We find robust statistical evidence that a 1°C increase in local temperature reduces transmission by 13% [−21%, −4%, 95%CI]. In contrast, we do not find that specific humidity or precipitation influence transmission. Our statistical approach separates effects of climate variation on COVID-19 transmission from other potentially correlated factors, such as differences in public health responses across countries and heterogeneous population densities. Using constructions of expected seasonal temperatures, we project that changing temperatures between March 2020 and July 2020 will cause COVID-19 transmission to fall by 43% on average for Northern Hemisphere countries and to rise by 71% on average for Southern Hemisphere countries. However, these patterns reverse as the boreal winter approaches, with seasonal temperatures in January 2021 increasing average COVID-19 transmission by 59% relative to March 2020 in northern countries and lowering transmission by 2% in southern countries. These findings suggest that Southern Hemisphere countries should expect greater transmission in the coming months. Moreover, Northern Hemisphere countries face a crucial window of opportunity: if contagion-containing policy interventions can dramatically reduce COVID-19 cases with the aid of the approaching warmer months, it may be possible to avoid a second wave of COVID-19 next winter.
Inclusive Costs of NPI Measures for COVID-19 Pandemic: Three Approaches
Authors: Ugarov Alexander
Published: March 2020

The paper evaluates total inclusive costs of three public health approaches to address the COVID-19 epidemic in the US based on epidemiological projections in Ferguson et al (2020). We calculate and add costs of lost productivity and costs of mortality measured through the value of statistical life. We find that the aggressive approach which involves strict suppression measures and a drastic reduction of economic activity for three months with extensive testing and case tracking afterwards results in the lowest total costs for the society. The approach of doing no non-pharmaceutical measures results in the lowest total costs if the infection fatality rate falls below 0.15%.
Doubling time tells how effective Covid-19 prevention works
Authors: Weon Byung Mook
Published: March 2020

Covid-19 (coronavirus disease 2019) is a rapidly spreading pandemic in many countries. The total confirmed cases of Covid-19 are exponentially increasing and many countries are fighting Covid-19 with all strategies. However, there is still lacking consensus for effective strategies. Here, I demonstrate the time dependence of the doubling time in the Covid-19 exponential growths. Tracking the time-dependent doubling time tells how well Covid-19 prevention works, giving an index for successful fighting.
Crowdfunding Medical Care: A Comparison of Online Medical Fundraising in Canada, the United Kingdom, and the United States
Authors: Saleh Sameh N. , Ajufo Ezimamaka , Lehmann Christoph U. , Medford Richard J.
Published: March 2020

Background

Medical crowdfunding is increasingly used to finance personal healthcare costs in Canada (CAN), United Kingdom (UK), and United States (US) despite major differences in their healthcare systems. Yet, it lacks comparative descriptive research to guide policy changes that can promote equitable and accessible healthcare.

Methods

We conducted a cross-sectional analysis of Canadian, British, and American campaigns between February 2018 and March 2019 on the GoFundMe platform (n=3,396). We extracted and manually reviewed variables from campaigns on each country’s GoFundMe discovery webpage, explored campaign characteristics, and compared each country’s campaign demographics to its respective national census. We fit multivariate linear regression models for funds raised for the cohort and for each country.

Results

We examined 1,091 Canadian, 1,082 British, and 1,223 American campaigns. US campaigns (median [IQR] $38,204 [$31,200 to $52,123]) raised more funds than those in CAN ($12,662 [$9,377 to $19,251]) and the UK ($6,285 [$4,028 to $12,348]). Female (38.4% of campaigns vs. 50.9% of US census; p<0.001) and black (5.3% of campaigns vs. 13.4% of US census; p<0.001) beneficiaries were underrepresented in US campaigns. In the full cohort, blacks raised $4,007 less (95% confidence interval [CI] -$6,913 to -$1,101; p=0.007) and males raised $1,742 more (95% CI $583 to $2,901; p=0.003) per campaign. Cancer was the most common diagnosis represented overall (54.5%). Across all diagnoses, campaigns primarily for routine treatment expenses were three times more common in the United States compared to Canada and the United Kingdom (CAN 21.9% vs. UK 26.6% vs. US 77.9%; p<0.001). However, campaigns with routine care were less successful overall, raising $4,589 less per campaign (CI -$6,429 to - $2,749; p<0.001). Campaigns primarily for alternative treatment expenses were nearly five times as common for cancer (24%) than for non-cancer (5%) diagnoses.

Discussion

The trends observed suggest that there are important gaps in healthcare provision in all of the countries examined across a wide range of diagnoses. Although medical crowdfunding has the potential to provide short-term relief from medical financial burden for a privileged subset of patients, it may carry wider-reaching adverse societal effects including the promotion of racial and gender disparities in healthcare. Further work is needed to inform policy changes that promote equitable and accessible healthcare through this practice.

Funding

None.
Global, Regional and National Incidence and Case-fatality rates of Novel Coronavirus (COVID-19) across 154 countries and territories: A systematic assessment of cases reported from January to March 16, 2020
Authors: Bhagavathula Akshaya Srikanth , Rahmani Jamal , Aldhaleei Wafa Ali , Kumar Pavan , Rovetta Alessandro
Published: March 2020

Background

The 2019 novel coronavirus disease (COVID-19) outbreak turned into a pandemic, with hundreds of thousands of cases reported globally. The number of cases dramatically increased beginning in early March 2020.

Aim

We assessed the cumulative change in the incidence and case-fatality rates of COVID-19 at the global, regional, and national levels from January to March 16, 2020, in 154 affected countries and territories globally.

Methods

We collected data of COVID-19 cases using the GitHub repository, which provided real-time surveillance information developed by the Center for Systems Science and Engineering (CSSE), Johns Hopkins University (USA). Information such as confirmed COVID-19 cases, deaths, and recoveries reported across all affected countries was collected from January 22 to March 16, 2020. We estimated the change in the incidence rate, case-fatality rate, and recovery rate from January 22 to February 29 and from March 1 to March 16, 2020.

Results

From January 22 to March 16, 2020, globally, the number of incident COVID-19 cases increased by 276.2%, and Europe recorded 65,281 new cases from March 1 to 16, 2020. Overall, the case-fatality rate was 3.92%, with a high COVID-19 fatality rate in Italy (7.7%), Iran (5.7%), China (4.2%) and the United Kingdom (3.6%). The estimated percentage change in COVID-19 cases from March 1 to 16, 2020, was highest in Belgium (105.8/100,000 population), followed by Qatar (439/100,000 population) and Portugal (331/100,000 population). The overall recovery rate of COVID-19 was 43%; China (35.5%) had the highest recovery rate, while the United States of America recorded a recovery rate of 0.3%.

Conclusion

Overall, all the COVID-19-affected countries showed an upward trend in incidence, with little change in the incidence rate of -0.20% from January to Mid-March. The case-fatality rate was found to be 3.92%, and the recovery rate was observed to be less than half (43%) among COVID-19 patients. Italy, Iran, and Spain had the largest numbers of new cases of COVID-19 from March 1 to 16, 2020.
Evaluating and integrating spatial capture-recapture models with data of variable individual identifiability
Authors: Ruprecht Joel S. , Eriksson Charlotte E. , Forrester Tavis D. , Clark Darren A. , Wisdom Michael J. , Rowland Mary M. , Johnson Bruce K. , Levi Taal
Published: March 2020

Spatial capture-recapture (SCR) models have become the preferred tool for estimating densities of carnivores. Within this family of models are variants requiring identification of all individuals in each encounter (SCR), a subset of individuals only (generalized spatial mark-resight, gSMR), or no individual identification (spatial count or spatial presence-absence). Although each technique has been shown through simulation to yield unbiased results, the consistency and relative precision of estimates across methods in real-world settings are seldom considered. We tested a suite of models ranging from those only requiring detections of unmarked individuals to others that integrate remote camera, physical capture, genetic, and global positioning system (GPS) data into a ‘hybrid’ model, to estimate population densities of black bears, bobcats, cougars, and coyotes. For each species we genotyped fecal DNA collected with detection dogs during a 20-day period. A subset of individuals from each species was affixed with GPS collars bearing unique markings and resighted by remote cameras over 140 days contemporaneous with scat collection. Camera-based gSMR models produced density estimates that differed by less than 10% from genetic SCR for bears, cougars, and coyotes once important sources of variation (sex or behavioral status) were controlled for. For bobcats, SCR estimates were 33% higher than gSMR. The cause of the discrepancies in estimates was likely attributable to challenges designing a study compatible for species with disparate home range sizes and the difficulty of collecting sufficient data in a timeframe in which demographic closure could be assumed. Unmarked models estimated densities that varied greatly from SCR, but estimates became more consistent in models wherein more individuals were identifiable. Hybrid models containing all data sources exhibited the most precise estimates for all species. For studies in which only sparse data can be obtained and the strictest model assumptions are unlikely to be met, we suggest researchers use caution making inference from models lacking individual identity. For best results, we further recommend the use of methods requiring at least a subset of the population is marked and that multiple datasets are incorporated when possible.
Disruption by virtual reality of the cortical oscillations related to visuotactile integration during an embodiment process
Authors: Kanayama Noriaki , Hara Masayuki , Kimura Kenta
Published: March 2020

Virtual reality (VR) enables fast, free, and highly controllable experimental body image setting. Illusions pertaining to a body, like the rubber hand illusion (RHI), can be easily conducted in VR settings, and some phenomena, such as full-body illusions, are only realized in virtual environments. However, the multisensory integration process in VR is not yet fully understood, and we must clarify the limitations and whether specific phenomena can also occur in real life or only in VR settings. One useful investigative approach is measuring brain activities during a psychological experiment. Electroencephalography (EEG) oscillatory activities provide insight into the human multisensory integration process. Unfortunately, the data can be vulnerable to VR noise, which causes measurement and analytical difficulties for EEG data recorded in VR environments. Here, we took care to provide an experimental RHI setting using a head-mounted display, which provided a VR visual space and VR dummy hand along with EEG measurements. We compared EEG data taken in both real and VR environments and observed the gamma and theta band oscillatory activities. Ultimately, we saw statistically significant differences between congruent (RHI) and incongruent (not RHI) conditions in the real environment, which agrees with previous studies. No difference in the VR condition could be observed, suggesting that the VR setting itself altered the perceptual and sensory integration mechanisms. Thus, we must model this difference between real and VR settings whenever we use VR to investigate our bodily self-perception.
Quantifying myelin content in brain tissue using color spatial light interference microscopy (cSLIM)
Authors: Fanous Michael , Caputo Megan P. , Lee Young Jae , Rund Laurie A. , Best-Popescu Catherine , Kandel Mikhail E. , Johnson Rodney W. , Das Tapas , Kuchan Matthew J. , Popescu Gabriel
Published: March 2020

Deficient myelination of the brain is associated with neurodevelopmental delays, particularly in high-risk infants, such as those born small in relation to their gestational age (SGA). New methods are needed to further study this condition. Here, we employ Color Spatial Light Interference Microscopy (cSLIM), which uses a brightfield objective and RGB camera to generate pathlength-maps with nanoscale sensitivity in conjunction with a regular brightfield image. Using tissue sections stained with Luxol Fast Blue, the myelin structures were segmented from a brightfield image. Using a binary mask, those portions were quantitatively analyzed in the corresponding phase maps. We first used the CLARITY method to remove tissue lipids and validate the sensitivity of cSLIM to lipid content. We then applied cSLIM to brain histology slices. These specimens are from a previous MRI study, which demonstrated that appropriate for gestational age (AGA) piglets have increased internal capsule myelination (ICM) compared to small for gestational age (SGA) piglets and that a hydrolyzed fat diet improved ICM in both. The identity of samples was blinded until after statistical analyses.
Roads as conduits of taxonomic, functional and phylogenetic degradation in caatinga vegetation
Authors: Mota Nayara Mesquita , Gastauer Markus , Carrión Juan Fernando , Alves Meira-Neto João Augusto
Published: March 2020

Road networks cause disturbances that can alter the biodiversity and the functioning of the Caatinga ecosystems. We tested the hypotheses that (i) Caatinga vegetation near roads is less taxonomically, functionally and phylogenetically diverse, (ii) phylogenetically and functionally more clustered than vegetation further from roads, (iii) plant traits associated with herbivory deterrence are conserved within the phylogenetic lineages, and (iv) Caatinga vegetation near roads selects for disturbance-related traits. We sampled herbaceous and woody component of vegetation in four plots near roads and four plots further from roads to test these hypothesis. Sampled species were classified according to their resprouting capacity, nitrogen fixation, succulence/spines, urticancy/toxicity, lifeform, endozoochory, maximum height and maximum diameter, before we calculated the taxonomic, functional and phylogenetic diversity of plant communities. Species richness, taxonomic, functional and phylogenetic diversities were lower in plots close to the roads, confirming roads as sources of disturbances. The phylogenetic structure of the Caatinga vegetation near roads was clustered, indicating environmental filtering by herbivory as the main pervasive disturbance in Caatinga ecosystems, since traits related to herbivory deterrence were conserved within phylogenetic lineages and were filtered in near roads. Thus, roads should be considered degradation conduits causing taxonomic, phylogenetic and functional impoverishment of Caatinga vegetation.
Hair glucocorticoids are not a historical marker of stress – exploring the time-scale of corticosterone incorporation into hairs in a rat model
Authors: Colding-Jørgensen Pernille , Hestehave Sara , Abelson Klas S.P. , Kalliokoski Otto
Published: March 2020

Hair glucocorticoids are increasingly popular biomarkers, used across numerous research fields as a measure of stress. Although they are suggested to be a proxy of the average HPA axis activity spanning a period of weeks or months into the past, this theory has never been tested.

In the present study, adrenalectomized rats with no endogenous (adrenal) glucocorticoid production were used to study how circulating glucocorticoid levels would be reflected in the glucocorticoid levels found in hair samples. By dosing the animals daily with high levels of corticosterone for seven days, while sampling hairs before, during, and after treatments, a timeline for glucocorticoid uptake into hairs was constructed. This kinetic profile was compared to two hypothetical models, and the theory that hair glucocorticoids are a record of historical stress had to be rejected.

Corticosterone concentrations in hairs were found to increase within three hours of the first injection, the highest concentrations were found on the seventh day of treatments, and the decrease in concentrations post-treatment suggests rapid elimination. We speculate that hair glucocorticoid levels can only be used to characterize a stress-response for a few days following a postulated stressor.

An updated model, where glucocorticoids diffuse into, along, and out of hairs needs to be adopted to reconcile the experimentally obtained data. The inescapable consequence of this updated model is that hair glucocorticoids become a marker of – and can only be used to study – recent, or ongoing, stress, as opposed to historical events, weeks or months in the past.
Inhalation: A means to explore and optimize nintedanib’s pharmacokinetic/pharmacodynamic relationship
Authors: Epstein-Shochet Gali , Pham Stephen , Beck Steven , Naiel Safaa , Mekhael Olivia , Revill Spencer , Hayat Aaron , Vierhout Megan , Bardestein-Wald Becky , Shitrit David , Ask Kjetil , Montgomery A. Bruce , Kolb Martin R. , Surber Mark W.
Published: March 2020

Oral nintedanib is marketed for the treatment of idiopathic pulmonary fibrosis (IPF). While effective slowing fibrosis progression, as an oral medicine nintedanib is limited. To reduce side effects and maximize efficacy, nintedanib was reformulated as a solution for nebulization and inhaled administration. To predict effectiveness treating IPF, the nintedanib pharmacokinetic/pharmacodynamic relationship was dissected. Pharmacokinetic analysis indicated oral-delivered nintedanib plasma exposure and lung tissue partitioning were not dose-proportional and resulting lung levels were substantially higher than blood. Although initial-oral absorbed nintedanib efficiently partitioned into the lung, only a quickly eliminated fraction appeared available to epithelial lining fluid (ELF). Because IPF disease appears to initiate and progress near the epithelial surface, this observation suggests short duration nintedanib exposure (oral portion efficiently partitioned to ELF) is sufficient for IPF efficacy. To test this hypothesis, exposure duration required for nintedanib activity was explored.In vitro, IPF-cellular matrix (IPF-CM) increased primary normal human fibroblast (nHLF) aggregate size and reduced nHLF cell count. IPF-CM also increased nHLF ACTA2 and COL1A expression. Whether short duration (inhalation mimic) or continuous exposure (oral mimic), nintedanib (1-100 nM) reversed these effects.In vivo, intubated silica produced a strong pulmonary fibrotic response. Once-daily (QD) 0.021, 0.21 and 2.1 mg/kg intranasal (IN; short duration inhaled exposure) and twice daily (BID) 30 mg/kg oral (PO; long duration oral exposure) showed that at equivalent-delivered lung concentrations, QD short duration inhaled nintedanib exposure (0.21 mg/kg IN vs. 30 mg/kg PO) exhibited equivalent-to-superior activity as BID oral (reduced silica-induced elastance, alpha-smooth muscle actin, interleukin-1 beta (IL-1β) and soluble collagen, and lung macrophage and neutrophils). An increased lung dose (2.1 mg/kg IN vs. 30 mg/kg PO) exhibited increased effect by further reducing silica-induced elastance, IL-1β and soluble collagen. Neither oral nor inhaled nintedanib reduced silica-induced parenchymal collagen. Both QD inhaled and BID oral nintedanib reduced silica-induced inflammatory index with oral achieving significance. In summary, nintedanib pulmonary anti-fibrotic activity can be achieved using small, infrequent inhaled doses to deliver oral equivalent-to-superior therapeutic effect.
A two-stage ECG signal denoising method based on deep convolutional network
Authors: Qiu Lishen , Cai Wenqiang , Yu Jie , Zhong Jun , Wang Yan , Li Wanyue , Chen Ying , Wang Lirong
Published: March 2020

Electrocardiogram (ECG) is an effective and non-invasive indicator for the detection and prevention of arrhythmia. ECG signals are susceptible to noise contamination, which can lead to errors in ECG interpretation. Therefore, ECG pretreatment is important for accurate analysis. In this paper, a method of noise reduction based on deep learning is proposed. The method is divided into two stages, and two corresponding models are formed. In the first stage, a one-dimensional U-net model is designed for ECG signal denoising to eliminate noise as much as possible. The one-dimensional DR-net model in the second stage is used to reconstruct the ECG signal and to correct the waveform distortion caused by noise removal in the first stage. In this paper, the U-net and the DR-net are constructed by the convolution method to achieve end-to-end mapping from noisy ECG signals to clean ECG signals. The ECG data used in this paper are from CPSC2018, and the noise signal is from MIT-BIH Noise Stress Test Database (NSTDB). In the experiment, the improvement in the signal-to-noise ratioSNRimp, the root mean square error decreaseRMSEde, and the correlation coefficientP, are used to evaluate the performance of the network. This two-stage method is compared with FCN and U-net alone. The experimental results show that the two-stage noise reduction method can eliminate complex noise in the ECG signal while retaining the characteristic shape of the ECG signal. According to the results, we believe that the proposed method has a good application prospect in clinical practice.
Correlation between hypophosphatemia and the severity of Corona Virus Disease 2019 patients
Authors: Xue Xiaobo , Ma Jing , Zhao Yuxia , Zhao Aibin , Liu Xiaohong , Guo Wei , Yan Fang , Wang Zhixin , Guo Yanqing , Fan Mengbai
Published: March 2020

Objective

Retrospectively analyze the clinical data of Corona Virus Disease 2019 (COVID-19) patients and explore the value of serum phosphorus level in evaluating the severity and prognosis of the disease.

Methods

COVID-19 patients transferred from the first emergency ward of Taiyuan fourth people’s Hospital from February 8 to March 3, 2020 were enrolled. The information of general conditions, clinical manifestations, laboratory indexes, nucleic acid detection and treatment were collected. The changes of blood phosphorus level and absolute value of lymphocytes in ordinary and severe/critical patients were recorded and compared.

Results

A total of 32 patients with COVID-19 were collected, including 12 cases of common type and 20 cases of severe/critical type. Before treatment, the serum phosphorus levels of the two groups were significantly lower than the normal level, and the serum phosphorus levels of the severe/critical patients were lower than those of the common type patients (t = 2.767, P < 0.010). After treatment, the serum phosphorus levels of the two groups reached normal, and there was no significant difference between the two groups (t = 0.231, P >0.819). The level of lymphocytes in severe/critical patients was lower than that in normal patients (t = 4.636, P < 0.001) before treatment. After treatment, the absolute value of lymphocytes in the two groups reached normal, and there was no significant difference between the two groups (t=1.208,P=0.237). There was a positive correlation between lymphocytes and serum phosphorus, and the correlation coefficient was 0.479.

Conclusion

hypophosphatemia is related to the severity of COVID-19, and strengthening the monitoring of serum phosphorus level of COVID-19’s severe/critical patients and correcting hypophosphatemia in time are of significance to improve the prognosis.
Work Intensity and Labour Supply
Authors: Donsimoni Jean Roch
Published: March 2020

We develop a model where individuals accumulate fatigue from work intensity when choosing hours worked. Fatigue captures intertemporal costs of labour supply and leads to a utility loss. As fatigue increases, individuals optimally choose to work fewer hours. The model also predicts that if individuals cannot easily shift consumption over time, they will work fewer hours but accumulate more fatigue when work intensity increases. Calibration to 19 European countries provides evidence for the claim that a higher share of the service sector is linked to increasing work fatigue and that public provisions of healthcare improves recovery and mental health.

JEL codes

E71, I12, J22
Automated classification of neurodegenerative parkinsonian syndromes using multimodal magnetic resonance imaging in a clinical setting
Authors: Chougar Lydia , Faouzi Johann , Pyatigorskaya Nadya , Gaurav Rahul , Biondetti Emma , Villotte Marie , Valabrègue Romain , Corvol Jean-Christophe , Brice Alexis , Mariani Louise-Laure , Cormier Florence , Vidailhet Marie , Dupont Gwendoline , Piot Ines , Grabli David , Payan Christine , Colliot Olivier , Degos Bertrand , Lehéricy Stéphane
Published: March 2020

Background

Several studies have shown that machine learning algorithms using MRI data can accurately discriminate parkinsonian syndromes. Validation under clinical conditions is missing.

Objectives

To evaluate the accuracy for the categorization of parkinsonian syndromes of a machine learning algorithm trained with a research cohort and tested on an independent clinical replication cohort.

Methods

361 subjects, including 94 healthy controls, 139 patients with PD, 60 with PSP with Richardson’s syndrome, 41 with MSA of the parkinsonian variant (MSA-P) and 27 with MSA of the cerebellar variant (MSA-P), were recruited. They were divided into a training cohort (n=179) scanned in a research environment, and a replication cohort (n=182), scanned in clinical conditions on different MRI systems. Volumes and DTI metrics in 13 brain regions were used as input for a supervised machine learning algorithm.

Result

High accuracy was achieved using volumetry in the classification of PD versus PSP, PD versus MSA-P, PD versus MSA-C, PD versus atypical parkinsonian syndromes and PSP versus MSA-C in both cohorts, although slightly lower in the replication cohort (balanced accuracy: 0.800 to 0.915 in the training cohort; 0.741 to 0.928 in the replication cohort). Performance was lower in the classification of PSP versus MSA-P and MSA-P versus MSA-C. When adding DTI metrics, the performance tended to increase in the training cohort, but not in the replication cohort.

Conclusions

A machine learning approach based on volumetric and DTI data can accurately classify subjects with early-stage parkinsonism, scanned on different MRI systems, in the setting of their clinical workup.
Clinical characteristics associated with COVID-19 severity in California
Authors: Rubin Samuel J. S. , Falkson Samuel R. , Degner Nicholas , Blish Catherine
Published: March 2020

Given the rapidly progressing COVID-19 pandemic, this report on a US cohort of 54 COVID-19 patients from Stanford Hospital and data regarding risk factors for severe disease obtained at initial clinical presentation is of high importance and is immediately clinically relevant. We identified low presenting oxygen saturation as predictive of severe disease outcomes, such as diagnosis of pneumonia, acute respiratory distress syndrome (ARDS), and admission to the ICU, and also replicated data from China suggesting a link between hypertension and disease severity. Clinicians will benefit by tools to rapidly risk stratify patients at presentation by likelihood of progression to severe disease.
Evaluation of Group Testing for SARS-CoV-2 RNA
Authors: Sinnott-Armstrong Nasa , Klein Daniel L. , Hickey Brendan
Published: March 2020

During the current COVID-19 pandemic, testing kit and RNA extraction kit availability has become a major limiting factor in the ability to determine patient disease status and accurately quantify prevalence. Current testing strategies rely on individual tests of cases matching restrictive diagnostic criteria to detect SARS-CoV-2 RNA, limiting testing of asymptomatic and mild cases. Testing these individuals is one effective way to understand and reduce the spread of COVID-19.

Here, we develop a pooled testing strategy to identify these low-risk individuals. Drawing on the well-studied group testing literature, modeling suggests practical changes to testing protocols which can reduce test costs and stretch a limited test kit supply. When most tests are negative, pooling reduces the total number of tests up to four-fold at 2% prevalence and eight-fold at 0.5% prevalence. At current SARS-CoV-2 prevalence, randomized group testing optimized per country could double the number of tested individuals from 1.85M to 3.7M using only 671k more tests.

This strategy is well-suited to supplement testing for asymptomatic and mild cases who would otherwise go untested, and enable them to adopt behavioral changes to slow the spread of COVID-19.
In search for the hotspots of Disease X: A biogeographic approach to mapping the predictive risk of WHO’s Blueprint Priority Diseases
Authors: Jagadesh Soushieta , Combe Marine , Nacher Mathieu , Gozlan Rodolphe Elie
Published: March 2020

Anthropization of natural habitats including climate change along with overpopulation and global travel have been contributing to emerging infectious diseases outbreaks. The recent COVID-19 outbreak in Wuhan, highlights such threats to human health, social stability and global trade and economy. We used species distribution modelling and environmental data from satellite imagery to model Blueprint Priority Diseases occurrences. We constructed classical regression and Support Vector Machine models based on environmental predictor variables such as landscape, tree cover loss, climatic covariates. Models were evaluated and a weighed mean was used to map the predictive risk of disease emergence. We mapped the predictive risk for filovirus, Nipah, Rift Valley Fever and coronavirus diseases. Elevation, tree cover loss and climatic covariates were found to significant factors influencing disease emergence. We also showed the relevance of disease biogeography and in the identification potential hotspots for Disease X in regions in Uganda and China.

Article Summary Line

In our study with the use of a biogeographic approach, we were able to identify Wuhan as a potential hotspot of disease emergence in the absence of COVID-19 data and we confirm that distribution of disease emergence in humans is spatially dependent on environmental factors.
A modified SEIR model to predict the COVID-19 outbreak in Spain and Italy: simulating control scenarios and multi-scale epidemics
Authors: López Leonardo , Rodó Xavier
Published: March 2020

Abstract

After the spread of SARS-CoV-2 epidemic out of China, evolution in the pandemic worldwide shows dramatic differences among countries. In Europe, the situation of Italy first and later Spain has generated great concern, and despite other countries show better prospects, large uncertainties yet remain on the future evolution and the efficacy of containment, mitigation or attack strategies. Here we applied a modifiedSEIRcompartmental model accounting for the spread of infection during the latent period, in which we also incorporate effects of varying proportions of containment. We fit data to quarantined populations in order to account for the uncertainties in case reporting and study the scenario projections for the 17 individual regions (CCAA). Results indicate that with data for March 23, the epidemics follows an evolution similar to the isolation of 1, 5 percent of the population and if there were no effects of intervention actions it might reach a maximum over 1.4Minfected aroundApril27. The effect on the epidemics of the ongoing partial confinement measures is yet unknown (an update of results with data until March 31st is included), but increasing the isolation around ten times more could drastically reduce the peak to over 100kcases by early April, while each day of delay in taking this hard containment scenario represents an 90 percent increase of the infected population at the peak. Dynamics at the sub aggregated levels of CCAA show epidemics at the different levels of progression with the most worrying situation in Madrid an Catalonia. Increasing alpha values up to 10 times, in addition to a drastic reduction in clinical cases, would also more than halve the number of deaths. Updates for March 31st simulations indicate a substantial reduction in burden is underway. A similar approach conducted for Italy pre- and post-interventions also begins to suggest substantial reduction in both infected and deaths has been achieved, showing the efficacy of drastic social distancing interventions.