Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating COVID-19 Prevalence in the United States: A Sample Selection Model Approach

Background: Public health efforts to determine population infection rates from coronavirus disease 2019 (COVID-19) have been hampered by limitations in testing capabilities and the large shares of mild and asymptomatic cases. We developed a methodology that corrects observed positive test rates for non-random sampling to estimate population infection rates across U.S. states from March 31 to April 7. Methods We adapted a sample selection model that corrects for non-random testing to estimate population infection rates. The methodology compares how the observed positive case rate vary with changes in the size of the tested population, and applies this gradient to infer total population infection rates. Model identification requires that variation in testing rates be uncorrelated with changes in underlying disease prevalence. To this end, we relied on data on day-to-day changes in completed tests across U.S. states for the period March 31 to April 7, which were primarily influenced by immediate supply-side constraints. We used this methodology to construct predicted infection rates across each state over the sample period. We also assessed the sensitivity of the results to controls for state-specific daily trends in infection rates. Results The median population infection rate over the period March 31 to April 7 was 0.9% (IQR 0.64 1.77). The three states with the highest prevalence over the sample period were New York (8.5%), New Jersey (7.6%), and Louisiana (6.7%). Estimates from models that control for state-specific daily trends in infection rates were virtually identical to the baseline findings. The estimates imply a nationwide average of 12 population infections per diagnosed case. We found a negative bivariate relationship (corr. = -0.51) between total per capita state testing and the ratio of population infections per diagnosed case. Interpretation The effectiveness of the public health response to the coronavirus pandemic will depend on timely information on infection rates across different regions. With increasingly available high frequency data on COVID-19 testing, our methodology could be used to estimate population infection rates for a range of countries and subnational districts. In the United States, we found widespread undiagnosed COVID-19 infection. Expansion of rapid diagnostic and serological testing will be critical in preventing recurrent unobserved community transmission and identifying the large numbers individuals who may have some level of viral immunity.
Strong effect of socioeconomic levels on the spread and treatment of the 2019 novel coronavirus (COVID-19) in China

Background: Global response to the COVID-19 epidemic presents strengths and weaknesses in national and regional social governance capacities to address public health challenges. The emergence, detection, spread, treatment and containment of infectious diseases shows the considerable political and economic impacts in a highly interconnected world. We aimed to estimate the effects of socioeconomic levels on the spread and treatment of COVID-19 in China. Methods: We obtained daily COVID-19 cases at a city level in China. We used migration data from the major cities in Hubei Province, and macroeconomic data at city and province levels. We obtained social management measures in response to COVID-19 outbreak. We assessed the association between measures, migration and COVID-19 spread, and the association between socioeconomic levels and COVID-19 treatment capacity. Findings: On January 1, 2020, COVID-19 spread that affected by management measures and migration started across China. After Wuhan lockdown, the case number reached peak in 12 days, and COVID-19 outbreak was basically contained in China in four weeks due to intensive measures. Guangdong, Jiangsu and Zhejiang Provinces showed the most excellent COVID-19 treatment capacities. Socioeconomic levels in these provinces ranked top in China. Guangdong achieved the largest decline in severe case rate by 22.1%. Jiangsu had the lowest average rate of severe cases (1.7%) and zero death. Among the regions with top case number, Zhejiang showed the highest rate of cured cases on confirmed cases (96.3%), the lowest average rate of severe cases (7.7%), and one death. The COVID-19 treatment capacities were strongly affected by regional economics and measures on control, detection and treatment. Interpretation: Socioeconomic levels had strong effect on the spread and treatment of COVID-19 in China. Further investigations are needed on the effectiveness of Chinese measures and the effects of socioeconomic levels on COVID-19 treatment outside China. Fund Guangdong Natural Science Foundation
Pooled RNA sample reverse transcriptase real time PCR assay for SARS CoV-2 infection: a reliable, faster and economical method.

Background: Corona virus disease 2019 (COVID-19) which initially started as a cluster of pneumonia cases in the Wuhan city of China has now become a full blown pandemic. Timely diagnosis of COVID-19 is the key in containing the pandemic and breaking the chain of In low and middle income countries availability of testing kits has become the major bottle neck in testing. Novel methods like pooling of samples are the need of the hour. Method: Extracted RNA samples were randomly placed in pools of 8 on a 96 well plate. Both individual RNA (ID) and pooled RNA RT-qPCR for the screening E gene were done in the same plate and the positivity for the E gene was seen. Results: The present study demonstrated that pool testing with 8 RNA samples can easily detect even up to a single positive sample with Ct value as high as 38. The present study also showed that the results of pool testing is not affected by number of positive samples in a pool. Conclusion: Pooling of 8 RNA samples can reduce the time and expense by one eighth, and can help expand diagnostic capabilities, especially during constrained supply of reagents and PCR kits for the diagnosis of SARS-CoV-2 infection.
Eccentric-focused rehabilitation promotes myelin plasticity in individuals with chronic, incomplete spinal cord injury

Background: Myelin plasticity has emerged as a novel mechanism by which the nervous system can change with experience, offering new potential for rehabilitation-induced recovery after neurotrauma. This first-in-human study investigated whether innovative, downhill locomotor rehabilitation promotes myelin plasticity in individuals with chronic, incomplete spinal cord injury (SCI). Methods: Of 20 individuals with SCI that enrolled, 4 passed the imaging screen and had myelin water imaging (MWI) before and after a 12-week (3 times/week) downhill locomotor treadmill training program (SCI+DH). One individual was excluded for imaging artifacts. Uninjured control participants (n=7) had two MWI sessions within the same day. Changes in myelin water fraction (MWF), a histopathologically-validated myelin biomarker, were analyzed in a priori motor learning and non-motor learning brain regions and the cervical spinal cord using statistical approaches appropriate for small sample sizes. Results: Within SCI+DH individuals, significantly more motor learning regions showed increased MWF than non-motor learning regions (p<.05). Compared to Control, MWF in the SCI+DH group increased in white matter underlying postcentral and precuneus cortices, combined motor learning brain regions, and ventral spinal cord (p<.05). To account for small sample size, an estimation-based approach showed the pattern of MWF increase was specific to training and region. Conclusion: Downhill training increased MWF in brain regions specifically associated with motor learning and in the ventral spinal cord. Trial Registration: ClincialTrials.gov (NCT02498548, NCT02821845). Funding: National Institutes of Health [F31NS096921 (TDF), R21HD082808 (DMB)], Craig H. Neilsen Foundation [316282 (DMB)], Foundation for Physical Therapy Research [Promotion of Doctoral Studies Level II Scholarship (TDF)]
Inferred duration of infectious period of SARS-CoV-2: rapid scoping review and analysis of available evidence for asymptomatic and symptomatic COVID-19 cases

Objectives Our objective was to review the literature on the inferred duration of the infectious period of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, and provide an overview of the variation depending on the methodological approach. Design Rapid scoping review. Literature review with fixed search terms, up to 1 April 2020. Central tendency and variation of the parameter estimates for infectious period in (A) asymptomatic and (B) symptomatic cases from (1) virological studies (repeated testing), (2) tracing studies and (3) modelling studies were gathered. Narrative review of viral dynamics. Information sources Search strategies developed and the following searched: PubMed, Google Scholar, MedRxiv and BioRxiv. Additionally, the Health Information Quality Authority (Ireland) viral load synthesis was used, which screened literature from PubMed, Embase, ScienceDirect, NHS evidence, Cochrane, medRxiv and bioRxiv, and HRB open databases. Results There was substantial variation in the estimates, and how infectious period was inferred. One study provided approximate median infectious period for asymptomatic cases of 6.5–9.5 days. Median presymptomatic infectious period across studies varied over <1–4 days. Estimated mean time from symptom onset to two negative RT-PCR tests was 13.4 days (95% CI 10.9 to 15.8) but was shorter when studies included children or less severe cases. Estimated mean duration from symptom onset to hospital discharge or death (potential maximal infectious period) was 18.1 days (95% CI 15.1 to 21.0); time to discharge was on average 4 days shorter than time to death. Viral dynamic data and model infectious parameters were often shorter than repeated diagnostic data. Conclusions There are limitations of inferring infectiousness from repeated diagnosis, viral loads and viral replication data alone and also potential patient recall bias relevant to estimating exposure and symptom onset times. Despite this, available data provide a preliminary evidence base to inform models of central tendency for key parameters and variation for exploring parameter space and sensitivity analysis.
The natural history and transmission potential of asymptomatic SARS-CoV-2 infection

Background: Little is known about the natural history of asymptomatic SARS-CoV-2 infection or its contribution to infection transmission. Methods: We conducted a prospective study at a quarantine centre for COVID-19 in Ho Chi Minh City, Vietnam. We enrolled quarantined people with RT-PCR-confirmed SARS-CoV-2 infection, collecting clinical data, travel and contact history, and saliva at enrolment and daily nasopharyngeal throat swabs (NTS) for RT-PCR testing. We compared the natural history and transmission potential of asymptomatic and symptomatic individuals. Results: Between March 10th and April 4th, 2020, 14,000 quarantined people were tested for SARS-CoV-2; 49 were positive. Of these, 30 participated in the study: 13(43%) never had symptoms and 17(57%) were symptomatic. 17(57%) participants acquired their infection outside Vietnam. Compared with symptomatic individuals, asymptomatic people were less likely to have detectable SARS-CoV-2 in NTS samples collected at enrolment (8/13 (62%) vs. 17/17 (100%) P=0.02). SARS-CoV-2 RNA was detected in 20/27 (74%) available saliva; 7/11 (64%) in the asymptomatic and 13/16 (81%) in the symptomatic group (P=0.56). Analysis of the probability of RT-PCR positivity showed asymptomatic participants had faster viral clearance than symptomatic participants (P<0.001 for difference over first 19 days). This difference was most pronounced during the first week of follow-up. Two of the asymptomatic individuals appeared to transmit the infection to up to four contacts. Conclusions: Asymptomatic SARS-CoV-2 infection is common and can be detected by analysis of saliva or NTS. NTS viral loads fall faster in asymptomatic individuals, but they appear able to transmit the virus to others.
Lopinavir-ritonavir alone or combined with arbidol in the treatment of 73 hospitalized patients with COVID-19: a pilot retrospective study

Objectives: This study aimed to evaluate the antiviral efficacy of lopinavir/ritonavir alone or combined with arbidol in the treatment of hospitalized patients with common coronavirus disease-19 (COVID-19). Methods: In this retrospective observational study, COVID-19 hospitalized patients were identified and divided into two groups based on the antiviral agents used during their hospitalization. Group-LR patients were treated with single antiviral drug of lopinavir-ritonavir. Group-LR+Ar patients were treated with lopinavir-ritonavir combined with arbidol for antiviral therapy at least 3 days. Patients were assessed for different clinical outcomes. Results: A total of 34 and 39 patients were identified for Group-LR and Group-LR+Ar, respectively. Treatment with lopinavir-ritonavir alone was not difference from lopinavir-ritonavir combined with arbidol in overall cure rate of COVID-19 hospitalized patients (92.3% and 97.1%, respectively). In a modified intention-to-treat analysis, lopinavir-ritonavir combined with abidol led to a median time of hospital stay that was shorter by 1.5 days than group-LR (12.5 days vs. 14 days). The percentages of COVID-19 RNA clearance was 92.3 in group-LR and 97.1 in group-LR+Ar. The mean time of virus turning negative was 11.5 plus-or-minus sign 9.0 days in group-LR+Ar that were longer than group-LR. Treatment of lopinavir-ritonavir combined with arbidol did not significantly accelerate main symptoms improvement and promote the image absorption of pulmonary inflammation. Conclusion: No benefit was observed in the anti-virus effect of lopinavir-ritonavir combined with arbidol compared with lopinavir-ritonavir alone in the hospitalized patients with COVID-19. More clinical observations in COVID-19 patients may help to confirm or exclude the effect of antiviral agents.
A COVID-19 epidemic model integrating direct and fomite transmission as well as household structure

This paper stresses its base contribution on a new SIR-type model for COVID-19 including direct and fomite transmission as well as the effect of distinct household structures. To what extent increasing the physical-distancing-related contact radius and enhancing mass control (public curfew, lockdown, workplace clearance, and school closure) reduce the number of predicted active cases is studied via parameter estimation.
Transmission Genetics of a Sorghum bicolor × S. halepense Backcross Populations

Despite a “ploidy barrier,” interspecific crosses to wild and/or cultivated sorghum (Sorghum bicolor, 2n = 2x = 20) may have aided the spread across six continents of Sorghum halepense, also exemplifying risks of “transgene escape” from crops that could make weeds more difficult to control. Genetic maps of two BC1F1 populations derived from crosses of S. bicolor (sorghum) and S. halepense with totals of 722 and 795 single nucleotide polymorphism (SNP) markers span 37 and 35 linkage groups, with 2–6 for each of the 10 basic sorghum chromosomes due to fragments covering different chromosomal portions or independent segregation from different S. halepense homologs. Segregation distortion favored S. halepense alleles on chromosomes 2 (1.06–4.68 Mb, near a fertility restoration gene), 7 (1.20–6.16 Mb), 8 (1.81–5.33 Mb, associated with gene conversion), and 9 (47.5–50.1 Mb); and S. bicolor alleles on chromosome 6 (0–40 Mb), which contains both a large heterochromatin block and the Ma1 gene. Regions of the S. halepense genome that are recalcitrant to gene flow from sorghum might be exploited as part a multi-component system to reduce the likelihood of spread of transgenes or other modified genes. Its SNP profile suggests that chromosome segments from its respective progenitors S. bicolor and Sorghum propinquum have extensively recombined in S. halepense. This study reveals genomic regions that might discourage crop-to-weed gene escape, and provides a foundation for marker-trait association analysis to determine the genetic control of traits contributing to weediness, invasiveness, and perenniality of S. halepense.
Does Antenatal Betamethasone Alter White Matter Brain Development in Growth Restricted Fetal Sheep?

Fetal growth restriction (FGR) is a common complication of pregnancy often associated with neurological impairments. Currently, there is no treatment for FGR, hence it is likely these babies will be delivered prematurely, thus being exposed to antenatal glucocorticoids. While there is no doubt that antenatal glucocorticoids reduce neonatal mortality and morbidities, their effects on the fetal brain, particularly in FGR babies, are less well recognized. We investigated the effects of both short- and long-term exposure to antenatal betamethasone treatment in both FGR and appropriately grown fetal sheep brains. Surgery was performed on pregnant Border-Leicester Merino crossbred ewes at 105–110 days gestation (term ~150 days) to induce FGR by single umbilical artery ligation (SUAL) or sham surgery. Ewes were then treated with a clinical dose of betamethasone (11.4 mg intramuscularly) or saline at 113 and 114 days gestation. Animals were euthanized at 115 days (48 h following the initial betamethasone administration) or 125 days (10 days following the initial dose of betamethasone) and fetal brains collected for analysis. FGR fetuses were significantly smaller than controls (115 days: 1.68 ± 0.11 kg vs. 1.99 ± 0.11 kg, 125 days: 2.70 ± 0.15 kg vs. 3.31 ± 0.20 kg, P < 0.001) and betamethasone treatment reduced body weight in both control (115 days: 1.64 ± 0.10 kg, 125 days: 2.53 ± 0.10 kg) and FGR fetuses (115 days: 1.41 ± 0.10 kg, 125 days: 2.16 ± 0.17 kg, P < 0.001). Brain: body weight ratios were significantly increased with FGR (P < 0.001) and betamethasone treatment (P = 0.002). Within the fetal brain, FGR reduced CNPase-positive myelin staining in the subcortical white matter (SCWM; P = 0.01) and corpus callosum (CC; P = 0.01), increased GFAP staining in the SCWM (P = 0.02) and reduced the number of Olig2 cells in the periventricular white matter (PVWM; P = 0.04). Betamethasone treatment significantly increased CNPase staining in the external capsule (EC; P = 0.02), reduced GFAP staining in the CC (P = 0.03) and increased Olig2 staining in the SCWM (P = 0.04). Here we show that FGR has progressive adverse effects on the fetal brain, particularly within the white matter. Betamethasone exacerbated growth restriction in the FGR offspring, but betamethasone did not worsen white matter brain injury.
A Broad Spectrum Chemokine Inhibitor Prevents Preterm Labor but Not Microbial Invasion of the Amniotic Cavity or Neonatal Morbidity in a Non-human Primate Model

Leukocyte activation within the chorioamniotic membranes is strongly associated with inflammation and preterm labor (PTL). We hypothesized that prophylaxis with a broad-spectrum chemokine inhibitor (BSCI) would downregulate the inflammatory microenvironment induced by Group B Streptococcus (GBS, Streptococcus agalactiae) to suppress PTL and microbial invasion of the amniotic cavity (MIAC). To correlate BSCI administration with PTL and MIAC, we used a unique chronically catheterized non-human primate model of Group B Streptococcus (GBS)-induced PTL. In the early third trimester (128–138 days gestation; ~29–32 weeks human pregnancy), animals received choriodecidual inoculations of either: (1) saline (N = 6), (2) GBS, 1–5 × 108 colony forming units (CFU)/ml; N = 5), or (3) pre-treatment and daily infusions of a BSCI (10 mg/kg intravenous and intra-amniotic) with GBS (1–5 × 108 CFU/ml; N = 4). We measured amniotic cavity pressure (uterine contraction strength) and sampled amniotic fluid (AF) and maternal blood serially and cord blood at delivery. Cesarean section was performed 3 days post-inoculation or earlier for PTL. Data analysis used Fisher's exact test, Wilcoxon rank sum and one-way ANOVA with Bonferroni correction. Saline inoculation did not induce PTL or infectious sequelae. In contrast, GBS inoculation typically induced PTL (4/5, 80%), MIAC and fetal bacteremia (3/5; 60%). Remarkably, PTL did not occur in the BSCI+GBS group (0/4, 0%; p = 0.02 vs. GBS), despite MIAC and fetal bacteremia in all cases (4/4; 100%). Compared to the GBS group, BSCI prophylaxis was associated with significantly lower cytokine levels including lower IL-8 in amniotic fluid (p = 0.03), TNF-α in fetal plasma (p < 0.05), IFN-α and IL-7 in the fetal lung (p = 0.02) and IL-18, IL-2, and IL-7 in the fetal brain (p = 0.03). Neutrophilic chorioamnionitis was common in the BSCI and GBS groups, but was more severe in the BSCI+GBS group with greater myeloperoxidase staining (granulocyte marker) in the amnion and chorion (p < 0.05 vs. GBS). Collectively, these observations indicate that blocking the chemokine response to infection powerfully suppressed uterine contractility, PTL and the cytokine response, but did not prevent MIAC and fetal pneumonia. Development of PTL immunotherapies should occur in tandem with evaluation for AF microbes and consideration for antibiotic therapy.
Finite Difference Method for the One-Dimensional Non-linear Consolidation of Soft Ground Under Uniform Load

Initial stress and additional effective stress distributions in soil greatly influence the degree of ground consolidation when calculating one-dimensional soft clay ground consolidation in deep soil. The one-dimensional non-linear consolidation governing equations of soft ground under uniform load are derived and solved with the finite difference method. This method is based on the assumptions that the initial stress in soil varies with the ground depth and that the additional effective stress caused by external loads changes with both the ground depth and consolidation time and the hyperbolic model of the soil stress–strain relationship. Formulas for the degree of consolidation and the settlement of the ground are presented. A case study shows that the degree of consolidation in the ground calculated with the finite difference method agrees well with the traditional analytical solution, and the computational efficiency of the finite difference method can be effectively improved when the segmental calculation method is used throughout the consolidation process. The results of another example show that the settlement of the ground calculated with the finite difference method agrees with the in situ data. The suggested method can greatly simplify the consolidation calculation and has a high application value in engineering.