Correlation and prediction of dynamic human isolated joint strength from lean body mass

A relationship between a person's lean body mass and the amount of maximum torque that can be produced with each isolated joint of the upper extremity was investigated. The maximum dynamic isolated joint torque (upper extremity) on 14 subjects was collected using a dynamometer multi-joint testing unit. These data were reduced to a table of coefficients of second degree polynomials, computed using a least squares regression method. All the coefficients were then organized into look-up tables, a compact and convenient storage/retrieval mechanism for the data set. Data from each joint, direction and velocity, were normalized with respect to that joint's average and merged into files (one for each curve for a particular joint). Regression was performed on each one of these files to derive a table of normalized population curve coefficients for each joint axis, direction, and velocity. In addition, a regression table which included all upper extremity joints was built which related average torque to lean body mass for an individual. These two tables are the basis of the regression model which allows the prediction of dynamic isolated joint torques from an individual's lean body mass

Impact of communicative and informative strategies on influenza vaccination adherence and absenteeism from work of health care professionals working at the university hospital of palermo, Italy: A quasi-experimental field trial on twelve influenza seasons

Every year, about 20% of health care workers (HCWs) acquire influenza, continuing to work and encouraging virus spreading. Influenza vaccination coverage rates and absenteeism from work among HCWs of the University Hospital (UH) of Palermo were analyzed before and after the implementation of several initiatives in order to increase HCWs’ awareness about influenza vaccination. Vaccines administration within hospital units, dedicated web pages on social media and on the UH of Palermo institutional web site, and mandatory compilation of a dissent form for those HCWs who refused vaccination were carried out during the last four influenza seasons. After the introduction of these strategies, influenza vaccination coverage went up from 5.2% (2014/2015 season) to 37.2% (2018/2019 season) (p<0.001), and mean age of vaccinated HCWs significantly decreased from 48.1 years (95% CI: 45.7–50.5) to 35.9 years (95% CI: 35.0–36.8). A reduction of working days lost due to acute sickness among HCWs of the UH of Palermo was observed. Fear of adverse reactions and not considering themselves as a high-risk group for contracting influenza were the main reasons reported by HCWs that refused vaccination. Strategies undertaken at the UH of Palermo allowed a significant increase in vaccination adherence and a significant reduction of absenteeism from work

Socio-demographic factors involved in a low-incidence phase of sars-cov-2 spread in sicily, italy

Background: The present study analysed SARS-CoV-2 cases observed in Sicily and investigated social determinants that could have an impact on the virus spread. Methods: SARS-CoV-2 cases observed among Sicilian residents between the 1 February 2020 and 15 October 2020 have been included in the analyses. Age, sex, date of infection detection, residency, clinical outcomes, and exposure route have been evaluated. Each case has been linked to the census section of residency and its socio-demographic data. Results: A total of 10,114 patients (202.3 cases per 100,000 residents; 95% CI = 198.4–206.2) were analysed: 45.4% were asymptomatic and 3.62% were deceased during follow-up. Asymptomatic or mild cases were more frequent among young groups. A multivariable analysis found a reduced risk of SARS-CoV-2 cases was found in census sections with higher male prevalence (adj-OR = 0.99, 95% CI = 0.99–0.99; p < 0.001) and presence of immigrants (adj-OR = 0.89, 95% CI 0.86–0.92; p < 0.001). Proportion of residents aged <15 years, residents with a university degree, residents with secondary education, extra-urban mobility, presence of home for rent, and presence of more than five homes per building were found to increase the risk of SARS-CoV-2 incidence. Conclusion: Routinely collected socio-demographic data can be predictors of SARS-CoV-2 risk infection and they may have a role in mapping high risk micro-areas for virus transmission

Characterisation of Bombyx mori odorant-binding proteins reveals that a general odorant-binding protein discriminates between sex pheromone components

In many insect species, odorant-binding proteins (OBPs) are thought to be responsible for the transport of pheromones and other semiochemicals across the sensillum lymph to the olfactory receptors (ORs) within the antennal sensilla. In the silkworm Bombyx mori, the OBPs are subdivided into three main subfamilies; pheromone-binding proteins (PBPs), general odorant-binding proteins (GOBPs) and antennal-binding proteins (ABPs). We used the MotifSearch algorithm to search for genes encoding putative OBPs in B. mori and found 13, many fewer than are found in the genomes of fruit flies and mosquitoes. The 13 genes include seven new ABP-like OBPs as well as the previously identified PBPs (three), GOBPs (two) and ABPx. Quantitative examination of transcript levels showed that BmorPBP1, BmorGOBP1, BmorGOBP2 and BmorABPx are expressed at very high levels in the antennae and so could be involved in olfaction. A new two-phase binding assay, along with other established assays, showed that BmorPBP1, BmorPBP2, BmorGOBP2 and BmorABPx all bind to the B. mori sex pheromone component (10E,12Z)-hexadecadien-1-ol (bombykol). BmorPBP1, BmorPBP2 and BmorABPx also bind the pheromone component (10E,12Z)-hexadecadienal (bombykal) equally well, whereas BmorGOBP2 can discriminate between bombykol and bombykal. X-ray structures show that when bombykol is bound to BmorGOBP2 it adopts a different conformation from that found when it binds to BmorPBP1. Binding to BmorGOBP2 involves hydrogen bonding to Arg110 rather than to Ser56 as found for BmorPBP1

Measurement and Validation of Bidirectional Reflectance of Space Shuttle and Space Station Materials for Computerized Lighting Models

Task illumination has a major impact on human performance: What a person can perceive in his environment significantly affects his ability to perform tasks, especially in space's harsh environment. Training for lighting conditions in space has long depended on physical models and simulations to emulate the effect of lighting, but such tests are expensive and time-consuming. To evaluate lighting conditions not easily simulated on Earth, personnel at NASA Johnson Space Center's (JSC) Graphics Research and Analysis Facility (GRAF) have been developing computerized simulations of various illumination conditions using the ray-tracing program, Radiance, developed by Greg Ward at Lawrence Berkeley Laboratory. Because these computer simulations are only as accurate as the data used, accurate information about the reflectance properties of materials and light distributions is needed. JSC's Lighting Environment Test Facility (LETF) personnel gathered material reflectance properties for a large number of paints, metals, and cloths used in the Space Shuttle and Space Station programs, and processed these data into reflectance parameters needed for the computer simulations. They also gathered lamp distribution data for most of the light sources used, and validated the ability to accurately simulate lighting levels by comparing predictions with measurements for several ground-based tests. The result of this study is a database of material reflectance properties for a wide variety of materials, and lighting information for most of the standard light sources used in the Shuttle/Station programs. The combination of the Radiance program and GRAF's graphics capability form a validated computerized lighting simulation capability for NASA

Gastrointestinal Bleeding in COVID-19 Patients: A Systematic Review with Meta-Analysis

The novel coronavirus disease 2019 (COVID-19) has been reported to affect the gastrointestinal system with a variety of symptoms, including bleeding. The prevalence of bleeding in these patients remains unclear. The aim of this meta-Analysis is to estimate the rate of gastrointestinal bleeding in COVID-19 patients and its association with mortality. MEDLINE and Embase were searched through December 20, 2020. Studies reporting COVID-19 patients with and without gastrointestinal bleeding were included. Estimated prevalence with 95% confidence intervals (CI) was pooled; heterogeneity was expressed as I2. Metaregression analysis was performed to assess the impact of confounding covariates. Ten studies met the inclusion criteria and were included in the analysis. A total of 91887 COVID-19 patients were considered, of whom 534 reported gastrointestinal bleeding (0.6%) [409 (76.6%) upper and 121 (22.7%) lower gastrointestinal bleeding (UGIB and LGIB, resp.)]. The overall pooled gastrointestinal bleeding rate was 5% [95% CI 2-8], with high heterogeneity (I2 99.2%); "small study effect"was observed using the Egger test (p=0.049). After removing two outlier studies, the pooled bleeding rate was 2% [95% CI 0-4], with high heterogeneity (I2 99.2%), and no "small study effect"(p=0.257). The pooled UGIB rate was 1% (95% CI 0-3, I2 98.6%, p=0.214), whereas the pooled LGIB rate was 1% (95% CI 0-2, I2 64.7%, p=0.919). Metaregression analysis showed that overall estimates on gastrointestinal bleeding were affected by studies reporting different sources of bleeding. No significant association between gastrointestinal bleeding and mortality was found. In this meta-Analysis of published studies, individuals with COVID-19 were found to be at risk for gastrointestinal bleeding, especially upper gastrointestinal bleeding