Compared to the control condition, the passive, active, and mixed playing strategy conditions induce up to large effects on the external loads (running distances with high acceleration and deceleration), up to moderate effects on the internal loads (energy expenditures spent with high metabolic power, lactate concentration, and rating of effort), and up to very large effects on the technical-tactical actions (number of ground strokes and errors) and activity profiles (strokes per rally, rally duration, work to rest ratio, and effective playing time). Our study shows that passive, active, and mixed playing strategies have an impact on the external and internal loads, technical-tactical actions, and activity profiles of female tennis players during match play. This finding should be considered for practical purposes like match analyses and training procedures in the tennis environment.DNA topoisomerase II (topo II) is an essential enzyme that regulates DNA topology by DNA cleavage and re-ligation. In vertebrates, there are two isozymes, α and β. The C-terminal domain (CTD) of the isozymes, which shows a low degree of sequence homology between α and β, is involved in each isozyme-specific intracellular behavior. The CTD of topo IIβ is supposedly involved in topo II regulation. Topo IIβ is maintained in an inactive state in the nucleoli by the binding of RNA to the 50-residue region termed C-terminal regulatory domain (CRD) present in the CTD. Although in vitro biochemical analysis indicates that the CTD of topo IIβ has DNA binding activity, it is unclear whether CTD influences catalytic reaction in the nucleoplasm. Here, we show that the proximal CTD (hereafter referred to as pCTD) of rat topo IIβ, including the CRD, is involved in the catalytic reaction in the nucleoplasm. We identified the pCTD as a domain with DNA binding activity by in vitro catenation assay and electrophoretic mobility shift assay. Fluorescence recovery after photo-bleaching (FRAP) analysis of pCTD-lacking mutant (ΔpCTD) showed higher mobility in nucleoplasm than that of the wild-type enzyme, indicating that the pCTD also affected the nuclear dynamics of topo IIβ. ICRF-193, one of the topo II catalytic inhibitors, induces the formation of closed-clamp intermediates of topo II. Treatment of ΔpCTD with ICRF-193 significantly decreased the efficiency of closed-clamp formation. Altogether, our data indicate that the binding of topo IIβ to DNA through the pCTD is required for the catalytic reaction in the nucleoplasm.

This study sought to determine the incidence rates of cancer, overall and by site, among active component U.S. Air Force fighter pilots, and to compare the rates with those in other active component Air Force officers.

Using a matched retrospective cohort design, U.S. Air Force fighter pilots were compared with other commissioned officers who entered active component service between 1 January 1986 and 31 December 2006. The cohort was followed for cancer diagnoses in TRICARE and the Veterans Health Administration from 1 October 1995 through 31 December 2017. Fighter pilots and non-fighter pilot officers were compared after matching on sex, age at first observation (15 age groups), and age at last observation (15 age groups). Sex-stratified overall and site-specific cancer rates were compared with matched Poisson regression to determine incidence rate ratios with 95% confidence intervals.

During 1,412,590 person-years of follow-up, among the study population of 88,432 service members (4,949 fighter pilots and 83,483 matched officers), 977 incident cancer cases were diagnosed (86 in fighter pilots and 891 in matched officers). Male fighter pilots and matched officers had similar rates of all malignant cancers (RR = 1.04; 95% CI 0.83-1.31) and of each cancer site. click here Female fighter pilots and matched officers also had similar rates of all malignant cancers (RR = 0.99; 95% CI 0.25-4.04).

In the active component U.S. Air Force, fighter pilots and their officer peers had similar overall and site-specific cancer rates.

In the active component U.S. Air Force, fighter pilots and their officer peers had similar overall and site-specific cancer rates.Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim was to develop and evaluate a machine learning algorithm to diagnose COVID-19 in the inpatient setting. The algorithm was based on basic demographic and laboratory features to serve as a screening tool at hospitals where testing is scarce or unavailable. We used retrospectively collected data from the UCLA Health System in Los Angeles, California. We included all emergency room or inpatient cases receiving SARS-CoV-2 PCR testing who also had a set of ancillary laboratory features (n = 1,455) between 1 March 2020 and 24 May 2020. We tested seven machine learning models and used a combination of those models for the final diagnostic classification. In the test set (n = 392), our combined model had an area under the receiver operator curve of 0.91 (95% confidence interval 0.87-0.96). The model achieved a sensitivity of 0.93 (95% CI 0.85-0.98), specificity of 0.64 (95% CI 0.58-0.69). We found that our machine learning algorithm had excellent diagnostic metrics compared to SARS-CoV-2 PCR. This ensemble machine learning algorithm to diagnose COVID-19 has the potential to be used as a screening tool in hospital settings where PCR testing is scarce or unavailable.Rice root-knot nematode (RRKN), Meloidogyne graminicola is one of the major biotic constraints in rice-growing countries of Southeast Asia. Host plant resistance is an environmentally-friendly and cost-effective mean to mitigate RRKN damage to rice. Considering the limited availability of genetic resources in the Asian rice (Oryza sativa) cultivars, exploration of novel sources and genetic basis of RRKN resistance is necessary. We screened 272 diverse wild rice accessions (O. nivara, O. rufipogon, O. sativa f. spontanea) to identify genotypes resistant to RRKN. We dissected the genetic basis of RRKN resistance using a genome-wide association study with SNPs (single nucleotide polymorphism) genotyped by 50K “OsSNPnks” genic Affymetrix chip. Population structure analysis revealed that these accessions were stratified into three major sub-populations. Overall, 40 resistant accessions (nematode gall number and multiplication factor/MF less then 2) were identified, with 17 novel SNPs being significantly associated with phenotypic traits such as number of galls, egg masses, eggs/egg mass and MF per plant.