Elbow Injuries in National Collegiate Athletic Association Athletes A 5-Season Epidemiological Study

Background: Little research has focused on the rates and patterns of elbow injuries in National Collegiate Athletic Association (NCAA) student-athletes. Purpose: To describe the epidemiological patterns of elbow injuries in NCAA athletes during 5 seasons over the academic years 2009 through 2014 using the NCAA Injury Surveillance Program (NCAA-ISP) database. Study Design: Descriptive epidemiology study. Methods: A voluntary convenience sample of NCAA varsity teams from 11 sports was examined to determine the rates and patterns of elbow injuries. Rates and distributions of elbow injuries were identified within the context of sport, event type, time in season, mechanism, time lost from sport, surgical treatment, and injury type. Rates of injury were calculated as the number of injuries divided by the total number of athlete-exposures (AEs). An AE was defined as any student participation in 1 NCAA-sanctioned practice or competition with an inherent risk of exposure to potential injury. Injury rate ratios (IRRs) and injury proportion ratios (IPRs) were then calculated to compare the rates within and between sports by event type, season, sex, mechanism, surgical treatment, and time lost from sport. Comparisons between sexes were made using only sports data that had both male and female samples. Results: Overall, 373 elbow injuries were reported in the NCAA-ISP data set during the 2009-2010 through 2013-2014 academic years among 11 varsity sports. The overall rate of injury was 1.76 per 10,000 AEs. The rate of elbow injuries in men was 0.74 per 10,000 AEs, while women experienced injuries at a rate of 0.63 per 10,000 AEs. In sex-comparable sports, men were 1.17 times more likely to experience an elbow injury compared with women. Men's wrestling (6.00/10,000 AEs) and women's tennis (1.86/10,000 AEs) were the sports with the highest rates of elbow injuries by sex, respectively. The top 3 highest injury rates overall occurred in men's wrestling, baseball, and tennis. Elbow injuries were 3.5 times more likely to occur during competition compared with practice. Athletes were 0.76 times less likely to sustain an elbow injury during the preseason compared with in-season. Contact events were the most common mechanism of injury (67%). For sex-comparable sports, men were 2.41 times more likely than women to have contact as their injury mechanism (95% CI, 0.78-7.38). The majority of athletes missed less than 24 hours of participation time (67%), and only a minority (3%) of patients with elbow injuries went on to have surgical intervention. Elbow ulnar collateral ligament injuries were most common (26% of total injuries). Conclusion: Analysis of the study data demonstrated a significant rate of elbow injuries, 1.76 injuries per 10,000 AEs in NCAA collegiate athletes. Higher injury rates can be expected in males within sex-comparable sports. Elbow injuries are most common in the setting of competitions and most commonly occur secondary to contact-type mechanisms. Injuries were more likely to occur during in-season play. The majority of injuries required less than 24 hours of time away from sport and did not require surgical intervention

Analysis and comparison of gamma-retroviral vector integration behaviour in human Cd34+Cells transduced under conditions employed in the French and English Scid-X1 clinical trials

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Co-infection with SARS-COV-2 Omicron and Delta Variants Revealed by Genomic Surveillance

We identified the co-infection of the SARS-CoV-2 Omicron and Delta variants in two epidemiologically unrelated patients with chronic kidney disease requiring haemodialysis. Both SARS-CoV-2 variants were co-circulating locally at the time of detection. Amplicon- and probe-based sequencing using short- and long-read technologies identified and quantified Omicron and Delta subpopulations in respiratory samples from the two patients. These findings highlight the importance of genomic surveillance in vulnerable populations

Co-infection with SARS-CoV-2 Omicron and Delta variants revealed by genomic surveillance

Co-infections with different variants of SARS-CoV-2 are a key precursor to recombination events that are likely to drive SARS-CoV-2 evolution. Rapid identification of such co-infections is required to determine their frequency in the community, particularly in populations at-risk of severe COVID-19, which have already been identified as incubators for punctuated evolutionary events. However, limited data and tools are currently available to detect and characterise the SARS-CoV-2 co-infections associated with recognised variants of concern. Here we describe co-infection with the SARS-CoV-2 variants of concern Omicron and Delta in two epidemiologically unrelated adult patients with chronic kidney disease requiring maintenance haemodialysis. Both variants were co-circulating in the community at the time of detection. Genomic surveillance based on amplicon- and probe-based sequencing using short- and long-read technologies identified and quantified subpopulations of Delta and Omicron viruses in respiratory samples. These findings highlight the importance of integrated genomic surveillance in vulnerable populations and provide diagnostic pathways to recognise SARS-CoV-2 co-infection using genomic data

Coherence analysis discriminates between retroviral integration patterns in CD34+ cells transduced under differing clinical trial conditions

Unequivocal demonstration of the therapeutic utility of γ-retroviral vectors for gene therapy applications targeting the hematopoietic system was accompanied by instances of insertional mutagenesis. These events stimulated the ongoing development of putatively safer integrating vector systems and analysis methods to characterize and compare integration site (IS) biosafety profiles. Continuing advances in next-generation sequencing technologies are driving the generation of ever-more complex IS datasets. Available bioinformatic tools to compare such datasets focus on the association of integration sites (ISs) with selected genomic and epigenetic features, and the choice of these features determines the ability to discriminate between datasets. We describe the scalable application of point-process coherence analysis (CA) to compare patterns produced by vector ISs across genomic intervals, uncoupled from association with genomic features. To explore the utility of CA in the context of an unresolved question, we asked whether the differing transduction conditions used in the initial Paris and London SCID-X1 gene therapy trials result in divergent genome-wide integration profiles. We tested a transduction carried out under each condition, and showed that CA could indeed resolve differences in IS distributions. Existence of these differences was confirmed by the application of established methods to compare integration datasets

Lymphomagenesis in SCID-X1 Mice Following Lentivirus-mediated Phenotype Correction Independent of Insertional Mutagenesis and γc Overexpression

The development of leukemia as a consequence of vector-mediated genotoxicity in gene therapy trials for X-linked severe combined immunodeficiency (SCID-X1) has prompted substantial research effort into the design and safety testing of integrating vectors. An important element of vector design is the selection and evaluation of promoter-enhancer elements with sufficient strength to drive reliable immune reconstitution, but minimal propensity for enhancer-mediated insertional mutagenesis. In this study, we set out to explore the effect of promoter-enhancer selection on the efficacy and safety of human immunodeficiency virus-1-derived lentiviral vectors in γc-deficient mice. We observed incomplete or absent T- and B-cell development in mice transplanted with progenitors expressing γc from the phosphoglycerate kinase (PGK) and Wiscott–Aldrich syndrome (WAS) promoters, respectively. In contrast, functional T- and B-cell compartments were restored in mice receiving an equivalent vector containing the elongation factor-1-α (EF1α) promoter; however, 4 of 14 mice reconstituted with this vector subsequently developed lymphoma. Extensive analyses failed to implicate insertional mutagenesis or γc overexpression as the underlying mechanism. These findings highlight the need for detailed mechanistic analysis of tumor readouts in preclinical animal models assessing vector safety, and suggest the existence of other ill-defined risk factors for oncogenesis, including replicative stress, in gene therapy protocols targeting the hematopoietic compartment

DNA methylation networks underlying mammalian traits

Using DNA methylation profiles ( = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating.Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 7