Epidemiology of open fractures in sport: One centre's 15-year retrospective study

AIM To describe the epidemiology of sport-related open fractures from one centre's adult patient population over a 15-year period. METHODS A retrospective review of a prospectively-collected database was performed: The database contained information all sport-related open fractures, sustained from 1995 to 2009 in the Edinburgh, Mid and East Lothian Populations.RESULTS Over the 15-year period, there were 85 fractures recorded in 84 patients. The annual incidence of open sport-related fractures was 0.01 per 1000 population. The mean age at injury was 29.2 years(range 15-67). There were 70(83%) males and 14 females(17%).The 6 most common sports were soccer(n = 19, 22%), rugby(n = 9, 11%), cycling(n = 8, 9%), hockey(n = 8, 9%); horse riding(n = 6, 7%) and skiing(n = 6, 7%). The five most common anatomical locations were finger phalanges(n = 30, 35%); tibial diaphysis(n = 19, 23%); forearm(n = 12, 14%); ankle(n = 7, 8%) and metacarpals(n = 5, 6%). The mean injury severity score was 7.02. According to the Gustilo-Anderson classification system, 45(53%) fractures were grade 1; 28(33%) fractures were grade 2; 8(9%) fractures were grade 3a; and 4(5%) fractures were grade 3b. Out of the total number of fractures, 7(8%) required plastic surgical intervention as part of management. The types of flaps used were split skin graft(n = 4), fasciocutaneous flaps(n = 2); and adipofascial flap(n = 1). CONCLUSION We analysed the epidemiology of open fractures secondary to sport in one centre over a 15-year period. Soccer and rugby were the most common causative sports while fractures of the finger phalanx and of the tibial diaphysis were the most common sites. Open fractures are uncommon in sport; however, when they are sustained they usually occur on muddy sport fields or forest tracks and therefore must be treated appropriately. It is important that clinicians and sports therapists have knowledge of these injuries, in order to ensure they are managed optimally.

A novel engineered IL-21 receptor arms T-cell receptor-engineered T cells(TCR-T cells)against hepatocellular carcinoma

Strategies to improve T cell therapy efficacy in solid tumors such as hepatocellular carcinoma(HCC)are urgently needed.The common cytokine receptorγchain(γc)family cytokines such as IL-2,IL-7,IL-15 and IL-21 play fundamental roles in T cell development,differentiation and effector phases.This study aims to determine the combination effects of IL-21 in T cell therapy against HCC and investigate optimized strategies to utilize the effect of IL-21 signal in T cell therapy.The antitumor function of AFP-specific T cell receptor-engineered T cells(TCR-T)was augmented by exogenous IL-21 in vitro and in vivo.IL-21 enhanced proliferation capacity,promoted memory differentiation,downregulated PD-1 expression and alleviated apoptosis in TCR-T after activation.A novel engineered IL-21 receptor was established,and TCR-T armed with the novel engineered IL-21 receptors(IL-21R-TCR-T)showed upregulated phosphorylated STAT3 expression without exogenous IL-21 ligand.IL-21R-TCR-T showed better proliferation upon activation and superior antitumor function in vitro and in vivo.IL-21R-TCR-T exhibited a less differentiated,exhausted and apoptotic phenotype than conventional TCR-T upon repetitive tumor antigen stimulation.The novel IL-21 receptor in our study programs powerful TCR-T and can avoid side effects induced by IL-21 systemic utilization.The novel IL-21 receptor creates new opportunities for next-generation TCR-T against HCC.

glbase:a framework for combining,analyzing and displaying heterogeneous genomic and high-throughput sequencing data

Genomic datasets and the tools to analyze them have proliferated at an astonishing rate.However,such tools are often poorly integrated with each other:each program typically produces its own custom output in a variety of non-standard file formats.Here we present glbase,a framework that uses a flexible set of descriptors that can quickly parse non-binary data files.glbase includes many functions to intersect two lists of data,including operations on genomic interval data and support for the efficient random access to huge genomic data files.Many glbase functions can produce graphical outputs,including scatter plots,heatmaps,boxplots and other common analytical displays of high-throughput data such as RNA-seq,ChIP-seq and microarray expression data.glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing.In summary,glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data(especially next-generation sequencing and genome-wide data),and which has been instrumental in the analysis of complex data sets.glbase is freely available at http://bitbucket.org/oaxiom/glbase/.