Experimental model for the study of the effects of platelet-rich plasma on the early phases of muscle healing

BACKGROUND: There is abundant evidence suggesting that growth factors may play a key role in the healing process, especially in the early stages of inflammation. Despite the reported clinical successes with the use of growth factors there is still a lack of knowledge on the biological mechanism underlying the activity of platelet-rich plasma during the process of muscle healing. The aim of this study was to analyse the early effects of platelet- rich plasma in an easily reproducible animal model. MATERIALS AND METHODS: Wistar male adult rats (n =102) were used in this study. The muscle lesion was created with a scalpel in the flexor sublimis muscles. Platelet-rich plasma was applied immediately after surgery. Treated, untreated and contralateral muscles were analysed by morphological evaluation and western blot assay. RESULTS: Leucocyte infiltration was significantly greater in muscles treated with platelet-rich plasma than in both untreated and contralateral muscles. The latter showed greater leucocyte infiltration when compared to the untreated muscles. Platelet-rich plasma treatment also modified the cellular composition of the leucocyte infiltration leading to increased expression of CD3, CD8, CD19 and CD68 and to decreased CD4 antigen expression in both platelet-rich plasma treated and contralateral muscles. Blood vessel density and blood vessel diameters were not statistically significantly different between the three groups analysed. DISCUSSION: The results of this study showed that treatment with platelet-rich plasma magnified the physiological early inflammatory response following a muscle injury, modifying the pattern of cellular recruitment. Local platelet-rich plasma treatment may exert a direct or, more plausibly, indirect systemic effect on healing processes, at least in the earliest inflammatory phase

Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics.

Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns we developed Recombulator-X, a new open-source Python tool. The most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm. Compared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. In conclusion, Recombulator-X makes the estimation process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices