Search

Deer antlers are the only mammalian appendages that can fully regenerate from periosteum of pedicles (PP). This regeneration process starts from regenerative healing of wounds. Removal of PP abolishes antler regeneration, however, the regenerative cutaneous wound healing proceeds, indicating that some factors in the circulation contribute to this healing. In this study, we produced a wound in the scalp of deer either in antler regeneration period (ARP) (n = 3) or in non-ARP (n = 3). Results showed full regeneration took place only when the wound was created during ARP. Interestingly, topical application of systemic factors from ARP (n = 9) promoted regenerative wound healing in rats. Comparative proteomics analysis (n = 3) revealed that PRG4 and IGF-1 were high during ARP, and topical application of PRG4 + IGF-1 promoted restoration in rat FTE wounds. We believe that, ultimately, incorporating systemic factors into advanced wound care modalities could offer new opportunities for regenerative healing in the clinical setting. [ABSTRACT FROM AUTHOR]

AbstractPurposeMethodsResultsConclusionPterygium is a common ocular surface disease characterized by a high recurrence rate and unknown etiology.In this study, we investigated the upregulation of matrix metalloproteinase genes, including MMP1, MMP2, MMP3, MMP7, MMP9, MMP11, MMP12, MMP13, MMP23B, and MMP28, in pterygium tissue using RNA sequencing, Western blotting, and immunohistochemistry.Employing the MEME tool, we identified a conserved DNA motif within the promoter regions of these matrix metalloproteinase genes. Mass spectrometry analysis revealed an interaction between the cohesin complex and this motif. Disrupting the cohesin complex through RNA interference of RAD21 cohesin complex component or structural maintenance of chromosomes 3 in primary pterygial fibroblasts led to decreased matrix metalloproteinase gene expression and reduced recruitment of twist family bHLH transcription factor 1 and transcription factor 4 to matrix metalloproteinase gene promoters.Overall, our findings suggest a novel epigenetic mechanism regulating matrix metalloproteinase transcription in pterygium. [ABSTRACT FROM AUTHOR]

Predicting the credit risk of small and medium-sized enterprises (SMEs) in supply chain finance accurately is critical to the sustainability of the entire supply chain and supply chain participants (e.g., core enterprises and financial service providers). Previous studies apply a series of machine learning algorithms to address this issue. However, these methods are inadequate in terms of prediction efficiency and accuracy. Therefore, we propose a novel approach based on the Improved Sparrow Search Algorithm (ISSA) and Light Gradient Boosting Machine (LightGBM). ISSA is an enhanced Sparrow Search Algorithm (SSA), which combines original SSA with fractional calculus concepts and Cauchy–Gaussian mutation, to accelerate convergence and reinforce global search capability. Then ISSA is used to search the global optimal hyper-parameters of LightGBM since the prediction performance of LightGBM is determined by numerous hyper-parameters. The experimental results show that the proposed ISSA-LightGBM approach has a superior prediction performance compared with the other five models and the ISSA possesses better convergence speed and global search capability over the other four swarm intelligence optimization algorithms. DeLong's test results show that ISSA-LightGBM is statistically significant in terms of AUC score compared to other models. Finally, machine learning model is interpreted using the Shapley-Lorenz tool to comply with the requirements of industry practitioners and policy makers. [ABSTRACT FROM AUTHOR]