TCM formula for trauma treatment screening and its role of promoting infectious wound coalescence investigating.

In pet clinics, the number of cases using trauma drugs accounts for >10% of the total number of cases, and most wounds are healing by second intention. The prolongation of wound healing time causes inconvenience and burden to pets and pet owners. Therefore, how to reduce wound healing time and achieve maximum recovery of tissue function and aesthetics is one of the focuses of veterinary clinical practice. Wound suppuration caused by Staphylococcus aureus and Pseudomonas aeruginosa is the main cause of delaying wound healing. Clinically, available antimicrobial treatments are almost exhausted due to the production of large numbers of resistant bacteria. At present, there are no bacteria resistant to traditional Chinese medicine (TCM), which makes TCM have the potential to become an effective drug for the treatment of bacterial infections, so the use of TCM in the treatment of traumatic infections has broad prospects. Based on the characteristics of infection syndrome, three different prescriptions were formulated in our laboratory, and the most effective prescription and dosage form was screened and named Lianrong Healing Cream (LRHC). The results showed that LRHC regulated the expression of fibroblast growth factor-2 (FGF-2), epidermal growth factor-1 (EGF-1), transforming growth factor-ß (TGF-ß) and vascular endothelial growth factor-1 (VEGF-1) genes in wound tissues and fibroblasts, thereby accelerating wound healing and repairing wound appearance and function. The results of this study may be help to develop TCM formulation for traumatic infections.

PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks.

Pollen grains, the male gametophytes for reproduction in higher plants, are vulnerable to various stresses that lead to loss of viability and eventually crop yield. A conventional method for assessing pollen viability is manual counting after staining, which is laborious and hinders high-throughput screening. We developed an automatic detection tool (PollenDetect) to distinguish viable and nonviable pollen based on the YOLOv5 neural network, which is adjusted to adapt to the small target detection task. Compared with manual work, PollenDetect significantly reduced detection time (from approximately 3 min to 1 s for each image). Meanwhile, PollenDetect can maintain high detection accuracy. When PollenDetect was tested on cotton pollen viability, 99% accuracy was achieved. Furthermore, the results obtained using PollenDetect show that high temperature weakened cotton pollen viability, which is highly similar to the pollen viability results obtained using 2,3,5-triphenyltetrazolium formazan quantification. PollenDetect is an open-source software that can be further trained to count different types of pollen for research purposes. Thus, PollenDetect is a rapid and accurate system for recognizing pollen viability status, and is important for screening stress-resistant crop varieties for the identification of pollen viability and stress resistance genes during genetic breeding research.

Rapid Identification of Pollen- and Anther-Specific Genes in Response to High-Temperature Stress Based on Transcriptome Profiling Analysis in Cotton.

Anther indehiscence and pollen sterility caused by high temperature (HT) stress have become a major problem that decreases the yield of cotton. Pollen- and anther-specific genes play a critical role in the process of male reproduction and the response to HT stress. In order to identify pollen-specific genes that respond to HT stress, a comparative transcriptome profiling analysis was performed in the pollen and anthers of Gossypium hirsutum HT-sensitive Line H05 against other tissue types under normal temperature (NT) conditions, and the analysis of a differentially expressed gene was conducted in the pollen of H05 under NT and HT conditions. In total, we identified 1111 pollen-specific genes (PSGs), 1066 anther-specific genes (ASGs), and 833 pollen differentially expressed genes (DEGs). Moreover, we found that the late stage of anther included more anther- and pollen-specific genes (APSGs). Stress-related cis-regulatory elements (CREs) and hormone-responsive CREs are enriched in the promoters of APSGs, suggesting that APSGs may respond to HT stress. However, 833 pollen DEGs had only 10 common genes with 1111 PSGs, indicating that PSGs are mainly involved in the processes of pollen development and do not respond to HT stress. Promoters of these 10 common genes are enriched for stress-related CREs and MeJA-responsive CREs, suggesting that these 10 common genes are involved in the process of pollen development while responding to HT stress. This study provides a pathway for rapidly identifying cotton pollen-specific genes that respond to HT stress.