Search

Aim: To investigate the DNA damage response (DDR) in a cyclophosphamide (CTX)‐induced mouse model of premature ovarian failure (POF). Methods: The POF model was established by injecting mice with CTX. The body, ovarian weights, the estrus cycle, and pathological changes of the ovaries were recorded. The serum levels of 17 β‐estradiol (E2) and follicle‐stimulating hormone (FSH) were measured. The expression of Ki67, β‐galactosidase (β‐gal), p21, p53, γH2AX, and pATM in ovarian tissues was detected by immunohistochemistry. The expression of β‐gal, γH2AX, and pATM was analyzed by immunofluorescence staining of primary cultured granulosa cells (GCs). Results: The body and ovarian weights decreased, the estrus cycles were erratic, and the FSH level increased, whereas the E2 level decreased in POF mice compared to controls. The pathological consequences of POF revealed an increase in atretic follicles, corpus luteum, and primordial follicles and a decrease in the number of primary, secondary, and tertiary follicles. Ki67 expression was reduced, β‐gal, p21, p53, γH2AX, and pATM expression were elevated in the ovaries of POF mice. The expression of β‐gal, γH2AX, and pATM increased in GCs with the concentration in a time‐dependent manner. Conclusion: In total, CTX induced POF in mice, which was mediated by the DDR pathway of ATM‐P53‐P21. [ABSTRACT FROM AUTHOR]

Tuber is the main economic organ of potato. It is of great significance to illustrate its formation and development mechanism for high yield breeding of potato. Although some related genes have been reported, there are still a large number of genes involved in tuber production which need to be further excavated and identified. With the continuous innovation and development of sequencing technology, transcriptome data has become more abundant and complicated. The method of screening genes related to specific traits, tissues or developmental stages using Weighted Gene Co-expression Network Analysis (WGCNA) has been widely used. In this study, to construct co-expression networks and screen co-expression modules related to tuber development, WGCNA was used to analyze transcriptome data of potato DM 1-3516 R44 (DM) material and RH89-039-16 (RH) material from 15 tissues and organs, respectively. GO and KEGG pathway enrichment were performed on the genes in the screening expression module. The top 10 genes in the module were taken as the hub genes, annotated by PGSC database and NCBI, and verified by qRT-PCR. 13 co-expression modules were obtained in both DM and RH materials, among which the Cray module in DM material analysis and the Black module in RH material analysis were significantly correlated with tubers by WGCNA. The analysis showed that the genes of the two modules were significantly enriched in related processes such as hormone metabolism, starch and sucrose metabolism, and cell formation. In addition, gene StGA2ox1, which had been proved to be related to tuber development, was noted in Cyan, and StGA2ox1 was correlated with 10 hub genes in the module in the co-expression analysis. The qRT-PCR results of the hub genes were basically consistent with the results of RNA-seq. In this study, two co-expression modules related to tuber development were identified by WGCNA, and several candidate genes related to tuber development were screened out, which laid a foundation for high yield potato breeding. [ABSTRACT FROM AUTHOR]

Phytochrome interacting factors (PIFs) belong to the basic helix-loop-helix (bHLH) transcription factor family, which integrates external environmental signals such as light and temperature with plant endogenous signal pathways, and then form a complex signal transduction network to precisely regulate the growth and development of plants. Up to now, there are few studies of PIF family genes in potato. Identification and analysis of StPIF family members will help to further improve the yield and quality of potatoes. In this study, BlastP analysis was performed in the potato genome database using Arabidopsis PIFs family member protein sequences as source sequences and seven StPIFs family members were identified. Systemic evolution, chromosome distribution, replication events, protein physicochemical properties, gene structure, motif prediction, promoter cis-acting elements, gene expression pattern, and the response to high temperature stress were also conducted. These results showed that all members of the StPIFs gene family contain Motif 1 (bHLH domain) and Motif 2 (APB domain); multiple cis-regulatory elements involved in light response, hormones, drought, low temperature, and circadian rhythm as well as defense and stress response regulatory elements were predicted in the promoter regions of the StPIF genes. Results of gene expression patterns and high temperature stress response at budding stage revealed that StPIFs family members had obvious tissue expression specificity, indicating their functional differentiation, and most StPIFs members had obvious responses to biotic stress and abiotic stresses including high temperature. In conclusion, these foundlings greatly enriched the understanding of the members of the StPIF family, and laid a theoretical foundation for further exploring the functions of StPIFs genes in responses to biotic stress and abiotic stress during potato growth period including high temperature at tuber stage. [ABSTRACT FROM AUTHOR]

This paper constructs a prediction model of material attribute-tensile strength based on principal component analysis-radial basis neural network( PCA-RBF),in order to predict the formability of traditional Chinese medicine tablets. Firstly,design Expert8. 0 software was used to design the dosage of different types of extracts,the mixture of traditional Chinese medicine with different physical properties was obtained,the powder properties of each extract and the tensile strength of tablets were determined,the correlation of the original input layer data was eliminated by PCA,the new variables unrelated to each other were trained as the input data of RBF neural network,and the tensile strength of the tablets was predicted. The experimental results showed that the PCA-RBF model had a good predictive effect on the tensile strength of the tablet,the minimum relative error was 0. 25%,the maximum relative error was2. 21%,and the average error was 1. 35%,which had a high fitting degree and better network prediction accuracy. This study initially constructed a prediction model of material properties-tensile strength of Chinese herbal tablets based on PCA-RBF,which provided a reference for the establishment of effective quality control methods for traditional Chinese medicine preparations.