A specimen of genus Hebius was collected from Gaowangjie National Nature Reserve (28°41′36″N, 110°09′30″E; 212 m) in Hunan Province on May 24, 2023. Through comparison of morphological characteris-tics, it was found that the reptile species was in accord with the morphological description of Hebius maxi-mus. The Bayesian phylogenetic tree of Hebius based on mitochondrial cytb genes showed that the specimen was clustered into a branch with H. maximus, with a genetic distance of 1.7%~2.2%. Based on these analy-ses, the specimen can be identified as H. maximus. At the same time, according to the reported distribution of H. maximus in China, it proved to be a new record in Hunan. Therefore, up to now there are eight species of genus Hebius recorded in Hunan Province.

Studies have shown that transcription factors binding to open chromatin regions in breast tumor cells significantly influence the clinical phenotype and prognosis of breast cancer patients. However, it is unclear how these regulatory elements regulate the occurrence and development of breast cancer at the sin-gle-cell level. Herein, single-cell chromatin accessibility sequencing (single-cell ATAC sequencing, scATAC-seq) data of 45 216 normal and tumor breast tissues were downloaded from the GEO database, and seven breast cell types were obtained after cell type annotation based on gene activity scores of marker genes in cell populations. Pearson correlation analysis showed significant differences in chromatin accessibility be-tween tumor and normal breast epithelial cells, and a high degree of inter-sample heterogeneity of breast epithelial cells (PCC=-0.07), implying that they are the main malignant cell type in breast tumors. To explore the enrichment of transcription factor motifs in the differentially accessible regions of normal and malignant mammary epithelial cells, motif enrichment analysis was performed on the characteristic open regions of the four epithelial cell subtypes after extraction of the epithelial cell populations. The results showed that malig-nant breast epithelial cells were significantly enriched for 194 transcription factors (P<0.001), which may be involved in regulatory processes of breast tumor development and metastasis. Calculation of activity scores and validation of transcriptome data for transcription factors highly enriched in epithelial cell subtypes fur-ther showed that these differential regulatory elements may be associated with malignant development of breast cells. In addition, differences in the accessibility of transcription factor binding motifs in different breast can-cer subtypes were analyzed, and SNAI2 was found to have significantly high accessibility in triple-negative breast cancer samples, suggesting that SNAI2 has a potential specific regulatory role in triple-negative breast cancer.

Angiogenesis related genes (ARGs) associated with the occurrence, development and prognosis of cervical cancer (CC) were screened using bioinformatics methods, and then the related prognostic risk model was constructed and verified. Firstly, the expression profile and clinical characteristics of CC patients were searched and differentially expressed ARGs were extracted from TCGA database. Through Lasso Cox regres-sion analysis, the ARGs for predicting prognosis were then selected to construct a relevant model. Further-more, external validation was performed with the GSE52903 and GSE44001 datasets. Finally, the mechanism of CC prognosis was discussed by gene set enrichment analysis (GSEA). Fifteen prognosis-related ARGs were selected out, including EFNA1, ITGA5, EPHB4, NRP1, CDH5, PLAU, BMP6, DLL4, JUN, CA9, MMP1, BA-IAP2L1, SERPINF1, F2RL1 and FGFR2. Kaplan-Meier survival curves based on GSE52903 and GSE44001 datasets showed that the overall survival (OS) (P=0.005) and disease-free survival (DFS) (P<0.001) of high-risk group were significantly lower than those of low-risk group. Receiver operating characteristic (ROC) curve analysis showed that, in the GSE52903 validation set, the area under the curve (AUC) values at 1 year, 3 years and 5 years were 0.84, 0.77 and 0.73, respectively, and the C-index was 0.72, and in the GSE44001 validation set, the AUC values were 0.71, 0.72 and 0.70, respectively, and the C-index was 0.70, indicating that the model has a strong predictive effect on the prognosis of CC patients. The pathways enriched by GSEA are mainly involved in DNA replication, extracellular matrix (ECM) receptor interactions, complement and coagulation cascades, the processes of which are closely related to cervical carcinogenesis and progression. These results suggest that the 15 key ARGs may be potential biomarkers for the prognosis of CC.