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Abstract Purpose Trop2, a cell membrane glycoprotein, is overexpressed in almost all epithelial cancers. This study aimed to explore the mutational characteristics and significance of Trop2 in breast cancer (BC). Methods Patients diagnosed with BC (n = 77) were enrolled to investigate expression level and clinical characteristics of Trop2. Database of cBioPortal and Kaplan–Meier Plotter were used to evaluate the effects of Trop2 (TACSTD2) genomic ateration and mRNA expression levels on disease-free survival (DFS) and relapse-free survival (RFS), respectively. Based on next generation sequencing analysis, the Trop2 mutation characteristics of BC patients were deeply depicted. In addition, Trop2 expression, mutation and methylation signature associated with Trop2 mutations were analyzed. Results Trop2 mutation and high expression of Trop2 were predictive biomarker for shorter DFS and RFS in BC. The positive rate of Trop2 expression in these 77 BC patients was 96.1% (74/77). Based on the Trop2 expression level, the patients were classified into Trop2 negative group, medium expression group and high expression group. The mutation frequencies of MAP3K1, NOTCH2, PTEN and MAGI2 were significantly higher in Trop2 medium expression group than high expression group. Moreover, we investigated the effect of the Trop2 mutations on other genes, including co-expressed genes, differentially mutated genes, differentially expressed genes, gene methylation and phosphorylation. We found that MED8, DPH2, KDM4A, EBNA1BP2, USP1, IPO13, CGAS, PRKAA2, NCOA7, ASCC3 and ABRACL were differentially expressed, mutated and methylated between Trop2 mutation group and wild group. Conclusion MAP3K1, NOTCH2, PTEN and MAGI2 mutations were significantly different between Trop2 medium expression and Trop2 high expression BC patients. The effects of Trop2 mutation on the expression, variation, methylation, and phosphorylation of other genes were comprehensively revealed. High expression level of Trop2 and Trop2 mutation were predictive biomarker for poor prognosis and targeted therapy in BC.

Advancements in single-cell sequencing research have revolutionized our understanding of cellular heterogeneity and functional diversity through the analysis of single-cell transcriptomes and genomes. A crucial step in single-cell RNA sequencing (scRNA-seq) analysis is identifying cell types. However, scRNA-seq data are often high dimensional and sparse, and manual cell type identification can be time-consuming, subjective, and lack reproducibility. Consequently, analyzing scRNA-seq data remains a computational challenge. With the increasing availability of well-annotated scRNA-seq datasets, advanced methods are emerging to aid in cell type identification by leveraging this information. Deep learning neural networks have great potential for analyzing single-cell data. This paper proposes MulCNN, a multi-level convolutional neural network that uses a unique cell type-specific gene expression feature extraction method. This method extracts critical features through multi-scale convolution while filtering noise. Extensive testing using datasets from various species and comparisons with popular classification methods show that MulCNN has outstanding performance and offers a new and scalable direction for scRNA-seq analysis.

The Ordos Relict Gull National Nature Reserve (Taolimiao-Alashan Nur, TAN) was once the most important breeding place for the Ordos sub-population of relict gulls Ichthyaetus relictus, but there were no more gulls breeding here since the lake dried up in the early 21st century. Since the water diversion started in 2018, five and 35 nests have been recorded breeding here in 2020 and 2021, but the arthropod community in the wetland has not been completely rebuilt. Whether its diversity and biomass can provide sufficient food during the breeding period is the key to the recovery of the relict gull. Here we investigated aquatic arthropods in the TAN and Hotong Qagan Nur (HQN) to compare the food supply and predict the capacity of the reserve after the lake water was restored. The results showed that the arthropod communities are low abundant in two lakes with a total of 16 taxa, but their biomass in TAN was significantly lower than HQN. According to the breeding records of relict gulls in HQN, we roughly estimate that up to 400 relict gulls pairs may be able to breed in TAN. The low availability of food supply during the brooding period might still be a limiting factor for the restoration of the TAN relict gull population in the following years. [ABSTRACT FROM AUTHOR]