A prognostic model related to necrotizing apoptosis of breast cancer based on biorthogonal constrained depth semi-supervised nonnegative matrix decomposition and single-cell sequencing analysis.

Breast cancer (BC) is one of the most common malignant tumours in women, and its prognosis is poor. The prognosis of BC patients can be improved by immunotherapy. However, due to the heterogeneity of BC, the identification of new biomarkers is urgently needed to improve the prognosis of BC patients. Necrotic apoptosis has been shown to play an essential role in many cancers. First, this study proposed a novel clustering algorithm called biorthogonal constrained depth semisupervised nonnegative matrix factorization (DO-DSNMF). The DO-DSNMF algorithm added multilayer nonlinear transformation to the coefficient matrix obtained after decomposition, which was used to mine the nonlinear relationship between samples. In addition, we also added orthogonal constraints on the basis matrix and coefficient matrix to reduce the influence of redundant features and samples on the results. We applied the DO-DSNMF algorithm and analysed the differences in survival and immunity between the subtypes. Then, we used prognosis analysis to construct the prognosis model. Finally, we analysed single cells using single-cell sequencing (scRNA-seq) data from the GSE75688 dataset in the GEO database. We identified two BC subtypes based on the BC transcriptome data in the TCGA database. Immune infiltration analysis showed that the necrotizing apoptosis-related genes of BC were related to various immune cells and immune functions. Necrotizing apoptosis was found to play a role in BC progression and immunity. The role of prognosis-related NRGs in BC was also verified by cell experiments. This study proposed a novel clustering algorithm to analyse BC subtypes and constructed an NRG prognostic model for BC. The prognosis and immune landscape of BC patients were evaluated by this model. The cell experiment supported its role in BC, which provides a potential therapeutic target for the treatment of BC.

[Clinical features of neuromyelitis optica and the distribution of Chinese medical syndrome types: a case report of 63 cases].

OBJECTIVE: To explore the clinical features of neuromyelitis optica (NMO) patients, and to study the distribution of Chinese medical syndrome types and the pathogenesis of NMO. METHODS: The clinical features, figures of tongue and pulse, Chinese medical syndromes were comprehensively analyzed in 63 NMO patients using statistical methods for clinical data. RESULTS: The age ratio of male to female in 63 NMO patients was 1: 6.88. Their average age of first onset was 31.67 +/- 12.44 years old, and 28. 57% of patients had obvious inducing factor. Urgent onset with relieved recurrence were often seen, with the average recurrence times of 4.60. Most patients complained about sensation disorders, vision disorders, and movement disorders as their first attack and visit. The Chinese medical syndrome types included Gan-Shen yin deficiency syndrome and phlegm-heat collateral stagnation syndrome, mainly involved Gan and Shen. Gan-Shen yin deficiency, sputum, blood stasis, and heat were most often seen syndrome elements. CONCLUSIONS: Gan-Shen yin deficiency was dominated in the deficiency in origin of NMO. Phlegm, blood stasis, mingled heat were main dominant evils. Of them, the pathogenesis of Gan-Shen yin deficiency and phlegm-heat collateral stagnation had universality and representativeness, which could be verified from patients' tongue picture and pulse picture.