Identification and exploration of the pyroptosis-related molecular subtypes of breast cancer by bioinformatics and machine learning.

Objectives: To classify breast cancer (BRCA) according to the expression of pyroptosis-related genes and explore their molecular characteristics.

Methods: Nonnegative matrix factorization (NMF) was used for subtype classification based on 21 pyroptosis-related genes in the TCGA database. Survival analysis and t-distributed stochastic neighbor embedding (t-SNE) analysis were conducted to assess the NMF results' performance.

[Early diagnosis and treatment of intracranial venous thrombosis].

Objective: To study the early diagnosis and treatment of intracranial venous thrombosis.

Method: The etiology, clinical manifestations, presentations in cerebral CT and magnetic resonance imaging (MRI), electroencephalogram (EEG) features, and the results of cerebral spinal fluid and blood rheological examinations were analyzed in 8 cases of intracranial venous thrombosis.

Results: Thrombosis often arose during the puerperium and from infection, with the frequent presentations of intracranial hypertension and focal neurological defect.