Analysis of the influence of pyroptosis-related genes on molecular characteristics in patients with acute myocardial infarction.

Pyroptosis is a newly identified mode of programmed cell death, but the potential role in patients with acute myocardial infarction (AMI) remains unclear. In this study, bioinformatics methods were used to identify differentially expressed genes from peripheral blood transcriptome data between normal subjects and patients with AMI which were downloaded by the Gene Expression Omnibus database. Comparing Random Forest (RF) and Support Vector Machine (SVM) training algorithms were used to identify pyroptosis-related genes, predicting patients with AMI by nomogram based on informative genes.

Prediction Model of Three-Dimensional Machined Potassium Dihydrogen Phosphate Surfaces Based on a Dynamic Response Machining System.

To comprehensively obtain the effect of the machining process on the three-dimensional surface topography of machined potassium dihydrogen phosphate crystals, a dynamic response model of a machining system was built to calculate the dynamic displacement variables in the different processing directions. This model includes almost all processing factors, such as cutting parameters, environment vibration, radial and axial runout of the spindle, cutting tool parameters, material parameters, guide way error, fast tool servo and lubrication condition errors, etc. Compared with the experimental results, the three-dimensional topographies and two-dimensional profiles of the simulation surfaces were nearly consistent with those of experimental machined surfaces.