Exploring the predictive values of CRP and lymphocytes in coronary artery disease based on a machine learning and Mendelian randomization.

Purpose: To investigate the predictive value of leukocyte subsets and C-reactive protein (CRP) in coronary artery disease (CAD).

Methods: We conducted a Mendelian randomization analysis (MR) on leukocyte subsets, C-reactive protein (CRP) and CAD, incorporating data from 68,624 patients who underwent coronary angiography from 2010 to 2022. After initial screening, clinical data from 46,664 patients were analyzed.

Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma.

BACKGROUND Multiple myeloma (MM) is the second most common hematologic cancer with poor prognosis. Novel therapeutic strategies are needed to decrease the high mortality rate. The aim of this study was to identify prospective agents for MM.

[The Use of FTIR Coupled with Partial Least Square for Quantitative Analysis of the Main Composition of Bamboo/Polypropylene Composites].

The biomass to plastic ratio in wood plastic composites (WPCs) greatly affects the physical and mechanical properties and price. Fast and accurate evaluation of the biomass to plastic ratio is important for the further development of WPCs. Quantitative analysis of the WPC main composition currently relies primarily on thermo-analytical methods.

Bone marrow plasma macrophage inflammatory protein protein-1 alpha(MIP-1 alpha) and sclerostin in multiple myeloma: relationship with bone disease and clinical characteristics.

The aim of the study was to investigate the expression of MIP-1 alpha and sclerostin in bone marrow of patients with multiple myeloma (MM), the possible association of the sclerostin and MIP-1 alpha with MBD and the clinical characteristics. 53 patients (29 M, 24 F), median age 64 years was studied. MIP-1 alpha, sclerostin and bone-specific alkaline phosphatase (bALP) levels were quantified using an enzyme-linked immunosorbent assay (ELISA).