Combined metabolomics and machine learning algorithms to explore metabolic biomarkers for diagnosis of acute myocardial ischemia.

Acute myocardial ischemia (AMI) remains the leading cause of death worldwide, and the post-mortem diagnosis of AMI represents a current challenge for both clinical and forensic pathologists. In the present study, the untargeted metabolomics based on ultra-performance liquid chromatography combined with high-resolution mass spectrometry was applied to analyze serum metabolic signatures from AMI in a rat model (n = 10 per group). A total of 28 endogenous metabolites in serum were significantly altered in AMI group relative to control and sham groups. A set of machine learning algorithms, namely gradient tree boosting (GTB), support vector machine (SVM), random forest (RF), logistic regression (LR), and multilayer perceptron (MLP) models, was used to screen the more valuable metabolites from 28 metabolites to optimize the biomarker panel. The results showed that classification accuracy and performance of MLP model were better than other algorithms when the metabolites consisting of L-threonic acid, N-acetyl-L-cysteine, CMPF, glycocholic acid, L-tyrosine, cholic acid, and glycoursodeoxycholic acid. Finally, 17 blood samples from autopsy cases were applied to validate the classification model's value in human samples. The MLP model constructed based on rat dataset achieved accuracy of 88.23%, and ROC of 0.89 for predicting AMI type II in autopsy cases of sudden cardiac death. The results demonstrated that MLP model based on 7 molecular biomarkers had a good diagnostic performance for both AMI rats and autopsy-based blood samples. Thus, the combination of metabolomics and machine learning algorithms provides a novel strategy for AMI diagnosis.

Estimating the time of skeletal muscle contusion based on the spatial distribution of neutrophils: a practical approach to forensic problems.

The study aimed to explore the neutrophil's spatial distributions used to estimate the histological age of contused skeletal muscle, and assessed the accuracy of various indicators, such as the proportion of neutrophils, "neutrophil mean distance," and distribution of neutrophils in areas of "contiguous contour lines." Fifty-five Sprague-Dawley rats were divided randomly into a control group and contusion groups at 1, 1.5, 2, 3, 4, and 6 h, as well as 1, 3, 5, and 15 days, post-injury (n = 5 per group). Nuclei and neutrophils were detected by hematoxylin and eosin (HE) staining and immunohistochemical (IHC) staining. At 0-24 h after injury, the distribution of neutrophils at distances of 100, 200, 300, 400, 500, and 600 µm from adjacent blood vessels was determined, and the best samples were screened to estimate wound age. To estimate wound age as accurately as possible, Fisher discriminant analysis (FDA) of the proportion of neutrophils, neutrophil mean distance, and distribution of neutrophils was performed, and 100.0% and 95.0% of the original and cross-validated cases were correctly classified, respectively. The spatial distribution of neutrophils at different distances from adjacent blood vessels showed a strong correlation with the histological age of contusion skeletal muscle, and the combination of the proportion of neutrophils, neutrophil mean distance, and distribution of neutrophils could be used to accurately estimate wound age.

N-Acetyl-N-{2-[(Z)-2-chloro-3,3,3-tri-fluoro-prop-1-en-yl]phen-yl}acetamide.

The title compound, C(13)H(11)ClF(3)NO(2), adopts a Z conformation. Halogen⋯oxygen inter-actions [Cl⋯O = 2.967 (3) Å] in the crystal packing lead to the formation of a dimer joined by two Cl⋯O bonds.

Tetraaqua(1,10-phenanthroline-kappa(2)N,N')cobalt(II) dinitrate: a hydrogen-bonded supramolecular network.

The structure of the title compound, [Co(C(12)H(8)N(2))(H(2)O)(4)](NO(3))(2), consists of tetraaqua(1,10-phenanthroline)cobalt(II) cations and nitrate anions. The Co atom is located on a twofold rotation axis and is coordinated by the two N atoms of a 1,10-phenanthroline ligand and four O atoms of water molecules. The cations and anions are linked by hydrogen-bond interactions into a three-dimensional supramolecular network.