LXRß is involved in the control of platelet production from megakaryocytes.

Liver X receptor ß (LXRß), a nuclear receptor involved in important cellular processes such as cholesterol, glucose and fatty acid metabolism, was suggested to be involved in platelet aggregation but its detailed roles are not clear. In the present study, we evaluated the contribution of LXRß to platelet functions and production. In the systemic collagen-epinephrine thrombosis mouse model, LXRß-deficient mice showed increased area of blood clots compared with control wide-type littermates. The aggregation of LXRß-deficient platelets in response to ADP was stronger than that of control mice platelets. More importantly, the number of platelets in blood of LXRß-deficient mice was significantly higher than that of wild-type mice, especially for female mice. Knockdown of LXRß expression in human megakaryoblastic Dami cells also enhanced cell polyploidization, formation of proplatelets and production of platelet-like particles. Increase in expression levels of proteins related to oxidative phosphorylation such as NADH:ubiquinone oxidoreductase core subunit V1 (Ndufv1) was observed in LXRß-knockdown Dami cells. The levels of Ndufv1 in LXRß-deficient mice platelets were also higher than that of wild-type mice. Taken together, our findings suggested LXRß might participate in control of platelet production from megakaryocytes by regulating mitochondrial metabolism.

Gastrodin protects H9c2 cardiomyocytes against oxidative injury by ameliorating imbalanced mitochondrial dynamics and mitochondrial dysfunction.

Gastrodin (GAS) is the main bioactive component of Tianma, a traditional Chinese medicine widely used to treat neurological disorders as well as cardio- and cerebrovascular diseases. In the present study, the protective effects of GAS on H9c2 cells against ischemia-reperfusion (IR)-like injury were found to be related to decreasing of oxidative stress. Furthermore, GAS could protect H9c2 cells against oxidative injury induced by H2O2. Pretreatment of GAS at 20, 50, and 100 µM for 4 h significantly ameliorated the decrease in cell viability and increase in apoptosis of H9c2 cells treated with 400 µM H2O2 for 3 h. Furthermore, we showed that H2O2 treatment induced fragmentation of mitochondria and significant reduction in networks, footprint, and tubular length of mitochondria; H2O2 treatment strongly inhibited mitochondrial respiration; H2O2 treatment induced a decrease in the expression of mitochondrial fusion factors Mfn2 and Opa1, and increase in the expression of mitochondrial fission factor Fis1. All these alterations in H2O2-treated H9c2 cells could be ameliorated by GAS pretreatment. Moreover, we revealed that GAS pretreatment enhanced the nuclear translocation of Nrf2 under H2O2 treatment. Knockdown of Nrf2 expression abolished the protective effects of GAS on H2O2-treated H9c2 cells. Our results suggest that GAS may protect H9c2 cardiomycytes against oxidative injury via increasing the nuclear translocation of Nrf2, regulating mitochondrial dynamics, and maintaining the structure and functions of mitochondria.

Abnormal patterns recognition in bivariate autocorrelated process using optimized random forest and multi-feature extraction.

Traditional multivariate control charts are unable to determine the specific abnormal variables as detecting process abnormality. To solve this problem, a new model based on optimized random forest (RF) and multi-feature extraction has been proposed. First, four patterns of process state according to different combinations of abnormal variables are defined. Next, four statistical features and seven shape features are extracted to construct a feature vector, which is used as input of RF in the advanced model. Finally, the particle swarm optimization (PSO) is introduced to optimize the two key parameters of RF. The recognition accuracies of the proposed model are studied through simulation experiments. The experiment results show that the accuracy of this model rises from 91.25% to 98.33% through extracting multi-feature and PSO optimization. The superiority of the proposed model is verified, as evidence by comparing with other algorithms. Thus, we confirm that the proposed model is promising for being applied in real-time process control.