Cerebral ischemia/reperfusion (I/R) injury can induce the mitophagy of neurons in the ischemic brain. Electroacupuncture (EA) pretreatment has a protective effect on cerebral ischemia/reperfusion injury. However, its internal mechanism still needs to be further studied. The present study’s purpose is to investigate whether mitophagy is involved in neuroprotection elicited by EA pretreatment in a rat model of cerebral ischemia/reperfusion injury. The rats were pretreated with vehicle, EA at the Baihui (GV20) and Shuigou (GV26) acupoints 30 min daily, for 5 days consecutively prior to the focal cerebral ischemia injury induced by the middle cerebral artery occlusion (MCAO) model. Compared to the sham group, the neurological scores, infarction volume, number of autophagosomes, FUNDC1, p62, and the ratio of LC3-II/I were significantly increased but mitochondrial membrane potential and autophagy-related protein p-mTORC1 significantly decreased in the I/R group. However, EA pretreatment significantly reversed these trends. Overall, the results of this study demonstrated that EA pretreatment protected the cerebral ischemia/reperfusion injury which maybe correlated with mitophagy.

EA of 3 mA intensity could strengthen aerobic metabolism by elevating the activities of SDH and LDH, meanwhile maintaining the ionic equilibrium in the exterior and interior brain cell and relieving the cellular edema by reinforcing the activities of Na(+)-K(+)-ATPase.

Background Breast cancer (BC) has a high incidence and mortality rate in females. Its conventional clinical characteristics are far from accurate for the prediction of individual outcomes. Therefore, we aimed to develop a novel signature to predict the survival of patients with BC. Methods We analyzed the data of a training cohort from the Cancer Genome Atlas (TCGA) database and a validation cohort from the Gene Expression Omnibus (GEO) database. After the applications of Gene Set Enrichment Analysis (GSEA) and Cox regression analyses, a glycolysis-related signature for predicting the survival of patients with BC was developed; the signature contained AK3, CACNA1H, IL13RA1, NUP43, PGK1, and SDC1. Furthermore, on the basis of expression levels of the six-gene signature, we constructed a risk score formula to classify the patients into high- and low-risk groups. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to assess the predicted capacity of the model. Later, a nomogram was developed to predict the outcomes of patients with risk score and clinical features over a period of 1, 3, and 5 years. We further used Human Protein Atlas (HPA) database to validate the expressions of the six biomarkers in tumor and sample tissues, which were taken as control. Results We constructed a six-gene signature to predict the outcomes of patients with BC. The patients in the high-risk group showed poor prognosis than those in the low-risk group. The area under the curve (AUC) values were 0.719 and 0.702, showing that the prediction performance of the signature is acceptable. Additionally, Cox regression analysis revealed that these biomarkers could independently predict the prognosis of BC patients with BC without being affected by clinical factors. The expression levels of all six biomarkers in BC tissues were higher than that in normal tissues; however, AK3 was an exception. Conclusion We developed a six-gene signature to predict the prognosis of patients with BC. Our signature has been proved to have the ability to make an accurate prediction and might be useful in expanding the hypothesis in clinical research.