Objective: To investigate the change of serum microRNA-15 a(miR-15 a) expression level in patients with gestational diabetes mellitus and its relationship with maternal and infant adverse outcomes. Methods: 143 cases of gestational diabetes mellitus patients were selected as the study group, and 124 healthy pregnant women were selected as the control group, and the expression levels of serum miR-15 a of the two groups were detected by real time fluorescent quantitative reverse transcription polymerase chain reaction(qRT-PCR). Follow up to delivery, the adverse maternal and infant outcomes of the two groups were observed, and the relationship between the expression level of serum miR-15 a and the adverse outcomes of maternal and infant in gestational diabetes mellitus was analyzed by multivariate Logistic regression analysis method. Results: The expression level of serum miR-15 a in the study group was higher than that in the control group, and the difference was statistically significant(P<0.05). The incidence rates of abortion, premature rupture of membranes, polyhydramnios, postpartum hemorrhage, postpartum infection, premature infants, macrosomia, fetal distress, neonatal asphyxia, neonatal respiratory distress syndrome and neonatal hypoglycemia and the total incidence rates of maternal and perinatal adverse outcomes in the study group were higher than those in the control group(P<0.05), but there was no significant difference in the incidence rate of fetal death between the study group and the control group(P>0.05). The proportions of age>35 years old, pre-pregnancy body mass index ≥24.0 kg/m2, history of adverse pregnancy and childbirth and poor blood glucose control and the expression level of serum miR-15 a in poor maternal outcome group and poor perinatal outcome group were higher than those in good maternal outcome group and good perinatal outcome group(P<0.05), and multivariate Logistic regression analysis showed that the above indicators were the risk factors of adverse maternal and infant outcomes in patients with gestational diabetes mellitus(P<0.05). Conclusion The expression level of serum miR-15 a in gestational diabetes mellitus patients abnormally increases, and it can increase the risk of adverse maternal and infant outcomes, which is closely related to the occurrence of adverse maternal and infant outcomes. Besides, the age, pre-pregnancy body mass index, adverse pregnancy history, blood glucose control also have a certain impacts on the occurrence of adverse maternal and infant outcomes in patients with gestational diabetes mellitus.

There is increasing evidence that the activation of glucagon-like peptide-1 receptor(GLP-1R)can be used as a therapeutic intervention for cognitive disorders.Here,we have screened GLP-1 R targeted com-pounds from Scutellaria baicalensis,which revealed baicalein is a potential GLP-1 R small-molecule agonist.Mitophagy,a selective autophagy pathway for mitochondrial quality control,plays a neuro-protective role in multiple cognitive impairment diseases.We noticed that Glp1r knock-out(KO)mice present cognitive impairment symptoms and appear worse in spatial learning memory and learning capacity in Morris water maze(MWM)test than their wide-type(WT)counterparts.Our mechanistic studies revealed that mitophagy is impaired in hippocampus tissue of diabetic mice and Glp1r KO mice.Finally,we verified that the cognitive improvement effects of baicalein on diabetic cognitive dysfunction occur through the enhancement of mitophagy in a GLP-1 R-dependent manner.Our findings shed light on the importance of GLP-1 R for cognitive function maintenance,and revealed the vital significance of GLP-1R for maintaining mitochondrial homeostasis.Furthermore,we identified the therapeutic potential of baicalein in the treatment of cognitive disorder associated with diabetes.

Recent years with the rapid progress in high-throughput omics techniques, the accumulation of population cohorts and biobanks, great advances in internet and information technology, and the emerging tools for big data utilization, health care big data provide abundant data resources and broad research platforms for epidemiological research. We aimed to review the opportunities and challenges of epidemiological research in the era of big data, and explore the future development of epidemiology. Epidemiology should seize the opportunities, open up new directions, develop new methods, and promote the translation of research results into public health and clinical medicine, which will eventually realize the vision of "Healthy China".