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Investigate the effect of long-term COVID-19 on maternal and fetal complications. A retrospective cohort study was conducted. A total of 623 pregnant women who delivered in Kunming First People's Hospital from November 1, 2022 to July 31, 2023 were selected. By employing statistical methods, we compared the associations between maternal and fetal complications in pregnant women with acute COVID-19 during pregnancy, long-term COVID-19, and non-COVID-19 pregnant women. In the final 623 samples, there were 209 pregnant women with acute COVID-19, 72 pregnant women with long-term COVID-19, and 342 pregnant women without COVID-19. The epidemiological and clinical characteristics of all subjects were similar. Pregnant individuals who developed long-term COVID-19 during their pregnancy had an increased risk of experiencing gestational hypertension (OR 3.344, 95% CI 1.544–7.243), gestational diabetes mellitus (OR 2.301, 95% CI 1.290–4.102), and fetal intrauterine growth restriction (OR 2.817, 95% CI 1.385–5.952). Multivariate binary logistic regression analysis showed that this association remained consistent even after adjusting for confounders and performing subgroup analyses. Other maternal and fetal complications, such as premature rupture of membranes, preterm delivery, neonatal asphyxia, and transfer of neonates to NICU, did not exhibit statistically significant associations. After linear regression analysis, the platelet count (β: − 0.127, 95% CI − 0.001–0.000) of pregnant women with long-term COVID-19 was slightly lower than that of non-COVID-19 pregnant women, and the other coagulation parameters were not statistically significant. The incidence of gestational hypertension, gestational diabetes mellitus and fetal intrauterine growth restriction in pregnant women with long-term COVID-19 is significantly increased, but it does not further increase the coagulation status. [ABSTRACT FROM AUTHOR]

Our study aimed to investigate the relationship between sleep–wake changes and depressive symptoms events among midlife women. We enrolled 1579 women aged 44–56 years who had no clinically relevant depressive symptoms at baseline. Depressive symptoms were assessed at each visit using the Center for Epidemiologic Studies Depression scale. At the third and fourth follow-up visits, women reported their sleep habits. The sleep midpoint was defined as the time to fall asleep plus one-half of the sleep duration. Sleep–wake changes were determined by the difference in the midpoint of sleep between the third and fourth visits, which were 1 year apart. The median follow-up time was 7 years (range 1–7 years). Cox proportional hazard models were fitted to calculate hazard ratios and 95% confidence intervals for the incidence of depressive symptoms associated with sleep–wake changes. After adjusting for potential confounding factors, the hazard ratio (95% confidence interval) of depressive symptoms for severe sleep midpoint changes was 1.51 (1.12, 2.05) compared with mild sleep midpoint changes. This relationship remained statistically significant and changed little when additionally controlling for sleep duration, sleep quality, insomnia symptoms, use of sleep medications, use of nervous medications, glucose, insulin, lipids, dietary energy intake, and C-reactive protein. Our findings indicate that exposure to long-term severe sleep–wake changes increases the risk of depressive symptoms in midlife women. [ABSTRACT FROM AUTHOR]

Immune thrombocytopenia (ITP), an acquired autoimmune disease, is characterized by immune-mediated platelet destruction. A biomarker is a biological entity that contributes to disease pathogenesis and reflects disease activity. Metabolic alterations are reported to be associated with the occurrence of various diseases. As metabolic biomarkers for ITP have not been identified. This study aimed to identify metabolism-related differentially expressed genes as potential biomarkers for pathogenesis of ITP using bioinformatic analyses.The microarray expression data of the peripheral blood mononuclear cells were downloaded from the Gene Expression Omnibus database (GSE112278 download link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112278). Key module genes were intersected with metabolism-related genes to obtain the metabolism-related key candidate genes. The hub genes were screened based on the degree function in the coytoscape sofware. The key ITP-related genes were subjected to functional enrichment analysis. Immune infiltration analysis was performed using a single-sample gene set enrichment analysis algorithm to evaluate the differential infiltration levels of immune cell types between ITP patient and control. Molecular subtypes were identified based on the expression of hub genes. The expression of hub genes in the ITP patients was validated using quantitative real-time polymerase chain reaction analysis. This study identified five hub genes (ADH4, CYP7A1, CYP1A2, CYP8B1, and NR1H4), which were be associated with the pathogenesis of ITP, and two molecular subtypes of ITP. Among these hub genes, CYP7A1 and CYP8B1 involved in cholesterol metabolism,were further verified in clinical samples. [ABSTRACT FROM AUTHOR]