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Background: The etiology of depression involves many biological and environmental factors, among which the inflammatory process is an important contributor. However, the role of pro-inflammatory cytokines in postmenopausal depression is unclear. Therefore, we aimed to explore the association between the serum concentrations of four pro-inflammatory cytokines (IL-1β, IL-6, IL-18, and TNF-α) and depressive symptoms in postmenopausal women who had been receiving menopause hormone therapy (MHT) for at least 6 months and postmenopausal women who had not received MHT. Methods: This study included a total of 136 Chinese postmenopausal women aged 40 to 65 years who visited the gynecology outpatient department between June 2020 and December 2022. They were divided into the POST group (n = 94) and the POST + MHT (n = 42) group. Demographic information was collected, and the Hamilton Rating Scale for Depression (HAMD) was used to assess depression. The circulating levels of IL-1β, IL-6, IL-18, and TNF-α were determined using ELISA kits. Results: According to the HAMD score, 39.36% of the participants in the POST group and 14.29% in the POST + MHT group were considered to have depression. The POST + MHT group had significantly lower serum concentrations of IL-18 and TNF-α than the POST group. Multiple linear regression analysis showed that the serum IL-18 (β = 3.996, 95% CI = 0.508–7.484), and TNF-α levels (β = 4.784, 95% CI = 0.939–8.629) were significant predictors of the HAMD-24 scores in women in the POST group. In addition, age was found to be positively related with the level of depression (β = 0.531, 95% CI = 0.063–0.999). Conclusions: Postmenopausal women who received MHT had a lower HAMD-24 score as well as lower serum TNF-α and IL-18 levels than women who did not receive MHT. Further, the TNF-α and IL-18 level were positively associated with the HAMD-24 score in women who had not received MHT. [ABSTRACT FROM AUTHOR]

In this paper, a novel deep learning method Mamba-RAYOLO is presented, which can improve detection and classification in the processing and analysis of ECG images in real time by integrating three advanced modules. The feature extraction module in our work with a multi-branch structure during training can capture a wide range of features to ensure efficient inference and rich feature extraction. The attention mechanism module utilized in our proposed network can dynamically focus on the most relevant spatial and channel-wise features to improve detection accuracy and computational efficiency. Then, the extracted features can be refined for efficient spatial feature processing and robust feature fusion. Several sets of experiments have been carried out to test the validity of the proposed Mamba-RAYOLO and these indicate that our method has made significant improvements in the detection and classification of ECG images. The research offers a promising framework for more accurate and efficient medical ECG diagnostics. [ABSTRACT FROM AUTHOR]

Objectives: Menopause is a significant life transition for women, impacting their physical and psychological health. The age at natural menopause (ANM) and its associated factors have differed by race and region. This study aimed to investigate ANM and associated factors of early and late menopause among Chinese women in Zhejiang province. Methods: A cross-sectional study was conducted using a multi-stage stratified cluster sampling method to recruit 8,006 women aged 40–69 years who had resided in Zhejiang province for over 6 months between July 2019 and December 2021. Self-reported ANM and sociodemographics, lifestyle behaviors, reproductive history, and health-related factors were collected using questionnaires in face-to-face surveys. ANM were categorized into three groups: early menopause (<45 years), normal menopause (45–54 years), and late menopause (≥55 years). Kaplan-Meier survival analysis was utilized to calculate the median ANM. Multivariable multinomial logistic regression was employed to explore the associated factors of early menopause and late menopause. Results: A total of 6,047 women aged 40–69 years were included for survival analysis, with 3,176 of them for the regression analysis. The overall median ANM was 51 years (Inter-quartile range [IQR]: 51–52). Women who were smokers (odds ratio [OR]:4.54, 95% confidence interval [CI]:1.6–12.84), had irregular menstrual cycles (OR:1.78, 95% CI:1.12–2.83) and hypertension (OR:1.55, 95% CI:1.09–2.21) had a higher odds ratio of early menopause, while central obesity (OR:1.33, 95% CI:1.03–1.73) and hyperlipidemia (OR:1.51, 95% CI:1.04–2.18) were factors associated with late menopause. Conclusions: This study revealed the associations between ANM and various factors among Chinese women. These factors included socio-demographic factors such as age; life behavior factors like current or prior smoking status; reproductive history factors such as irregular menstrual cycles, miscarriages, and breastfeeding; and health-related factors like central adiposity, hypertension, and hyperlipidemia. These findings provided a basis for understanding factors associated with ANM. [ABSTRACT FROM AUTHOR]