Body composition in second trimester is associated with dyslipidemia in third trimester.

OBJECTIVE: The aim of this study was to examine the correlation between maternal body composition during the second trimester and the occurrence of dyslipidemia in the third trimester. METHODS: A cohort of 1508 pregnant women who underwent antenatal testing at Shanghai Sixth People's Hospital, affiliated with Shanghai Jiao Tong University School of Medicine, were included in this study. Maternal body composition was assessed using bioimpedance analysis between 14 and 22 weeks of gestation. RESULTS: Among the 1508 participants, a total of 1420 individuals (94.2%) were diagnosed with dyslipidemia. Notably, there were significant differences in body composition between the normal lipid group and the dyslipidemia group. Logistic regression analysis revealed that various factors including BMI, total body water (TBW), intra-cellular water (ICW), extra-cellular water (ECW), percent body fat (PBF), visceral fat area (VFA), fat-free mass (FFM) and arm circumference (AC) during the second trimester were all found to be associated with dyslipidemia in the third trimester. CONCLUSION: The present study found that maternal body composition was associated with dyslipidemia. The BMI, TBW, ICW, ECW, PBF, VFA, FFM and AC in second trimester were associated with dyslipidemia in third trimester.

Insulin sensitivity, ß cell function, and adverse pregnancy outcomes in women with gestational diabetes.

BACKGROUND: The potential impact of ß cell function and insulin sensitivity on adverse pregnancy outcomes in women with gestational diabetes mellitus (GDM) remains uncertain. We aimed to investigate the association between ß cell dysfunction, insulin resistance, and the composite adverse pregnancy outcomes. METHODS: This observational study included 482 women diagnosed with GDM during pregnancy. Quantitative metrics on ß cell function and insulin sensitivity during pregnancy were calculated using traditional equations. The association of ß cell dysfunction and insulin resistance with the risk of the composite adverse pregnancy outcomes was investigated using multivariable-adjusted logistic regression models. RESULTS: Multivariable-adjusted odds ratios (ORs) of adverse pregnancy outcomes across quartiles of homeostatic model assessment for insulin resistance (HOMA-IR) were 1.00, 0.95, 1.34, and 2.25, respectively (P for trend = 0.011). When HOMA-IR was considered as a continuous variable, the multivariable-adjusted OR of adverse pregnancy outcomes was 1.34 (95% confidence interval 1.16-1.56) for each 1-unit increase in HOMA-IR. Multivariable-adjusted ORs of adverse pregnancy outcomes across quartiles of homeostatic model assessment for ß cell function (HOMA-ß) were 1.00, 0.51, 0.60, and 0.53, respectively (P for trend = 0.068). When HOMA-ß was considered as a continuous variable, the multivariable-adjusted OR of adverse pregnancy outcomes was 0.57 (95% CI 0.24-0.90) for each 1-unit increase in HOMA-ß. However, other quantitative metrics were not associated with the composite adverse pregnancy outcomes. CONCLUSIONS: We demonstrated a significant association of ß cell function and insulin sensitivity with the risk of adverse pregnancy outcomes. We have provided additional evidence on the early identification of adverse pregnancy outcomes besides the glycemic values.

Template-Aware Transformer for Person Reidentification.

Person reidentification (ReID) is a challenging computer vision task for identifying or verifying one or more persons when the faces are not available. In ReID, the indistinguishable background usually affects the model's perception of the foreground, which reduces the performance of ReID. Generally, the background of the same camera is similar, whereas that of different cameras is quite different. Based on this finding, we propose a template-aware transformer (TAT) method which can learn intersample indistinguishable features by introducing a learnable template for the transformer structure to cut down the model's attention to regions of the image with low discrimination, including backgrounds and occlusions. In the multiheaded attention module of the encoder, this template directs template-aware attention to indistinguishable features of the image and gradually increases the attention to distinguishable features as the encoder block deepens. We also increase the number of templates using side information considering the characteristics of ReID tasks to adapt the model to backgrounds that vary significantly with different camera IDs. Finally, we demonstrate the validity of our theories using various public data sets and achieve competitive results via a quantitative evaluation.

Anthropogenic impacts on Late Holocene land-cover change and floristic biodiversity loss in tropical southeastern Asia.

Southern China and Southeast Asia witnessed some of their most significant economic and social changes relevant to human land use during the Late Holocene, including the intensification and spread of rice agriculture. Despite rice growth being associated with a number of earth systems impacts, how these changes transformed tropical vegetation in this region of immense endemic biodiversity remains poorly understood. Here, we compile a pollen dataset incorporating ∼150,000 identifications and 233 pollen taxa to examine past changes in floral biodiversity, together with a compilation of records of forest decline across the region using 14 pollen records spanning lowland to mountain sites. Our results demonstrate that the rise of intensive rice agriculture from approximately 2,000 y ago led not only to extensive deforestation but also to remarkable changes of vegetation composition and a reduction in arboreal diversity. Focusing specifically on the Tertiary relic tree species, the freshwater wetland conifer Glyptostrobus (Glyptostrobus pensilis), we demonstrate how key species that had survived changing environmental conditions across millions of years shrank in the face of paddy rice farming and human disturbance.

Effect of Menopausal Hormone Therapy on the Vaginal Microbiota and Genitourinary Syndrome of Menopause in Chinese Menopausal Women.

Genitourinary syndrome of menopause (GSM) is a chronic and progressive condition with a series of vulvovaginal, sexual, and lower urinary tract discomforts, mainly due to hypoestrogenism. Menopausal hormone therapy (MHT) has generally been considered as the most effective treatment for GSM. In addition, vaginal microbiota is of particular significance to gynecological and reproductive illnesses and potentially has some intimate connections with GSM. Consequently, we sought to evaluate how MHT impacts the composition and structure of vaginal microbiota while alleviating GSM in Chinese menopausal women aged 45-65 years, which has not been investigated previously. 16S rRNA gene sequencing was performed to analyze microbial diversity and composition using vaginal swabs obtained from 100 menopausal women, classified as MHT women who have been taking tibolone regularly (n = 50) and non-treated women who never received any treatment (n = 50). Vaginal Health Index Score (VHIS) and GSM symptoms inquiry were also performed. We found that the vaginal microbial diversity decreased and that the abundance of Lactobacillus increased to be the dominant proportion significantly in the MHT group, in considerable contrast to vaginal microbiota of the non-treated group, which significantly comprised several anaerobic bacteria, namely, Gardnerella, Prevotella, Escherichia-Shigella, Streptococcus, Atopobium, Aerococcus, Anaerotruncus, and Anaerococcus. In this study, women without any MHT had significantly more severe GSM symptoms than those receiving tibolone, especially with regard to vulvovaginal dryness and burning, as well as decreased libido (P < 0.01). However, there was no significant difference in the severity of urological symptoms between the groups (P > 0.05). Furthermore, Lactobacillus was demonstrated to be associated with VHIS positively (r = 0.626, P < 0.001) and with GSM negatively (r = -0.347, P < 0.001). We also identified Chlamydia (r = 0.277, P < 0.01) and Streptococcus (r = 0.270, P < 0.01) as having a prominent association with more serious GSM symptoms. Our study provided an elucidation that MHT could notably alleviate GSM and conspicuously reshape the composition of the vaginal microbiota, which is of extreme importance to clinical practice for the management of GSM.

Association of snoring and body composition in (peri-post) menopausal women.

BACKGROUND: Little attention has been paid to whether snoring frequency is associated with body composition in menopausal women, particularly in China. This study objected to investigate the association between self-reported snoring and body composition in (peri-post) menopausal Chinese women as well as metabolic indicators. METHODS: This cross-sectional study enrolled 715 participants aged 40-67 years from the Menopause Clinic in the Shanghai Sixth People's Hospital. Participants were categorized into four subgroups stratified by self-reported snoring frequency: never, rarely (< 1 night per week), occasionally (1-2 nights per week), regularly (≥3 nights per week), while body composition was measured using bioelectrical impedance analysis (BIA). Besides, blood sample were collected to test the glycolipid indicators. RESULTS: In our sample of investigation, regular snoring (≥3 nights per week) was found to be an independent risk factor for higher fat mass (total, upper limbs, trunk), with the highest risk of 2.4 times for fat mass of trunk after adjusting for metabolic confounders(p = 0.003). Meanwhile, regular snoring was independently associated with higher fat mass (total and each segment) only in menopausal transition (p = 0.023). CONCLUSIONS: We suggested that self-reported regular snoring may be taken as a simple alternative to predict higher fat mass (≥17.11 kg, upper quartile) in menopausal women. Similarly, body composition should be attached to the great importance to those who in menopausal transition in order to help to prevent obstructive sleep apnea (OSA).

Maternal glycemic parameters and adverse pregnancy outcomes among high-risk pregnant women.

Objective: We aimed to investigate the association between maternal glycemic parameters and adverse pregnancy outcomes among high-risk pregnant women. Research design and methods: A total of 1976 high-risk pregnant women were enrolled between 2015 and 2017. All participants received a 75 g oral glucose tolerance test during the 24-30 gestational weeks and complete birth and delivery information was collected. Adverse pregnancy outcomes were defined as premature birth, birth weight >90th percentile, primary cesarean section, and pre-eclampsia. Logistic regression models were used to assess the association between five maternal glycemic parameters during pregnancy (fasting glucose, 1-hour glucose, 2-hour glucose, HbA1c, and serum 1,5-anhydroglucitol (1,5-AG)) and adverse pregnancy outcomes. Results: Of 1976 participants, 498 were diagnosed with gestational diabetes. The multivariable-adjusted ORs of adverse pregnancy outcomes for each one unit increase (1 mmol/L, 1%, or 1 µg/mL) were 2.32 (95% CI 1.85 to 2.92) for fasting glucose, 1.07 (95% CI 1.01 to 1.15) for 1-hour glucose, 1.03 (95% CI 0.96 to 1.10) for 2-hour glucose, 1.77 (95% CI 1.34 to 2.33) for HbA1c, and 0.96 (95% CI 0.94 to 0.98) for 1,5-AG, respectively. When all five glycemic parameters were simultaneously entered into the multivariable-adjusted model, only fasting glucose was significantly associated with total and individual adverse pregnancy outcomes. Receiver operating characteristic curve showed that fasting glucose plus any one of other four glycemic parameters had significantly enhanced the sensitivity of detecting adverse pregnancy outcomes. Conclusions: Fasting glucose at 24-30 gestational weeks was strongly associated with adverse pregnancy outcomes. Fasting glucose combined with one additional glycemic measurement showed non-inferiority indicating that post-load glycemic measurement was not necessary in detecting adverse pregnancy outcomes among high-risk pregnant women.

Demands for perimenopausal health care in women aged 40 to 60 years-a hospital-based cross-sectional study in Shanghai, China.

OBJECTIVES: The aim of the study was to describe the major complaints of menopausal symptoms among middle-aged women who initiated healthcare seeking for menopausal symptoms and to understand the factors influencing women's decisions to seek perimenopausal health care in Shanghai, China. METHODS: A cross-sectional study was performed in five hospitals in Shanghai. Women aged 40 to 60 years at their first visit to the perimenopausal outpatient departments/clinics were investigated in person over a 3-month period. Information on sociodemographics, menopausal symptoms, and experiences in seeking perimenopausal health care was collected using a structured questionnaire. Menopausal symptoms were assessed with the modified Kupperman Menopausal Index (mKMI). RESULTS: A total of 316 women were enrolled in the study, with an average age of 50.5 years (SD: 5.1 y). The prevalence of menopausal syndrome (mKMI >6 points) was 80%, with 7% of the cases being severe. The top five reported symptoms were hot flushes/sweating (62%), fatigue (54%), sleep disturbance (51%), mood swings (40%), and joint/muscle pain (40%). The median interval between symptom occurrence and seeking perimenopausal health care was 5.0 months (IQR: 2.0-23.3 mo). Cox regression analysis revealed that older age, no health insurance, employment, multiple symptoms, sleep disturbance, urinary incontinence, and visits to nonspecialized departments were significantly associated with a longer delay in seeking perimenopausal health services (P < 0.05). CONCLUSIONS: The prevalence of menopausal syndrome was relatively high among 40- to 60-year-old women who initiated healthcare seeking in Shanghai. Months of delay occurred before they sought perimenopausal health services. The delay was related to age, the nature and number of symptoms, working status, and health insurance. Improvement of the menopausal health knowledge in Chinese middle-aged women may lead to more timely healthcare seeking. Professional and accessible perimenopausal health services are in high demand in Shanghai.

A simple risk score based on sleep quality for predicting depressive symptoms in menopausal women: a multicenter study.

OBJECTIVE: We aim to establish a simple risk score based on sleep quality for predicting depressive symptoms in menopausal women through a cross-sectional investigation. MATERIALS AND METHODS: A total of 705 Chinese women aged 40-60 years were included in this cross-sectional investigation of a self-report questionnaire from the Physical Examination Center at Shanghai Jiao Tong University Affiliated Sixth People's Hospital. Depressive symptoms and sleep quality were evaluated using self-rating depressive symptom scale (SDS)and the Pittsburgh Sleep Quality Index (PSQI), respectively. After setting up a logistic regression model and computing the odds ratio value, we further calculated and predicted the risk score for depressive symptoms and then established a risk score system. Finally, we validated the risk score in two investigations (Validation 1 and Validation 2). RESULTS: The risk scoring system for predicting depressive symptoms included a history of cancer, subjective sleep quality, sleep disorder and daytime dysfunction, with total scores ranging from 0-35 points. The receiver operating characteristic (ROC) sample curve was 0.801 (95% CI 0.753-0.848). The Area Under the Curve (AUC) was 0.832 (95% CI 0.738-0.925) in Validation 1 and 0.799 (95%CI 0.667-0.930) in Validation 2. The best cutoff point for depressive symptoms in the sample population was ≥8 points, and the sensitivity and specificity were 0.698 and 0.824, respectively. The sensitivity was 0.775 and 0.667 in Validation 1 and Validation 2, respectively. CONCLUSIONS: The risk score for predicting depressive symptoms in menopausal women based on sleep is convenient. Because there is no complex assessment of multiple scales requiredIt may be a preliminary screening tool for depressive symptoms in menopausal women.

Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study.

OBJECTIVE: The present study aimed to develop a symptom-based (namely, hot flashes and sweating) scoring system for predicting the risk of depressive symptoms in menopausal women via a multicentre cross-sectional survey. METHODS: The data examined in the present study were obtained from 1,004 women aged 40-60 years who underwent physical examination at A Hospital. The basic information was obtained using a questionnaire-based survey. A self-rating depression scale was used to obtain the depressive symptom scores, while the Kupperman Menopausal Index was used to obtain the scores for the frequency of hot flashes and sweating. A logistic regression model was also established. The resulting ß coefficient was employed to calculate and predict the risk of depressive symptoms in these women and a risk scoring system was established. The scoring system was validated using samples from 2 other centers (validation sample 1: B Hospital, 440 women; validation sample 2: C Hospital, 247 women). RESULTS: The scoring system developed to predict the risk of depressive symptoms in menopausal women was based on hot flash and sweating symptoms and associated with menopausal status, hot flash scores, education level (high school education and below) and being diabetic. The scoring system yielded a total score of 0-54 points. For women in the study sample, the area under the curve (AUC) of depressive symptom risk score was 0.750 (95% CI, 0.708-0.793). Validation sample 1 had an AUC of 0.731 (95% CI, 0.667-0.794), while validation sample 2 had an AUC of 0.744 (95% CI, 0.669-0.820). The optimal cut-off score to assess depressive symptoms in women participating in the present study was 31 points. The sensitivity and specificity for predicting depressive symptoms in the study sample were 0.667 and 0.701, respectively. In contrast, the sensitivity was 0.840 in validation sample 1 and 0.879 in validation sample 2. CONCLUSION: The hot flash and sweating symptom-based scoring system developed to predict the risk of depressive symptoms in menopausal women relies on non-laboratory survey data. The system is simple, practical, and convenient to use. For Chinese huge population of menopausal women, the scoring system should be considered a reliable screening tool for depressive symptoms.