Assessment of neutrophil to lymphocyte ratio, C-reactive protein, mean platelet volume in obese, and nonobese patients with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is associated with low-grade chronic inflammation. This was a retrospective case-control study. In the present study, the risk coefficients of neutrophil to lymphocyte ratio (NLR), high-sensitive C-reactive protein (hs-CRP), and mean platelet volume (MPV) in obese patients with PCOS were determined. This study was designed to investigate NLR, hs-CRP, and MPV levels in 68 obese patients with PCOS and 44 nonobese patients with PCOS, and our study group was matched with 47 obese and 43 nonobese controls, respectively. PCOS group had higher MPV, NLR, insulin, glucose, and HOMA-IR rates than those of the controls. Subgroup analyses revealed that the obese PCOS group had higher NLR, hs-CRP, and MPV levels compared to those of controls. The obese PCOS group had higher NLR, hs-CRP, and MPV levels compared to those of the nonobese PCOS group. The odds ratios and 95% confidence intervals of those variables (NLR, hs-CRP, MPV) were found significant (P < .05). NLR, hs-CRP, and MPV variables were found statistically significant in the analysis of receiver operating characteristics. Our study demonstrated that NLR, hs-CRP, and MPV levels are increased in patients with obese PCOS.

Transfer learning for bearing performance degradation assessment based on deep hierarchical features.

Bearing design, production and complicated operating condition can lead to the scattered life cycle degradation distribution, which will bring a challenge of generalization for performance degradation assessment models. And it is costly and time-consuming to collect a large amount of labeled data for supervised diagnosis, especially when the task comes from a new operating condition. Thus in this paper, a novel bearing degradation assessment model is proposed based on transfer learning and deep hierarchical features extraction. The research of degradation assessment is transformed to the classification task of degradation pattern, which divides degradation process into the normal, slight fault, fault development and damage patterns. The hierarchical network with random weight parameters is introduced to extract the local sub-band characteristics of spectrum, in which the multiple alternately convolution and pooling layers without supervised fine-tuning are employed. Joint Geometrical and Statistical Alignment method is then utilized to obtain projected sharing feature space, and thus the knowledge of bearing degradation process is transferred to accomplish degradation pattern assessment under different operating conditions. Results of the experiments on bearing fault severity and degradation process show that the proposed method reduces the feature distribution divergence between the degradation processes and accomplishes bearing performance degradation assessment in different operating condition.

The influence of educational level in peri-menopause syndrome and quality of life among Chinese women.

Objective: To investigate the influence of education level in the peri-menopausal symptoms and quality of life (QoL) among Chinese women.Methods: We carried out a cross-sectional study of 1632 peri-menopausal women (age 40-60 y) who visited Hangzhou Women's Hospital from November 2018 to November 2019. The menopausal symptoms were evaluated by modified Kupperman index (KI). World Health Organization Quality of Life (WHOQOL-BREF) questionnaire was used to evaluate the QoL.Result: In total, 1501 women were included in the analysis. The mean age of natural menopause was 49.63 years in China. The five most frequent symptoms in menopausal women were Hot flash (75.53%), sexual problems (72.62%), insomnia (67.29%), fatigue (65.56%), and irritability (61.89%). Natural menopausal age, parity, BMI, bone mineral density, depression, skin formication, total score of KI, and the score of WHOQOL-BREF questionnaire were different in different educational background women (p < .05).Conclusions: The results of the study suggest that education level is associated with the age of natural menopause and menopausal symptoms. A high educational level is correlated with a better score of WHOQOL-BREF in peri-menopause women.