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PurposeTo construct and compare machine learning models for predicting the risk of gestational diabetes mellitus (GDM).MethodThe clinical data of 2048 pregnant women who gave birth at Shunde Women’s and Children’s Hospital of Guangdong Medical University between June 2019 and June 2021 were retrospectively collected. Logistic regression, backpropagation neural networks, random forests, and support vector machines were constructed with the R studio and Python software programs. The logistic regression and random forest models were used to identify significant influencing factors. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive performance and discriminative ability of the models, and the Hosmer-Lemeshow test was used to determine goodness of fit.ResultsAge, glycated hemoglobin, fasting blood glucose, white blood cell count, hemoglobin, and activated partial prothrombin time were identified as significant factors associated with GDM. The random forest model had the best prediction effect (accuracy, 78.07%; Youden index, 1.56). In all four models, AUC was greater than 78%. The Hosmer–Lemeshow fit test showed that all four models were a good fit.ConclusionIt was concluded that age, GHB, FBG, WBC, HB, and APTT are the more important related influencing factors or early predictors of gestational diabetes. Among the tested models, random forest was the best one for predicting the risk of GDM in early pregnancy.

Objective: This research analyzed the current anxiety situation and its influencing factors of online home classes among college students in the context of the COVID-19 epidemic. The study aims to prevent psychological disorders and improve the efficiency of college students online classes. Methods: We developed a questionnaire on the factors affecting anxiety in online classes for college students. A total of 225 college students participated in the survey. Factor analysis and cluster analysis were used to analyze the data. Results : The anxiety score of college students was (97.19 ± 18.60). Factor analysis on the 25 questions in the questionnaire according to the KMO statistic 0.904 and Bartlett's spherical test (p < 0.05). Six common factors: epidemic (13. 914%), online course model (12.601%), the external environment (11.397%), psychological factors (10.477%), pedagogical factors (7.716%), and self-adjustment factors (7.404%), with a cumulative contribution of 63.51%. On this basis, the total scores of factor analysis by K-means cluster analysis and four types of college students with different degrees of online course anxiety, normal (6.13%), mild anxiety (28.30%), moderate anxiety (45.75%), severe anxiety (19.81%). Conclusions： College students have mild to moderate anxiety in home-based online classes. Male, first-year, and non-medical students are more likely to have anxiety. Factor analysis and cluster analysis can summarize the main influencing factors of college students' online class anxiety, which can provide a practical reference for alleviating college students' online class anxiety and then taking measures.

The integration of the variable renewable energies makes the operation conditions of the power system ever-changeable. Consequently, the power system operational reliability evaluation is increasingly important. This paper introduces the concept of decision-dependent uncertainty (DDU) in the operational reliability evaluation. Unlike the exogenous uncertainties, DDU reveals that the decisions of the system operation could significantly affect the resolution of the uncertainties which influence the reliability metrics. In this paper, the proposed DDU modeling method links the device reliability indices, i.e., the forced outage rate, and the operational-decision variables. The impacts of DDU on operational reliability are analyzed based on a reliability-constrained stochastic unit commitment (UC) model. An adaptive reliability improvement UC (ARIUC) algorithm is proposed to efficiently solve the problem. Case studies underline the necessity of considering DDU in power system operational reliability evaluations.

Background Chronic obstructive pulmonary disease (COPD) is a chronic disease with high mortality and severe morbidity that keep increasing the burden of the health of the population. Chronic Obstructive Pulmonary Disease (QLICD-COPD) (V2.0) was used to measure the quality of life for patients with COPD. The study aimed to develop the instruments to evaluate a quality-of-life questionnaire for COPD. Methods The questionnaires were developed after reviewing the literature and three hundred and twenty-one patients with COPD were evaluated by a series of statistical methods consisting of the paired t-test, correlation analysis, and factor analysis. Results The overall Cronbach’s alpha coefficient was 0.889 (greater than the accepted reference value of 0.7), and the coefficients of most domains and facets were in the range 0.6 to 0.88, except some facets of psychological domain and social domain. The split-half reliability coefficients of the domains and the total scale is greater than 0.6 apart from the physiological domain. Intra-domain internal consistency coefficients were higher than inter-domain correlation coefficients and each item was more strongly correlated with its domain than with other domains. SF-36 domains with high reliability and validity closed linked with the scores of QLICD-COPD (2.0) except the general health and social domains. The paired t-test showed significant changes in the scores of most domains after treatment with PConclusion The QLICD-COPD (V2.0) questionnaire shows good reliability, validity, and responsiveness, and can serve as an instrument for evaluating the quality of life of patients with COPD in China.

Background. The aim of this study was to investigate the association between single nucleotide polymorphism (SNP) rs9891119 of the signal transducer and activator of the transcription 3 (STAT3) gene and genetic susceptibility to type 2 diabetes in Chinese Han population from the Guangdong province. Objective. The aim of the present study was to explore the relationship between single nucleotide polymorphism rs9891119 of STAT3 gene and type 2 diabetes mellitus (T2DM), which provides a basis for molecular genetic research on the pathogenesis of T2DM in Chinese Han population. Methods. In our case-control study, the SNP rs9891119 was picked out from the STAT3 gene and the SNP genotyping was performed by using the SNPscan™ kit in 1092 patients with type 2 diabetes as cases and 1092 normal persons as controls. The distributions of genotype and allele frequencies in two groups were analyzed by SPSS 20.0 software. Results. Our results showed that the alleles of A and C of rs9891119 of the STAT3 gene were 54.3 and 45.7% in patients with type 2 diabetes, while 55.5% and 44.5% in the normal persons, which have no statistical significance P > 0.05 . There were also no significant differences in AA, AC, and CC genotype frequencies between type 2 diabetes patients and normal persons. There were no significant differences in codominant, dominant, recessive, and overdominant genetic models of SNP rs9891119 before and after adjusting the covariant factors P > 0.05 . Conclusions. Therefore, genetic susceptibility to type 2 diabetes may be not associated with SNP rs9891119 of the STAT3 gene in Chinese Han population from the Guangdong province.

Agricultural drought risk analysis is useful for reducing probable drought risk in the background of global warming. This study aims to identify spatiotemporal characteristics of drought and drought disaster risk in the summer maize growth period under climate change condition. In this research, we use daily datasets from 79 meteorological stations and the maize yield data in the Huang-Huai-Hai (HHH) plain, eastern China during the period 1960-2015. The drought disaster risk index (DDRI) model was applied to assess the drought disaster risk. The maize drought disaster risk maps were drawn under current and future climate change conditions. The results showed that the high DDRI was distributed in northern region and low DDRI was distributed in most of southern region in the HHH plain. During the summer maize growth period, the DDRI decreased gradually from the northern to southern region. The results also exhibited that under the RCP4.5 (Representative Concentration Pathway 4.5) scenario, about one half of the HHH plain belonged to the slight and sub-slight DDRI region in the future 80 years. Overall, our results demonstrated that the DDRI model provided an accurate assessment in both spatial and temporal scales and had a theoretical guidance for improving the adaptation of crop production. Elevating maize drought risk management helps to lessen the anticipated risk to crop production in the HHH plain under the context of climate change.

Gastric cancer (GC) has one of the highest mortality rates of malignancies globally. Currently, ciRS-7, a novel circular RNA, has emerged as a potential sponge for miR-7. However, few studies on ciRS-7 in GC have been performed. In this study, we investigated the clinical significance and function of ciRS-7 in GC. First, the expression levels of ciRS-7 in 102 primary GC tissues and the matched para-carcinoma tissues were evaluated and the clinical relevance was confirmed in an independent validation cohort (n = 154). Second, the effects of ciRS-7 on miR-7, PTEN, and PI3K were evaluated. Finally, the function of ciRS-7 in GC was analyzed with cell lines and nude mice. The expression of ciRS-7 was significantly upregulated in GC tissues compared with the matched para-carcinoma tissues (P = 0.0023), and the upregulation of ciRS-7 was linked to poor survival in the testing (P = 0.0143) and validation cohort (P = 0.0061). Multivariate survival analysis revealed that ciRS-7 was probably an independent risk factor of overall survival (P

The management of the demand side in the power system, such as data centers (DCs), can improve the stability of the grid and bring economic benefits in planning and operation. Considering the increasing applications of big data and net-based technologies, the computational jobs in different region can be shifted as flexible load. In this paper, a new type of decomposition method is proposed to solve the model of the stochastic economic dispatch (ED) incorporating DCs, which considers the uncertainties of job arriving rates in DCs and wind generation in power systems. The original ED formulations are decomposed with Benders decomposition to improve computational performance, and a new type of group based multi-cut Benders decomposition is applied to improve the convergence. Case studies on a joint 18-bus system illustrate the benefits of spacial coordination between DCs and power system. The comparison between single-cut and multi-cut approach proved the effectiveness of the proposed method.

The aim of this study was to compare the outcomes of laparoscopic surgery (LAP) and open gastric surgery (OP) in early gastric cancer patients aged ≥70 years.We conducted a retrospectively analysis among patientswith pathological T1N0M0 gastric cancer,who underwent LAP or OP between January 1, 2001 and December 31, 2008. We identified a well-balanced cohort of 2,360 patients (1180 patients in each group). LAP has been shown to offer a superior perioperative results to OP, including lower blood loss, shorter time to oral intake, walk and bowel function recovery, shorter time of hospital stay, and less blood transfusion required. However, the intraoperative and postoperative complications, local recurrence, and metastasis didn’t show statistically significant differences between groups. The 5-year overall survival (OS), disease-free survival (DFS), and cancer-specific survival (CSS) were 60.1% vs.63.2%, 80.8% vs. 83.3%, and 87.6% vs. 89.5% in the LAP group and OP group, respectively. The hazard ratios (HR) for OS, DFS, and CSS were 1.09(95% confidence interval [CI]: 0.95–1.25; P = 0.215), 1.03(95% CI: 0.91–1.18; P = 0.636), and 1.07 (95% CI: 0.88–1.30; P = 0.484), respectively, compared LAP group with OP group. In conclusion, LAP is an acceptable alternative to OP in elderly patients with early gastric cancer.

The aim of this study was to compare the outcomes of laparoscopic surgery (LAP) and open gastric surgery (OP) in early gastric cancer patients aged ≥70 years.We conducted a retrospectively analysis among patientswith pathological T1N0M0 gastric cancer,who underwent LAP or OP between January 1, 2001 and December 31, 2008. We identified a well-balanced cohort of 2,360 patients (1180 patients in each group). LAP has been shown to offer a superior perioperative results to OP, including lower blood loss, shorter time to oral intake, walk and bowel function recovery, shorter time of hospital stay, and less blood transfusion required. However, the intraoperative and postoperative complications, local recurrence, and metastasis didn’t show statistically significant differences between groups. The 5-year overall survival (OS), disease-free survival (DFS), and cancer-specific survival (CSS) were 60.1% vs.63.2%, 80.8% vs. 83.3%, and 87.6% vs. 89.5% in the LAP group and OP group, respectively. The hazard ratios (HR) for OS, DFS, and CSS were 1.09(95% confidence interval [CI]: 0.95–1.25; P = 0.215), 1.03(95% CI: 0.91–1.18; P = 0.636), and 1.07 (95% CI: 0.88–1.30; P = 0.484), respectively, compared LAP group with OP group. In conclusion, LAP is an acceptable alternative to OP in elderly patients with early gastric cancer.