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Abstract Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease, complications, and treatment outcomes by applying specific methodologies. Polycystic ovary syndrome (PCOS) is a common disease with a high incidence rate, huge heterogeneity, short- and long-term complications, and complex treatments. In this systematic review study, we reviewed the progress of clinical prediction models in PCOS patients, including diagnosis and prediction models for PCOS complications and treatment outcomes. We aimed to provide ideas for medical researchers and clues for the management of PCOS. In the future, models with poor accuracy can be greatly improved by adding well-known parameters and validations, which will further expand our understanding of PCOS in terms of precision medicine. By developing a series of predictive models, we can make the definition of PCOS more accurate, which can improve the diagnosis of PCOS and reduce the likelihood of false positives and false negatives. It will also help discover complications earlier and treatment outcomes being known earlier, which can result in better outcomes for women with PCOS.

IntroductionDetermining the causal relationship between polycystic ovary syndrome (PCOS) and gestational diabetes mellitus (GDM) holds significant implications for GDM prevention and treatment. Despite numerous observational studies suggesting an association between PCOS and GDM, it remains unclear whether a definitive causal relationship exists between these two conditions and which specific features of PCOS contribute to increased incidence of GDM.MethodsThe causal relationship between polycystic ovary syndrome (PCOS), its characteristic indices, and gestational diabetes mellitus (GDM) was investigated using a two-sample Mendelian randomization study based on publicly available statistics from genome-wide association studies (GWAS). The inverse-variance weighted method was employed as the primary analytical approach to examine the association between PCOS, its characteristic indices, and GDM. MR Egger intercept was used to assess pleiotropy, while Q values and their corresponding P values were utilized to evaluate heterogeneity. It is important to note that this study adopts a two-sample MR design where PCOS and its characteristic indices are considered as exposures, while GDM is treated as an outcome.ResultsThe study results indicate that there is no causal relationship between PCOS and GDM (all methods P > 0.05, 95% CI of OR values passed 1). The IVW OR value was 1.007 with a 95% CI of 0.906 to 1.119 and a P value of 0.904. Moreover, the MR Egger Q value was 8.141 with a P value of 0.701, while the IVW Q value was also 8.141 with a P value of 0.774, indicating no significant heterogeneity. Additionally, the MR Egger intercept was 0.0004, which was close to zero with a P value of 0.988, suggesting no pleiotropy. However, the study did find a causal relationship between several other factors such as testosterone, high-density lipoprotein, sex hormone-binding globulin, body mass index, waist-hip ratio, apolipoprotein A-I, number of children, diabetes illnesses of mother, father and siblings, hemoglobin A1c, fasting insulin, fasting blood glucose, years of schooling, and GDM based on the IVW method.ConclusionWe observed no association between genetically predicted PCOS and the risk of GDM, implying that PCOS itself does not confer an increased susceptibility to GDM. The presence of other PCOS-related factors such as testosterone, high-density lipoprotein, and sex hormone-binding globulin may elucidate the link between PCOS and GDM. Based on these findings, efforts aimed at preventing GDM in individuals with PCOS should prioritize those exhibiting high-risk features rather than encompassing all women with PCOS.

Abstract The security of natural gas supply and demand has always been an important topic, and as a result, analyzing and predicting the supply and demand of natural gas has received considerable attention from researchers. Numerous studies have extensively researched the supply and demand of natural gas. The main purpose of this study is to explore the supply‐demand balance mechanism for natural gas security. A system dynamics model is constructed to assess the supply and demand of natural gas in Sichuan Province, China. A new system dynamics model based on domestic gas, production gas, ecological environment and natural gas supply is proposed. The study considers four scenarios: natural development, economic priority development, environmental priority development and coordinated development. The results show that the rapid economic development has led to an excessive environmental carrying capacity, a larger gap between natural gas supply and demand, a decline in the quality of life of residents, and even affected the energy security of Sichuan Province and China. The findings also show that people's overprotection of the environment can lead to slow economic development, which prevents it from achieving its desired goals. The coordinated development scenario in this paper not only ensures the production of natural gas and the quality of life of residents, but also is an optimal scheme with low energy consumption and pollution. According to the research conclusions, considering the overall situation of China's energy security and the situation in Sichuan Province, the author proposes reforms from the supply and demand sides of natural gas.

Focusing on the complex market environment of Guangdong Province, this research pioneers a model for assimilating external power sources into the intra-provincial power market, a critical move to support the region’s high demand for electricity driven by robust economic activities. Our study innovatively tackles the province’s fluctuating power supply and demand by employing a novel power supply equivalence and co-modulation technique, enhancing system modeling efficiency and computational effectiveness. Comparative evaluations demonstrate that our approach significantly reduces the power market’s purchase costs by 15% while safeguarding power supply stability and security. The proposed model presents a breakthrough in optimizing Guangdong’s power market’s economic and reliability aspects, offering a promising pathway for future market clearing practices.

Lotus seed protein isolate (LSPI) was used as emulsifier to prepare high internal phase (high load) β-carotene-loaded emulsion (LSPI-BC). The stability and β-carotene retention rate of LSPI-BC were measured, and the mechanism of the changes in LSPI-BC at different stages of in vitro digestion was investigated. The results showed that LSPI-BC had long-term stability at low temperature (4 ℃), and the retention rate of β-carotene was over 85%. However, the stability and β-carotene retention rate of LSPI-BC decreased significantly when the temperature was above 25 ℃. High temperature treatment caused LSPI to unfold and expose hydrophobic groups, forming a spatial network structure that imparts LSPI-BC with good thermal stability and protects the β-carotene from further degradation. In the in vitro digestion experiment, salivary mucin and high concentrations of ions in the oral digestive fluid decreased the magnitude of surface charge on the droplets and then affected the stability of the emulsion. In the gastric phase, flocculation or fusion occurred due to the effect of pH, the potential changed from negative to positive, and the protein aggregates dispersed. In the intestinal phase, the droplet size decreased obviously and the absolute value of potential increased. After hydrolysis, the 1,1-diphenyl-2-picylhydrazyl (DPPH) radical scavenging ability increased significantly. In addition, free fatty acids were released gradually during simulated digestion, and the amount of free fatty acids released increased obviously in the first 30 min of digestion, and then reached 61.94% at 60 min, indicating that LSPI was more suitable for encapsulating active substances. The encapsulated active substance remained stable in acidic medium, its release was delayed during in vitro digestion and its bioavailability was increased to 58.51%. This study may provide a theoretical basis for the development and utilization of LSPI for high loading and sustained release of lipid-soluble active substances.