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This study creates a Chinese financial cycle index to examine the lead-and-lag relations between business and financial cycles. We examine the macroeconomic performance when these cycles are in boom, bust, and other combinations. We have four interesting results. First, financial cycles occur less frequently than business cycles. Second, the upturn phase of a financial cycle is significantly longer than the downturn phase. Third, gross domestic product growth rates are at their lowest when the two cycles are in troughs and the highest when they reach their peaks. We find similar results for employment, inflation, and consumption rates. Fourth, financial cycles lead business cycles but not vice versa. Hence, policymakers should consider the financial system before bailing out the real economy, which alone is insufficient for the recovery of the macro economy. [ABSTRACT FROM AUTHOR]

Purpose: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated co-morbidities. The aim is to use machine learning (ML) algorithms to study data gathered throughout the first trimester in order to predict GDM., Methods: Two independent cohorts with forty-five features gathered through first trimester were included. We constructed prediction models based on three different algorithms and traditional logistic regression, and deployed additional two ensemble algorithms to identify the importance of individual features., Results: 4799 and 2795 pregnancies were included in the Xinhua Hospital Chongming branch (XHCM) and the Shanghai Pudong New Area People's Hospital (SPNPH) cohorts, respectively. Extreme gradient boosting (XGBoost) predicted GDM with moderate performance (the area under the receiver operating curve (AUC) = 0.75) at pregnancy initiation and good-to-excellent performance (AUC = 0.99) at the end of the first trimester in the XHCM cohort. The trained XGBoost showed moderate performance in the SPNPH cohort (AUC = 0.83). The top predictive features for GDM diagnosis were pre-pregnancy BMI and maternal abdominal circumference at pregnancy initiation, and FPG and HbA1c at the end of the first trimester., Conclusion: Our work demonstrated that ML models based on the data gathered throughout the first trimester achieved moderate performance in the external validation cohort., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: To investigate the genetic polymorphisms of 15 STRs loci in Chinese E Wen-ke population., Methods: DNA samples from 99 unrelated individuals in Chinese E Wen-ke population were screened by Power Plex 16 System and ABI3100 Genetic Analyzer., Results: The genotype frequencies of these 15 STR loci meet the Hardy-Weinberg expectation. The Matching probability of 15 STRs loci were between 0.0205-0.1733, discriminating power (DP) at 0.8267-0.9795, heterozygosity (Ho) at 0.6061-0.9091, power of exclusion (PE) at 0.4038-0.7690, polymorphism information content (PIC) at 0.5985-0.8734. The total DP of 15 STRs loci is 0.9999999999998., Conclusion: Our results showed that the 15 STRs loci of Power Plex 16 System are valuable STR loci genetic marker system having high DP and are useful in forensic case work in Chinese E Wen-ke population.