Objective: To investigate the early immune effects of rabies vaccine combined with human rabies immunoglobulin (HRIG). Methods: Rapid fluorescent focus inhibition test (RFFIT) was used to test the titers of rabies virus neutralizing antibodies (RVNA). The titers of RVNA of persons who had exposed to rabies at degree III on day 0, day 1, day 7, day 14 and day 45 were compared. The dynamic curves and seroconversion rates (SCR) of RVNA in persons of different genders, age and vaccine regimens (Essen and Zagreb) groups were analyzed. Results: No significant differences of SCR among different genders, age and vaccine regimens groups were observed on the same day. SCR could be 100% on day14 in different groups. The dynamic curves of RVNA within the first 14 days showed the models of gradual rise, rapid rise and rapid decline. Conclusions The dynamic curves of RVNA within the first 14 days varied when rabies vaccines were used in combination with HRIG, and not all subjects were proved to be protected based on the RVNA detection within this period.

Background/Aims: The aim of this study was to analyze the chronological changes in postoperative complications in surgical ulcerative colitis patients over the past decade in China and to investigate the potential parameters that contributed to the changes. Methods: Ulcerative colitis patients who underwent surgery during 2008–2017 were retrospectively enrolled from 13 hospitals in China. Postoperative complications were compared among different operation years. Risk factors for complications were identified by logistic regression analysis. Results: A total of 446 surgical ulcerative colitis patients were analyzed. Fewer short-term complications (24.8% vs. 41.0%, P=0.001) and more laparoscopic surgeries (66.4% vs. 25.0%, P<0.001) were found among patients who received surgery during 2014–2017 than 2008–2013. Logistic regression suggested that independent protective factors against short-term complications were a higher preoperative body mass index (odds ratio [OR], 0.870; 95% confidence interval [CI], 0.785–0.964; P=0.008), laparoscopic surgery (OR, 0.391; 95% CI, 0.217–0.705; P=0.002) and elective surgery (OR, 0.213; 95% CI, 0.067–0.675; P=0.009). The chronological decrease in short-term complications was associated with an increase in laparoscopic surgery. Conclusions Our data revealed a downward trend of short-term postoperative complications among surgical ulcerative colitis patients in China during the past decade, which may be due to the promotion of minimally invasive techniques among Chinese surgeons.

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.