Objective To observe the clinical efficacy of acupuncture in treating severe pneumonia complicated with gastrointestinal dysfunction (GIDF).Method Sixty patients with severe pneumonia complicated with GIDF were randomized into a treatment group and a control group, 30 cases in each group. The two groups were both given conventional Western medications. In addition, the treatment group was intervened by acupuncture, and the control group by oral administration of Mosapride citrate capsules and enteral nutrition via nasogastric tube. After 7-day treatment, the changes of GIDF score, intraabdominal pressure, bowel sound and gastric retention were observed in the two groups, and the clinical efficacies were compared.Result The total effective rate was 93.1% in the treatment group versus 78.6% in the control group, and the between-group difference was statistically significant (P<0.05). The scores of GIDF and the indexes (intraabdominal pressure, bowel sound, and gastric retention) were significantly changed after the treatment in both groups (P<0.05). The scores of GIDF and the indexes in the treatment group were significantly different from those in the control group after the intervention (P<0.05).Conclusion Acupuncture can promote the recovery of gastrointestinal function in severe pneumonia patients, since it can significantly improve the intraabdominal pressure, bowel sound and gastric retention.

Objective This study aimed to evaluate the association between the paraoxonase (PON) genes variants and Alzheimer's disease (AD) using systematic review with meta-analysis.Methods Relevant studies were identified by searching English and Chinese databases extensively.Newcastle-Ottawa Scale (NOS) was employed to evaluate the quality of included studies.The odds ratio (OR) was calculated using a random-effects or fixed-effects model.A Q statistic was used to evaluate homogeneity,and fail-safe number,Egger's test and funnel plot were used to assess publication bias.Results A total of 15 studies were included and identified for the current meta-analysis.The NOS scores ranged from 7 to 8,meaning good quality of studies.It was found that the SS genotype of PON2 S311C polymorphism had an significant association with AD in the studied population (OR=0.82,P=0.04).However,there was no significant relationship between other three genetic variants of PON genes and AD.Conclusions Existing evidence indicated that the PON2 S311C polymorphism (SS genotype) was associated with risk of AD in studied population.Future studies with larger sample sizes will be necessary to confirm the present results.

Professor Li Candong puts forward the"five differentiation"thinking in TCM:symptom differentiation,syndrome differentiation,disease differentiation,person differentiation and mechanism differentiation.This article discussed the thinking and method of application of classical prescriptions based on the mode of"five differentiation".Treatment based on symptom differentiation is a quick method of application of classic prescriptions,which includes searching for specific symptoms or symptom groups and according to special tongue images.Treatment based on syndrome differentiation is a commonly used method in classic prescriptions,distinguishing between primary and secondary syndromes and the authenticity of cold and heat.Treatment based on disease differentiation is the inherent meaning of classic prescriptions,which is mainly to distinguish six meridian diseases and special prescriptions for specific diseases.Treatment based on person differentiation embodies the individual differences in the use of classic prescriptions,which include age,gender,constitution and abdominal syndrome.Treatment based on mechanism differentiation is an ingenious method used by classic prescriptions.When practicing clinical medicine,we should adhere to the integrated mode of"five differentiation"in the application of classic prescriptions,comprehensively considering the five dimensions,in order to improve the accuracy and effectiveness of the application of classic prescriptions,reveal and improve the academic system of classic prescriptions,and better guide their clinical application.

Objective To provide a system for warning, preventing and controlling emerging infectious diseases from a macroscopic perspective, using the COVID-19 epidemic data and effective distance model. Methods The dates of hospitalization/isolation treatment of the first confirmed cases of COVID-19 and the cumulative numbers of confirmed cases in different provinces in China reported as of 23 February, 2020 were collected. The Location Based Service (LBS) big data platform of 'Baidu Migration' was employed to obtain the data of the proportion of the floating population from Wuhan to all parts of the country. Effective distance models and linear regression models were established to analyze the relationship between the effective distance and the arrival time of the epidemic as well as the number of cumulative confirmed cases at provincial and municipal levels. Results The arrival time of the epidemic and the cumulative number of confirmed cases of COVID-19 had significant linear relationship at both provincial and municipal levels in China, and the regression coefficients of each linear model were significant ( P <0.001). At the provincial level, the effective distance could explain about 71% of the variation of the model with arrival time along with around 90% of the variation for the model in the cumulative confirmed case magnitude; at the municipal level, the effective distance could explain about 66% of the variation for the model in arrival time, and about 85% of the variation of the model with the cumulative confirmed case magnitude. Conclusions The fitting degree of the models are good. The LBS big data and effective distance model can be used to estimate the track, time and extent of epidemic spread to provide useful reference for early warning, prevention and control of emerging infectious diseases.

It is noteworthy that only 5% of more than 7000 described rare diseases are treated. In the era of big data, there is ever-increasing data for understanding biomedicine. The need for efficient and rapid data collection, analyses and characterization methods is pressing. Rare diseases can particularly benefit from artificial intelligence (AI) application. AI, with an emphasis on machine learning, creates a path for such efforts and is being applied to diagnosis and treatment. AI has demonstrated its potential to learn and analyze data from different sources with results in prediction。Presently, there are AI-driven technologies applied for rare diseases and this review aims to summarize these advances. Moreover, this review scrutinizes the limitation and identifies the pitfalls of AI applications in the diagnosis and treatment of rare diseases.