The combination of sourness,bitterness,sweetness,pungency,and saltness results in different effects.Through the analysis of the theory of combining five flavours in Fu Qingzhu's Obstetrics and Gynecology,this article explores its application in formulation ideas and the characteristics of Chinese medication,summarized as"primarily sweet,with all four flavors harmonized".FU Qingzhu emphasizes the central role of sweet-flavour medicine in facilitating conception,while incorporating the other four flavours in synergy.For instance,sweet and pungent flavours can boost yang energy,eliminating chilliness and warming the uterus;sour and sweet flavours can nourish yin essence and protect the uterus;bitter and sweet flavours can tonify yin,supporting the kidneys and moistening the uterus;and pungent and salty flavours can eliminate stasis,regenerate blood,and enhance uterine functions.By flexibly utilizing the flavours and meridian affinity of traditional Chinese medicine,along with the theory of combining five flavours,it is possible to enhance drug compatibility,deepen the theoretical connotation of Chinese formulas,and regulate the uterus from both yin and yang aspects to facilitate conception.FU Qingzhu's integration of multiple Chinese formulas into a single formula allows for comprehensive treatment.Clear differentiation of dosages within the formula highlights the primary and secondary relationships of traditional Chinese medicines.Additionally,the utilization of pharmaceutical processing techniques optimizes efficacy and regulates meridians and collaterals.This article explores FU Qingzhu's application of the"pure and harmonious traditional Chinese medicines"theory.His prescription thinking enables the attainment of multi-level therapeutic effects,which greatly benefits the optimization of traditional Chinese medicine fertility assistance programs and increases pregnancy rates among infertility patients.

Objective:To understand the epidemiological characteristics of imported COVID-19 cases in Guangzhou and provide scientific basis for the prevention and control of the disease.Methods:The data of imported COVID-19 in Guangzhou reported as of April 1, 2020 were collected from National Notifiable Disease Report System of China. The software Excel 2010 and SPSS 19.0 were applied for data cleaning and statistical analysis.Results:As of April 1, 2020, a total of 103 imported COVID-19 cases had been reported in Guangzhou, in which 92 were confirmed cases and 11 were asymptomatic infection cases. The number of the confirmed imported cases accounted for 11.4 % (92/806) in of the total in China at the same time. The male to female ratio of the cases was 1.58∶1 (63∶40). The median age of the cases was 31 years ( P 25- P 75:22-40 years), range of age was 11-63 years. The main occupational distributions of the cases were business services (41/103, 39.8 %) and students (36/103, 35.0 %). The imported cases whose destinations were 19 provinces and municipalities rather than Guangdong after entering the country accounted for 43.7 %. The main source countries of infections were the United Kingdom (27/103, 26.2 %), the Philippines (13/103, 12.6 %), the United States (13/103, 12.6 %) and Nigeria (7/103, 6.8 %). There were 34 inbound flights from which the imported COVID-19 cases were detected, in which 10 flights (10/34, 29.4 %) were found to carry more than 3 cases, with an average voyage time of (11.14±0.53) hours. A total of 29 imported cases(28.2 %) showed symptoms before entering the country, and 65 cases (63.1 %) had been isolated before the onset of the disease. The mean free activity time of the isolated cases after the onset was (6.76±0.79) days. The average number of the imported cases’ close contacts was 53. There were 13 clusters of COVID-19 caused by the imported cases, involving 36 cases (including 1 imported associated case). Conclusions:The sources of the imported COVID-19 cases in Guangzhou were widely distributed, and no cases had been found to be infected on the flights. In the early stage of the imported epidemic, there was high risk for the spread of the epidemic. Strengthened prevention and control of imported COVID-19 effectively reduced the of transmission risk of COVID-19 in communities.

Objective:To analyze the characteristics of COVID-19 case spectrum and spread intensity in different provinces in China except Hubei province.Methods:The daily incidence data and case information of COVID-19 were collected from the official websites of provincial and municipal health commissions. The morbidity rate, severity rate, case-fatality rate, and spread ratio of COVID-19 were calculated.Results:As of 20 March, 2020, a total of 12 941 cases of COVID-19 had been conformed, including 116 deaths, and the average morbidity rate, severity rate and case-fatality rate were 0.97/100 000, 13.5 % and 0.90 %, respectively. The morbidity rates in Zhejiang (2.12/100 000), Jiangxi (2.01/100 000) and Beijing (1.93/100 000) ranked top three. The characteristics of COVID-19 case spectrum varied from province to province. The first three provinces (autonomous region, municipality) with high severity rates were Tianjin (45.6 %), Xinjiang (35.5 %) and Heilongjiang (29.5 %). The case-fatality rate was highest in Xinjiang (3.95 %), followed by Hainan (3.57 %) and Heilongjiang (2.70 %). The average spread ratio was 0.98 and the spread intensity varied from province to province. Tibet had the lowest spread ratio (0), followed by Qinghai (0.20) and Guangdong (0.23). Conclusion:The intervention measures were effective in preventing the spread of COVID-19 and improved treatment effect in China. However, there were significant differences among different regions in severity, case-fatality rate and spread ratio.

Objective To examine the association of pre?pregnancy body mass and weight gain during pregnancy with macrosomia. Methods From January 2015 to December 2015, a total of 20 477 pregnant women were recruited by probabilistic proportional scale sampling with simple randomization in Sichuan, Yunnan and Guizhou Provinces. Basic information of pregnant women, weight gain during pregnancy and weight of newborn were collected. A multiple logistic regression model was used to assess the association between the pre?pregnancy body mass and gestational weight gain indicators with macrosomia. Results 20 321 mother?infant were included in the final analysis. 20 321 pregnant women were (30.09 ± 4.10) years old and delivered at (39.20 ± 1.29) weeks, among which 12 341 (60.73%) cases were cesarean delivery. The birth weight of 20 321 infants were (3 292.26 ± 431.67) grams, and 970 (4.77%) were macrosomia. The multiple logistic regression model showed that after adjusting for the age of women, compared to the normal weight group in the pre?pregnancy, the overweight and obesity group elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI: 1.69-2.35) and 4.05 (95%CI: 3.05-5.39), respectively. After adjusting for the age, the pre?pregnancy BMI, delivery weeks, delivery mode and infant's gender, compared to the weight?gain appropriate group, higher weight gain rate in the mid?pregnancy and excessive total gestational weight gain elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI:1.66-2.39) and 1.80 (95%CI: 1.55-2.08), respectively. Conclusion The overweight before pregnancy, obesity before pregnancy, the rate of weight gain in the second trimester and the high total weight gain during pregnancy could increase the risk of macrosomia.

Objective:To compare the incidence of coronary microvascular disease (CMVD) between patients with non-obstructive and obstructive coronary arteries.Methods:We retrospectively analyzed 97 patients with angina pectoris, who underwent the absolute quantitative PET examination of myocardial perfusion and coronary anatomy examination within 90 days. All patients were divided into two groups: non-obstructive group (72 cases, no stenosis ≥50% in all three coronary arteries) and obstructive group (25 cases, at least one coronary stenosis ≥50%; and at least one coronary stenosis<50%). Quantitative parameters derived from PET including rest myocardial blood flow (RMBF), stress myocardial blood flow (SMBF), coronary flow reserve (CFR) and cardiovascular risk factors were compared between the two groups. CMVD was defined as CFR<2.90 and SMBF <2.17 ml·min -1·g -1. Results:Incidence of CMVD was significant higher in the non-obstructive coronary arteries of the obstructive group than in the non-obstructive coronary arteries of non-obstructive group (47.1% (16/34) vs. 25.5% (55/216), χ 2=6.738, P=0.009) while incidence of CMVD was similar between non-obstructive and obstructive patients ((44% (11/25) vs. 33.3% (24/72), χ 2=0.915, P=0.339). RMBF ((0.83±0.14) ml·min -1·g -1 vs. (0.82±0.17) ml·min -1·g -1), SMBF ((2.13±0.60) ml·min -1·g -1 vs. (1.91±0.50) ml·min -1·g -1) and CFR (2.59±0.66 vs. 2.36±0.47) were similar between the two groups (all P>0.05). Conclusions:CMVD can occur in non-obstructive coronary arteries in both patients with non-occlusive coronary arteries and patients with obstructive coronary arteries. Prevalence of CMVD is significantly higher in patients with obstructive coronary arteries than in patients with non-obstructive coronary arteries. The CMVD severity is similar between the two groups.

Objective To examine the association of pre?pregnancy body mass and weight gain during pregnancy with macrosomia. Methods From January 2015 to December 2015, a total of 20 477 pregnant women were recruited by probabilistic proportional scale sampling with simple randomization in Sichuan, Yunnan and Guizhou Provinces. Basic information of pregnant women, weight gain during pregnancy and weight of newborn were collected. A multiple logistic regression model was used to assess the association between the pre?pregnancy body mass and gestational weight gain indicators with macrosomia. Results 20 321 mother?infant were included in the final analysis. 20 321 pregnant women were (30.09 ± 4.10) years old and delivered at (39.20 ± 1.29) weeks, among which 12 341 (60.73%) cases were cesarean delivery. The birth weight of 20 321 infants were (3 292.26 ± 431.67) grams, and 970 (4.77%) were macrosomia. The multiple logistic regression model showed that after adjusting for the age of women, compared to the normal weight group in the pre?pregnancy, the overweight and obesity group elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI: 1.69-2.35) and 4.05 (95%CI: 3.05-5.39), respectively. After adjusting for the age, the pre?pregnancy BMI, delivery weeks, delivery mode and infant's gender, compared to the weight?gain appropriate group, higher weight gain rate in the mid?pregnancy and excessive total gestational weight gain elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI:1.66-2.39) and 1.80 (95%CI: 1.55-2.08), respectively. Conclusion The overweight before pregnancy, obesity before pregnancy, the rate of weight gain in the second trimester and the high total weight gain during pregnancy could increase the risk of macrosomia.

Objective: To examine the association of pre-pregnancy body mass and weight gain during pregnancy with macrosomia. Methods: From January 2015 to December 2015, a total of 20 477 pregnant women were recruited by probabilistic proportional scale sampling with simple randomization in Sichuan, Yunnan and Guizhou Provinces. Basic information of pregnant women, weight gain during pregnancy and weight of newborn were collected. A multiple logistic regression model was used to assess the association between the pre-pregnancy body mass and gestational weight gain indicators with macrosomia. Results: 20 321 mother-infant were included in the final analysis. 20 321 pregnant women were (30.09±4.10) years old and delivered at (39.20±1.29) weeks, among which 12 341 (60.73%) cases were cesarean delivery. The birth weight of 20 321 infants were (3 292.26±431.67) grams, and 970 (4.77%) were macrosomia. The multiple logistic regression model showed that after adjusting for the age of women, compared to the normal weight group in the pre-pregnancy, the overweight and obesity group elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI: 1.69−2.35) and 4.05 (95%CI: 3.05−5.39), respectively. After adjusting for the age, the pre-pregnancy BMI, delivery weeks, delivery mode and infant′s gender, compared to the weight-gain appropriate group, higher weight gain rate in the mid-pregnancy and excessive total gestational weight gain elevated the risk of macrosomia, with OR (95%CI) about 1.99 (95%CI: 1.66−2.39) and 1.80 (95%CI: 1.55−2.08), respectively. Conclusion The overweight before pregnancy, obesity before pregnancy, the rate of weight gain in the second trimester and the high total weight gain during pregnancy could increase the risk of macrosomia.