Probiotics-Fermented Grifola frondosa Total Active Components: Better Antioxidation and Microflora Regulation for Alleviating Alcoholic Liver Damage in Mice.

Alcoholic liver damage is caused by long-term drinking, and it further develops into alcoholic liver diseases. In this study, we prepared a probiotic fermentation product of Grifola frondosa total active components (PFGF) by fermentation with Lactobacillus acidophilus, Lactobacillus rhamnosus, and Pediococcus acidilactici. After fermentation, the total sugar and protein content in the PFGF significantly decreased, while the lactic acid level and antioxidant activity of the PFGF increased. Afterward, we investigated the alleviating effect of PFGF on alcoholic liver injury in alcohol-fed mice. The results showed that the PFGF intervention reduced the necrosis of the liver cells, attenuated the inflammation of the liver and intestines, restored the liver function, increased the antioxidant factors of the liver, and maintained the cecum tissue barrier. Additionally, the results of the 16S rRNA sequencing analysis indicated that the PFGF intervention increased the relative abundance of beneficial bacteria, such as Lactobacillus, Ruminococcaceae, Parabacteroids, Parasutterella, and Alistipes, to attenuate intestinal inflammation. These results demonstrate that PFGF can potentially alleviate alcoholic liver damage by restoring the intestinal barrier and regulating the intestinal microflora.

Interaction between maternal passive smoking during pregnancy and CYP1A1 and GSTs polymorphisms on spontaneous preterm delivery.

OBJECTIVE: The present study aimed to examine the association between maternal passive smoking during pregnancy and the risk of spontaneous PTD and to explore the potential interaction of the single or joint gene polymorphism of CYP1A1 and GSTs with maternal passive smoking on the risk of spontaneous PTD. METHOD: We investigated whether the association between maternal passive smoking and PTD can be modified by 2 metabolic genes, i.e. cytochrome P4501A1 (CYP1A1) and glutathione S-transferases (GSTs), in a case-control study with 198 spontaneous preterm and 524 term deliveries in Shenzhen and Foshan, China. We used logistic regression to test gene-passive smoking interaction, adjusting for maternal socio-demographics and prepregnancy body mass index. RESULTS: Overall, maternal passive smoking during pregnancy was associated with higher risk of PTD (adjusted odds ratio = 2.20 [95% confidence interval: 1.56-3.12]). This association was modified by CYP1A1 and GSTs together, but not by any single genotype. For cross-categories of CYP1A1 Msp I and GSTs, maternal passive smoking was associated with higher risk of PTD among those women with CYP1A1 "TC/CC"+ GSTs "null", but not among women with other genotypes; and this interaction was significant (OR = 2.66 [95% CI: 1.19-5.97]; P-value: 0.017). For cross-categories of CYP1A1 BsrD I and GSTs, maternal passive smoking was associated with higher risk of PTD only among those women with CYP1A1"AG/GG"+ GSTs "null", but not among women with other genotypes; and this interaction was significant (OR = 3.00 [95% CI: 1.17-7.74]; P-value: 0.023). CONCLUSIONS: Our findings suggest that the combined genotypes of CYP1A1 and GSTs can help to identify vulnerable pregnant women who are subject to high risk of spontaneous PTD due to passive smoking.

[Study on the impact of related psychological stress and fatigue to different smoking behaviors among undergraduate students].

OBJECTIVE: To explore the relationship between psychological stress, fatigue and different smoking behaviors among undergraduate students. METHODS: 8138 undergraduate students in grade 1 to 3 were sampled with cluster sampling method from a comprehensive university in Guangzhou, and were studied on their psychological stress, peer and self smoking behaviors, as well as socio-demographic factors with a self-administered questionnaire. Physical and mental fatigue was measured by Chalder fatigue scale. A multinomial logistic regression analysis was performed to explore the association between psychological stress, fatigue and different smoking behaviors with 'non-smokers' defined as control group while 'triers' and 'current smokers' as case group, respectively. RESULTS: There were students trying to smoke or becoming current smokers on university campus. After adjusting the effect of relevant socio-demographic factors and peer smoking behavior, physical fatigue (OR = 1.044, 95% CI: 1.013-1.075) and 'worry about current academic and future work' (OR = 1.020, 95% CI: 1.001-1.040) were the risk factors of trying to smoke among male students, while 'study stress (OR = 1.063,95% CI: 1.012-1.117) was the risk factor for female students when start smoking. 'Personnel relationship and environment stress' (OR = 1.152, 95% CI: 1.012-1.312) were the risk factors for female students' current smoking behavior. CONCLUSION: Psychological stress and fatigue were moderately associated with smoking behavior among undergraduate students and the impact was different on different gender and smoking behaviors that suggesting that some specific psychological measures should be taken so as to control different smoking behaviors among undergraduate students.

[Analysis on factors influencing the smoking behaviors among male secondary school students under the structural equation model].

OBJECTIVE: To analyze the direct and indirect outcomes of influencing factors on smoking behaviors among adolescents. METHODS: Self-administered questionnaires were used to collect smoking-related information from 2021 respondents. Measurement models were built by confirmatory factor analysis and parameters were estimated by ERLS method. The final structural equation model was determined by comprehensive evaluation and necessary modification. RESULTS: Three latent variables were extracted from 10 manifest variables of environment, while only one latent variable was identified from 9 manifest variables of attitudes. The goodness of fit for the structural equation model was satisfactory that all indices had met corresponding requirements. The final model could explain 38.8% of the variance of smoking behaviors. Four factors (smoking environment, smoking restriction from parents and teachers, determination of cigarette refusal and attitudes toward smoking) were directly affecting the smoking behaviors, while another three factors (grade, health knowledge and school environment) had indirect impacts. According to the percentages of their contribution, the risk factors were ranked as follows: smoking environment (45.76%), attitudes toward smoking (19.88%) and grade at school (0.44%). Similarly, the top protective factor were: determination of cigarette refusal (16.61%), followed by smoking restriction from parents and teachers (10.51%), health knowledge (3.89%) and school environment (2.92%). CONCLUSIONS: Heath knowledge had minor effect on smoking in adolescents but could indirectly affect their smoking behaviors through changing their belief. Grade at school had a doubled influence on smoking, but mainly served as a risk factor. Tobacco control measures for adolescents should not only be limited to health education but environment factors as well.

[Study on the related factors of smoking behavior transition at different stages among undergraduate students].

OBJECTIVE: To explore the influencing factors of smoking behavior transition at different stage of smoking among undergraduate students. METHODS: 8138 undergraduate students from grade 1 to 3 were selected using cluster sampling method from an university in Guangzhou with their smoking behaviors and relevant factors studied through a self-administered questionnaire. Beginners, un-regular smokers and regular smokers were defined as "case group", while non-smokers, beginners and un-regular smokers were defined as "control group" accordingly. Three multivariable logistic regressions were separately conducted to explore the influencing factors of behavioral transition at different stage of smoking. RESULTS: Of the 8138 students investigated, the prevalence rates of beginners, un-regular smokers and regular smokers were 19.6%, 2.0% and 1.1%, respectively; while all of the above said three rates increased with grades of the students. Some students might still try to smoke or become regular smoker in the university. In male undergraduate students, determinants for the transition from non-smokers to s mokers were: source of students, father' s educational level, smoking-related knowledge and belief, and smoking habit of the roommates. Risks that influencing the transition from beginners to un-regular smokers were: being non-medical students,smoking-related belief, roommates and classmates who were smokers and transition from un-regular smokers to regular smokers would include father' s educational level and average income of family. In female undergraduate students,influencing factors from non-smokers to beginners were mother's educational level, smoking-related belief, and roommates smokers, while father's educational level, roommates and classmates' smoking habits were significant associated with beginners' change to un-regular smokers. CONCLUSION: The influencing factors related to the transition of different stage on smoking would be different in undergraduate students,and some specific measures should be taken based on the different stage of smoking.