Modulation of Gut Microbiota in Pathological States

The human microbiota is an aggregate of microorganisms residing in the human body, mostly in the gastrointestinal tract (GIT). Our gut microbiota evolves with us and plays a pivotal role in human health and disease. In recent years, the microbiota has gained increasing attention due to its impact on host metabolism, physiology, and immune system development, but also because the perturbation of the microbiota may result in a number of diseases. The gut microbiota may be linked to malignancies such as gastric cancer and colorectal cancer. It may also be linked to disorders such as nonalcoholic fatty liver disease (NAFLD); obesity and diabetes, which are characterized as “lifestyle diseases” of the industrialized world; coronary heart disease; and neurological disorders. Although the revolution in molecular technologies has provided us with the necessary tools to study the gut microbiota more accurately, we need to elucidate the relationships between the gut microbiota and several human pathologies more precisely, as understanding the impact that the microbiota plays in various diseases is fundamental for the development of novel therapeutic strategies. Therefore, the aim of this review is to provide the reader with an updated overview of the importance of the gut microbiota for human health and the potential to manipulate gut microbial composition for purposes such as the treatment of antibiotic-resistant Clostridium difficile (C. difficile) infections. The concept of altering the gut community by microbial intervention in an effort to improve health is currently in its infancy. However, the therapeutic implications appear to be very great. Thus, the removal of harmful organisms and the enrichment of beneficial microbes may protect our health, and such efforts will pave the way for the development of more rational treatment options in the future

Association between stroke and physical activities in Shanghai Community Elderly Cohort

Objective·To compare the physical activities of stroke population and non-stroke population based on the baseline survey of the elderly population cohort in Shanghai communities, and explore the participation in different types of physical activities of stroke population.Methods·The subjects were screened from Shanghai Community Elderly Cohort constructed from February to August, 2019 according to the admission criteria. The subjects were divided into non-stroke group and stroke group according to whether they had reported a history of stroke by themselves, and the two groups were matched 2 to 1 by controlling age and sex with propensity score matching. The baseline characteristics of the two groups were collected, and the physical activities related to sports, transportation and housework in the last week were investigated with the International Physical Activity Questionnaire (IPAQ). Pittsburgh Sleep Quality Index (PSQI) was used to evaluate the sleep quality of the subjects. Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) were used to evaluate anxiety and depression of the subjects, respectively. The above characteristics were compared between the stroke group and non-stroke group, and the participation of different types of physical activities were compared between the two groups by multivariate Logistic regression model.Results·Among the 17 948 people included, there were 993 (5.5%) in the stroke group and 16 955 (94.5%) in the non-stroke group. After propensity score matching, there were 1 984 people (66.7%) in the non-stroke group and 992 people (33.3%) in the stroke group. There were significant differences in education level, pre-retirement occupation, waist circumference, body mass index, sleep status, anxiety symptoms, depression symptoms and disease history between the two groups (all P<0.05). In terms of physical activities, the female stroke group had shorter daily moderate exercises time, fewer riding and walking days in one week, and shorter daily riding time, compared with the non-stroke people, with statistical significance (all P<0.05). Compared with the non-stroke people, the weekly housework days and daily housework time in the male and female stroke groups were lower than those in the non-stroke group, while the daily sedentary time was longer, with statistical significance (all P=0.000). In terms of physical activity level, the proportions of men and women in the stroke group who reached medium or high level were lower than those in the non-stroke group, and the differences were statistically significant (all P=0.000). After adjusting for gender, age, occupation, anxiety symptoms, history of hyperlipidemia, history of atrial fibrillation, history of chronic gastritis and history of hip fracture by multivariate Logistic regression model, the level of vigorous exercise participation in the stroke group was lower, the proportions of no housework in the last week and sedentary time greater than 180 min per day were higher, and the proportion at medium and high activity levels was lower (all P<0.05).Conclusion·The frequency and duration of housework participation and the physical activity level of elderly people with a history of stroke in Shanghai communities are at a lower level than those without stroke, and they also have a longer sedentary time

A smart chicken farming platform for chicken behavior identification and feed residual estimation

It is very potential to develop digital villages for promoting smart agriculture. As one of the important research fields of smart agriculture, smart chicken farms encounter management problems such as difficulties in quickly and accurately warning of sick and dead chickens and estimating feed residuals. Therefore, this study not only respectively proposed CKTrack and FRCM to detect sick and dead chickens and estimate feed residuals, but also developed a smart chicken farming platform for automagical management. Our main results include (1) the proposed CKTrack method can effectively identify sick and dead chickens under the condition of limited data volume and computing capacity; (2) the proposed FRCM method can accurately estimate the feed residuals; and (3) the smart chicken farming platform developed can provide farmers with functions such as early warning of sick and dead chickens, visualization of the chicken quantity inventory, and feed residual estimation.<br/

An efficient double-fluorescence approach for generating fiber-2-edited recombinant serotype 4 fowl adenovirus expressing foreign gene

Recently, the infection of serotype 4 fowl adenovirus (FAdV-4) in chicken flocks has become endemic in China, which greatly threatens the sustainable development of poultry industry. The development of recombinant FAdV-4 expressing foreign genes is an efficient strategy for controlling both FAdV-4 and other important poultry pathogens. Previous reverse genetic technique for generating the recombinant fowl adenovirus is generally inefficient. In this study, a recombinant FAdV-4 expressing enhanced green fluorescence protein (EGFP), FA4-EGFP, was used as a template virus and directly edited fiber-2 gene to develop an efficient double-fluorescence approach to generate recombinant FAdV-4 through CRISPR/Cas9 and Cre-Loxp system. Moreover, using this strategy, a recombinant virus FAdV4-HA(H9) stably expressing the HA gene of H9N2 influenza virus was generated. Chicken infection study revealed that the recombinant virus FAdV4-HA(H9) was attenuated, and could induce haemagglutination inhibition (HI) titer against H9N2 influenza virus at early time points and inhibit the viral replication in oropharynx. All these demonstrate that the novel strategy for constructing recombinant FAdV-4 expressing foreign genes developed here paves the way for rapidly developing attenuated FAdV-4-based recombinant vaccines for fighting the diseases caused by both FAdV-4 and other pathogens