Gut microbes on the risk of advanced adenomas.

BACKGROUND: More than 90% of colorectal cancer (CRC) arises from advanced adenomas (AA) and gut microbes are closely associated with the initiation and progression of both AA and CRC. OBJECTIVE: To analyze the characteristic microbes in AA. METHODS: Fecal samples were collected from 92 AA and 184 negative control (NC). Illumina HiSeq X sequencing platform was used for high-throughput sequencing of microbial populations. The sequencing results were annotated and compared with NCBI RefSeq database to find the microbial characteristics of AA. R-vegan package was used to analyze α diversity and ß diversity. α diversity included box diagram, and ß diversity included Principal Component Analysis (PCA), principal co-ordinates analysis (PCoA), and non-metric multidimensional scaling (NMDS). The AA risk prediction models were constructed based on six kinds of machine learning algorithms. In addition, unsupervised clustering methods were used to classify bacteria and viruses. Finally, the characteristics of bacteria and viruses in different subtypes were analyzed. RESULTS: The abundance of Prevotella sp900557255, Alistipes putredinis, and Megamonas funiformis were higher in AA, while the abundance of Lilyvirus, Felixounavirus, and Drulisvirus were also higher in AA. The Catboost based model for predicting the risk of AA has the highest accuracy (bacteria test set: 87.27%; virus test set: 83.33%). In addition, 4 subtypes (B1V1, B1V2, B2V1, and B2V2) were distinguished based on the abundance of gut bacteria and enteroviruses (EVs). Escherichia coli D, Prevotella sp900557255, CAG-180 sp000432435, Phocaeicola plebeiuA, Teseptimavirus, Svunavirus, Felixounavirus, and Jiaodavirus are the characteristic bacteria and viruses of 4 subtypes. The results of Catboost model indicated that the accuracy of prediction improved after incorporating subtypes. The accuracy of discovery sets was 100%, 96.34%, 100%, and 98.46% in 4 subtypes, respectively. CONCLUSION: Prevotella sp900557255 and Felixounavirus have high value in early warning of AA. As promising non-invasive biomarkers, gut microbes can become potential diagnostic targets for AA, and the accuracy of predicting AA can be improved by typing.

Age and aging process alter the gut microbes.

BACKGROUND: Gut microbes and age are both factors that influence the development of disease. The community structure of gut microbes is affected by age. OBJECTIVE: To plot time-dependent gut microbe profiles in individuals over 45 years old and explore the correlation between age and gut microbes. METHODS: Fecal samples were collected from 510 healthy individuals over 45 years old. Shannon index, Simpson index, Ace index, etc. were used to analyze the diversity of gut microbes. The beta diversity analysis, including non-metric multidimensional scaling (NMDS), was used to analyze community distribution. Linear discriminant analysis (LDA) and random forest (RF) algorithm were used to analyze the differences of gut microbes. Trend analysis was used to plot the abundances of characteristic gut microbes in different ages. RESULTS: The individuals aged 45-49 had the highest richness of gut bacteria. Fifteen characteristic gut microbes, including Siphoviridae and Bifidobacterium breve, were screened by RF algorithm. The abundance of Ligiactobacillus and Microviridae were higher in individuals older than 65 years. Moreover, the abundance of Blautia_A massiliensis, Lubbockvirus and Enterocloster clostridioformis decreased with age and the abundance of Klebsiella variicola and Prevotella increased with age. The functional genes, such as human diseases and aging, were significantly different among different aged individuals. CONCLUSIONS: The individuals in different ages have characteristic gut microbes. The changes in community structure of gut microbes may be related to age-induced diseases.

Clinical efficacy of Guipi granule in elderly malnutrition osteoporosis and effcts on serum ion levels / 中国生化药物杂志

Objective To investigate the curative efficacy of Guipi granule in treatment of elderly patients osteoporosis with malnutrition and its effects on serum ion levels.Methods A total of 80 patients of osteoporosis with malnutrition in Huzhou Central Hospital from July 2013 to July 2016 in this study were selected and randomly divided into the observation group and the control group with 40 cases in each group.The control group was treated with routine treatment, while the observation group was treated with Guipi granule on the basis of the control group.After three months of treatment, the bone mineral density, leptin, blood calcium, blood phosphorus, alkaline phosphatase, score of TCM syndrome and the treatment effect were compared. Results After treatment, the bone mineral density and leptin in the observation group (0.78 ±0.09)g/cm2, (12.45 ±1.85)ng/mL were higher than the control group (0.69 ±0.07)g/cm2, (9.85 ±1.52 ng/mL)(P <0.05), the blood calcium, blood phosphorus, alkaline phosphatase in the observation group (2.56 ±0.08)mmol/L, (1.43 ±0.13)mmol/L, (33.41 ±9.31)U/L were better than the control group (2.27 ±0.06)mmol/L, (1.85 ±0.21)mmol/L, (39.12 ±10.21)U/L(P<0.05), the total score of TCM syndrome in the observation group (2.85 ±0.32) were lower than the control group (5.03 ±0.49) (P<0.05), the total effective rate of clinical efficacy in the observation group 95.00%(38/40) was higher than the control group 67.50%(27/40)(P<0.05).Conclusion Guipi granule is well for osteoporosis with malnutrition patients, which can effectively improve bone mineral density, maintain the blood calcium and blood phosphorus balance, reduce the level of alkaline phosphatase, relieve the clinical symptoms.