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1.
Journal of Southern Medical University ; (12): 251-260, 2018.
Article in Chinese | WPRIM | ID: wpr-690479

ABSTRACT

<p><b>OBJECTIVE</b>To investigate the effects of prebiotics supplementation for 9 days on gut microbiota structure and function and establish a machine learning model based on the initial gut microbiota data for predicting the variation of Bifidobacterium after prebiotic intake.</p><p><b>METHODS</b>With a randomized double-blind self-controlled design, 35 healthy volunteers were asked to consume fructo-oligosaccharides (FOS) or galacto-oligosaccharides (GOS) for 9 days (16 g per day). 16S rRNA gene high-throughput sequencing was performed to investigate the changes of gut microbiota after prebiotics intake. PICRUSt was used to infer the differences between the functional modules of the bacterial communities. Random forest model based on the initial gut microbiota data was used to identify the changes in Bifidobacterium after 5 days of prebiotic intake and then to build a continuous index to predict the changes of Bifidobacterium. The data of fecal samples collected after 9 days of GOS intervention were used to validate the model.</p><p><b>RESULTS</b>Fecal samples analysis with QIIME revealed that FOS intervention for 5 days reduced the intestinal flora alpha diversity, which rebounded on day 9; in GOS group, gut microbiota alpha diversity decreased progressively during the intervention. Neither FOS nor GOS supplement caused significant changes in β diversity of gut microbiota. The area under the curve (AUC) of the prediction model was 89.6%. The continuous index could successfully predict the changes in Bifidobacterium (R=0.45, P=0.01), and the prediction accuracy was verified by the validation model (R=0.62, P=0.01).</p><p><b>CONCLUSION</b>Short-term prebiotics intervention can significantly decrease α-diversity of the intestinal flora. The machine learning model based on initial gut microbiota data can accurately predict the changes in Bifidobacterium, which sheds light on personalized nutrition intervention and precise modulation of the intestinal flora.</p>

2.
Journal of Southern Medical University ; (12): 1333-1335, 2010.
Article in Chinese | WPRIM | ID: wpr-336186

ABSTRACT

<p><b>OBJECTIVE</b>To analyze the characteristics and etiology of hand, foot and mouth disease (HFMD) in a sentinel hospital of Guangzhou.</p><p><b>METHODS</b>The epidemiological data and clinical specimens were collected from May to December, 2008 for virological investigations (viral isolation, RT-PCR and molecular identification) and phylogenetic analysis.</p><p><b>RESULTS</b>A total of 309 clinical cases were reported, and the incidence was the highest in 2-4-year-old children, among whom only 15 developed complications, with human enterovirus 71 (HEV71) as the main pathogen (64.7%). Phylogenetic analysis indicated that ten Guangzhou EV71 isolates belonged to Cluster C4a.</p><p><b>CONCLUSION</b>HFMD is an important infectious disease in children resulting from infections by HEV71 as the main pathogen in 2008, and the Guangzhou C4a strains co-evolved with the isolates from other provinces in China and the neighboring countries.</p>


Subject(s)
Child, Preschool , Female , Humans , Male , China , Epidemiology , Enterovirus A, Human , Hand, Foot and Mouth Disease , Epidemiology , Virology , Incidence , Reverse Transcriptase Polymerase Chain Reaction
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