Chen L.,Southern Medical University |
Chen L.,Dongguan SMU Metabolic Medicine Ltd Company |
Liu C.,Jinan University |
Kang T.,Dongguan SMU Metabolic Medicine Ltd Company |
And 6 more authors.
Tumor | Year: 2015
Objective: To compare the volatile organic compounds (VOCs) in exhaled breath between the patients with lung cancer and the healthy controls, and explore the specific biomarkers for diagnosis of lung cancer. Methods: The exhaled breath from 63 patients with pathologyconfirmed lung cancer (study group) and 72 healthy controls was collected. The VOCs in the exhaled breath were determined qualitatively and quantitatively by electric nose (Z-nose 4200 equipment). The VOCs between the two groups were compared by Mann-Whitney U test, and the stepwise logistic regression analysis was used to select statistically significant variables to establish a prediction model for diagnosis of lung cancer. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of this prediction model. Results: The concentrations of dimethylmethane, ethanol, methane, hexane, 2,2,4,6,6-pentamethylheptane, 2,5,5-trimethyl-2,6-heptadien- 4-one, 1-isopropyl-4-methylbicyclo[3.1.0]hexan-3-ol, dodecane and 1,2,6-trimethylnaphthalene in the exhaled breath of study group were significantly different from those of control group. A panel of biomarkers was selected to set up a decision tree as the prediction model: P = 1/[1+e(-9.006+0.101×X 1+0.01×X 2+0.02×X 3-|0.518×X 4)] (X 1, X 2, X 3 and X 4 for age, hexane, 2,2,4,6,6-pentamethylheptane and 1,2,6-trimethylnaphthalene, respectively). This prediction model could effectively separate lung cancer from control samples (an accuracy of 80.6% in study group and 83.9% in control group) with a sensitivity of 74.0% and a speci.city of 93.0%. Conclusion: The profile of VOCs in exhaled breath can reflect the metastatic status of cancer and specific medical conditions. The database concerning VOCs in the exhaled breath should be developed and may be helpful in diagnosis of lung cancer. Copyright © 2015 by TUMOR All rights reserved. Source
Le K.-A.,Southern Medical University |
Le K.-A.,Nestle |
Li Y.,Southern Medical University |
Li Y.,Dongguan SMU Metabolic Medicine Ltd Company |
And 18 more authors.
Frontiers in Physiology | Year: 2013
Background: The connection between gut microbiota and metabolism and its role in the pathogenesis of diabetes are increasingly recognized. The objective of this study was to quantitatively measure Bifidobacterium and Lactobacillus species, members of commensal bacteria found in human gut, in type 2 diabetic patients (T2D) patients from Southern China. Methods: Fifty patients with T2D and thirty control individuals of similar body mass index (BMI) were recruited from Southern China. T2D and control subjects were confirmed with both oral glucose tolerance test (OGTT) and HbA1c measurements. Bifidobacterium and Lactobacillus species in feces were measured by real-time quantitative PCR. Data were analyzed with STATA 11.0 statistical software. Results: In comparison to control subjects T2D patients had significantly more total Lactobacillus (+18%), L. bugaricus (+13%), L. rhamnosum (+37%) and L. acidophilus (+48%) (P < 0.05). In contrast, T2D patients had less amounts of total Bifidobacteria (-7%) and B. adolescentis (-12%) (P < 0.05). Cluster analysis showed that gut microbiota pattern of T2D patients is characterized by greater numbers of L. rhamnosus and L. acidophillus, together with lesser numbers of B. adolescentis (P < 0.05). Conclusion: The gut microflora in T2D patients is characterized by greater numbers of Lactobacillus and lesser numbers of Bifidobacterium species. © 2013 Lê, Li, Xu, Yang, Liu, Zhao, Tang, Cai, Go, Pandol and Hui. Source