Integrated Analyses of the Gut Microbiota, Intestinal Permeability, and Serum Metabolome Phenotype in Rats with Alcohol Withdrawal Syndrome.

The etiology of alcohol dependence is not completely understood. Increasing evidence reveals that gut microbiota dysbiosis is associated with certain psychiatric disorders, including alcoholism, through the "microbiota-gut-brain" axis. The aims of this study were to evaluate the effect of alcohol abuse on the gut microbiota, intestinal permeability and serum metabolic profile and to determine whether alcohol-induced alterations in gut microbiota are correlated with gut permeability and serum metabolic phenotype changes. 16S rRNA gene high-throughput sequencing and nontarget metabolomics techniques were applied in an alcohol-dependent rat model in the present study. The results showed that alcohol intake altered the composition and structure of the colonic microbiota, especially the relative abundances of commensal microbes in the families Lachnospiraceae and Prevotellaceae, which were significantly decreased. Alcohol-dependent rats developed gut leakiness and a serum metabolic phenotype disorder. The valine, leucine and isoleucine biosynthesis pathways and arginine and proline metabolism pathways were obviously influenced by alcohol intake. Moreover, alcohol consumption disturbed the brain's neurotransmitter homeostasis. Regression analysis showed that alcohol-induced colonic microbiota dysbiosis was strongly associated with increased intestinal permeability and serum metabolic phenotype and neurotransmitter disorders. These results revealed that gut microbiota dysbiosis and serum metabolite alteration might be a cofactor for developing of alcohol dependence. IMPORTANCE Gut microbiota dysbiosis is associated with certain psychiatric disorders through the "microbiota-gut-brain" axis. Here, we revealed that alcohol consumption induced colonic microbiota dysbiosis, increased intestinal permeability, and altered the serum metabolic phenotype in rats, and there was a strong correlation between gut microbiota dysbiosis and serum metabolite disorders. Thus, gut microbiota dysbiosis and serum metabolite alteration may be a cofactor for development of alcohol dependence.

Measurement of Water Velocity in Gas-Water Two-Phase Flow with the Combination of Electromagnetic Flowmeter and Conductance Sensor.

A method to measure the superficial velocity of the water phase in gas-water flow using an electromagnetic flowmeter (EMF) and rotating electric field conductance sensors (REFCSs) is introduced in this paper. An electromagnetic flowmeter instrument factor model is built and the correlation between electromagnetic flowmeter output and gas holdup in different flow patterns are explored through vertical upward gas-water flow dynamic experiments in a pipe with an inner diameter (ID) of 20 mm. Water superficial velocity is predicted based on pattern identification among bubble, churn, and slug flows. The experimental results show that water superficial velocity can be predicted fairly accurately for bubble, churn, and slug flows with a water cut higher than 60% (absolute average percentage deviation and absolute average deviation are 4.1057% and 0.0281 m/s, respectively). The output of the electromagnetic flowmeter is unstable and invalid in slug flows with a water cut below 60% due to the non-conducting gas slug is almost filling the pipe. Therefore, the electromagnetic flowmeter is not preferred to be used in such conditions.

Flow Measurement of Oil-Water Two-Phase Flow at Low Flow Rate Using the Plug-in Conductance Sensor Array.

In order to improve the flow measurement accuracy of oil-water two-phase flow at low flow rate, this paper presents a plug-in conductance sensor array (PICSA) for the measurement of water holdup and cross-correlation velocity. Due to the existence of the insert body in PICSA, the effect of slippage and the non-uniform distribution of dispersed phase on the measurement of oil-water two-phase flow at low flow rate can be reduced. The finite element method is used to analyze the electric field distribution characteristics of the plug-in conductance sensor, and the sensor geometry is optimized. The dynamic experiment of oil-water two-phase flow is carried out where water cut Kw and mixture velocity Um are set in the range of 10-98% and 0.0184-0.2580 m/s respectively. Experimental results show that the PICSA has good resolution in water holdup measurement for dispersed oil-in-water slug flow (D OS/W), transition flow (TF), dispersed oil-in-water bubble flow (D O/W) and very fine dispersed oil-in-water bubble flow (VFD O/W). In addition, the cross-correlation velocity of the oil-water two-phase flow is obtained by using the plug-in upstream and downstream conductance sensor arrays. The relationship between the cross-correlation velocity and mixture velocity is found to be sensitive to the change of flow pattern, but it has a good linear relationship under the same flow pattern. Based on the flow pattern identification, a good prediction result of the mixture velocity is obtained using kinematic wave theory. Finally, a high precision prediction of the individual phase volume fraction of oil-water two-phase flow at low flow rate is achieved by using the drift flux model.

High rate of multiresistant Klebsiella pneumoniae from human and animal origin.

PURPOSE: The main objectives of the present study were to detect the antimicrobial susceptibility and molecular characteristics of Klebsiella pneumoniae isolated from different hosts and to investigate the possibility of K. pneumoniae transmission between animals and humans. MATERIALS AND METHODS: A total of 189 nonduplicate K. pneumoniae isolates were collected from hospitals and four species of animals in Henan Province, China. The disk diffusion method was used for antimicrobial susceptibility testing, and resistance and virulence genes were screened by polymerase chain reaction (PCR). The molecular types were identified through multilocus sequence typing (MLST), and the hypermucoviscous (HMV) phenotype was identified using the "string-forming test". Pearson's parameters were used to determine the potential link among the molecular types and resistance and virulence genes of all K. pneumoniae strains. RESULTS: The resistance rates of the 189 K. pneumoniae isolates against 15 antibiotics ranged from 11.6% to 77.8%. The highest multidrug resistance rate was detected in the pig strains (93.6%), followed by the human strains (90.4%), chicken strains (88.9%), cow strains (52.0%) and sheep strains (50.0%). Forty-eight (25.4%) K. pneumoniae strains presented the HMV phenotype. entB, fimH-1 and mrkD were the most prevalent of the detected virulence genes, and magA and rmpA were the least prevalent genes in all the isolates. The MLST analysis revealed 24 unique sequence types (STs) among from the 189 isolates. ST11, ST235 and ST258 were common STs among the five isolates of host origin. ST258 exhibited significantly positive correlations with blaNDM, magA and the HMV phenotype and a negative correlation with qnrB. CONCLUSION: K. pneumoniae strains from different hosts, including humans and animals, have common molecular types and similar phenotypes, and these strains can potentially be transmitted between humans and animals.