Green tea polyphenols ameliorate non-alcoholic fatty liver disease through upregulating AMPK activation in high fat fed Zucker fatty rats

© The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved. To investigate protective effects and molecular mechanisms of green tea polyphenols (GTP) on nonalcoholic fatty liver disease (NAFLD) in Zucker fatty (ZF) rats. METHODS Male ZF rats were fed a high-fat diet (HFD) for 2 wk then treated with GTP (200 mg/kg) or saline (5 mL/kg) for 8 wk, with Zucker lean rat as their control. At the end of experiment, serum and liver tissue were collected for measurement of metabolic parameters, alanine aminotransferase (ALT) and aspartate aminotransferase (AST), inflammatory cytokines and hepatic triglyceride and liver histology. Immunoblotting was used to detect phosphorylation of AMP-activated protein kinase (AMPK) acetyl-CoA carboxylase (ACC), and sterol regulatory element-binding protein 1c (SREBP1c). RESULTS Genetically obese ZF rats on a HFD presented with metabolic features of hepatic pathological changes comparable to human with NAFLD. GTP intervention decreased weight gain (10.1%, P = 0.052) and significantly lowered visceral fat (31.0%, P < 0.01). Compared with ZF-controls, GTP treatment significantly reduced fasting serum insulin, glucose and lipids levels. Reduction in serum ALT and AST levels (both P < 0.01) were observed in GTP-treated ZF rats. GTP treatment also attenuated the elevated TNFα and IL-6 in the circulation. The increased hepatic TG accumulation and cytoplasmic lipid droplet were attenuated by GTP treatment, associated with significantly increased expression of AMPK-Thr172 (P < 0.05) and phosphorylated ACC and SREBP1c (both P < 0.05), indicating diminished hepatic lipogenesis and triglycerides out flux from liver in GTP treated rats. CONCLUSION The protective effects of GTP against HFD-induced NAFLD in genetically obese ZF rats are positively correlated to reduction in hepatic lipogenesis through upregulating the AMPK pathway

Early and efficient detection of Mycobacterium tuberculosis in sputum by microscopic observation of broth cultures.

Early, efficient and inexpensive methods for the detection of pulmonary tuberculosis are urgently needed for effective patient management as well as to interrupt transmission. These methods to detect M. tuberculosis in a timely and affordable way are not yet widely available in resource-limited settings. In a developing-country setting, we prospectively evaluated two methods for culturing and detecting M. tuberculosis in sputum. Sputum samples were cultured in liquid assay (micro broth culture) in microplate wells and growth was detected by microscopic observation, or in Löwenstein-Jensen (LJ) solid media where growth was detected by visual inspection for colonies. Sputum samples were collected from 321 tuberculosis (TB) suspects attending Bugando Medical Centre, in Mwanza, Tanzania, and were cultured in parallel. Pulmonary tuberculosis cases were diagnosed using the American Thoracic Society diagnostic standards. There were a total of 200 (62.3%) pulmonary tuberculosis cases. Liquid assay with microscopic detection detected a significantly higher proportion of cases than LJ solid culture: 89.0% (95% confidence interval [CI], 84.7% to 93.3%) versus 77.0% (95% CI, 71.2% to 82.8%) (p = 0.0007). The median turn around time to diagnose tuberculosis was significantly shorter for micro broth culture than for the LJ solid culture, 9 days (interquartile range [IQR] 7-13), versus 21 days (IQR 14-28) (p<0.0001). The cost for micro broth culture (labor inclusive) in our study was US $4.56 per sample, versus US$11.35 per sample for the LJ solid culture. The liquid assay (micro broth culture) is an early, feasible, and inexpensive method for detection of pulmonary tuberculosis in resource limited settings

Building robust prediction models for defective sensor data using Artificial Neural Networks

Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges. The primary aim of such predictive systems is to use the high-dimensional data acquired from different sensors and predict the state-of-health of a particular component, e.g., brake pad. The classical approach involves selecting a smaller set of relevant sensor signals using feature selection and using them to train a machine learning algorithm. However, this fails to address two prominent problems: (1) sensors are susceptible to failure when exposed to extreme conditions over a long periods of time; (2) sensors are electrical devices that can be affected by noise or electrical interference. Using the failed and noisy sensor signals as inputs largely reduce the prediction accuracy. To tackle this problem, it is advantageous to use the information from all sensor signals, so that the failure of one sensor can be compensated by another. In this work, we propose an Artificial Neural Network (ANN) based framework to exploit the information from a large number of signals. Secondly, our framework introduces a data augmentation approach to perform accurate predictions in spite of noisy signals. The plausibility of our framework is validated on real life industrial application from Robert Bosch GmbH.Comment: 16 pages, 7 figures. Currently under review. This research has obtained funding from the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking, the framework programme for research and innovation Horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-

Honeybee Colony Vibrational Measurements to Highlight the Brood Cycle

Insect pollination is of great importance to crop production worldwide and honey bees are amongst its chief facilitators. Because of the decline of managed colonies, the use of sensor technology is growing in popularity and it is of interest to develop new methods which can more accurately and less invasively assess honey bee colony status. Our approach is to use accelerometers to measure vibrations in order to provide information on colony activity and development. The accelerometers provide amplitude and frequency information which is recorded every three minutes and analysed for night time only. Vibrational data were validated by comparison to visual inspection data, particularly the brood development. We show a strong correlation between vibrational amplitude data and the brood cycle in the vicinity of the sensor. We have further explored the minimum data that is required, when frequency information is also included, to accurately predict the current point in the brood cycle. Such a technique should enable beekeepers to reduce the frequency with which visual inspections are required, reducing the stress this places on the colony and saving the beekeeper time

Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

Allergic Rhinitis and its Associated Co-Morbidities at Bugando Medical Centre in Northwestern Tanzania; A Prospective Review of 190 Cases.

Allergic rhinitis is one of the commonest atopic diseases which contribute to significant morbidity world wide while its epidemiology in Tanzania remains sparse. There was paucity of information regarding allergic rhinitis in our setting; therefore it was important to conduct this study to describe our experience on allergic rhinitis, associated co-morbidities and treatment outcome in patients attending Bugando Medical Centre. This was descriptive cross-sectional study involving all patients with a clinical diagnosis of allergic rhinitis at Bugando Medical Centre over a three-month period between June 2011 and August 2011. Data was collected using a pre-tested coded questionnaire and analyzed using SPSS statistical computer software version 17.0. A total of 190 patients were studied giving the prevalence of allergic rhinitis 14.7%. The median age of the patients was 8.5 years. The male to female ratio was 1:1. Adenoid hypertrophy, tonsillitis, hypertrophy of inferior turbinate, nasal polyps, otitis media and sinusitis were the most common co-morbidities affecting 92.6% of cases and were the major reason for attending hospital services. Sleep disturbance was common in children with adenoids hypertrophy (χ2 = 28.691, P = 0.000). Allergic conjunctivitis was found in 51.9%. The most common identified triggers were dust, strong perfume odors and cold weather (P < 0.05). Strong perfume odors affect female than males (χ2 = 4.583, P = 0.032). In this study family history of allergic rhinitis was not a significant risk factor (P =0.423). The majority of patients (68.8%) were treated surgically for allergic rhinitis co morbidities. Post operative complication and mortality rates were 2.9% and 1.6% respectively. The overall median duration of hospital stay of in-patients was 3 days (2 - 28 days). Most patients (98.4%) had satisfactory results at discharge. The study shows that allergic rhinitis is common in our settings representing 14.7% of all otorhinolaryngology and commonly affecting children and adolescent. Sufferers seek medical services due to co-morbidities of which combination of surgical and medical treatment was needed. High index of suspicions in diagnosing allergic rhinitis and early treatment is recommended

Airflow Dynamics of Coughing in Healthy Human Volunteers by Shadowgraph Imaging: An Aid to Aerosol Infection Control

Cough airflow dynamics have been previously studied using a variety of experimental methods. In this study, real-time, non-invasive shadowgraph imaging was applied to obtain additional analyses of cough airflows produced by healthy volunteers. Twenty healthy volunteers (10 women, mean age 32.2±12.9 years; 10 men, mean age 25.3±2.5 years) were asked to cough freely, then into their sleeves (as per current US CDC recommendations) in this study to analyze cough airflow dynamics. For the 10 females (cases 1–10), their maximum detectable cough propagation distances ranged from 0.16–0.55 m, with maximum derived velocities of 2.2–5.0 m/s, and their maximum detectable 2-D projected areas ranged from 0.010–0.11 m2, with maximum derived expansion rates of 0.15–0.55 m2/s. For the 10 males (cases 11–20), their maximum detectable cough propagation distances ranged from 0.31–0.64 m, with maximum derived velocities of 3.2–14 m/s, and their maximum detectable 2-D projected areas ranged from 0.04–0.14 m2, with maximum derived expansion rates of 0.25–1.4 m2/s

Quantitative analysis of residual protein contamination of podiatry instruments reprocessed through local and central decontamination units

&lt;p&gt;Background: The cleaning stage of the instrument decontamination process has come under increased scrutiny due to the increasing complexity of surgical instruments and the adverse affects of residual protein contamination on surgical instruments. Instruments used in the podiatry field have a complex surface topography and are exposed to a wide range of biological contamination. Currently, podiatry instruments are reprocessed locally within surgeries while national strategies are favouring a move toward reprocessing in central facilities. The aim of this study was to determine the efficacy of local and central reprocessing on podiatry instruments by measuring residual protein contamination of instruments reprocessed by both methods. Methods&lt;/p&gt; &lt;p&gt;The residual protein of 189 instruments reprocessed centrally and 189 instruments reprocessed locally was determined using a fluorescent assay based on the reaction of proteins with o-phthaldialdehyde/sodium 2-mercaptoethanesulfonate.&lt;/p&gt; &lt;p&gt;Results: Residual protein was detected on 72% (n = 136) of instruments reprocessed centrally and 90% (n = 170) of instruments reprocessed locally. Significantly less protein (p &#60; 0.001) was recovered from instruments reprocessed centrally (median 20.62 μg, range 0 - 5705 μg) than local reprocessing (median 111.9 μg, range 0 - 6344 μg).&lt;/p&gt; &lt;p&gt;Conclusions: Overall, the results show the superiority of central reprocessing for complex podiatry instruments when protein contamination is considered, though no significant difference was found in residual protein between local decontamination unit and central decontamination unit processes for Blacks files. Further research is needed to undertake qualitative identification of protein contamination to identify any cross contamination risks and a standard for acceptable residual protein contamination applicable to different instruments and specialities should be considered as a matter of urgency.&lt;/p&gt