Study of chemical-based induced bacterial ghost applied in vaccine production

Introduction: Bacterial ghosts (BGs), known as the empty cell envelope of gram-negative bacteria lacking cytoplasmic content yet retaining all unaltered morphological and structural features of their living counterparts, are widely studied and used as the platform for the production of the vaccines as well as the transporting drug and gene delivery. However, the study related to the creation of BGs based on gene expression is still limited because of the difference in cell wall structure between microorganisms. Therefore, in the current study, for the aims to determine chemicals combination and minimum inhibition concentration (MIC) to optimize BGs production. Material and method: Salmonella choleraesuis strain was collected from NAVETCO company. The study used critical concentrations from chemical combination to convert salmonella cells to BGs. Chemicals combination and MIC, temperature, shaking speed were optimized using Plakett- Burman matrix and response surface methodology. Cell structure was determined by using a scanning electron microscope, experimental mice were vaccinated and challenged with virulence to determine immune responses of bacterial ghost.\ud Results: The appropriate chemicals for the production of BGs biomass were NaOH 3.125 mg/ml; SDS 1.15 mg/ml, H2O2 8.79 µl/ml, ethanol. The observation of morphology, BGs have remained the structure and shape, which were like the living microbial cells. Conclusions: The conditions of BGs production have been identified to produce large amounts of bacterial ghost biomass to further application in vaccine production and pharma

Eating Habits, Physical Activity, and Their Associated Factors among Vietnamese School Children

The purposes of this study were to examine eating habits and physical activity and determine association between eating habits and physical activity, and study factors, including age, gender, weight, years of study, mothers’ education and family income among Vietnamese school children. Sample included 227 school children currently studying in grade 3-7 in primary and secondary schools children in Ho Chi Minh city, Vietnam. Stratified random sampling was used to recruit the sample. Data were collected from February – April 2012. Research instruments contained the demographic information form, the eating habits and the physical activity questionnaires, which their internal consistency reliability of .80 and .82 respectively. Data were analyzed by using descriptive statistics, Pearson correlation, t-test and one-way ANOVA. Results revealed that mean total score of eating habits was 31.18 (S.D.=5.08), and of physical activity was 10.31 (S.D. = 2.82), which could be implied that the sample had high health eating habits while it had moderate healthy physical activity. There were significant correlations between eating habits and child age (r=-0.22, p=<.01), physical activity and child age (r=-0.19, p<.01), and physical activity and weight (r=-.15, p<.05). Significant differences of eating habits and physical activity were found between the children with different family incomes (5,000.000) (t=-4.05, p<.001 and t=2.87, p<.01). The results also showed significant differences of eating habits and physical activity over the differences of the child’s years of study (F=4.97, p<.01 and (F=2.67, p<.05). In addition, eating habits of the sample with different mother’s education was significantly difference (F=28.86, p<.001). These finding suggest that nurse should promote and encourage older and heavier school children as well as children with different family income, years of study and mother’s education to have better and more appropriate eating habits and physical activity

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method

Damage detection for a large-scale truss bridge using Tranmissibility and ANNAOA

In this paper, we propose an efficient approach to enhance the capacity of Artificial Neural Network (ANN) to deal with Structural Health Monitoring (SHM) problems.  Over the last decades, ANN has been extensively utilized for damage detection in structures. In order to identify damages, ANN frequently utilizes input information that is based on dynamic features such as mode shapes or natural frequencies. However, this type of data may not be able to detect minor damages if the structural defects are insignificant. To transcend these limitations, in this work, we propose utilizing transmissibility to create input data for the input layer of ANN. Moreover, to deal with local minimum problems of ANN, a combination between the Arithmetic Optimization Algorithm (AOA) and ANN is proposed. The global search capacity of AOA is employed to remedy the local minima of ANN. To evaluate the effectiveness of the proposed approach, a numerical model with different damage scenarios is considered. The suggested approach detects damage location precisely and with higher severity detection precision than the conventional ANN method

Burden of diarrheal diseases from biogas wastewater exposure among smallholder farmers in Ha Nam province, Vietnam

Livestock production has developed rapidly in Vietnam in recent years, particularly at the small-scale which account for 65% of the total livestock production. Biogas systems are commonly used to treat livestock waste, however, the health risks from biogas wastewater exposure at smallholder farms are not yet well understood. A quantitative microbial risk assessment approach was applied to estimate the burden of diarrheal diseases from biogas wastewater exposure among 451 smallholder farmers using biogas systems in Ha Nam province. A total of 150 biogas wastewater samples were collected and analysed for E. coli, Giardia, and Cryptosporidium. The study showed that farmers faced diarrheal disease risks due to exposure to biogas wastewater at different exposure scenarios. The calculated annual risk of diarrheal disease by E. coli ranked from 0.15 to 0.21; by Giardia ranked from 0.022 to 0.095; and by Cryptosporidium ranked from 0.006 to 0.015. The estimated diarrheal diseases burden from pathogens in all exposure scenarios largely exceeded the reference level of health outcome target of 10-6DALYs loss per person per year recommended by WHO. The results suggest the importance in reducing concentrations of pathogens in biogas wastewater before use in the fields as a means for mitigating public health impacts

Risk-based approach to food safety research: Application to pork value chains in Vietnam

Introduction: Food-borne disease is a major public health issue in Vietnam. The contamination of popular foods can occur all along the food value chains. It is important to understand how and where food safety issues arise in order to mitigate and prevent food-borne diseases. Risk-based approach is a tool for managing food safety, however in Vietnam it is rarely applied and the capacity for application is still lacking. This paper describes how food safety risk assessment research has been applied for the pork value chain in Vietnam. Methods: We have conducted a risk assessment research to assess health risks related to pork consumption in the context of pig smallholder value chains and pork traded in informal markets. We collected 216 samples from 72 pig farms (floor swab, drinking and waste water), 545 samples from 49 slaughterhouses (carcass swab, lymph node, rectal feces, floor swab and washing water) and 514 samples from 220 pork retailed shops at informal markets (pork cuts, ground pork and cutting board swab) in Hung Yen and Nghe An provinces in the north and central of Vietnam. These 1275 samples were analyzed to detect qualitatively and quantitatively for Salmonella and E. coli. Chemical hazards (antibiotic, growth promoters, and heavy metal residues) in 190 pork samples from informal markets were also analyzed. Pork consumption behavior and cross-contamination modalities during pork preparation were assessed. Findings and interpretations: Overall prevalence of Salmonella combined from all types of above mentioned samples at pig farms, slaughterhouses and pork shops were 35%, 30% and 37%, respectively. Salmonella contamination in the final product (pork at market) was 45% and an average concentration of 9 MPN/g was recorded. E. coli average loads along different points of the chain were 5.3±1.4 (farm floor swabs), 2.9±0.9 (carcass swabs), 3.1±1.0 (slaughterhouse floor swabs), and 3.3±1.1 (market shop cutting board swabs) logCFU/cm2 , whereas pork from market had 3.4±0.9 logCFU/g. Demonstrated high levels of Salmonella in the final product (pork at market) induces the potential health risks for the consumers. High values for E. coli indicates general poor hygiene along the chain. 50% and 16.7% pooled samples were positive with sulfamethazine and chloramphenicol, with average residue levels of 156 µg/kg and 0.54 µg/kg, respectively. A quantitative risk model is being developed and integrates information on contamination along the pork value chain to characterize the health risk caused by Salmonella. Appropriate hygiene practices and management are required to achieve better pork quality and reduce the risk for the consumers