Antiviral Effects of Lactococcus lactis on Feline Calicivirus,A Human Norovirus Surrogate

Foodborne viruses, particularly human norovirus (NV) and hepatitis virus type A, are a cause of concern for public health making it necessary to explore novel and effective techniques for prevention of foodborne viral contamination, especially in minimally processed and ready-to-eat foods. This study aimed to determine the antiviral activity of a probiotic lactic acid bacterium (LAB) against feline calicivirus (FCV), a surrogate of human NV. Bacterial growth medium filtrate (BGMF) of Lactococcus lactis subsp. lactis LM0230 and its bacterial cell suspension (BCS) were evaluated separately for their antiviral activity against FCV grown in Crandell–Reese feline kidney (CRFK) cells. No significant antiviral effect was seen when CRFK cells were pre-treated with either BGMF (raw or pH 7-adjusted BGMF) or BCS. However, pre-treatment of FCV with BGMF and BCS resulted in a reduction in virus titers of 1.3 log₁₀ tissue culture infectious dose (TCID)₅₀ and 1.8 log₁₀ TCID₅₀, respectively. The highest reductions in FCV infectivity were obtained when CRFK cells were co-treated with FCV and pH 7-adjusted BGMF or with FCV and BCS (7.5 log₁₀ TCID₅₀ and 6.0 log₁₀ TCID₅₀, respectively). These preliminary results are encouraging and indicate the need for continued studies on the role of probiotics and LAB on inactivation of viruses in various types of foods.     

Biocosmetics: technological advances and future outlook

Environmental Science and Pollution Research - The paper provides an overview of biocosmetics, which has tremendous potential for growth and is attracting huge business opportunities. It emphasizes...     

Development of a method for bacteria and virus recovery from heating, ventilation, and air conditioning (HVAC) filters

The aim of the work presented here is to study the effectiveness of building air handling units (AHUs) in serving as high volume sampling devices for airborne bacteria and viruses. An HVAC test facility constructed according to ASHRAE Standard 52.2-1999 was used for the controlled loading of HVAC filter media with aerosolized bacteria and virus. Nonpathogenic Bacillus subtilis var. niger was chosen as a surrogate for Bacillus anthracis. Three animal viruses; transmissible gastroenteritis virus (TGEV), avian pneumovirus (APV), and fowlpox virus were chosen as surrogates for three human viruses; SARS coronavirus, respiratory syncytial virus, and smallpox virus; respectively. These bacteria and viruses were nebulized in separate tests and injected into the test duct of the test facility upstream of a MERV 14 filter. SKC Biosamplers upstream and downstream of the test filter served as reference samplers. The collection efficiency of the filter media was calculated to be 96.5 +/- 1.5% for B. subtilis, however no collection efficiency was measured for the viruses as no live virus was ever recovered from the downstream samplers. Filter samples were cut from the test filter and eluted by hand-shaking. An extraction efficiency of 105 +/- 19% was calculated for B. subtilis. The viruses were extracted at much lower efficiencies (0.7-20%). Our results indicate that the airborne concentration of spore-forming bacteria in building AHUs may be determined by analyzing the material collected on HVAC filter media, however culture-based analytical techniques are impractical for virus recovery. Molecular-based identification techniques such as PCR could be used.     

Applying Fuzzy logic and the point count system to select landfill sites

The treatment of solid waste is currently one of the major environmental problems facing municipalities. Thousands of tonnes of waste are generated each day, requiring a large area for disposal purposes. It is difficult to find suitable areas for the construction of such sanitary landfills as numerous criteria must be met, and landfill sites vary considerably in terms of their sophistication. The selection criteria for landfill sites should be as simple as possible, and with this in mind, we have evaluated a large number of random cases for the suitability of the site for landfill purposes using the recently advocated fuzzy approach. Using the fuzzy classification, we have attempted to develop a simple classification which uses only certain point values for available attributes. A normalized average of such attributes based on the proposed classifier is further evaluated using additionally generated random data sets. The results appear to be encouraging and indicate that the present classifier can be used as a substitute for the fuzzy-based ranking of landfill sites.     

A Classification System for Characterization of Physical and Non-Physical Work Factors

A comprehensive evaluation of work-related perfomance factors is a prerequisite to developing integrated and long-term solutions to workplace performance improvement. This paper describes a work-factor classification system that categorizes the entire domain of workplace factors impacting performance. A questionnaire-based instrument was developed to implement this classification system in industry. Fifty jobs were evaluated in 4 different service and manufacturing companies using the proposed questionnaire-based instrument. The reliability coefficients obtained from the analyzed jobs were considered good (.589 to .862). In general, the physical work factors resulted in higher reliability coefficients (.847 to .862) than non-physical work factors (.589 to .768). performance work-factor system classification     

Design of fuzzy synthetic evaluation model for air quality assessment

Little attention was paid to growing air quality concerns until about a decade earlier in India. Indian Government started continuous monitoring of the urban air quality in Taj corridor area to protect the heritage monuments like Agra Fort, Fatehpur Sikri, the bird sanctuary at Bharatpur National Park and also the human health associated with air pollution. The aim of this study was to address air quality assessment using fuzzy synthetic evaluation model. The model was designed for four air pollutants (sulphur dioxide, nitrogen dioxide, suspended particulate matters and respirable suspended particulate matter). In the present paper, an approach is demonstrated for the determination of fuzzy air quality index by aggregating the four pollutants. The model also considers the weights of individual pollutants during aggregation. The weights of individual pollutants were determined using analytical hierarchical process. The model was applied for air quality assessment in four monitoring stations situated in Taj Trapezium Zone.     

Comparative study on the effect of chemicals on Alternaria blight in Indian mustard--a multi-location study in India

High severity of Altemaria blight disease is a major constraint in production of rapeseed-mustard in India. The aim of this study was to investigate the suppressive potential of chemicals viz., zinc sulphate, borax, sulphur, potash and calcium sulphate, aqueous extracts viz., Eucalyptus globosus (50 g l-1) leaf extract and garlic (Allium sativum) bulb (20 g l-1) extract, cow urine and bio-agents Trichoderma harzianum, Pseudomonas fluorescence in comparison with the recommended chemical fungicide (mancozeb), against foliar disease Alternaria blight of Indian mustard [Brassica juncea (L.) Czern. and Coss] under five different geographical locations of India. Mancozeb recorded the lowest mean severity (leaf: 33.1%; pod: 26.3%) of Alternaria blight with efficacy of garlic bulb extract alone (leaf = 34.4%; pod = 27.3%) or in combination with cow urine (leaf = 34.2%; pod = 28.6%) being statistically at par with the recommended chemical fungicide. Chemicals also proved effective in reducing Alternaria blight severity on leaves and pods of Indian mustard (leaf = 36.3-37.9%; pod = 27.5-30.1%). The effective treatments besides providing significant reduction in disease severity also enabled increase in dry seed yield of the crop (mancozeb = 2052 kg ha-1; garlic = 2006 kg ha-1; control = 1561 kg ha-1).     

The Impact of Air Pollutants and Meteorological Variables on Visibility in Delhi

A study has been made to analyze the impact of air pollutants and meteorological variables on visibility in Delhi, for the years 2003–2006. The correlation matrix of daily visibility, meteorological variables, and air pollutants concentration during the period has been studied. The matrix reflects the negative values of the correlation coefficient of visibility with respirable suspended particulate matter, suspended particulate matter, relative humidity, and, positive values with dry bulb temperature, maximum temperature, minimum temperature, and sunshine hours. The annual average visibility has been estimated as approximately 2.77 km. Furthermore, it is found to be maximum in monsoon, followed by summer, post-monsoon, and winter seasons. It is also noticeable that the visibility is always higher in rainy days when compared with that in dry days. Similarly, the annual average visibility during the weekends is found to be higher than that in the weekdays. The daily visibility has been forecasted through two statistical techniques namely, multiple linear regression (MLR) and principal component regression (PCR). The results obtained from these two techniques have been evaluated by comparing with observed data. This proves satisfactory performance of both the techniques. In addition, it reflects that the PCR performs better than the MLR technique.     

Antibacterial activity of soil-bound antibiotics

There is some concern that antibiotic residues in land-applied manure may promote the emergence of antibiotic resistant bacteria in the environment. The goal of this study was to determine whether or not soil bound antibiotics are still active against bacteria. The procedure involved sorbing various amounts of tetracycline or tylosin on two different textured soils (Webster clay loam [fine-loamy, mixed, superactive, mesic Typic Endoaquolls] and Hubbard loamy sand [sandy, mixed, frigid Entic Hapludolls]), incubating these soils with three different bacterial cultures (an antibiotic resistant strain of Salmonella sp. [Salmonella(R)], an antibiotic sensitive strain of Salmonella sp. [Salmonella(S)], and Escherichia coli ATCC 25922), and then enumerating the number of colony forming units relative to the control. Incubation was done under both static and dynamic conditions. Soil-adsorbed antibiotics were found to retain their antimicrobial properties since both antibiotics inhibited the growth of all three bacterial species. Averaged over all other factors, soil adsorbed antimicrobial activity was higher for Hubbard loamy sand than Webster clay loam, most likely due to higher affinity (higher clay content) of the Webster soil for antibiotics. Similarly, there was a greater decline in bacterial growth with tetracycline than tylsoin, likely due to greater amounts of soil-adsorbed tetracycline and also due to lower minimum inhibitory concentration of most bacteria for tetracycline than tylosin. The antimicrobial effect of tetracycline was also greater under dynamic than static growth conditions, possibly because agitation under dynamic growth conditions helped increase tetracycline desorption and/or increase contact between soil adsorbed tetracycline and bacteria. We conclude that even though antibiotics are tightly adsorbed by clay particles, they are still biologically active and may influence the selection of antibiotic resistant bacteria in the terrestrial environment.     

Green supply chain management in the chemical industry: structural framework of drivers

ABSTRACT

The main purpose of Green Supply Chain Management (GSCM) is to improve the quality of supply chain management strategies and environmental performance. As per current statistics, the chemical industry is growing fast in Bangladesh. In order to compete for global competition, GSCM is essential in this sector. This paper proposes a systematic approach of structural framework whose aim is to enhance the probability of constructive implementation of GSCM in the field chemical industry in Bangladesh. Therefore, this framework evaluates the appropriate interrelationship along with the drivers of GSCM in the chemical industry. In total, eight drivers were finalized from an associated literature review with the help of survey and by taking expert opinions via the Delphi methodology. In addition to MICMAC analysis, the driving and the dependence powers for all the drivers were determined. Moreover, the structural frameworks for the drivers were developed by means of total interpretive structural modeling (TISM) technique. As a result, the findings indicate that the most significant driver was supplier pressure and willingness and the most important barrier was high cost. Finally, the main objective of this research is expected to help industrial managers to evaluate and understand the critical areas where they should emphasize to implement GSCM in the chemical industry.