Molds constitute a very important contaminating flora of dairy products. Contamination with undesirable molds has been a serious and frequently disturbing problem in the dairy industry that results in huge losses due to spoilage of cheese and other fermented foods incriminated by a variety of mycoflora such as Aspergillus, Penicillium, Fusarium, Rhizopus, and Mucor. The considerable drop in pH caused by the growth of lactic acid bacteria (LAB) in fermented milk makes such foods a breeding ground for the highly opportunistic fungi to proliferate and thrive, spoiling the products and effecting cost and its commensurate accessories. The major antimicrobial substances isolated from the LAB are found effective against bacteria only and their inhibition toward the growth of contaminating bacteria has been explored in detail. However, studies on the fungistatic properties of LAB are relatively rare. This article reviews the investigative studies on the antifungal aspects of different lactic acid bacteria and the prospects of this exceptional trait as a potential food biopreservative.

In the present study, an attempt was made to biochemically characterize the antimicrobial substance from the soil isolate designated as RLID 12.1 and explore its potential applications in biocontrol of drug-resistant pathogens. The antimicrobial potential of the wild-type isolate belonging to the genus Bacillus was determined by the cut-well agar assay. The production of antimicrobial compound was recorded maximum at late exponential growth phase. The ultrafiltered concentrate was insensitive to organic solvents, metal salts, surfactants, and proteolytic and nonproteolytic enzymes. The concentrate was highly heat stable and active over a wide range of pH values. Partial purification, zymogram analysis, and TLC were performed to determine the preliminary biochemical nature. The molecular weight of the antimicrobial peptide was determined to be less than 2.5 kDa in 15% SDS-PAGE and in zymogram analysis against Streptococcus pyogenes. The N-terminal amino acid sequence by Edman degradation was partially determined to be T-P-P-Q-S-X-L-X-X-G, which shows very insignificant identity to other antimicrobial peptides from bacteria. The minimum inhibitory concentrations of dialysed and partially purified ion exchange fractions were determined against some selected gram-positive and gram-negative bacteria and some pathogenic yeasts. The presence of three important antimicrobial peptide biosynthesis genes ituc, fend, and bmyb was determined by PCR.

A seven-parameter family of bivariate probability distributions is developed which allows for any gamma marginal distributions, any associated correlation (positive or negative), and a range of regression curves. The form of the family, which relies on the reproducibility property of the gamma distribution, is motivated by the search for tractable parameter estimation, general dependency structure, and straightforward computer sampling for simulation modeling. A modification with closed-form parameter estimation, but less general dependency structure, is also given. Finally, the use of these distributions in the form of first order autoregressive time series is discussed.

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A reduced system is a smaller system derived in the process of analyzing a larger system. In solving for steady state probabilities of a Markov chain, generally the solution can be found by first solving a reduced system of equations which is obtained by appropriately partitioning the transition probability (or rate) matrix. Following Lal (Lal, R. 1981. A unified study of algorithms for steady state probabilities in Makov chains. Ph.D. Dissertation, Department of Operations Research and Engineering Management, School of Engineering and Applied Sciences, Southern Methodist University, Dallas, TX 75275.), a Markov chain can be categorized as standard or nonstandard depending on the location of an invertible submatrix necessary for an efficient solution in a transition probability (or rate) matrix. In this paper, algorithms for the determination of steady state probabilities are developed by using (i) a backward recursion which is efficient for standard systems and (ii) a forward recursion which is efficient for nonstandard systems. It is also shown that the backward recursion can be used for finding the first passage time distribution and its mean and variance.reduced system, steady state probabilities, queueing theory