In vitro antifungal activity of lactic acid bacteria low molecular peptides against spoilage fungi of bakery products

Bio-preservation, a promising preservation method that involves the use of “friendly” microorganisms such as lactic acid bacteria, has recently become a topic of considerable interest. In the present study, 16 lactic acid bacteria isolates were evaluated for antifungal activity against six fungi commonly associated with bread spoilage. The antifungal compounds were heat stable at 121 °C, and only four isolates, DU15, IT10, TE10, and IS10, showed partial loss of activity when supernatants were treated with proteolytic enzymes. The four isolates showed high inhibition activity at pH 3 and were identified using 16S rDNA sequencing as belonging to Leuconostoc mesenteroides DU15, Lactobacillus plantarum TE10, Lactobacillus plantarum IT10, and Lactobacillus plantarum IS10. The minimum germination inhibitions were 30 mg, 50 mg, 40 mg, and 50 mg for TE10, IT10, DU15, and IS10 respectively. The optimum conditions for the strains to produce antifungal compounds were 37 °C for 48 h for IT10, IS10, and TE10, and 30 °C for 24 h for DU15. Antifungal activity was increased threefold when supernatants were filtered using 10 KDa membranes. These findings demonstrate the potential of using lactic acid bacteria antifungal peptides as natural preservatives in bakery products to control the growth of spoilage fungi.     

Use of randomly amplified polymorphic DNA analysis to differentiate isolates of Vibrio parahaemolyticus from cockles (Anadara granosa)

A total of 35 Kanagawa-negative strains of Vibrio parahaemolyticus isolated from cockles (Anadara granosa) were investigated by randomly amplified polymorphic DNA fingerprinting with three primers and their plasmid profiles. Eighteen strains carried small plasmid(s) of 2.4 to 7.3kb that enabled the V. parahaemolyticus to be grouped into eight plasmid patterns. The three primers generated polymorphisms in all 35 strains of V. parahaemolyticus tested, producing bands ranging from 0.25 to 3.9kb. The RAPD profiles revealed a high level of DNA sequence diversity within the Vibrio parahaemolyticus strains tested, and that cockles in the study area are populated by genetically polymorphic strains of V. parahaemolyticus.     

Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis.     

A Stochastic Simulation Framework for the Prediction of Strategic Noise Mapping and Occupational Noise Exposure Using the Random Walk Approach

Strategic noise mapping provides important information for noise impact assessment and noise abatement. However, producing reliable strategic noise mapping in a dynamic, complex working environment is difficult. This study proposes the implementation of the random walk approach as a new stochastic technique to simulate noise mapping and to predict the noise exposure level in a workplace. A stochastic simulation framework and software, namely RW-eNMS, were developed to facilitate the random walk approach in noise mapping prediction. This framework considers the randomness and complexity of machinery operation and noise emission levels. Also, it assesses the impact of noise on the workers and the surrounding environment. For data validation, three case studies were conducted to check the accuracy of the prediction data and to determine the efficiency and effectiveness of this approach. The results showed high accuracy of prediction results together with a majority of absolute differences of less than 2 dBA; also, the predicted noise doses were mostly in the range of measurement. Therefore, the random walk approach was effective in dealing with environmental noises. It could predict strategic noise mapping to facilitate noise monitoring and noise control in the workplaces.     

Windows Instant Messaging App Forensics: Facebook and Skype as Case Studies

Instant messaging (IM) has changed the way people communicate with each other. However, the interactive and instant nature of these applications (apps) made them an attractive choice for malicious cyber activities such as phishing. The forensic examination of IM apps for modern Windows 8.1 (or later) has been largely unexplored, as the platform is relatively new. In this paper, we seek to determine the data remnants from the use of two popular Windows Store application software for instant messaging, namely Facebook and Skype on a Windows 8.1 client machine. This research contributes to an in-depth understanding of the types of terrestrial artefacts that are likely to remain after the use of instant messaging services and application software on a contemporary Windows operating system. Potential artefacts detected during the research include data relating to the installation or uninstallation of the instant messaging application software, log-in and log-off information, contact lists, conversations, and transferred files.     

An improved hybrid of SVM and SCAD for pathway analysis

Pathway analysis has lead to a new era in genomic research by providing further biological process information compared to traditional single gene analysis. Beside the advantage, pathway analysis provides some challenges to the researchers, one of which is the quality of pathway data itself. The pathway data usually defined from biological context free, when it comes to a specific biological context (e.g. lung cancer disease), typically only several genes within pathways are responsible for the corresponding cellular process. It also can be that some pathways may be included with uninformative genes or perhaps informative genes were excluded. Moreover, many algorithms in pathway analysis neglect these limitations by treating all the genes within pathways as significant. In previous study, a hybrid of support vector machines and smoothly clipped absolute deviation with groups-specific tuning parameters (gSVM-SCAD) was proposed in order to identify and select the informative genes before the pathway evaluation process. However, gSVM-SCAD had showed a limitation in terms of the performance of classification accuracy. In order to deal with this limitation, we made an enhancement to the tuning parameter method for gSVM-SCAD by applying the B-Type generalized approximate cross validation (BGACV). Experimental analyses using one simulated data and two gene expression data have shown that the proposed method obtains significant results in identifying biologically significant genes and pathways, and in classification accuracy.     

Raw starch-degrading enzyme from newly isolated strains of endophytic fungi

Four newly isolated strains of endophytic fungi namely Gibberella pulicaris, Acremonium sp., `Synnematous' sp. and Nodilusporium sp. were compared for their degradative activity on raw and gelatinized starches, substrate specificity and optimum pH. Results showed that the raw starch-degrading enzyme from Acremonium sp. had a broad activity towards both small and large granule size of raw starches while the enzyme from other strains showed high activity toward starches of smaller granule size. Analysis of the end product by TLC showed that enzyme from Gibberella pulicaris, Acremonium and Nodilusporium sp. hydrolysed raw sago starch to produce solely glucose but the enzyme of `Synnematous' sp. produced glucose and maltose. This revised version was published online in July 2006 with corrections to the Cover Date.