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Healthy humans and animals commonly harbor lactic acid bacteria (LAB) on their mucosal surfaces, which are often associated with food fermentation. These microorganisms can produce amphiphilic compounds, known as microbial surface-active agents, that exhibit remarkable emulsifying activity. However, the exact functions of these microbial surfactants within the producer cells remain unclear. Consequently, there is a growing urgency to develop biosurfactant production from nonpathogenic microbes, particularly those derived from LAB. This approach aims to harness the benefits of biosurfactants while ensuring their safety and applicability. This review encompasses a comprehensive analysis of native and genetically modified LAB biosurfactants, shedding light on microbial interactions, cell signaling, pathogenicity, and biofilm development. It aims to provide valuable insights into the applications of these active substances in therapeutic use and food formulation as well as their potential biological and other benefits. By synthesizing the latest knowledge and advancements, this review contributes to the understanding and utilization of LAB biosurfactants in the food and nutritional areas. [ABSTRACT FROM AUTHOR]

Abstract Background microRNAs (miRNAs) regulate target gene expression by controlling their mRNAs post-transcriptionally. Increasing evidence demonstrates that miRNAs play important roles in various biological processes. However, the functions and precise regulatory mechanisms of most miRNAs remain elusive. Current research suggests that miRNA regulatory modules are complicated, including up-, down-, and mix-regulation for different physiological conditions. Previous computational approaches for discovering miRNA-mRNA interactions focus only on down-regulatory modules. In this work, we present a method to capture complex miRNA-mRNA interactions including all regulatory types between miRNAs and mRNAs. Results We present a method to capture complex miRNA-mRNA interactions using Bayesian network structure learning with splitting-averaging strategy. It is designed to explore all possible miRNA-mRNA interactions by integrating miRNA-targeting information, expression profiles of miRNAs and mRNAs, and sample categories. We also present an analysis of data sets for epithelial and mesenchymal transition (EMT). Our results show that the proposed method identified all possible types of miRNA-mRNA interactions from the data. Many interactions are of tremendous biological significance. Some discoveries have been validated by previous research, for example, the miR-200 family negatively regulates ZEB1 and ZEB2 for EMT. Some are consistent with the literature, such as LOX has wide interactions with the miR-200 family members for EMT. Furthermore, many novel interactions are statistically significant and worthy of validation in the near future. Conclusions This paper presents a new method to explore the complex miRNA-mRNA interactions for different physiological conditions using Bayesian network structure learning with splitting-averaging strategy. The method makes use of heterogeneous data including miRNA-targeting information, expression profiles of miRNAs and mRNAs, and sample categories. Results on EMT data sets show that the proposed method uncovers many known miRNA targets as well as new potentially promising miRNA-mRNA interactions. These interactions could not be achieved by the normal Bayesian network structure learning.

Several studies are conducted to demonstrate the application of the microRNA-200 (miR-200) family as the marker for cells expressing E-cadherin. The analysis proves that the miR-200 family is extremely helpful in determining the epithelial phenotype of cancer cells by targeting the repressors, ZEB1 and ZEB2.

Agriculture is the backbone of the economic system of an agrarian country like India. In addition to providing food and raw materials, it also provides employment opportunities to a large percentage of population. The present study discusses the various demographic factors of agriculture in three selected districts of Haryana-Kaithal, Bhiwani and Fatehabad. The various demographics studied in this paper will be of help to financial institutions to construct a decision base for institutional credit disbursement and generalization of the concept of entrepreneurship among the farming community in other regions. [ABSTRACT FROM AUTHOR]

The growth trajectory of the economic development of a country depends to a large extent upon the success of its foreign trade policy. Having a favorable or minimize the unfavorable trade balance is a daunting task for the Indian economy which at present is suffering from negative trade balance. However, this objective of a country's foreign trade policy can be achieved only by undertaking suitable efforts to accelerate the volume of exports while shrinking the unnecessary imports to the maximum possible extent. This study is of immense use for policy planners to get a trade snapshot of India for identifying the role of export and import growth in generating the favorable status of India's trade balance. The common financial theory of portfolio diversification for reducing risk also holds true in context of foreign trade portfolio and this study will prove extremely valuable for economists to examine whether or not the structure of India's foreign trade portfolio is diversified enough to minimize the associated risk. [ABSTRACT FROM AUTHOR]