Explore the vast range of titles available.

Background Quorum sensing is a mechanism of cell to cell communication that requires the production and detection of signaling molecules called autoinducers. Although mesophilic bacteria is known to utilize this for synchronization of physiological processes such as bioluminescence, virulence, biofilm formation, motility and cell competency through signaling molecules (acyl homoserine lactones, AI-1; oligopeptides, peptide based system and furanosyl borate diester, AI-2), the phenomenon of quorum sensing in thermophiles is largely unknown. Results In this study, proteomes of 106 thermophilic eubacteria and 21 thermophilic archaea have been investigated for the above three major quorum sensing systems to find the existence of quorum sensing in these thermophiles as there are evidences for the formation of biofilms in hot environments. Our investigation demonstrated that AI-1 system is absent in thermophiles. Further, complete peptide based two component systems for quorum sensing was also not found in any thermophile however the traces for the presence of response regulators for peptide based system were found in some of them. BLASTp search using LuxS (AI-2 synthase) protein sequence of Escherichia coli str. K-12 substr. MG1655 and autoinducer-2 receptors (LuxP of Vibrio harveyi , LsrB of E. coli str. K-12 substr. MG1655 and RbsB of Aggregatibacter actinomycetemcomitans ) as queries revealed that 17 thermophilic bacteria from phyla Deinococcus- Thermus and Firmicutes possess complete AI-2 system (LuxS and LsrB and/or RbsB). Out of 106 thermophilic eubacteria 18 from phyla Deinococcus- Thermus , Proteobacteria and Firmicutes have only LuxS that might function as AI-2 synthesizing protein whereas, 16 are having only LsrB and/or RbsB which may function as AI-2 receptor in biofilms. Conclusions We anticipate that thermophilic bacteria may use elements of LsrB and RbsB operon for AI-2 signal transduction and they may use quorum sensing for purposes like biofilm formation. Nevertheless, thermophiles in which no known quorum sensing system was found may use some unknown mechanisms as the mode of communication. Further information regarding quorum sensing will be explored to develop strategies to disrupt the biofilms of thermophiles.

This paper addresses the limitations of existing deep learning techniques in retinal disease diagnosis from fundus images, specifically focusing on inadequate feature representation, localization challenges, and the lack of interpretability. Current methods also struggle with class imbalance and the need for simultaneous multi-task learning. To overcome these issues, we propose a novel interpretable deep learning framework for the simultaneous segmentation of multiple retinal lesions and multi-categorical disease classification with grading. Our framework incorporates a modified Convolutional Neural Network (CNN) with separable convolution layers for efficient parameter utilization and an attention mechanism to focus on critical image regions, enabling accurate lesion mapping. To tackle class imbalance, the framework utilizes the Synthetic Minority Over-Sampling Technique (SMOTE). Furthermore, Explainable AI (XAI) techniques, including Grad-Cam, are integrated to enhance the model's interpretability and provide insights into its decision-making process. The effectiveness of the proposed framework is evaluated on several publicly available datasets, including ODIR, RFMiD, and IDRiD. The framework aims to provide a comprehensive, balanced, and interpretable solution for real-time fundus disease diagnosis in healthcare. The proposed architecture outperforms existing models in accuracy, AUC, mAUPR, and mIoU on retinal fundus image datasets. Heatmaps and segmentation masks confirm their effectiveness in identifying disease regions and segmenting lesions.

Biofilms enable bacterial cells to adhere and thrive on surfaces, with associated changes in growth and gene expression aiding their survival in challenging environments. While previous research has explored E. coli biofilm formation, there has been limited exploration of its application in industrial production. Prior studies have shown that immobilized fermentation can enhance L-threonine production. This study aims to augment biofilm formation and subsequently increase L-threonine production in E. coli by regulating the quorum sensing system, focusing on key AI-2-related genes, including luxS, lsrB, lsrK, and lsrR. In +pluxS and +plsrB strains, AI-2 levels were significantly altered, resulting in enhanced biofilm formation, increased curli expression, shorter free-cell fermentation periods, and improved production efficiency through immobilized continuous fermentation. In a single batch of free-cell fermentation with E. coli W1688, L-threonine production was 10.16 g/L. However, +pluxS and +plsrB strains achieved L-threonine yields of 15.27 g/L and 13.38 g/L, respectively, after seven fermentation batches. Additionally, the fermentation period was reduced from 36 h to 28 h and 30 h, respectively.

The luxS gene is required for autoinducer-2 (AI-2) synthesis in many bacterial species. AI-2 is taken up by a specific receptor to regulate multiple bacterial activities. However, the lack of methods to identify AI-2 receptors has impeded investigations into the roles of AI-2. Here, a luxS mutant of Escherichia coli strain BL21 (DE3) was constructed (named BL21∆luxS), and the recombinant LsrB protein of Salmonella enterica was expressed in BL21∆luxS and BL21 cells, which were named LsrB (BL21∆luxS) and LsrB (BL21), respectively. The results of the activity of recombinant LsrB binding showed that LsrB (BL21) bound to endogenous AI-2 (produced from BL21 strain), while LsrB (BL21∆luxS) did not (as BL21∆luxS cannot produce AI-2). However, the results of recombinant LsrB binding showed that LsrB (BL21∆luxS) can bind exogenous AI-2, which was released from LsrB (BL21∆luxS) at 55 °C for 10 min, while LsrB (BL21) could not bind exogenous AI-2 (due to binding of endogenous AI-2 before). Furthermore, analysis of the thermal stability of AI-2 showed that that AI-2 activity was relatively high at incubation temperatures below 65 °C. These findings will be beneficial for screening of new AI-2 receptors in different bacterial species.