Daily Archives: August 14, 2025

Authors: Labdhi Jain, Rajesh Dhakad Associate Professor

Abstract: In the current digital era, the volume of data produced every second is staggering, making it challenging for users to find relevant information. Recommendation systems utilize extensive data and data mining techniques to analyze large amounts of data and provide accurate, personalized sug- gestions. Recommendation systems are information filter- ing systems that provide particular suggestions for items that are most pertinent to a particular user or a group of users. The algorithms and methods used for recommender systems are Content-Based Filtering, Collaborative Filtering, and Hybrid Methods. Recommendation systems include diverse applications and domains such as books, e-commerce ser- vices, social network services, movies, and tourism services. Key evaluation metrics of different recommender systems are discussed to provide insights into the assessment of mod- els and the optimization of their performance. Globally, recommendation systems have become important. The pur- pose of this paper is to include and give knowledge of each method, from a traditional-based recommendation system to a deep learning-based recommendation system. By synthe- sizing current trends, challenges, and future research direc- tions, this paper offers a comprehensive understanding of the recommendation system for both researchers and industry professionals.

DOI: http://doi.org/

Published by: vikaspatanker

Authors: Dr. V.Vijayalakshmi, Dr. D. Sridevi, L. Mohan, N.Sundarakannan

Abstract: In Genomic analysis, a comprehensive theoretical study is the need of the hour. Genomic analysis is an elaborate network that comprises various, expendable data. Such data has to be organized leading to comprehensible, practical data which is used to extricate critical information. A feasible procedure called SILE (Search, Identification, Load and Exploitation), is applied to assimilated genomic data with appropriate alterations that is associated with a certain disease. The principal aim is to propose natural drugs for treatment to those patients diagnosed with the disease and this is achieved by substantiating genes that have mutated. In this research, triangular fuzzy numbers are incorporated by considering three symptoms for examining the genes.

Published by: vikaspatanker

Authors: Pankaj Kumar Yadav, Rashmi Dubey

Abstract: Biosurfactant-producing microbes have emerged as crucial agents in eco-friendly environmental remediation, particularly for cleaning up oil spills, heavy metal contaminants, and industrial pollutants. These naturally derived surface-active compounds, produced by bacteria such as Pseudomonas aeruginosa, Bacillus subtilis, and Rhodococcus erythropolis, exhibit high emulsifying activity, low toxicity, and exceptional biodegradability. The focus of this research is to evaluate how microbial biosurfactants contribute to environmental cleaning through mechanisms of emulsification, desorption, and biostimulation. Emphasis is placed on their structural diversity, metabolic pathways, and potential applications in oil spill mitigation, soil washing, and heavy metal recovery. Through a review of current studies, laboratory findings, and emerging field applications, this article investigates the comparative performance of biosurfactants against synthetic surfactants. It also explores genetic and process engineering strategies to enhance biosurfactant yields. The results point toward biosurfactant-driven bioremediation as a promising frontier for sustainable environmental management. The article concludes with future research directions, highlighting bioreactor scalability and regulatory considerations necessary for large-scale deployment. These insights underscore the transformative role of biosurfactant-producing microbes in redefining the future of green technology and environmental restoration.

DOI: http://doi.org/10.5281/zenodo.16871248

Published by: vikaspatanker

Authors: Vivek Kumar Ghosh, Kusum Singh

Abstract: Electronic waste (e-waste) bioremediation has emerged as a sustainable approach to manage the growing burden of discarded electronics. This study investigates microbial communities in e-waste bioreactors using metagenomic techniques to identify key species and functional pathways involved in metal recovery and detoxification. By deploying next-generation sequencing (NGS) and shotgun metagenomic approaches, we uncovered taxonomic diversity and biochemical functions encoded in the resident microbiota. Our results revealed a predominance of metal-resistant bacteria, including Pseudomonas, Cupriavidus, and Desulfovibrio species, which possess genes for metal reduction, transport, and biofilm formation. Functional annotation indicated the prevalence of resistance-nodulation-division (RND) transporters, metallothioneins, and oxidoreductases crucial for heavy metal sequestration. This study underscores the utility of metagenomics in unraveling complex microbial interactions and their adaptive strategies in hostile e-waste environments. Insights from this research can facilitate the engineering of microbial consortia tailored for enhanced metal recovery and minimal ecological impact. The findings also establish a foundational knowledge base for bioaugmentation practices in electronic waste treatment systems. Ultimately, the integration of omics-based techniques into environmental biotechnology can accelerate the development of efficient and eco-friendly waste valorization platforms.

DOI: http://doi.org/10.5281/zenodo.16871064

Published by: vikaspatanker

Authors: Raghavendra Kumar, Smita Tiwari

Abstract: Microbial communities inhabiting contaminated ecosystems often develop complex resistance mechanisms to survive toxic environmental stressors. Understanding the molecular basis of this resistance is essential for ecological risk assessment and the development of bioremediation strategies. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technology, originally discovered as an adaptive immune system in bacteria and archaea, has emerged as a transformative tool for functional genomics and microbial ecology. This study explores how CRISPR-based approaches can elucidate microbial resistance mechanisms in polluted habitats, including heavy metal-rich soils, industrial effluents, and pesticide-contaminated farmlands. Using CRISPR interference (CRISPRi) and activation (CRISPRa), researchers can selectively knock down or upregulate microbial genes linked to metal ion transport, oxidative stress response, and efflux pump regulation. Metagenome-assembled genomes (MAGs) in tandem with CRISPR screens provide a robust framework to map resistance pathways at the community level. This article presents an overview of current CRISPR applications in microbial resistance research, evaluates their ecological implications, and highlights their potential to inform biotechnological interventions for ecosystem restoration. By integrating gene-editing precision with metagenomic profiling, CRISPR tools open new avenues to monitor, model, and modulate microbial responses to contamination.

DOI: http://doi.org/10.5281/zenodo.16871016

Published by: vikaspatanker

Authors: Lalit Kumar Sen, Madhvi Chourasiya

Abstract: Soil contamination by heavy metals, pesticides, hydrocarbons, and industrial pollutants disrupts microbial ecology, affecting soil health and plant productivity. Metatranscriptomics, the large-scale sequencing of environmental RNA, offers an advanced approach to decipher real-time microbial responses to such stressors. This study investigates the functional gene expression profiles of soil microbiomes under contaminant stress using metatranscriptomic analysis. By examining transcripts linked to oxidative stress, metal resistance, and pollutant degradation, we identify key microbial pathways that mediate adaptation and survival. Our findings highlight the upregulation of genes involved in efflux pumps, antioxidative enzymes like catalases and peroxidases, and biodegradative enzymes including monooxygenases and dioxygenases. Community-level expression patterns reveal taxonomic shifts favoring resilient genera such as Pseudomonas, Acinetobacter, and Rhodococcus. The data suggest that contaminated environments exert strong selective pressures, driving microbial communities toward functional redundancy and niche specialization. This study underscores the potential of metatranscriptomics as a tool to monitor ecological risk, assess bioremediation capacity, and develop precision strategies for soil restoration. Our work provides a foundational framework for future research aiming to optimize microbial functions for environmental detoxification and sustainable land management.

DOI: http://doi.org/10.5281/zenodo.16870960

Published by: vikaspatanker

Authors: Akhilesh Kumar Mandal, Savita Patra

Abstract: Acidic mine drainage (AMD) environments are characterized by extreme acidity and elevated concentrations of heavy metals, making them inhospitable to most life forms. Yet, microbial life thrives in these ecosystems through unique metabolic adaptations, particularly enzyme systems that function under such harsh conditions. This study explores the functional diversity of microbial enzymes in AMD sites, with a focus on their ecological roles, biogeochemical contributions, and potential applications in bioremediation. Through metagenomic analyses, microbial communities are examined for genes encoding enzymes involved in sulfur and iron oxidation, heavy metal resistance, and acid tolerance. The findings reveal a complex microbial network dominated by acidophilic chemolithoautotrophs such as Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans, which orchestrate critical oxidation-reduction processes. The presence of specialized enzymes like rusticyanin, cytochrome c oxidase, and ATPases adapted for low pH indicates functional specialization. Furthermore, these enzymes facilitate biogeochemical cycling and influence AMD chemistry, contributing to both environmental degradation and potential restoration when harnessed correctly. This study underscores the value of microbial enzyme diversity in understanding AMD ecology and leveraging it for sustainable environmental cleanup strategies.

DOI: http://doi.org/10.5281/zenodo.16870814

Published by: vikaspatanker