Agricultural and Biological Sciences, Molecular Biology, Water Science and Technology, Microbiology
92
Scopus Publications
Scopus Publications
Tissue-Specific Anticancer Peptide Prediction Using Machine Learning and Pfeature Descriptors Riya Varma, Vijay Tripathi, Jonathan A. Lal, Pooja Tripathi Journal of Computational Biophysics and Chemistry, 2026 Cancer remains one of the leading causes of mortality worldwide, with the World Health Organization (WHO) reporting approximately 10 million cancer-related deaths in 2020. Cancer is a collective term for a group of diseases characterized by the uncontrolled proliferation of abnormal cells, which can invade or spread to other parts of the body. Traditional treatment approaches, such as radiotherapy and chemotherapy, are widely used but come with significant drawbacks, including severe side effects and nonselective toxicity that affects both healthy and cancerous cells. An alternative and promising therapeutic strategy involves the use of anticancer peptides (ACPs) — short peptides that selectively target and kill cancer cells with minimal toxicity to normal cells. However, identifying novel ACPs through experimental (wet-lab) approaches is both expensive and time-consuming. To address this challenge, this study uniquely focuses on the development of separate machine learning models for prediction of ACPs for six tissue-specific cancer types i.e., breast, cervix, colon, lung, prostate and skin — which offers a more targeted framework. The dataset was sourced from CancerPPD, a database containing experimentally validated ACPs. Our methodology integrates the Pfeature library to compute four composition-based feature descriptors. To select the machine learning algorithms with high performance, we employed LazyPredict which is a rapid and unbiased model screening tool, that allows to select highly promising and common ML algorithms such as Support Vector Machine (SVM) and Random Forest (RF), followed by rigorous hyperparameter tunning. The performance of the models was evaluated using Accuracy, Matthews Correlation Coefficient (MCC) and [Formula: see text]1-score. Additionally, key features associated with high anticancer activity were identified. This study aims to contribute to the field of computational peptide-based drug discovery by providing an efficient and cost-effective method for ACP prediction, ultimately facilitating the development of novel peptide-based targeted cancer therapies.
Deriving the contribution of parameters & optimisation of Kusum oil transesterification Rachan Karmakar, Nitin Kumar, Rajesh Kumar, Saroj K. Mohapatra, Satish S. Ragit, Krishnendu Kundu, Rachna Sharma, Pradeep Kumar Sharma, Vijay Tripathi Proceedings of Institution of Civil Engineers Energy, 2026 With rapid technological growth, the demand for renewable energy sources continues to rise. In this study, Kusum oil has been explored as a raw material for biodiesel production, with efforts directed towards improving the process efficiency. Kusum oil was chosen because it is a non-edible resource that is available in several parts of India and contains a high proportion of suitable fatty acids for biodiesel conversion compared to other non-edible oils. The work focuses on understanding how parameters, such as the molar ratio, reaction time, catalyst concentration, and reaction temperature, affect the yield and quality of the biodiesel. Using the Taguchi approach with a three-level design, these parameters were fine-tuned. The highest biodiesel yield achieved was 86.65%, with lowest 0.23% free fatty acid at a molar ratio of 6:1, 1% (weight) catalyst concentration, 90 min reaction time, and 50°C reaction temperature. Analysis showed that the molar ratio, for the two-step transesterification process which led to reduce the free fatty acid content at first and helped the alcohol to react better with the oil, significantly influenced biodiesel yield (38.29% contribution), while catalyst concentration primarily affected free fatty acid content (67.48% impact) as was found in previous studies on algal or safflower oil biodiesel.
Preface Nature Based Solutions for Remediation of Emerging Pollutants in Wastewater, 2026
Perspective of Nature-based Solution in Wastewater Treatment: Challenges and Benefits Shaziya Siddiqui, Runit Isaac, Aparna, Vijay Tripathi Nature Based Solutions for Remediation of Emerging Pollutants in Wastewater, 2026 Nature-based solutions (NBS) are an effective way to combat pollution in wastewater treatment. Bioremediation using natural processes converts toxic pollutants into suitable or eco-friendly products, avoiding future pollution with chemical reagents. Nature-based methods include using algae, bacteria, viruses, plant and animal waste, polymers, and clays, which convert the waste into nontoxic or undetectable compounds present within low permissible limits. Various pollutants in wastewater streams, including heavy metals, dyes, pharmaceutical drugs, cosmetics, and personal care products, are disseminated through wastewater treatment plants into different environmental compartments. Environmental pollution is one of the important discussions due to rapid industrialization and urbanization. Recently, treatment methods have focused on using natural solutions because of their cost-effectiveness, ease of degradation, reduced spoilage, and minimal release of toxic chemicals. Various remediation techniques involve using nature-based materials like biosurfactants, adsorption, photocatalysis, nanotechnology, and the application of genetically engineered microorganisms. Due to their ease of use and abundant availability, these materials are often inefficient in terms of regeneration ability. The consortium of nature-based materials with different chemicals provides complete mineralization and strong potential for the remediation of pollutants from wastewater streams.
Role of Constructed Wetlands in Wastewater Treatment and Mitigation of Emerging Contaminants Sweta Upadhyay, Pradeep Kumar Sharma, Rachan Karmakar, Vijay Tripathi, Varij Panwar, Amit Mittal Nature Based Solutions for Remediation of Emerging Pollutants in Wastewater, 2026 Traditional wastewater treatment methods are not enough in the current scenario due to the emergence of various kinds of pollutants in the environment. Emerging contaminants (ECs), including pharmaceuticals, endocrine-disrupting chemicals, and nanoplastics, pose significant risks to ecosystems and human health due to their persistence and toxicity. New approaches are being developed that concentrate on the simultaneous removal of pollutants like carbon, nitrogen, phosphorus, and ECs. Constructed wetlands (CWs) have proven to be effective, sustainable systems for mitigating these contaminants through integrated physical, chemical, and biological mechanisms. Constructed wetlands offer a cost-effective and sustainable alternative for wastewater treatment, capable of removing organic pollutants, nutrients, and emerging contaminants (ECs) like pharmaceuticals and personal care products. Advanced configurations include vertical subsurface flow systems and aerated CWs. This chapter explores the role of CWs in wastewater treatment, focusing on the mechanisms enabling the removal of ECs, such as pharmaceuticals, endocrine-disrupting pollutants, and microplastics. The chapter emphasizes the importance of physical, chemical, and biological processes, such as sorption, phytoremediation, and microbial biodegradation. Key findings include the influence of hydraulic retention time, aeration rates, and substrate composition on pollutant removal, and the critical role of plant-microbe interactions in degrading ECs. Combining advanced processes with CW systems is also discussed in the chapter, such as adding biochar for enhanced removal efficiency. By synthesizing recent advances, this work provides a roadmap for optimizing CW systems to address emerging contaminants and meet the growing demand for environmentally sustainable wastewater treatment technologies.
Microalgae-based Wastewater Treatment and Production of Value Added Products Sonal Singh, Kuldeep Dwivedi, Rwitabrata Mallick, Shashank Gupta, Kumar Shrestha, Vijay Tripathi, Nidhi Shukla Nature Based Solutions for Remediation of Emerging Pollutants in Wastewater, 2026 Using microalgae in wastewater treatment is a cost-effective and environmentally friendly alternative to energy-consuming conventional methods. Microalgae include cyanobacteria and eukaryotic algae, which can bio-fix CO₂ and utilize nutrients such as nitrogen and phosphorus in the wastewater, reducing their concentrations and aiding in biomass production. These microorganisms help to remove nutrients by photosynthesis of carbon dioxide into oxygen so that heterotrophic bacteria can utilize the oxygen to degrade the soluble organic pollutants and augment wastewater treatment operations. Phosphorus recovery with algae granules has been particularly effective and essential for resource recycling in the circular green economy. Emerging contaminants, including pharmaceutical and personal care products (PPCPs), agrochemicals, single-use plastics, and heavy metals, are detected in wastewater and rivers and are causing a threat to humans and aquatic organisms. In contrast, single-use plastic contributes to pollution by microplastics. Water sources are affected by the effluence of heavy metals, which are by-products of different industries. Microalgae can remove contaminants and produce biofuels, among other benefits. This chapter explores the ability of microalgae to recover nutrients from wastewater, reduce greenhouse gases, and remove pollutants to improve the sustainability of wastewater treatment systems.
Monitoring and assessing different strategies of wastewater treatment plants on dissemination of antibiotic resistance in the downstream river environment Sachin Saurabh, Shabnam Khan, Rajan Anand, Shashank Singh, Ramendra Soni, Arun Kumar Pal, Jonathan A. Lal, Pooja Tripathi, Vijay Tripathi Journal of Water Sanitation and Hygiene for Development, 2025 Nowadays, wastewater discharge is a significant challenge, particularly in developing countries. This study aimed to evaluate the treatment strategies of wastewater treatment plants (WWTPs) and their role in disseminating antibiotic-resistant E. coli in the downstream Ganges River. The removal efficiencies and reduction of antibiotic-resistant E. coli were examined in each treatment step. Physicochemical analysis revealed that removal efficiencies of parameters such as TDS, BOD, and COD were highest by MBBR (moving bed biofilm reactor)-based WWTP, and lowest by UASB (upflow anaerobic sludge blanket)-based WWTP. The E. coli isolates showed maximum resistance against vancomycin, erythromycin, doxycycline, and ampicillin antibiotics. The Ganges River water samples were also highly abundant with antibiotic-resistant E. coli, suggesting that while WWTPs contribute to the microbial load, greater contamination observed in the Ganges River likely results from additional point and non-point sources, including untreated discharges, which may surpass the impact of treated WWTP effluent. This study highlights the presence of antibiotic-resistant bacteria (ARB) across different treatment stages in WWTPs and indicates the potential for treated effluents to contribute to downstream ARB loads. This is an alarming issue that requires stringent surveillance and minor improvements in existing treatment technologies to prevent the dissemination of antibiotic resistance.
Physicochemical Analysis of Wastewater through Moringa oliefera and Azadirachta indica Biochars: A Nature-based Solution Water and Energy International, 2025
Fighting Cancer around the World: A Framework for Action Denis Horgan, Rizwana Mia, Tosan Erhabor, Yosr Hamdi, Collet Dandara, Jonathan A. Lal, Joel Fokom Domgue, Oladimeji Ewumi, Teresia Nyawira, Salomé Meyer, Dominique Kondji, Ngiambudulu M. Francisco, Sadakatsu Ikeda, Chai Chuah, Roselle De Guzman, Anupriya Paul, Krishna Reddy Nallamalla, Woong-Yang Park, Vijay Tripathi, Ravikant Tripathi, Amber Johns, Mohan P. Singh, Maude E. Phipps, France Dube, Kate Whittaker, Deborah Mukherji, Hadi Mohamad Abu Rasheed, Marta Kozaric, Joseph A. Pinto, Stephen Doral Stefani, Federico Augustovski, Maria Eugenia Aponte Rueda, Ricardo Fujita Alarcon, Hugo A. Barrera-Saldana Healthcare Switzerland, 2022
Efficacy, safety, and lot-to-lot immunogenicity of an inactivated SARS-CoV-2 vaccine (BBV152): interim results of a randomised, double-blind, controlled, phase 3 trial Raches Ella, Siddarth Reddy, William Blackwelder, Varsha Potdar, Pragya Yadav, Vamshi Sarangi, Vinay K Aileni, Suman Kanungo, Sanjay Rai, Prabhakar Reddy, Savita Verma, Chandramani Singh, Sagar Redkar, Satyajit Mohapatra, Anil Pandey, Pajanivel Ranganadin, Raghavendra Gumashta, Manish Multani, Shameem Mohammad, Parul Bhatt, Laxmi Kumari, Gajanan Sapkal, Nivedita Gupta, Priya Abraham, Samiran Panda, Sai Prasad, Balram Bhargava, Krishna Ella, Krishna Mohan Vadrevu, P. Aggarwal, V. Aglawe, A. Ali, N. Anand, N. Awad, V. Bafna, G. Balasubramaniyam, A. Bandkar, P. Basha, V. Bharge, A. Bhate, S. Bhate, V. Bhavani, R. Bhosale, DV Chalapathy, C. Chaubal, D. Chaudhary, A. Chavan, P. Desai, D. Dhodi, S. Dutta, R. Garg, K. Garg, M. George, P. Goyal, R. Guleria, S. Gupta, M. Jain, M.K. Jain, S. Jindal, M. Kalra, S. Kant, P. Khosla, P. Kulkarni, P. Kumar, Y. Kumar, A. Majumdar, P. Meshram, V. Mishra, S. Mohanty, J. Nair, S. Pandey, S.K. Panigrahi, B. Patil, V. Patil, P. Rahate, V. Raj, S. Ramanand, K. Rami, B. Ramraj, S. Rane, E.V. Rao, N. Rao, R. Raphael, G. Reddy, V. Redkar, S. Redkar, A. Sachdeva, J. Saha, J. Sahoo, P. Sampath, A. Savith, M. Shah, L. Shanmugam, R. Sharma, P. Sharma, D. Sharma, A. Singh, J. Singh, P. Singh, S. Sivaprakasam, S. Subramaniam, D. Sudheer, S. Tandon, M. Tariq, V. Tripathi, M. Vable, R. Verma, S. Waghmare Lancet, 2021
Phytotherapy and food applications from Brassica genus Bahare Salehi, Cristina Quispe, Monica Butnariu, Ioan Sarac, Ilias Marmouzi, Madhu Kamle, Vijay Tripathi, Pradeep Kumar, Abdelhakim Bouyahya, Esra Capanoglu, Fatma Duygu Ceylan, Laxman Singh, Indra D. Bhatt, Barbara Sawicka, Barbara Krochmal‐Marczak, Dominika Skiba, Meryem El Jemli, Yousra El Jemli, Ericsson Coy‐Barrera, Javad Sharifi‐Rad, Senem Kamiloglu, María de la Luz Cádiz‐Gurrea, Antonio Segura‐Carretero, Manoj Kumar, Miquel Martorell Phytotherapy Research, 2021
High Throughput Analysis of Integron Gene Cassettes in Wastewater Environments Joao Gatica, Vijay Tripathi, Stefan Green, Celia M. Manaia, Thomas Berendonk, Damiano Cacace, Christophe Merlin, Norbert Kreuzinger, Thomas Schwartz, Despo Fatta-Kassinos, Luigi Rizzo, Carsten U. Schwermer, Hemda Garelick, Edouard Jurkevitch, Eddie Cytryn Environmental Science and Technology, 2016
