Latest Articles | 2025 | Vol 05
by Priya G and Subana S
Department of Microbiology, Muthayammal College of Arts and Science,
Rasipuram, Namakkal, Tamilnadu, India
Abstract : The green synthesis of copper nanoparticles (CuNPs) using Bauhinia variegata leaf extract presents a cost-effective and environmentally sustainable approach to developing alternative antimicrobial agents. Bauhinia variegata is a medicinal plant rich in bioactive compounds, including anthraquinones, flavonoids, phenolic glycosides, alkaloids, saponins, reducing sugars, and tannins, which facilitate nanoparticle formation and stabilization. The synthesis of CuNPs was indicated by a color change from light to dark green and confirmed through UV-Vis spectroscopy and FTIR analysis, which identified key functional groups responsible for nanoparticle stabilization. The antibacterial potential of the synthesized CuNPs was evaluated against Pseudomonas spp., Klebsiella spp., and Staphylococcus spp., revealing significant inhibitory effects. Among the tested species, Pseudomonas spp. exhibited the highest susceptibility, while Staphylococcus spp. showed the lowest inhibition. Ethanol extracts demonstrated superior antimicrobial activity compared to other solvent extracts. These findings highlight the potential of Bauhinia variegata-mediated CuNPs as promising antimicrobial agents, particularly against multidrug-resistant bacterial strains. Further research should explore their mechanism of action and potential applications in pharmaceutical and biomedical fields.
by Perumal R and Subana S
Department of Microbiology, Muthayammal College of Arts and Science,
Rasipuram, Namakkal, Tamilnadu, India
Abstract : Cancer remains one of the leading causes of morbidity and mortality worldwide, driven by uncontrolled cell proliferation and resistance to apoptosis. Despite significant advances in cancer treatment, including surgery, chemotherapy, and radiation therapy, challenges such as drug resistance and adverse side effects continue to limit their effectiveness. Consequently, there has been a growing interest in exploring natural compounds with potential anticancer properties. Asparagus racemosus, a plant known for its medicinal properties, has garnered attention for its antioxidant and anticancer effects. This study investigates the bioactive extracts of Asparagus racemosus for their ability to induce cytotoxicity in liver cancer cells and modulate key genes involved in apoptosis, particularly the Bcl-2 gene. Our findings reveal that the plant extracts exhibit a dose-dependent reduction in cell viability and downregulate the Bcl-2 gene expression, suggesting that Asparagus racemosus has the potential to serve as an alternative or complementary cancer treatment. This research contributes to the expanding body of knowledge on plant-derived anticancer agents, highlighting Asparagus racemosus as a promising natural therapeutic candidate for liver cancer and other malignancies.
by Nivetha B, Tamil Bharathi V and Gnanendra TS
Department of Biotechnology, Vivekanandha College of arts and Sciences for Women (Autonomous),
Elayampalyam, Tiruchengode, Tamilnadu, India.
Abstract : Chikungunya, a virus that is transmitted to humans by the bite of an infected mosquito. Chikungunya is caused by the Chikungunya virus (CHIKV), an RNA virus belonging to the alphavirus genus and Togaviridae family. The term Chikungunya comes from the Kimakonda language and means "to become contorted." The most common symptoms include fever, headache, and joint pain that persist. Africa, Southeast Asia, India, and Brazil are endemic regions for Chikungunya fever. The primary objective of this work is to identify an effective epitope based subunit vaccine against the virus through computational analysis and a reverse vaccinology approach. T cell epitopes were predicted and evaluated for antigenicity and population coverge based on the CHIKV structural proteins. In this, the epitope PRNVELGDRKGK exhibited the highest antigenicity score of 2.4092, indicating its strong potential as an immunogenic candidate. Also, the population coverage analysis revealed its global effectiveness with 71.70% coverage. Further, protein-peptide docking of the modelled peptide with the CHIKV envelope glycoprotein identified the most stable molecular complex based on a lowest binding energy of -556.0 kcal/mol, with key interactions were visualized. This immunoinformatics investigation demonstrates that the anticipated epitopes are capable of inducing adequate antibodies against CHIKV and suggests that their epitopes can be exploited in the development of the novel effective and successful CHIKV vaccine.
by Priyadharshini Balasubramani and Gnanendra TS
Department of Biotechnology, Vivekanandha College of arts and Sciences for Women (Autonomous),
Elayampalyam, Tiruchengode, Tamilnadu, India.
Abstract : Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) representing the primary histological subtypes. Approximately 85% of cases are classified as NSCLC, whereas SCLC is characterized by its aggressive clinical course and poor prognosis. Major risk factors for SCLC include smoking, environmental exposures, and genetic predispositions. Early detection is critical; low-dose computed tomography (LDCT) has demonstrated a significant reduction in lung cancer–specific mortality. The use of biomarkers, such as microRNAs (miRNAs), has enhanced diagnostic accuracy by improving risk stratification and distinguishing malignant from benign pulmonary nodules. Artificial intelligence (AI)-driven imaging technologies have revolutionized lung cancer screening by increasing diagnostic precision and operational efficiency. Advances in molecular characterization, including identification of mutations and gene fusions involving EGFR, KRAS, ALK, and NTRK, have facilitated the development of personalized therapeutic strategies. In particular, immunotherapies and targeted agents, such as TRK inhibitors, have demonstrated promising efficacy in NSCLC. Nevertheless, significant challenges remain, including therapy resistance, healthcare disparities, and limited accessibility to screening programs. Emerging technologies, such as liquid biopsies and deep learning–enhanced imaging, continue to drive improvements in early detection and treatment paradigms. Future research should prioritize the integration of AI, novel therapeutics, and precision medicine approaches to optimize lung cancer management. By advancing early diagnostic capabilities, expanding personalized interventions, and addressing disparities in access to care, meaningful progress can be achieved in reducing lung cancer mortality.
by Naveena Sakthivel and Gnanendra TS
Department of Biotechnology, Vivekanandha College of arts and Sciences for Women (Autonomous),
Elayampalyam, Tiruchengode, Tamilnadu, India.
Abstract : Phytochemicals, a diverse class of bioactive compounds derived from plants, play a pivotal role in modern drug discovery and natural product research. The ability to accurately predict their biological activities based on chemical structure is essential for enhancing screening efficiency and minimizing experimental costs. This review presents an overview of state-of-the-art computational strategies employed to forecast the pharmacological potential of phytochemicals. Key methodologies discussed include quantitative structure–activity relationship (QSAR) modeling, molecular docking, cheminformatics tools, and machine learning algorithms. Emphasis is placed on the use of molecular descriptors and structural fingerprints for functional classification of phytochemicals into categories such as antioxidant, anticancer, antimicrobial, and anti-inflammatory agents. The review also addresses current challenges, including limitations in data availability, issues of model interpretability, and the critical need for experimental validation. With ongoing advancements in artificial intelligence and big data analytics, predictive modeling continues to evolve, offering transformative opportunities for the identification and development of plant-derived therapeutics. Integrating computational predictions with empirical research holds significant promise for accelerating the discovery of novel bioactive compounds.
by Tamil Bharathi Viswanathan and Gnanendra TS
Department of Biotechnology, Vivekanandha College of arts and Sciences for Women (Autonomous),
Elayampalyam, Tiruchengode, Tamilnadu, India.
Abstract : Microbial metabolites are bioactive compounds produced by microorganisms, which plays a crucial role in biotechnology, pharmaceuticals, and natural product research. The rapid advancements in high-throughput sequencing, mass spectrometry, and NMR spectroscopy have led to an exponential increase in metabolite data making efficient data management essential. This need has driven the development of specialized microbial metabolite databases, designed to facilitate data storage, annotation, and analysis. This review explores the microbial metabolite databases, particularly focusing on their architecture, data curation strategies, and integration of genomic, metabolomic, and spectral data. Furthermore, a comparative analysis of major databases highlights their strengths, limitations, and areas for improvement. Additionally, we discuss the role of computational approaches in metabolite annotation, biosynthetic pathway mapping, and predictive biosynthesis models. Despite it’s significant progress, challenges such as data standardization, cross-database interoperability, and reproducibility remain major hurdles. To overcome these issues, recent advancements such as cloud-based repositories, multi-omics integration, and cheminformatics-driven metabolite prediction offers a promising solution. As this research advances, strengthening database connectivity, fostering collaboration, and integrating emerging technologies will be crucial for unlocking the vast potential of microbial metabolite exploration.
Immunoinformatical approach of Epitope based vaccine design for Dengu fever virus
by Nandhini C, Vijiya Dharshini V and Tamil Bharathi V
Department of Biotechnology, Vivekanandha College of arts and Sciences for Women (Autonomous),
Elayampalyam, Tiruchengode, Tamilnadu, India.
Abstract : Dengue virus (DENV) outbreaks are a major public health concern in India, necessitating the development of effective vaccination strategies. Existing dengue vaccines have limitations, such as incomplete protection against all virus serotypes and the risk of enhanced infection upon secondary exposure, driving the exploration of innovative vaccine development approaches. This study employs a combined reverse vaccinology and immunoinformatics approach to design a multi-epitope-based vaccine targeting various proteins of DENV. Computational immune-informatics techniques were utilized to identify B-cell and T-cell epitopes across the DENV genome, aiming to enhance the immune response against DENV infection. Bioinformatics tools were employed to predict epitopes, assess antigenicity, and conduct molecular docking to human HLA alleles. Peptides with the lowest binding affinity for each human allele were selected, and their structures were validated. The study identified promising vaccine candidates, including peptides from the whole genomes of DENV serotypes 1 (IGIGVLLTW), 2 (AAFSGVSWTM), 3 (WDFGSV), and 4 (NLEYTVVVTW). These findings highlight the potential of computational approaches in vaccine design, offering insights into novel strategies for combating DENV and potentially other infectious diseases.
by Narendra Chaudhari1, Jallavi Panchamia2, *Bharti Koria3, Hiral Raval4, Aniket Rana5, Bharat Solanki6 and Kamlesh Patel1
1Medical officer, District TB center, Mehsana, Gujarat; 2Department of public health, IIPH Gandhinagar, Gujarat; 3Department of Community Medicine, PDU Medical college, Rajkot, Gujarat; 4Departmne of Public Health, IIPH Gandhinagar, Gujarat,
5Department of Community Medicine, Swaminarayan Institute of medical science and research, Kalol, Gandhinagar, Gujarat ; 6Chief District heath officer, Mehsana, Gujarat.
Abstract : Tuberculosis is a major public health concern in India since decades. With growing private sector management role in TB treatment, effective coordination between public private sector becomes vital for post notification patient management. So, this study aimed to assess the public health system's response to TB notifications from the private sector in Mehsana district, Gujarat. This was an observational cross-sectional study with primary data from field visits and Key informant interviews while secondary data from Nikshay portal entries. The data were evaluated for timeliness and completeness following TB case notification by private sector. Data entry and analysis was done in Microsoft excel. As results total 380 cases notified to public sector, 92% case reported to the government facility within 7 days of reporting. However, among them 65% have received adherence support and 78% have received treatment literacy. Thematic analysis of KII showed key barrier factors like manpower shortage, logistic supply issues and non-cooperative behaviors from private sectors. In conclusion, post notification reporting was good in Mehsana district but gaps remaining in integrated patients support system and treatment adherence support remains question. Intersectoral support strengthening, capacity enhancement of health workers and establishing accountable system is necessary for better outcomes.
by Sowmiya Anandan and Gnanendra TS
Department of Biotechnology, Vivekanandha College of arts and Sciences for Women (Autonomous),
Elayampalyam, Tiruchengode, Tamilnadu, India.
Abstract : CRISPR-Cas9 technology has rapidly emerged as a transformative tool in breast cancer research, enabling precise genome editing that advances functional genomics, target discovery, and therapeutic development. This review highlights the fundamental principles of CRISPR-Cas9 and its diverse applications in breast cancer models, including gene function interrogation and high-throughput screening for oncogenic drivers. We discuss the role of CRISPR-based approaches in advancing precision medicine, such as genome editing for personalized therapies and immune cell engineering. Despite its promising potential, challenges including off-target effects, delivery efficiency, and ethical considerations remain significant barriers to clinical translation. We also explore emerging strategies to overcome these limitations and future directions aimed at optimizing CRISPR technology for improved breast cancer treatment. Integrating CRISPR-Cas9 with multidisciplinary research holds the key to unlocking novel therapeutic avenues and enhancing patient outcomes in the era of precision oncology.
by Swedha Ambigapathi and Gnanendra TS
Department of Biotechnology, Vivekanandha College of arts and Sciences for Women (Autonomous),
Elayampalyam, Tiruchengode, Tamilnadu, India.
Abstract : The rhizosphere represents a highly dynamic interface where plant roots interact with the surrounding soil matrix, fostering a diverse and functionally complex microbial community. These microbiota play essential roles in plant growth promotion, nutrient cycling, and resilience to biotic and abiotic stresses. In recent years, plant-associated microbial communities have garnered increasing attention for their potential to enhance agroecosystem sustainability. This review examines microbial community shifts in the rhizosphere and bulk soil of sunflower (Helianthus annuus), a key oilseed crop known for its adaptability to marginal soils and environmental stressors. The differences in microbial composition and functional potential between rhizosphere and bulk soil are analyzed, with emphasis on the roles of plant genotype, root exudation, and environmental variables such as salinity and climatic conditions. Particular focus is placed on beneficial bacterial genera including Pseudomonas, Azotobacter, and Bacillus, which contribute to nutrient acquisition and stress mitigation. Additionally, fungal taxa such as Fusarium, Aspergillus, and Alternaria are discussed in the context of decomposition, symbiosis, and plant–microbe interactions. Comparative insights from other oilseed crops—such as soybean, rapeseed, and peanut—are presented to contextualize microbiome patterns unique to sunflower. The functional attributes of rhizosphere microbes, including phytohormone production, pathogen suppression, and nutrient solubilization, are explored in detail. Furthermore, this review highlights microbiome engineering approaches, such as the application of biofertilizers and plant growth-promoting rhizobacteria (PGPR), aimed at improving crop productivity and resilience. The integration of high-throughput sequencing technologies and advanced bioinformatics has deepened our understanding of these complex microbial networks. Finally, the review identifies existing knowledge gaps and outlines future research directions to optimize rhizosphere microbiomes for enhanced agro-ecological performance in sunflower and related oilseed crops.
by Thilagavathi Santhappan and Subana suyambumani
Department of Microbiology, Muthayammal College of Arts and Science,
Rasipuram, Namakkal, Tamilnadu, India
Abstract : This study investigates the antimicrobial activity and phytochemical composition of Bauhinia tomentosa extracts and their synthesized nanoparticles. Bacterial pathogens isolated from diabetic wound samples— including Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, Escherichia coli, and Candida albicans were tested for susceptibility to the plant extracts. The methanol and acetone extracts of Bauhinia tomentosa demonstrated significant antimicrobial properties, with the methanol extract showing greater inhibition. Additionally, silver (AgNPs), copper (CuNPs), and zinc (ZnNPs) nanoparticles were synthesized using plant extracts and evaluated for their antimicrobial efficacy. Among these, AgNPs exhibited the strongest antimicrobial activity. Phytochemical screening revealed the presence of bioactive compounds such as flavonoids, phenols, terpenoids, alkaloids, and tannins, which contribute to the observed antimicrobial effects. Furthermore, the synthesized nanoparticles significantly enhanced plant growth in a dose-dependent manner, suggesting their potential as bio-stimulants. These findings underscore the potential applications of Bauhinia tomentosa extracts and their nanoparticles as therapeutic agents for diabetic wound infections and as bio-stimulants in agriculture.
International Journal of
Advances in Interdisciplinary Research
Journal Metrices
eISSN 2348-0696 | SJIF : 6.07 (2022)
Open Access | Peer-Reviewed | Indexed
Editor-in-Chief
Dr. Ruksana Raihan
US Bangla Medical College, Rupganj, Bangladesh.
Associate Editor(s)
Dr. Vijayalakshmi Selvakumar
Department of Microbiology and Immunology,
University of Rochester, Rochester, NY.
Dr.S De Mandal
Department of Agricultural Sciences,
South China Agricultural University,
Guangzhou, China.
Dr. Elayaraja Dhandapani
Northern Research and Development,
MIGAL Galilee Research Institute,
Kiryat Shmona, Israel.
Dr. Gnanendra Shanmugam
Department of Biotechnology,
Yeungnam University, South Korea.
Dr. Senthil Kumar Raju
Department of Pharmaceutical Chemistry,
Swamy Vivekanandha College of Pharmacy, Tiruchengode, Tamilnadu, India
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