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DEVELOPMENT OF A STANDARDIZED POLYHERBAL CAPSULE TARGETING OXIDATIVE STRESS AND ARTHRITIS INFLAMMATION.
Get PDFPurpose of the Work: The study aimed to develop a standardized polyherbal capsule combining Ochna obtusata, Tinospora cordifolia, and Boswellia serrata—three medicinal plants with known antioxidant, anti-inflammatory, and immunomodulatory properties—as a safer, multi-targeted herbal alternative for arthritis management.
Methods: Individual plant extracts underwent preliminary phytochemical screening, quantitative estimation of total phenolic and flavonoid contents, and Fourier Transform Infrared Spectroscopy (FTIR) for chemical characterization. Three polyherbal fractions (PHF1–PHF3) were formulated in different ratios and optimized using Quality by Design (QbD) principles. The optimized capsule batches were then evaluated for physicochemical parameters, drug content uniformity, disintegration time, and in vitro release profile. FTIR was used to assess compatibility between extracts and excipients.
Key Findings: Among all formulations, PHF2 showed the highest phenolic content (16.92 ± 0.057%) and flavonoid content (2.41 mg QE). The optimized capsule batch (S4) demonstrated excellent flow properties, uniform drug content (93.48 ± 0.4%), rapid disintegration (10.89 ± 0.1 min), and complete in vitro drug release (94.88% within 30 min). FTIR analysis confirmed chemical compatibility and stability of the formulation.
Conclusion: The standardized polyherbal capsule was found to be pharmaceutically stable, compositionally consistent, and potentially effective in reducing oxidative stress–mediated arthritic inflammation. These findings suggest it could serve as a promising and safer herbal alternative to conventional arthritis therapies
SURVEY ON DEEP LEARNING UTILITY FOR THE PURPOSE OF GARBAGE CATEGORIZATION
Get PDFThe increasing pace of solid waste production in the world has led to the overload of the municipal management systems, revealing the weakness of the manual sorting and manual automation of the robotic sorting of the heterogeneous waste under the conditions of variations. Convolutional Neural Network (CNN) and deep learning (DL) provide automated algorithms that enhance speed of classification, accuracy, and performance. The current trends combine real-time object detectors with multi-layered CNNs to deal with class imbalance, overfitting, and a lack of data diversity, and lightweight models and transfer learning permit deployment in low-resource IoT settings. Hybrid classification-detection algorithms improve model stability under cluttered environment, and UAVs-based surveillance is useful in fast mapping of hazardous waste piles. Applications of DL are all around urban streets, underwater debris tracking and construction site trash sorting, and natural language interfaces. Circular economy goals are also promoted by these technologies and allow recycling and resource recovery to be more efficient. However, there are still shortcomings, such as inadequate datasets, large computation energy demands, and realistic multi-scale implementation. Future directions to enhance the model architecture, use less energy in the training process and develop hardware-software architecture to implement it at large scale and in a sustainable manner should be considered in future research. On the whole, DL is revolutionizing waste management to enable the classification and monitoring of waste as accurate, automated and environmentally friendly, and make smart waste systems one of the most important elements of an urban infrastructure that is sustainable.
KEYWORDS
Categorization, Convolutional Neural Networks (CNNs), Deep Learning (DL), Internet of Things (IoT), Lightweight models, Transfer learning, Waste, Waste managemen
Prevalence and Trends of Non-Communicable Diseases Among Healthcare Workers Aged 40 and Above: A 5-Year Retrospective Study at a Tertiary Care Center in Puducherry
Get PDF Background: Non-communicable diseases (NCDs) are a leading global health challenge. Healthcare workers (HCWs), pivotal to health systems, are themselves at risk due to occupational stressors and lifestyle factors. However, comprehensive data on the NCD burden among HCWs in India is limited. This study aimed to determine the prevalence and trends of NCDs among HCWs aged ≥40 years at a tertiary care center in Puducherry.Methods: A retrospective cross-sectional study was conducted using annual health check-up data from 2019 to 2024. De-identified data of 2,731 HCWs were extracted from hospital records. NCDs were defined using standard criteria: diabetes (HbA1c ≥6.5%), hypertension (BP ≥140/90 mmHg), dyslipidemia (e.g., total cholesterol >200 mg/dL), and obesity (BMI ≥30 kg/m²). Data were analyzed using SPSS v26.0 to calculate prevalence, trends, and associations. Results: The cohort comprised 57.7% males and 42.3% females, predominantly aged 40-49 (65.9%). High prevalence rates were observed for diabetes (24.9%), high total cholesterol (30.3%), and high triglycerides (13.9%). Male HCWs had a significantly higher burden of dysglycemia (29% vs. 19%) and dyslipidemia than females. A strong positive correlation was found between age and LDL/HDL levels. Notably, 78.7% of the cohort had at least one abnormal component of metabolic syndrome. Conclusion: A high burden of NCDs exists among healthcare workers, with significant gender and age-related disparities. These findings underscore an urgent need for institutional workplace health programs focused on screening, lifestyle modification, and tailored interventions to safeguard this critical workforce and ensure a resilient healthcare system.
KEYWORDS Non-communicable diseases, Healthcare workers, Prevalence, Diabetes mellitus, Dyslipidemia, Metabolic syndrome, Occupational health, India
Machine Learning-Driven Data Mining Techniques for Enhancing Cyber Security
Get PDFAs cyberattacks become more complex and frequent, cybersecurity has emerged as a top research priority. Traditional signature-based defense systems struggle to identify new and evolving threats. To tackle this challenge, researchers are increasingly turning to machine learning and data mining techniques to uncover patterns, detect suspicious activities, and reveal hidden relationships within vast security datasets. This paper will take a deep dive into various data mining methods, including classification, clustering, association rule mining, and anomaly detection, and how they can be applied to enhance cybersecurity. Additionally, it will explore the integration of supervised, unsupervised, and ensemble learning approaches, such as Support Vector Machines, random forests, neural networks, and deep learning architectures, particularly in the contexts of intrusion detection, malware analysis, and fraud detection. The discussion will also cover benchmark datasets like KDD Cup 99, NSL-KDD, CICIDS 2017, and UNSW-NB15, along with performance metrics such as accuracy, precision, recall, F1-score, and AUC. Furthermore, the paper will address emerging challenges in the field, including class imbalance, concept drift, adversarial attacks, and scalability. Finally, it will outline promising research directions that focus on hybrid intelligent systems, explainable AI, and big data-driven cybersecurity analytics.
KeywordsCybersecurity, Data Mining, Machine Learning, Intrusion Detection, Anomaly Detection, Supervised Learning, Unsupervised Learning, Cyber threat, Adversarial Attack
To identify the trend of agroclimatic variabilities of eastern U. P.
Get PDFThis study analyzes the annual trends of maximum temperature,minimum temperature, and rainfall across the agroclimatic zones—NEPZ,EPZ, and Vindhyan zone—of Eastern Uttar Pradesh from 2004 to 2023.Linear trend analysis indicated a consistent rise in both maximum andminimum temperatures, while rainfall exhibited a declining trend across allzones. The Mann-Kendall test was employed to determine the statisticalsignificance of these trends at the district level. Results revealed thatmaximum temperature trends were significantly increasing in Ayodhya,Mirzapur, and Sonbhadra, while minimum temperature trends weresignificant in Kushinagar and Sonbhadra. Rainfall trends showed significantincreases only in Varanasi and Sonbhadra, with other districts showing nostatistically significant changes. The findings suggest emerging climaticshifts that may impact agriculture, requiring climate-resilient strategiestailored to district-specific trends
PRELIMINARY ANTIMICROBIAL SCREENING OF LEAF EXTRACT OF COSTUS IGNEUS USING ETHANOL EXTRACT
Get PDFCostus igneus, also known as the “insulin plant,” is a widelyrecognized medicinal plant in Indian traditional medicine, particularly for itsrole in managing diabetes and other metabolic disorders. This study exploresthe antimicrobial potential of Costus igneus, focusing on its ethanol extractderived from the leaves. The ethanol extract was tested for its antibacterialand antifungal activities using the agar well diffusion method against variousmicrobial pathogens, including Staphylococcus aureus, Bacillus subtilis,Pseudomonas aeruginosa, Aspergillus flavus, Aspergillus niger, andAspergillus terreus. Results indicated significant antibacterial activity,particularly against Gram-positive bacteria, with zones of inhibition rangingfrom 10 mm to 25 mm. The antifungal activity showed an inhibition rangeof 10 mm to 14 mm, with Aspergillus niger being most susceptible to theextract. The study also compared the effectiveness of Costus igneus extractsto standard antibiotics (streptomycin and fluconazole), revealingcomparable inhibitory effects. The findings suggest that Costus igneus, withits bioactive compounds, has considerable antimicrobial potential, making ita promising candidate for developing alternative antimicrobial agents. Theseresults further validate its medicinal significance in folk medicine and openpathways for future research into plant-based antimicrobial agents
Perception of Stakeholders on the Implementation of Integrated Teaching Module in a Medical College at Puducherry – Cross-sectional study
Get PDFBackground & Objectives: Integrated teaching is an educational approach that combines various disciplines of medicine, into a cohesive curriculum which fosters critical thinking, problem-solving skills, and prepares students for the complexities of healthcare practice. This study was conducted to assess the perception of Faculty and Final MBBS Part – I students on the implementation of Integrated Teaching Module as a part of their teaching curriculum.Methods: A Cross-sectional study was conducted among 47 Faculty and 127 Final MBBS Part – I students via separate Google forms after approval from Scientific Research Committee and Institutional Ethical Committee.Results: Total of 47 Faculty responses in which 76.6% comfortable and satisfactory lectures; 89.4% - relevant topics chosen; 70.2% time-saving;66% - was useful for both theory and practical; 87.2% creates interest into contents and 85.1% - important topics are covered, while 23.4% - faculty transitions were time-consuming. Total of 127 Student responses - 56.7% - engaging and interactive lectures; 66.1% improved their understanding of the subject; 57.5% stimulated analytical thinking; 70.9% - alignment of the content with the students' academic and professional needs; 74% need to incorporate lab and clinical exercises; 66.9% agreed for its inclusion in the routine curriculum.Interpretation and Conclusions: Integrated teaching method allows the student to develop the skills in investigation, analysis and also to perceive the patient as a whole and acts as a bridge for connecting knowledge and practices
Multi-Target Anti-Obesity Mechanisms of Pedalium murex Mucilage: A Cheminformatics and Network Pharmacology Study
Get PDFObesity is a global epidemic challenge with significant comorbidity-associated health risks, psychological implications, and economic burden. The inefficiency and side effects of current therapeutics highlight the necessity for safer alternative therapeutics and multi-target therapeutic strategies. Pedalium murex L., a plant used in culinary and medicinal practices across many cultures globally, has shown potential anti-obesity effects. This study used cheminformatics and network pharmacology to identify anti-obesity bioactive compounds in P. murex mucilage and understand their mechanism of action. Three key antiobesity compounds in P. murex mucilage, viz. 3-Oxo-12,18-ursadien-28-oic acid, Epifisetinidol-(4β→8)-catechin, and Moschamine were recognized and analysed for their anti-obesity properties and obesity pathway modulations. These compounds were shown to target 300 potential human targets, including PPARG, FASN, and UCP-1, which are key regulators of adipogenesis, lipogenesis, and thermogenesis. Network pharmacology revealed their involvement in lipid metabolism and the inflammatory response, highlighting their polypharmacological mode of action. This study provides evidence that P. murex mucilage bioactives have multi-target anti-obesity effects through the modulation of metabolic and inflammatory pathways, suggesting its potential as natural anti-obesity therapeutics
Qualitative Phytochemical Screening of Some Medicinal Plants
Get PDFMedicinal plants are abundant in bioactive compounds that are useful in the treatment of a wide range of human illnesses. The phytochemical compounds of these medicinal plants are thought to have medicinal potential. In the present study, qualitative phytochemical screening was conducted on leaf extracts of four medicinal plants - Sphaeranthus indicus, Celosia cristata, Tephrosia purpurea, and Kigelia africana. Solvent extraction was performed using a cold maceration method with ethylacetate, ethanol and aqueous solvents. Qualitative phytochemical analyses were carried out to detect the presence of flavonoids, saponins, tannins, phenolics compounds, coumarins, and quinine Among the extracts, the ethanol extract of S. indicus exhibited the highest number of phytochemicals, while other plants showed the least. The presence of these phytochemicals suggests that these plants possess significant therapeutic potential and may serve as valuable sources for the development of novel plant-based drugs.
Traditional medicine, Solvents, Secondary metabolites, Alkaloid
A Critical Study on Emerging Legal Challenges of Genetic Engineering: Global Innovations and India’s Response
Get PDFIn the era of rapid technological development, the field of biotech is not running late. The development in the molecular biology has called for upgradation in modern biotechnology. One of the important aspects of molecular biology is the study with gene, and the inter-related materials. With the passage of time, study of human gene urge for therapy to cure certain genetic diseases. By the process of genetic engineering, one can edit or alter the gene which is responsible for that particular disease. However, now the science has upgraded in this manner where the process of genetic engineering is able to edit the germ line gene not for therapy but also able to design one’s baby according to their choice. Hence, the human are able to interfere the most natural process of the earth, creating new life. The paper thus would be focused on analyzing the international instruments in terms of procreation of designer baby and would further analyze the position of Indian feasibility of the designer baby