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FORMULATION, OPTIMIZATION, AND CHARACTERIZATION OF A THERMOSENSITIVE IN SITU NASAL GEL INCORPORATING CHITOSAN NANOPARTICLES OF ZOLMITRIPTAN FOR THE MANAGEMENT OF ACUTE MIGRAINE ATTACKS
Get PDFThe current study concentrated on creating and refining a zolmitriptan in situ thermosensitive nasal gel with chitosan nanoparticles for improved migraine treatment. Sodium tripolyphosphate (TPP) was used as the cross-linking agent in the ionic gelation process to create chitosan nanoparticles. To make a formulation that changes from sol to gel at nasal cavity temperature, the nanoparticle suspension was mixed with a gel matrix that contained Poloxamer 407 and Poloxamer 188. Particle size, zeta potential, mucoadhesive strength, gelation temperature, viscosity, gel strength, and in vitro drug release were all assessed for a number of formulations (TSGF1–TSGF7). Among the formulations, TSGF3 was identified as the best optimized due to its ideal gelation temperature (35.45 ± 0.37°C), balanced viscosity (493 cP at 40°C and 3523 cP at 34°C), and satisfactory mucoadhesive strength (3614 ± 14.82 dynes/cm²). The drug release study revealed that TSGF3 provided a sustained release of 90.79% over 420 minutes, indicating its potential for prolonged therapeutic effect. The drug and excipients did not significantly interact, according to FTIR analysis. These findings support that the zolmitriptan-loaded thermosensitive chitosan nanoparticle gel is a promising system for intranasal delivery, offering both rapid onset and sustained migraine relief through improved bioadhesion and controlled drug release
Hematological and Urine Analysis Changes in Pre and Post Hemodialysis Patients with Chronic Kidney Disease in a Tertiary Care Hospital in Puducherry- South India
Get PDFBackground: Chronic kidney disease (CKD) often necessitates hemodialysis, which can impact hematological and urine parameters. This study aims to evaluate the changes in these parameters in CKD patients undergoing hemodialysis at a tertiary care hospital in Puducherry.Methods: An observational study was conducted at a tertiary care hospital involving 55 CKD patients (44 males and 11 females) aged 29 to 80 years (mean age 58.11 ± 1.46 years). Hematological and urine samples were collected pre- and post-dialysis. Complete blood count, coagulation profiles, and urine analysis were carried out using automated machinery. The paired t-test assessed significant differences between pre- and post-dialysis values.Results: Post-dialysis, there was a significant increase in mean hemoglobin (Hb) levels (7.70 g/dL to 8.35 g/dL, P = 0.0009) and a slight, non-significant decrease in hematocrit (HCT) levels (25.62% to 24.24%, P = 0.2772). Platelet counts significantly decreased (186.1818 x103/μl to 162.3455 x103/μl, P = 0.0008), with a slight reduction in platelet distribution width (PDW). Clotting time significantly increased (4.117273 minutes to 4.291818 minutes, P = 0.0241). Red blood cell (RBC) indices remained stable, with minor changes in MCV, MCH, and MCHC. Urine analysis showed no significant differences in pre- and post-dialysis.Conclusion: Hemodialysis in CKD patients induces significant hematological changes, particularly in Hb concentration, platelet count, and coagulation parameters, without significant alterations in urine composition. Limitations include the small sample size and single-center design. Future research should involve larger, multi-center cohorts and longitudinal follow-up to understand long-term trends and outcomes better
INNOVATIVE PEDAGOGY AND ITS REGULATORY AND LEGAL FOUNDATIONS IN THE MODERN EDUCATIONAL PROCESS
Get PDFThis article explores the crucial role of innovative pedagogy in the modern educational process. The rapid development of science and technology necessitates the integration of new approaches, methods, and technologies into teaching and learning practices. Special attention is given to the regulatory and legal frameworks that support the modernization of education systems, enhance students’ creativity, and foster independent thinking
Phytochemical Investigation & Diuretic Activity of Tecoma Stans Leaf Extract
Get PDFTecoma stans leaves were collected, dried, and processed to obtain a Hydroethanolic extract using percolation. The extract was then administered to adult male Wistar rats in varying doses (250 mg/kg, 375 mg/kg, and 500 mg/kg) to evaluate its diuretic activity over 14 days. Furosemide, a standard diuretic drug, served as the positive control. Urine volume, pH, and diuretic index were measured on days 1st, 7th, and 14th. Histopathological examinations of kidney and liver tissues were conducted post-experiment. Additionally, molecular docking studies were performed to understand the binding interactions of the extract's bioactive compounds with target proteins.The study demonstrated that the Hydroethanolic extract of Tecoma stans significantly increased urine output in a dose-dependent manner. The highest dose (500 mg/kg) produced a diuretic index of 4.80 and a Lipschitz value of 0.65 on the 14th day, indicating potent diuretic activity comparable to the standard drug furosemide. Histopathological analysis revealed no adverse effects on the kidneys and liver. Molecular docking studies suggested strong binding affinities of the extract's bioactive compounds with diuretic target proteins.Tecoma stans leaf extract exhibits significant diuretic activity, suggesting its potential as a natural alternative for managing body fluids. Further research is warranted to isolate specific bioactive compounds and elucidate their mechanisms of action
EVALUATION OF AGRICULTURAL SOIL HEALTH INDEX FOR SUSTAINABLE NUTRIENT MANAGEMENT IN ARMORI OF GADCHIROLI DISTRICT (M.S.)
Get PDFPresent study has been conducted in the Armori region of Gadchiroli district, during December 2024 to February 2025, for assessments of soil fertility and microbial populations. Nine soil samples were collected from three villages (V1, V2, V3) and analyzed for pH, organic carbon, macronutrients (N, P, K, S), and micronutrients (Zn, Mn, Fe, Cu). Soil pH ranged from 5.2 to 7.85, with Waghada Burdi (V2) having the highest pH. Electrical conductivity varied from 0.08 to 0.22 dS/m, and nitrogen levels ranged from 275 kg/ha in Arsoda to 310 kg/ha in Waghada Burdi. The Soil Health Index (SHI) ranged from 0.30 to 0.65, with Waghada Burdi showing the best soil health. The SHI, which integrates soil organic carbon, pH, conductivity, nutrient content, and microbial activity, revealed nutrient imbalances requiring targeted nutrient management interventions. The study highlights the importance of site-specific strategies, including organic practices, balanced fertilization, and soil conservation, to enhance productivity and ensure sustainable agriculture in the region
Trimester Specific Thyroid Profile Reference Ranges for Pregnant Women in South Indian Population
Get PDFIntroduction:It is crucial to measure thyroid function throughout pregnancy to determine the health of the mother and foetus. However, a woman's thyroid hormone levels alter during pregnancy due to complex physiological changes. If typical reference ranges are not established it becomes challenging to interpret the thyroid profile during pregnancy. The goal of the study was to identify reference levels for thyroid hormone in healthy pregnancy in particular to each trimester.Aim and Objectives:•To study the trimester – specific thyroid profile hormones in pregnant women.•To estimate the level of thyroid hormones ranges in the first, second and third trimester pregnant women.•To establish trimester – specific reference ranges for TSH, free T3 (FT3), and free T4 (FT4) in apparently healthy pregnant women and to compare with standard reference ranges.Methodology:•This study was conducted in a tertiary care hospital at Puducherry with 270 pregnant women•Estimation of thyroid profile using Chemiluminescence immunoassay technique.Result:The normal ranges of thyroid hormone in first, second and third trimesters during normal pregnancy in our study were: total FT3 (2.27-2.79, 2.55-2.82, 2.73- 2.91pg/ml, total FT4 (1.53-2.73, 1.00-1.40, 1.07-1.20ng/dl) and total TSH (1.78-2.32, 2.01-2.56, 2.02-2.46μIU/ml) respectively.Conclusion:The levels of thyroid hormones in pregnancy not only show characteristic changes from non-pregnant state but also vary with each trimester. Hence, trimester specific reference ranges for thyroid hormone need to be defined to ensure correct interpretation of these tests
Deep Learning Techniques for Early Detection of Chronic Diseases Using Electronic Health Records
Get PDFDisease early diagnosis is especially important for chronic diseases to achieve a positive outcome for patients with such ailments and minimal costs for the treatment. The possibility of early diagnosis and intervention based on the large amount of patient data that can be found in EHRs is already quite high. In this research, deep learning approaches will be used to screen EHR databases for early identification of Chronic diseases including diabetes, hypertension, and cardiovascular diseases. In this talk, based on the CNNs, RNNs, and transformer models, we illustrate how these approaches can explore patterns and risk factors of chronic diseases compared to conventional methodologies. These predictions imply that deep learning trained on large EHR can be used to identify tendencies for chronic diseases’ emergence, thus allowing for timely diagnosis and first-person treatment strategies development. Additionally, the work underscores the need for the fundamental steps of data preprocessing, feature selection, and model interpretability to maintain the accuracy and the ethical application of these predictive models among clinicians
A Comparative Study on Gurukul System and Modern Educational System
Get PDFRole of education plays a very crucialrole in shaping one’s individual life and indirectly shapes society. It helps in transmitting knowledge, values, and skills across generations. Since history, educational systems have evolved in response to cultural, social, and technological changes. Since the inception the oldest and most revered forms of education in India is the Gurukul system, which dates back since the ancient times thousands of years ago and continues to be admired for its holistic approach to learning. These ancient Indian traditions, the Gurukul system has been emphasized on personal development, values, and spiritual growth alongside intellectual knowledge. The relationship between the Guru (teacher) and the shishya (Student) in this system was one of mentorship, where learning was imparted in a natural, informal setting often outside traditional classrooms, focusing on experiential and personalized education
Cross domain innovations in Electric vehicles: management of Energy and Connectivity challenges
Get PDFThe quick growth of electric vehicle (EV) infrastructure has created severe problems regarding energy management and connection.The combination of smart grid advancements along with battery chemistry research and vehicle communication systems must happenbecause of these barriers. The research explores contemporary methods and approaches dedicated to enhancing EV energyconsumption along with vehicle-to---everything (V2X) connectivity. Research analysis shows three key findings about carcommunication protocols as well as intelligent charging infrastructure and predictive energy control systems. This document presentsdescriptions of actual implementations together with substantial effect descriptions regarding green transport systems. A multimodalapproach is necessary to manage the interactions between interconnected vehicle systems and energy distribution networks according to the study outcomes
A STUDY ON PREDICTION OF DIABETES MELLITUS USING ARTIFICIAL NEURAL NETWORK, CLASSIFICATION AND REGRESSION TREE, LOGISTIC REGRESSION ALGORITHMS
Get PDFDiabetes Mellitus is a chronic metabolic disorder characterized by high blood glucose levels resulting from either insufficient insulin production or the body's inability to effectively use insulin. Early detection and prediction are crucial for effective management and prevention of complications. Artificial intelligence is increasingly being utilized in healthcare for the prediction, management, and diagnosis of various diseases. This study aims to predict diabetes risk using an Artificial Neural Network, Classification and Regression Tree, and Logistic Regression algorithms.Objective: To predict the risk of diabetes mellitus using Artificial Neural Network (ANN), Classification and Regression Tree (CART), and Logistic Regression algorithms.Methodology: This case-control study included 400 diabetes patients and 400 healthy controls, recruited from the Medicine OPD of an MGM hospital. A comprehensive dataset, incorporating demographic characteristics, lifestyle factors, and medical history, was collected and used for diabetes prediction. Predictive models—ANN, CART, and Logistic Regression—were developed and validated using cross-validation techniques. Model performance was assessed based on accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve.Results: The study found that physical activity, gender, diet, parental history of diabetes, and stress were significantly associated with the prevalence of diabetes. The results showed that the ANN model achieved an accuracy of 82.1%, Logistic Regression achieved 76.0%, and the CART model demonstrated the highest accuracy at 86.8%.Conclusion: The study highlights that the factors such as physical activity, gender, diet, and stress play a significant role in predicting diabetes risk, with the CART model offering the highest accuracy of 86.8%