Piperine Modulates High Fat Diet - Induced Renal Damage by Regulating Kim-1 and Igf-1 Beta Signaling Molecules in Male Wistar Rats

Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia and other symptoms which ultimately cause various other complications like retinopathy , micro angioplasty and nephropathy . piperine shows antidiabetic activity by improving insulin level, signifying its usage in the management of hyperglycemia. IGF-1 is the insulin-like growth factor receptor . KIM-1 has proved to be an outstanding early indicator of kidney injury in the rats. Induction of type 2 diabetes to male wistar albino rats , they were divided into four groups , one group were treated with piperine , fasting blood glucose was analysed. Biochemical analysis and mRNA expression analysis of KIM-1 and IGF-1 by RT-PCR is done. Fasting blood glucose and the serum insulin was elevated in diabetes induced rats . piperine-treated animals exhibited a significant decrease in the level of FBG and serum insulin from the above study, it could show that piperine possesses antidiabetic activity

Effect of Piperine on an Nrf2/Keap 1 Signalling Mechanism in Adipose Tissue of High Fat Diet and Sucrose-Induced Experimental Diabetic Rats

Piperine, an alkaloid compound found in black pepper has been shown to have various health benefits such as anti-oxidants, anti-inflammatory, and anticancer activities. But mechanisms underlying the anti-diabetic activity are unclear. Keap1-Nrf2 is an anti-oxidant stress signal pathway and it is considered to be an intracellular defence mechanism to countered oxidative stress. The study was aimed at assessing antidiabetic activity of piperine against high fat diet and sucrose-induced (HFD) type-2 diabetic rats by regulating the expression of Nrf2/Keap 1 signalling. Healthy adult male albino rats of wistar strain were grouped in to 5. Considering healthy control (group-1), HFD-induced type-2 diabetes (group2), Diabetic rats treated with piperine (group 3), diabetic rats metformin (group 4) and control +Piperine treated rats ( group 5) respectively. After 30 days of treatment, fasting blood glucose (FBG) checked and adipose tissue from control and treated groups was used to determine the role of piperine on the expression of NrF2/Keap 1 mNRA in adipose by Real Time-PCR analysis. Data were analysed by one-way ANOVA and p<0.01 was considered to be statistical significance among the groups. HFD-induced T2DM showed a significant increase in the levels of FBG and altered levels of Nrf-2 and Keap-1 gene expression (2 fold) compared to normal control animals. Piperine at a dose of 40mg, fascinatingly improved the glycemic control and normalised the mRNA expression of both Nrf-2 and Keap-1 whose effects were near to that of standard drug metformin level (p<0.05) proving its potential mechanism of action. Conclusion: Our current study clearly indicates that piperine controls hyperglycemia in type-2 diabetic rats by facilitating the expression of antioxidant signalling (Nrf-2/Keap-1) in the adipose. In addition, this is the first of its kind to show the role of piperine in reducing hyperglycemia against high fat diet and sucrose –induced type-2 diabetic rats as an invivo experimental model. Hence, piperine could be considered as an important health supplement and potential drug candidate for the treatment of diabetes

A Structural Equation Modelling Approach Towards Taxpayers’ Perceptions on Goods and Services Tax in India

Purpose: The Purpose of this article is to comprehend how Indian taxpayers perceive the goods and services tax.   Theoretical Framework: India has completed five years after the successful implementation of Goods and Services Tax (GST). Many economic benefits were promised at the time of implementation of this tax regime. Thus, it becomes essential to understand tax payers’ perceptions by developing a strong framework that influences their perceptions.   Design/Methodology/Approach: A descriptive study approach was adopted for this objective. 200 replies were obtained in total. Using SPSS Amos, structural equation modelling was utilised to assess the assumptions produced. Attitude, knowledge, Equity, and fairness of taxpayers served as exogenous factors, while taxpayer impression served as the dependent variable. The real-world implication is used as a mediating variable in order to examine the impacts.   Findings: The findings of the research indicate that tax knowledge, Equity, and fairness impact tax attitudes. This study provides some useful recommendations for further research in this sector.   Research Implications: This study considers tax knowledge, tax equity and fairness and tax attitudes to measure tax payers’ perception. However, tax rates, regular amendments, circulars, technology and other variables could also be considered by future researchers on this study.   Originality/Value: Using a Structural Equation Modelling in understanding Tax Payers’ Perceptions was hardly adopted in these types of studies. Variables considered for this study were also unique. &nbsp

Synthesis, characterization and biological evaluation of novel 2,5 substituted-1,3,4 oxadiazole derivatives

In the present study, a series of 3-(5-cyclohexyl-1,3,4-oxadiazol-2-yl)-N-substituted aniline have been synthesized by multistep reaction scheme. Benzohydrazide was used as the starting material. The structures of all synthesized compounds are characterized and confirmed by FT-IR, 1H and C13 NMR and mass spectral studies with the intention of developing the novel biologically active compounds. All title synthetic compounds were screened for their antidiabetic, anti-inflammatory and anticancer activities

Stunting and Underweight among Adolescent Girls of Indigenous Communities in Telangana, India: A Cross-Sectional Study

India’s indigenous groups remain vulnerable to malnutrition, despite economic progress, reflecting the reliance on traditional agriculture and the problems of poverty and inadequate education and sanitation. This mixed-methods study analyzed the incidence, causes and determinants of chronic malnutrition, measured through stunting, thinness and underweight among adolescent indigenous girls in Telangana. Using 2017 data on 695 girls aged 11–18 years from 2542 households, the analysis showed that 13% had normal nutritional status, while 87% were stunted, underweight or thin. Early adolescents (11–14 years) had higher underweight prevalence (24.4%), while late adolescents (15–18 years) showed greater stunting (30%). Regressions identified key influencing factors. Higher education levels of heads of households and the girls themselves alongside household toilet access significantly improved nutritional status and reduced stunting and underweight. The sociocultural emphasis on starchy staple-based diets and early marriage also impacted outcomes. Tackling this crisis requires mainstreaming nutrition across development agendas via comprehensive policies, education, communication and community participation. Further research can guide context-specific solutions. But, evidence-based investments in indigenous education, livelihoods, sanitation and women’s empowerment are the first steps. Nutrition-sensitive development is indispensable for indigenous groups to fully participate in and benefit from India’s progress

A Multiclass Fault Diagnosis Framework Using Context-Based Multilayered Bayesian Method for Centrifugal Pumps

The notion of predictive maintenance is perceived as a breakthrough in the manufacturing and other industrial sectors. The recent developments in this field can be attributed to the amalgamation of Artificial Intelligence- and Machine Learning (ML)-based solutions in predicting the health state of the machines. Most of the existing machine learning models are a hybridization of common ML algorithms that require extensive feature engineering. However, the real time deployment of these models demands a lower computational effort with higher accuracy. The proposed Multi-labeled Context-based Multilayered Bayesian Inferential (M-CMBI) predictive analytic classification framework is a novel approach that uses a cognitive approach by mimicking the brain’s activity, termed MisMatch Negativity (MMN), to classify the faults. This adaptive model aims to classify the faults into multiple classes based on the estimated fault magnitude. This model is tested for efficacy on the Pump dataset which contains 52 items of raw sensor data to predict the class into normal, broken and recovering. Not all sensor data will contribute to the quality of prediction. Hence, the nature of the sensor data is analyzed using Exploratory Data Analysis (EDA) to prioritize the significance of the sensors and the faults are classified based on their fault magnitude. The results of the classification are validated on metrics such as accuracy, F1-Score, Precision and Recall against state of art techniques. Thus, the proposed model can yield promising results without time-consuming feature engineering and complex signal processing tasks, making it highly favorable to be deployed in real-time applications

Adsorption and Inhibitive Properties of Triazolo- pyrimidine Derivatives in Acid Corrosion of Mild Steel

Inhibitive and adsorption properties of synthesized triazolo- pryimidine derivatives (P1, P2 & P3 ) for the corrosion of mild steel was investigated using weight loss and electrochemical methods. Inhibition efficiency increased as the concentration of the inhibitor increased but decreased with increase in temperature. The triazolopyrimidines were found to act as adsorption inhibitors for the corrosion of mild steel. The adsorption mechanism of the triazolopyrimidine was found to be physisorption, spontaneous and exothermic. Also the adsorption followed Langmuir adsorption isotherm. polarisation studies showed that the inhibitors behave as cathodic type

Virological investigation of hand, foot, and mouth disease in a tertiary care center in South India

Context: Hand, foot, and mouth disease (HFMD) remains a common problem in India, yet its etiology is largely unknown as diagnosis is based on clinical characteristics. There are very few laboratory-based molecular studies on HFMD outbreaks. Aim: The aim of this study was to characterize HFMD-related isolates by molecular techniques. Settings and Design: Between 2005 and 2008, during two documented HFMD outbreaks, 30 suspected HFMD cases presented at the Outpatient Unit of the Department of Dermatology, Christian Medical College (CMC), Vellore. Seventy-eight clinical specimens (swabs from throat, mouth, rectum, anus, buttocks, tongue, forearm, sole, and foot) were received from these patients at the Department of Clinical Virology, CMC, for routine diagnosis of hand, foot, and mouth disease. Materials and Methods: Samples from these patients were cultured in Vero and rhabdomyosarcoma (RD) cell lines. Isolates producing enterovirus-like cytopathogenic effect (CPE) in cell culture were identified by a nested reverse transcription-based polymerase chain reaction (RT-PCR) and sequenced. The nucleotide sequences were analyzed using the BioEdit sequence program. Homology searches were performed using the Basic Local Alignment Search Tool (BLAST) algorithm. Statistical Analysis used: The statistical analysis was performed using Epi Info version 6.04b and Microsoft Excel 2002 (Microsoft Office XP). Results: Of the 30 suspected HFMD cases, only 17 (57%) were laboratory confirmed and Coxsackievirus A16 (CVA16) was identified as the etiological agent in all these cases. Conclusions: Coxsackievirus A16 (CVA16) was identified as the virus that caused the HFMD outbreaks in Vellore between 2005 and 2008. Early confirmation of HFMD helps to initiate control measures to interrupt virus transmission. In the laboratory, classical diagnostic methods, culture and serological tests are being replaced by molecular techniques. Routine surveillance systems will help understand the epidemiology of HFMD in India

Cryptographic Encryption and Optimization for Internet of Things Based Medical Image Security

The expansion of the Internet of Things is expected to lead to the emergence of the Internet of Medical Things (IoMT), which will revolutionize the health-care industry (IoT). The Internet of Things (IoT) revolution is outpacing current human services thanks to its bright mechanical, economical, and social future. Security is essential because most patient information is housed on a cloud platform in the hospital. The security of medical images in the Internet of Things was investigated in this research using a new cryptographic model and optimization approaches. For the effective storage and safe transfer of patient data along with medical images, a separate framework is required. The key management and optimization will be chosen utilizing the Rivest–Shamir–Adleman-based Arnold map (RSA-AM), hostile orchestration (HO), and obstruction bloom breeding optimization (OBBO) to increase the encryption and decryption processes’ level of security. The effectiveness of the suggested strategy is measured using peak signal-to-noise ratio (PSNR), entropy, mean square error (MSE), bit error rate (BER), structural similarity index (SSI), and correlation coefficient (CC). The investigation shows that the recommended approach provides greater security than other current systems