Evaluation and comparison of anti-cancer activity of dapagliflozin and canagliflozin in oral cancer cell line: an in vitro study

Background: Cancer is rapidly evolving life-threatening ailment in the mankind due to changes in daily food intake and lifestyle changes. Oral carcinoma is 6th major cause of cancer death in the world and it is third major reason of cancer mortality in India. Every cell in the human body requires glucose for its metabolic energy. Besides normal cell, cancer cells also require the glucose for its endurance and multiplication. SGLT2 inhibitors which are aimed at diabetes therapy exhibited anticancer properties also in colon and pancreatic cancer lines. Present study aim is to evaluate the anticancer activity of SGLT2 inhibitors against oral cancer cell by MTT Assay.Methods: To evaluate the anticancer activity of SGLT2 inhibitors MTT Cytotoxic assay is performed as per standard protocols. Cancer cells were plated in 24-well plates and incubated at 370C with 5% CO2 condition. After convergence, samples are added to the plates in various concentrations and allowed to incubate then they are detached from the plates and cleansed with the reagents. The wells are coated with the dye and incubated. Later samples are analysed in UV-spectrophotometer.Results: Cytotoxic assay showed decrease in cell viability with increasing dose of SGLT2 inhibitors. IC50 values were determined graphically. The IC50 value of dapagliflozin is 400µg/ml and canagliflozin is 250µg/ml respectively after 24 hours of Assessment.Conclusions: The results of the current study give us an evidence that SGLT2 inhibitors dapagliflozin and canagliflozin exhibits anticancer property in Oral Cancer cell line

Method development and validation of aspirin and clopidogrel pharmaceutical dosage forms by developing new RP HPLC method

A simple and selective LC method is described for the determination of Aspirin and Clopidogrel in tablet dosage forms. Chromatographic separation was achieved on a c18 column along with mobile phase consisting of a combination of fifty five volumes of Mixed Phosphate Buffer and forty five volumes of Acetonitrile with detection of 235 nm. Linearity was observed in the range 20-60 μg/ml for Aspirin (r2=0.998) and 10-30 μg /ml for Clopidogrel (r2 =0.998) for the amount of drugs estimated by the projected ways was in smart agreement with the label claim. The proposed methods were validated. The accuracy of the methods was assessed by recovery studies at three different levels. Recovery experiments indicated the absence of interference from commonly encountered pharmaceutical additives. The method was found to be precise as indicated by the repeatability analysis, showing %RSD trials. All statistical data proves validity of the ways and may be used for routine analysis of pharmaceutical dosage form

A Study on Management of Health Care Infrastructure Development in Rural India: Critical analysis of current status and future challenges

The study has focused on the role of rural health infrastructure development in India. Currently the health infrastructure development of India is poor and it needs fundamental reforms to deal with new emerging challenges. The role of private providers is increasing but simultaneously healthcare facilities are becoming costly. The study surveys the present position of rural health care infrastructure growth, the development of infrastructure, health care facilities, position of human resource, and quality of service delivery. The paper suggests future challenges of Indian healthcare infrastructure development in rural area, as the burden of disease, financial deficiency in a large section of the population, vaccination policy and poor access to health care. Longevity, literacy and per capita income are further considerations

A novel RP – HPLC methodology for method development and validation of aceclofenac and tizanidine pharmaceutical dosage forms

A simple and selective LC technique is chosen for the determination of Aceclofenac and Tizanidine in pill indefinite quantity forms. Chromatographic process separation was achieved on a c18 column victimization mobile part consisting of a combination of fifty volumes of Triethylamine buffer, fifty volumes of acetonitrile with detection of 230nm. Dimensionality was discovered within the vary 5-15 µg/ml for aceclofenac (r2 =0.999) and 1-3 µg /ml for tizanidine (r2 =0.998) for the number of medicine calculable by the planned strategies was in smart agreement with the label claim. The planned strategies have a sound procedure. At three completely different levels the accuracy of the strategies was assessed by recovery studies. The recovery experiments indicated the absence of interference from unremarkably encountered pharmaceutical additives showing %RSD below a pair of this technique was found to be precise as indicated by the repeatability analysis. All applied mathematics information proves all ways have valid procedure and might be used for routine analysis of pharmaceutical dose kin

A Novel Fast Path Planning Approach for Mobile Devices using Hybrid Quantum Ant Colony Optimization Algorithm

With IoT systems' increasing scale and complexity, maintenance of a large number of nodes using stationary devices is becoming increasingly difficult. Hence, mobile devices are being employed that can traverse through a set of target locations and provide the necessary services. In order to reduce energy consumption and time requirements, the devices are required to traverse following a Hamiltonian path. This problem can be formulated as a Travelling Salesman Problem (TSP), an NP-hard problem. Moreover, in emergency services, the devices must traverse in real-time, demanding speedy path planning from the TSP instance. Among the well-known optimization techniques for solving the TSP problem, Ant Colony Optimization has a good stronghold in providing good approximate solutions. Moreover, ACO not only provides near-optimal solutions for TSP instances but can also output optimal or near-optimal solutions for many other demanding hard optimization problems. However, to have a fast solution, the next node selection, which needs to consider all the neighbors for each selection, becomes a bottleneck in the path formation step. Moreover, classical computers are constrained to generate only pseudorandom numbers. Both these problems can be solved using quantum computing techniques, i.e., the next node can be selected with proper randomization, respecting the provided set of probabilities in just a single execution and single measurement of a quantum circuit. Simulation results of the proposed Hybrid Quantum Ant Colony Optimization algorithm on several TSP instances have shown promising results, thus expecting the proposed work to be important in implementing real-time path planning in quantum-enabled mobile devices

Reinforcing Security and Usability of Crypto-Wallet with Post-Quantum Cryptography and Zero-Knowledge Proof

Crypto-wallets or digital asset wallets are a crucial aspect of managing cryptocurrencies and other digital assets such as NFTs. However, these wallets are not immune to security threats, particularly from the growing risk of quantum computing. The use of traditional public-key cryptography systems in digital asset wallets makes them vulnerable to attacks from quantum computers, which may increase in the future. Moreover, current digital wallets require users to keep track of seed-phrases, which can be challenging and lead to additional security risks. To overcome these challenges, a new algorithm is proposed that uses post-quantum cryptography (PQC) and zero-knowledge proof (ZKP) to enhance the security of digital asset wallets. The research focuses on the use of the Lattice-based Threshold Secret Sharing Scheme (LTSSS), Kyber Algorithm for key generation and ZKP for wallet unlocking, providing a more secure and user-friendly alternative to seed-phrase, brain and multi-sig protocol wallets. This algorithm also includes several innovative security features such as recovery of wallets in case of downtime of the server, and the ability to rekey the private key associated with a specific username-password combination, offering improved security and usability. The incorporation of PQC and ZKP provides a robust and comprehensive framework for securing digital assets in the present and future. This research aims to address the security challenges faced by digital asset wallets and proposes practical solutions to ensure their safety in the era of quantum computing

The Linear and Nonlinear Relationship between Infrastructure and FDI in India

The study examines the linear and nonlinear relationship between Infrastructure and FDI, to understand whether there is a significant difference or not concerning the FDI equity inflows to infrastructure projects. The ARDL and Granger causality methods to cointegration; propose the existence of long-run function in two-directional causalities between foreign direct investment and infrastructure, whereas the nonlinear autoregressive distributed lag (ARDL) validates the asymmetries in the relationship between FDI and Infrastructure. The outcomes of the study are that foreign direct investment inflows are significant to improve the infrastructure projects in various sectors, in the short-run and long run. As enlightening infrastructure is dynamic to attract FDI, outcomes will be predominantly valuable to policymakers and related to the emerging markets

Hypoxia and HIF-1α promote lytic de novo KSHV infection

The impact of different stress conditions on the oncogenic Kaposi's sarcoma-associated herpesvirus (KSHV) primary infection that can occur in vivo remains largely unknown. We hypothesized that KSHV can establish a latency or lytic cycle following de novo infection, depending on the conditions of the cellular environment. Previous studies showed that hypoxia is a natural stress condition that promotes lytic reactivation and contributes to KSHV pathogenesis, but its effect on de novo KSHV infection is unknown. To test the effect of hypoxia on KSHV infection, we infected cells under normoxia and hypoxia, performed a comparative analysis of viral gene expression and viral replication, and tested chromatinization of the KSHV genome during infection. We found that hypoxia induces viral lytic gene expression and viral replication following de novo infection in several biologically relevant cell types, in which the virus normally establishes latency under normoxia. We also found that hypoxia reduces the level of repressive heterochromatin and promotes the formation of a transcriptionally permissive chromatin on the incoming viral DNA during infection. We demonstrate that silencing hypoxia-inducible factor-1 alpha (HIF-1 alpha) during hypoxia abrogates lytic KSHV infection, while the overexpression of HIF-1 alpha under normoxia is sufficient to drive lytic KSHV infection. Also, we determined that the DNA-binding domain and the N-terminal but not the C-terminal transactivation domain of HIF-1 alpha are required for HIF-1 alpha-induced lytic gene expression. Altogether, our data indicate that HIF-1 alpha accumulation, which can be induced by hypoxia, prevents the establishment of latency and promotes lytic KSHV infection following primary infection

A New Method for Ball Tracking Based on α-β, Linear Kalman and Extended Kalman Filters Via Bubble Sort Algorithm

Object tracking is one of the challenging issues in computer vision and video processing, which has several potential applications. In this paper, initially, a moving object is selected by frame differencing method and extracted the object by segment thresholding. The bubble sort algorithm (BSA) arranges the regions (large to small) to make sure that there is at least one big region (object) in object detection process. To track the object, a motion model is constructed to set the system models of Alpha-Beta (α-β) filter, Linear Kalman filter (LKF) and Extended Kalman filter (EKF). Many experiments have been conducted on balls with different sizes in image sequences and compared their tracking performance in normal light and bad light conditions. The parameters obtained are the root mean square error (RMSE), absolute error (AE), object tracking error (OTE), Tracking detection rate (TDR), and peak signal-to-noise ratio (PSNR) and they are compared to find the algorithm that performs the best for two conditions