STUDY OF THE IN-VITRO METABOLIC PROFILE OF AMLODIPINE IN HUMAN HEPATIC CELL LINE AND CHICKEN LIVER TISSUE USING LIQUID CHROMATOGRAPHY-MASS SPECTROMETRY/MASS SPECTROMETRY

ABSTRACTObjective: The main objective of this study was to investigate the in-vitro metabolic profile of Amlodipine (AMD) using normal human hepatic celllines and chicken liver tissue and to characterize the metabolites obtained using liquid chromatography-tandem mass spectrometry (LC-MS/MS).Methods: In the present study, the metabolic profile of AMD, a well-known calcium channel blocker, was investigated in normal human hepatic celllines and chicken liver tissue employing LC-MS/MS technique. The structural details on AMD metabolites were acquired using triple quadrupole massspectrometer (LCMS-8040, Shimadzu). The metabolites were produced by incubation of AMD with the human hepatic cell lines and chicken livertissue at 37 °C for 24 h. The incubated extracts were analyzed on LC-MS/MS and their product ion spectra were acquired, interpreted and tentativestructures were proposed.Results: Twelve Phase I and Phase II metabolites were successfully detected in the proposed study. The main metabolic changes observed were oxidativedeamination, N-acetylation, de-esterification, hydrogenation, de-methylation, aliphatic hydroxylation, and glucuronidation of dehydrogenated AMD.Based on this information, the tentative structures of the metabolites were postulated.Conclusion: The in-vitro metabolites of AMD were successfully investigated and characterized in human hepatic cell lines and chicken liver tissue.Furthermore, both models were found to be equally effective for carrying out the in-vitro metabolic study of AMD.Keywords: Amlodipine, Metabolites, Hepatic cell lines, Chicken liver tissue, Liquid chromatography, Liquid chromatography-mass spectrometry/mass spectrometry

INVESTIGATION OF IN VITRO METABOLITES OF ETODOLAC IN HUMAN HEPATIC CELL LINE AND CHICKEN LIVER TISSUE USING LC-MS/MS

Objective: The main objective of this study was to investigate the in vitro metabolic profile of etodolac (ETD) using normal human hepatic cell lines and chicken liver tissue, and to characterize the metabolites obtained using Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS).Methods: In the present study, the metabolic profile of ETD, a well-known non-steroidal anti-inflammatory drug (NSAID), was investigated in normal human hepatic cell lines and chicken liver tissue employing LC-MS/MS technique. The structural details on ETD metabolites were acquired using triple quadrupole mass spectrometer (LCMS-8040, Shimadzu). The metabolites were produced by incubation of ETD with the human hepatic cell lines and chicken liver tissue, at 37 °C for 24 h. The incubated extracts were analyzed with LC-MS/MS and their production spectra were acquired, interpreted and tentative structures were proposed.Results: Six phase I and phase II metabolites were successfully detected in the proposed study. The metabolic changes observed included-oxidation, N-acetylation, hydrogenation, decarboxylation, methylation and glucuronidation of dehydrogenated ETD. The tentative structures of the metabolites were postulated based on the chemical reactions predicted and the LC-MS/MS data obtained.Conclusion: The in vitro metabolites of ETD were successfully investigated and characterized in human hepatic cell lines and chicken liver tissue. Also, both the models were found to be equally effective for carrying out the in vitro metabolic study of ETD.Keywords: Etodolac, Metabolites, Hepatic cell lines, Chicken liver tissue, LC, LC-MS/M

Potential Role of Cancer Stem Cells in Glioblastoma: A Therapeutic Aspect

High-grade glioma (HGG) such as glioblastoma multiforme (GBM) is an aggressive brain tumor that is still associated with poor prognosis. With the discovery and advancement in understanding of cancer stem cells (CSC) in glioma, these cells have emerged as seed cells for tumor growth and recurrence and appear as a potential target for therapeutics. Glioma stem cells (GSCs) demonstrate capacity of self-renewal, proliferation, and differentiation into multiple cell types and can contribute to tumor heterogeneity. Their role is established in tumorigenesis, metastasis, chemo- and radio-resistance and appears as a major cause for tumor recurrence. Thus, targeting GSCs by various therapeutics may improve effectiveness of the drugs in use alone or in combination to significantly improve patient survival outcome in GBM cases. In this chapter, we have discussed various mechanisms that drive GSC including signaling pathways and tumor microenvironment. We have also discussed the mechanism behind resistance of GSCs toward therapeutics and the pathways that can be targeted to improve the outcome of the patients

Improving detection of false data injection attacks using machine learning with feature selection and oversampling

Critical infrastructures have recently been integrated with digital controls to support intelligent decision making. Although this integration provides various benefits and improvements, it also exposes the system to new cyberattacks. In particular, the injection of false data and commands into communication is one of the most common and fatal cyberattacks in critical infrastructures. Hence, in this paper, we investigate the effectiveness of machine-learning algorithms in detecting False Data Injection Attacks (FDIAs). In particular, we focus on two of the most widely used critical infrastructures, namely power systems and water treatment plants. This study focuses on tackling two key technical issues: (1) finding the set of best features under a different combination of techniques and (2) resolving the class imbalance problem using oversampling methods. We evaluate the performance of each algorithm in terms of time complexity and detection accuracy to meet the time-critical requirements of critical infrastructures. Moreover, we address the inherent skewed distribution problem and the data imbalance problem commonly found in many critical infrastructure datasets. Our results show that the considered minority oversampling techniques can improve the Area Under Curve (AUC) of GradientBoosting, AdaBoost, and kNN by 10–12%

Cell specific apoptosis by RLX is mediated by NFκB in human colon carcinoma HCT-116 cells

BACKGROUND: Resistance to chemotherapy represents a major obstacle in correcting colorectal carcinomas (CRC). Inspite of recent advances in the treatment of metastatic disease, the prognosis of the patients remains poor. RLX, a vasicinone analogue has been reported to possess potent bronchodilator, anti-asthmatic and anti-inflammatory properties. However, its anti-cancer activity is unknown. RESULTS: Here, we report for the first time that RLX has anti-cancer property against panel of human cancer cell lines and most potent activity was found against HCT-116 cells with IC(50) value of 12 μM and have further investigated the involvement of NFκB and caspase-3 in RLX action in CRC apoptosis. Following RLX and BEZ-235 treatment in HCT-116, we observed significant down-regulation of NFκB (1 to 0.1 fold) and up-regulation of caspase-3 (1 to 2 fold) protein expressions. Additionally, morphological studies revealed membrane blebbing, cell shrinkage, chromatin condensation and finally apoptosis in HCT-116 cells. CONCLUSIONS: Overall, these findings indicate that RLX is a potent small molecule which triggers apoptosis, and promising potential candidate to be a chemotherapeutic agent

Assessment of Vaccine Wastage during a Pulse Polio Immunization Programme in India

A study to assess the wastage factor of oral polio vaccine (OPV) in the Pulse Polio Immunization (PPI) programme of the Government of India was undertaken by the Indian Council of Medical Research (ICMR) at approximately 31,000 immunization booths all over the country. The study was conducted through the network of 31 Human Reproduction Research Centres (HRRCs) and other ICMR institutes. Wastage at the point of administration of OPV was estimated to be 14.5% with a wastage factor of 1.17 which is well below the assumed wastage of 33% and the corresponding wastage factor of 1.5 in the PPI programme. The wastage and wastage factor as estimated in the present study were also less than the wastage of 25% and the wastage factor of 1.33 recommended by the World Health Organization. Minimum wastage (6.3%) at Kanchipuram and maximum wastage (22.1%) at Kanpur were observed. Further, the wastage of unopened vials and vials during use was also observed following colour changes on the vaccine vial monitor (VVM), indicating poor coldchain maintenance at the immunization site. In total, 13 booths reported wastage of nine or more unopened vials, whereas 19 booths reported wastage of nine or more vials during use because of colour changes on VVM. Other reasons for wastage of vaccine were also observed from a sample of booths. The technology of introducing VVM on OPV vials for monitoring the cold-chain proved useful in situations in which mass vaccination programmes such as PPI are carried out

Numerical Investigation of the Performance of Three Hinge Designs of Bileaflet Mechanical Heart Valves

Thromboembolic complications (TECs) of bileaflet mechanical heart valves (BMHVs) are believed to be due to the nonphysiologic mechanical stresses imposed on blood elements by the hinge flows. Relating hinge flow features to design features is, therefore, essential to ultimately design BMHVs with lower TEC rates. This study aims at simulating the pulsatile three-dimensional hinge flows of three BMHVs and estimating the TEC potential associated with each hinge design. Hinge geometries are constructed from micro-computed tomography scans of BMHVs. Simulations are conducted using a Cartesian sharp-interface immersed-boundary methodology combined with a second-order accurate fractional-step method. Leaflet motion and flow boundary conditions are extracted from fluid–structure-interaction simulations of BMHV bulk flow. The numerical results are analyzed using a particle-tracking approach coupled with existing blood damage models. The gap width and, more importantly, the shape of the recess and leaflet are found to impact the flow distribution and TEC potential. Smooth, streamlined surfaces appear to be more favorable than sharp corners or sudden shape transitions. The developed framework will enable pragmatic and cost-efficient preclinical evaluation of BMHV prototypes prior to valve manufacturing. Application to a wide range of hinges with varying design parameters will eventually help in determining the optimal hinge design

Simulation of the Three-Dimensional Hinge Flow Fields of a Bileaflet Mechanical Heart Valve Under Aortic Conditions

Thromboembolic complications of bileaflet mechanical heart valves (BMHV) are believed to be due to detrimental stresses imposed on blood elements by the hinge flows. Characterization of these flows is thus crucial to identify the underlying causes for complications. In this study, we conduct three-dimensional pulsatile flow simulations through the hinge of a BMHV under aortic conditions. Hinge and leaflet geometries are reconstructed from the Micro-Computed Tomography scans of a BMHV. Simulations are conducted using a Cartesian sharp-interface immersed-boundary methodology combined with a second-order accurate fractional-step method. Physiologic flow boundary conditions and leaflet motion are extracted from the Fluid–Structure Interaction simulations of the bulk of the flow through a BMHV. Calculations reveal the presence, throughout the cardiac cycle, of flow patterns known to be detrimental to blood elements. Flow fields are characterized by: (1) complex systolic flows, with rotating structures and slow reverse flow pattern, and (2) two strong diastolic leakage jets accompanied by fast reverse flow at the hinge bottom. Elevated shear stresses, up to 1920 dyn/cm2 during systole and 6115 dyn/cm2 during diastole, are reported. This study underscores the need to conduct three-dimensional simulations throughout the cardiac cycle to fully characterize the complexity and thromboembolic potential of the hinge flows

Nutrition, atherosclerosis, arterial imaging, cardiovascular risk stratification, and manifestations in COVID-19 framework: a narrative review.

Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment