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Carboplatin-loaded zeolitic imidazolate framework-8: Induction of antiproliferative activity and apoptosis in breast cancer cell
The challenge with breast cancer is its ongoing high prevalence and difficulties in early detection and access to effective care. A solution lies in creating tailored metalorganic frameworks to encapsulate anticancer drugs, enabling precise and targeted treatment with less adverse effects and improved effectiveness. Zeolitic imidazolate framework-8 (ZIF-8) and carboplatin (CP)-loaded ZIF-8 were synthesized and characterized using various analytical techniques. High Resolution-transmission electron microscopy of ZIF-8 and CP@ZIF-8 indicates that the particles had a spherical shape and were nanosized. The drug release rate of CP is 98% under an acidic medium (pH 5.5) because of the dissolution of ZIF-8 into its coordinating ions, whereas 35% in a physiological medium (pH 7.4) with the addition of CP, the high porosity, and pore diameter of ZIF-8 decrease from 1243 to 1041m2/g. Breast cancer MCF-7 cells were shown greater IC50 in CP@ZIF-8 (15.013.03g/mL) than free CP (34.984.25g/mL) in an in vitro cytotoxicity assessment. The cytotoxicity of the CP@ZIF-8 against MCF-7 cells was studied using the methylthiazolyldiphenyl-tetrazolium bromide method. The morphological changes were examined using fluorescent staining (acridine orangeethidium bromide and Hoechst 33258) methods. The comet assay assessed the DNA fragmentation (single-cell gel electrophoresis). The results from the study revealed that CP@ZIF-8 can be used in the treatment of breast cancer. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Unveiling the Redox Characteristics of Rutin Trihydrate-Canvas-Based Sensor for Hydrazine Sensing in Water Samples
The inclusion of redox mediators into electrocatalytic systems facilitates rapid electron shuttling kinetics and boosts the overall catalytic performance of the electrode. This approach overcomes the sluggish reaction dynamics associated with direct electron transfer, which may be impeded by restricted analyte access to the electrodes active sites. In contrast to conventional synthetic redox mediators, naturally sourced phytomolecule rutin trihydrate (RT), extracted from apple juice, offers potential ecological advantages. This bands with green chemistry principles and sustainability in electroanalytical approaches. The current work presents an eco-friendly and direct electrochemical approach to fabricate a redox-active RT-immobilized MWCNT-infused PEDOT hybrid material-modified glassy carbon electrode (GCE/MWCNT + PEDOT@RT). The developed electrode showcased a sharp and stable redox signal at E0 = 0.63 V vs Ag/AgCl with no surface-fouling characteristics. The efficacious functionalization of RT onto MWCNT + PEDOT was corroborated by a remarkable increase in the surface characteristics, enhanced electrochemical current responses, and low charge transfer resistance. The GCE/MWCNT + PEDOT@RT exhibited highly selective and sensitive sensing responses toward the toxic and potentially carcinogenic hydrazine (HZ) via cyclic voltammetry and differential pulse voltammetry techniques, yielding a low detection limit (DL) of 1.02 ?M and a sensitivity of 0.032 ?A ?M-1 in a linear dynamic range between 0 and 1350 ?M. In addition, the method was highly efficient for HZ detection in real samples of tanker, tap, and wastewater samples, producing a good recovery of ?98%. 2025 American Chemical Society. -
Advanced Machine Vision Paradigms for Medical Image Analysis
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. 2020 Elsevier Inc. All rights reserved. -
Dual drug co-encapsulation of bevacizumab and pemetrexed clocked polymeric nanoparticles improves antiproliferative activity and apoptosis induction in liver cancer cells
Nanoparticle (NP) enabled approaches have been employed for chemotherapeutic administration due to their capacity to regulate drug release and reduce side effects. Additionally, these methods can use several drugs concurrently and impede the proliferation of cancer cells that have developed resistance. Bevacizumab (BVZ) and pemetrexed (PEM) have demonstrated encouraging outcomes in the treatment and management of cancer. This work investigates the combined antiproliferative efficacy of BVZ and PEM co-loaded PLGA-PEG NPs (BVZ/PEM@PLGA-PEG NPs) against HepG2 liver cancerous cells. The BVZ/PEM@PLGA-PEG exhibited a sphere-shaped and consistent nanosized distribution. In addition, we evaluated the potential mechanisms for inhibiting cell growth and inducing apoptosis using DAPI staining and cell cycle study. The beneficial combined antiproliferative activity and the apoptosis pathway were detected in the HepG2 cells exposed to BVZ/PEM@PLGA-PEG NPs. Our study determined that the combinational drug treatment of BVZ/PEM@PLGA-PEG NPs has a significant effect on promoting the effectiveness of liver cancer treatment. 2024 Wiley Periodicals LLC. -
Construction of Sorafenib Tosylate and Etoposide-loaded Liposomes: A Path to Precision Liver Cancer Therapy and its Apoptosis Induction
Nanotechnology is an effective tool in fighting against cancer, playing a crucial role in investigating and fabricating novel anticancer drugs. Recognizing the worldwide prevalence of cancer, we combined sorafenib tosylate (ST) and etoposide (ETP) within liposomes. We assessed their ability to kill human umbilical vein endothelial cells (HUVECs) and HepG2 liver cancer cells. The liposomes effectively contained ST and ETP, exhibiting a particle size distribution below 180nm, a polydisperse index (PDI) below 0.2, a spherical shape, a strong negatively charged zeta potential, and encapsulation efficiencies of 59% for ST, 88% for ETP, and 57% for ST combined with 87% for ETP. The FTIR analysis indicates that the drugs were incorporated within liposomes. Encapsulation of the drugs in liposomes resulted in a more significant cytotoxic impact on HepG2 cells and a reduced cytotoxic impact on HUVECs. The morphological assessment of the HepG2 liver cancer cells was investigated using AO-EB and Hoechst 33258 staining methods. Apoptosis mechanisms of HepG2 cells were examined by Annexin V and PI dual staining. Furthermore, the coadministration of ST and ETP, which were enclosed in liposomes, resulted in a synergistic impact on the drugs, leading to cell death by apoptosis. 2024 Wiley-VCH GmbH. -
Effectiveness and Perception of 4P's on Green Products in FMCG
International Journal of Multidisciplinary Research and Development, Vol. 3, Issue 11, pp. 311-355, ISSN No. 2349-4182 -
Dynamic Pricing in Airline Industry
Asian Journal of Research in Business Economics and Management, Vol. 7, Issue 1, pp. 15-29, ISSN No. 2249-7307 -
Implementing quality healthcare strategies for improving service delivery at private hospitals in India /
Journal of Health Management, ISSN No. 0972-0634. -
Information Extraction Using Data Mining Techniques For Big Data Processing in Digital Marketing Platforms
In the dynamic landscape of digital marketing, harnessing the potential of big data has become paramount for informed decision-making. This study explores the integration of data mining techniques within big data processing frameworks to extract valuable information in digital marketing platforms. With the exponential growth of data generated through online interactions, social media, and e-commerce, traditional methods fall short of uncovering meaningful insights. This research focuses on leveraging advanced data mining algorithms to sift through vast datasets, identifying patterns, trends, and user behaviours. The proposed approach aims to enhance marketing strategies by extracting actionable intelligence from diverse data sources. Techniques such as association rule mining, clustering, and sentiment analysis will be employed to unveil hidden correlations, segment target audiences, and gauge consumer sentiment. The scalability of big data frameworks ensures efficient processing of massive datasets, allowing marketers to make real-time, data-driven decisions. Additionally, the study explores the challenges and opportunities associated with implementing data mining in big data environments for digital marketing. This research contributes to the evolving field of digital marketing by providing a comprehensive framework for extracting, processing, and utilizing information from big data. The findings promise to empower marketers with a deeper understanding of consumer behaviour, enabling the development of more personalized and effective marketing strategies in the ever-evolving digital ecosystem. 2023 IEEE. -
An Aqueous Phase TEMPO-Mediated Electrooxidation of Benzyl Alcohol at ?-CD-PPy-Modified Carbon Fibre Paper Electrode
A green and facile electrocatalytic method for the oxidation of benzyl alcohol in an acidic aqueous medium was developed using an anionic micellar system. ?-cyclodextrin-polypyrrole-modified carbon fibre paper (?-CD-PPy/CFP) electrode was successfully used in the oxidation of benzyl alcohol with TEMPO as the mediator. The modified electrode was characterized by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. The modified electrode exhibited a strong electrocatalytic activity towards TEMPO-mediated oxidation of benzyl alcohol. [Figure not available: see fulltext.]. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Effect of nonlinear thermal radiation on double-diffusive mixed convection boundary layer flow of viscoelastic nanofluid over a stretching sheet
Background: The present exploration deliberates the effect of nonlinear thermal radiation on double diffusive free convective boundary layer flow of a viscoelastic nanofluid over a stretching sheet. Fluid is assumed to be electrically conducting in the presence of applied magnetic field. In this model, the Brownian motion and thermophoresis are classified as the main mechanisms which are responsible for the enhancement of convection features of the nanofluid. Entire different concept of nonlinear thermal radiation is utilized in the heat transfer process. Methods: Appropriate similarity transformations reduce the nonlinear partial differential system to ordinary differential system which is then solved numerically by using the RungeKuttaFehlberg method with the help of shooting technique. Validation of the current method is proved by having compared with the preexisting results with limiting solution. Results: The effect of pertinent parameters on the velocity, temperature, solute concentration and nano particles concentration profiles are depicted graphically with some relevant discussion and tabulated result. Conclusions: It is found that the effect of nanoparticle volume fraction and nonlinear thermal radiation stabilizes the thermal boundary layer growth. Also it was found that as the Brownian motion parameter increases, the local Nusselt number decreases, while the local friction factor coefficient and local Sherwood number increase. The Author(s). 2017. -
Radiative heat transfers of Carreau fluid flow over a stretching sheet with fluid particle suspension and temperature jump
The current study is to deliberate the flow and heat transfer of a Carreau fluid over a stretching sheet with fluid particle suspension. The temperature jump is also taken into account. The standard nonlinear system is resolved numerically via Runge-Kutta based shooting scheme. Role of substantial parameters on flow fields as well as on the fiction factor and heat transportation rates are determined and conferred in depth through graphs. It's found that the velocity profile decreases and temperature profile increases, with an increasing the values of Weissenberg parameter. Further, the higher thermal slip parameter reduces the thermal boundary layer thickness. The thermal boundary layer thickness of fluid and dust particles decreases with the rise in Prandtl number. 2017 The Authors -
MHD flow and nonlinear thermal radiative heat transfer of dusty prandtl fluid over a stretching sheet
Boundary layer flows and melting heat transfer of a Prandtl fluid over a stretching surface in the presence of fluid particle suspensions has been investigated. The converted set of boundary layer equations are solved numerically by RKF-45 method. Obtained numerical results for flow and heat transfer characteristics are deliberated for various physical parameters. Furthermore, the skin friction coefficient and Nusselt number are also presented in Tabs. 2 and 3. It is found that the heat transfer rates are advanced in occurrence of nonlinear radiation compered to linear radiation. Also, it is noticed that velocity and temperature profile increases by increasing Prandtl parameter. 2020 Tech Science Press. -
IoT and wearables for detection of COVID-19 diagnosis using fusion-based feature extraction with multikernel extreme learning machine
Presently, wearables act as a vital part of healthcare sector and they are able to offer exclusive perceptions about the person's health conditions. In contrast to traditional diagnosis in a hospital environment, wearables can give unrestricted access to real-time physiological data. COVID-19 epidemic is increasing at a faster rate with limited test kits. Hence, it becomes essential to develop a novel COVID-19 diagnostic model. Numerous studies were based on the utilization of artificial intelligence techniques on radiological images to precisely identify the disease. This chapter presents an efficient fusion-based feature extraction with multikernel extreme learning machine (FFE-MKELM) for COVID-19 diagnosis using internet of things (IoT) and wearables. Primarily, the wearables and IoT are used to capture the radiological images of the patient. The presented FFE-MKELM model incorporates Gaussian filtering based preprocessing for removing the noise that exists in the radiological image. Besides, directional local extreme patterns with deep features based on Inception v4 model are applied for the FFE process. In addition, MKELM model is utilized as a classification model to determine the appropriate class label of the input radiological images. Moreover, monarch butterfly optimization algorithm is applied to fine tune the parameters involved in the MKELM model. Experimental validation of the FFE-MKELM model is performed against benchmark dataset and the outcomes are inspected under different measures. The resultant simulation outcome ensured the betterment of the FFE-MKELM method by demonstrating an increased sensitivity of 97.34%, specificity of 97.26%, accuracy of 97.14%, and F-measure of 97.01%. 2022 Elsevier Inc. All rights reserved. -
A Survey Instrument for Ranking of the Critical Success Factors for the Successful ERP Implementation at Indian SMEs
Bioinfo Business Economics, Vol-1 (1), pp. 06-12. ISSN-2249-1775 -
Accessing the role of critical success factors for successful ERP implementation at Indian SMEs: A statistical validation
Indian SMEs are also integral part of Indian economy; they also face numerous challenges in implementing technologies such as enterprise resource planning (ERP) systems, including a lack of human, technical and financial resources to support such initiatives. Like many other technological advances, ERP systems were initially implemented mostly at large organisations even in India. Their relative absence from Indian SMEs has probably been the main reason for the research focus on large Indian enterprise. A model is developed with the help of quantitative survey-based method to identify and rank the 30 CSFs and, then a framework has been proposed in terms of recommendations for managing these CSFs. It was determined whether the survey instrument was complete and clear or not with the help of pre-pilot survey of 30 questionnaires responses from the Indian ERP consultants. As a result, the initial survey instrument was extensively revised. For the final data collection, new revised survey instruments were then given via a survey to 500+ Indian ERP consultants. Copyright 2013 Inderscience Enterprises Ltd. -
Perception of online adult education in different countries
Adult education has gained immense popularity during a pandemic. Adult learners are able to meet their educational requirements through online education. Adult learners also prefer online education due to convenience and self-learning interests. Online education also poses challenges and discomfort to online learners. Statistics indicate a higher dropout rate among adult online learners due to various factors. This chapter focuses on the significant challenges adult online learners face and has identified tools, strategies, and techniques to empower and motivate them. This chapter will also help us to understand how tools and techniques, such as information and communication technology, allow us to increase the number of such learners in different countries. Information and communication technology tools are used in developed and developing countries to encourage and motivate adult learners to improve their education virtually at their convenience. 2023, IGI Global. All rights reserved. -
EFFICIENT NON-DEGRADABLE WASTE PROCESSING TECHNOLOGIES INTEGRATED WITH MANETS FOR SUSTAINABLE WASTE MANAGEMENT MODELS
In order to handle the growing amount of non-biodegradable trash, creative and sustainable solutions are becoming more and more necessary as the global waste management challenge grows. To create a complete and sustainable waste management model, this investigation suggests a revolutionary approach that combines Mobile Ad-hoc Networks (MANETs) with effective non-degradable waste processing technology. Utilising cutting-edge waste processing technology that can efficiently handle non-biodegradable materials including plastic, e-waste, and other persistent pollutants is the main goal of this. With the goal of reducing their negative effects on the environment and advancing the concepts of circular economy, these technologies include sophisticated sorting systems, chemical treatments, and recycling procedures. Furthermore, the efficiency and real-time monitoring of waste processing processes are improved by the incorporation of MANETs into the waste management paradigm. MANETs enable smooth data transmission and communication between the central control centres, waste processing units, and monitoring sensors that make up the waste management system. Because of this connectedness, waste processing activities can be dynamically optimised, facilitating prompt resource allocation and decision-making. In addition to addressing the environmental issues raised by non-biodegradable garbage, the suggested paradigm advances the creation of intelligent and networked waste management systems. Because MANETs are used, the system is scalable and adaptable, making it appropriate for a variety of urban and rural areas. The model incorporates the Ant Colony Optimisation (ACO) algorithm for resource allocation. The integration of ACO optimises resource allocation, contributing to the reduction of environmental footprints associated with waste processing. The interconnectedness facilitated by MANETs, in conjunction with ACO, enables dynamic optimisation of waste processing operations, ensuring prompt resource allocation and decision-making. This investigation envisions a sustainable waste management model that minimises pollution, promotes resource recovery, and establishes a robust framework for addressing the growing challenges of non-degradable waste on a global scale by combining cutting-edge waste processing technologies with a strong communication infrastructure. The results of the investigation have a significant impact on waste management procedures by encouraging a more ecologically friendly and sustainable way to deal with non-biodegradable garbage. 2024, Scibulcom Ltd. All rights reserved. -
Consumer perception and acceptance of minute maid pulpy orange in puducherry
International Journal of Management & Business Studies, 3 (2), pp. 119-121. ISSN-2230-2463 -
Development of perceived prenatal maternal stress scale
Background: Pregnancy is a state, which is often associated with extreme joy and happiness. Women undergo a number of physiological and psychological changes during pregnancy, which are often stressful if aligned with other adverse life events, compromising their health and well-being. However, there exists no comprehensive psychological instruments for measuring this stress. Objectives: The study was conducted to develop a multidimensional scale to assess prenatal maternal stress (PNMS) comprehensively. Methods: The initial phase of the study focuses on developing items and assessing the content validity of these items. The second phase focuses on pilot-testing and field-testing the newly developed perceived PNMS scale (PPNMSS) among 356 pregnant women belonging to different parity and trimester from November 2015 to October 2016. Results: The underlying factor structure of the 28-item PPNMSS had explored using exploratory factor analysis. The final scale is retained with 15 items having considerable item loading under four major factors as follows: perceived social support, pregnancy-specific concerns, intimate partner relations, and financial concerns. Reliability of each of these dimensions was assessed using Cronbach's alpha. Convergent and divergent validity of the scale was assessed by correlating the scores with perceived stress scale and the World Health Organization (five) well-being index (1998 version). Conclusions: As a comprehensive scale, PPNMSS is efficient to measure PNMS, which facilitates an early detection of stress and depression among pregnant women and timely intervention by health care professionals.