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Institution

Parul Institute of Engineering and Technology

Education
About: Parul Institute of Engineering and Technology is a based out in . It is known for research contribution in the topics: Cloud computing & Encryption. The organization has 687 authors who have published 569 publications receiving 1905 citations.


Papers
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Journal ArticleDOI
TL;DR: A simplified view of the types and physiology of various glucose transporters is presented, which may be of interest to researchers involved in biochemical and pharmacological research.
Abstract: Glucose is a primary energy source for most cells and an important substrate for many biochemical reactions. As glucose is a need of each and every cell of the body, so are the glucose transporters. Consequently, all cells express these important proteins on their surface. In recent years developments in genetics have shed new light on the types and physiology of various glucose transporters, of which there are two main types—sodium–glucose linked transporters (SGLTs) and facilitated diffusion glucose transporters (GLUT)—which can be divided into many more subclasses. Transporters differ in terms of their substrate specificity, distribution and regulatory mechanisms. Glucose transporters have also received much attention as therapeutic targets for various diseases. In this review, we attempt to present a simplified view of this complex topic which may be of interest to researchers involved in biochemical and pharmacological research.

227 citations

Journal ArticleDOI
TL;DR: The in-vivo pharmacokinetic studies revealed increased concentration of the drug in brain, as desired, when administered through intranasal route indicating its potential for an attempt towards complete eradication of HIV and cure of HIV-infected patients.
Abstract: The nonnucleoside reverse transcriptase inhibitors, used for the treatment of HIV infections, are reported to have low bioavailability pertaining to high first-pass metabolism, high protein binding, and enzymatic metabolism. They also show low permeability across blood brain barrier. The CNS is reported to be the most important HIV reservoir site. In the present study, solid lipid nanoparticles of efavirenz were prepared with the objective of providing increased permeability and protection of drug due to biocompatible lipidic content and nanoscale size and thus developing formulation having potential for enhanced bioavailability and brain targeting. Solid lipid nanoparticles were prepared by high pressure homogenization technique using a systematic approach of design of experiments (DoE) and evaluated for particle size, polydispersity index, zeta potential, and entrapment efficiency. Particles of average size 108.5 nm having PDI of 0.172 with 64.9% entrapment efficiency were produced. Zeta potential was found to be −21.2 mV and the formulation was found stable. The in-vivo pharmacokinetic studies revealed increased concentration of the drug in brain, as desired, when administered through intranasal route indicating its potential for an attempt towards complete eradication of HIV and cure of HIV-infected patients.

115 citations

Journal ArticleDOI
TL;DR: In this paper, the phase contrast imaging of otherwise transparent objects is used to study the dynamics of phase objects in a digital holographic microscopy (DHM) system, where the Angular Spectrum Propagation (ASP) approach to scalar diffraction theory is used for numerical reconstruction of holograms.
Abstract: Digital holography is a very effective tool for three- dimensional imaging of objects, since it yields the phase information directly without the need for additional optics. Another advantage is that of numerical focusing, allowing one to focus on to any desired plane. It has been used for microscopy with high effectiveness. One of the important features of digital holographic microscopy (DHM) is that it can be used for phase contrast imaging of otherwise transparent objects. This aspect of DHM is utilized here to study the dynamics of phase objects. Angular spectrum propagation (ASP) approach to scalar diffraction theory is used for numerical reconstruction of holograms.

74 citations

Journal ArticleDOI
TL;DR: This review summarizes the current understanding on MAO‐A/MAO‐B including their structure, catalytic mechanism, and biological functions with emphases on the role of MAo‐B as a potential therapeutic target for the development of medications treating neurodegenerative disorders.
Abstract: Monoamine oxidase (MAO) inhibitors have made significant contributions and remain an indispensable approach of molecular and mechanistic diversity for the discovery of antineurodegenerative drugs. However, their usage has been hampered by nonselective and/or irreversible action which resulted in drawbacks like liver toxicity, cheese effect, and so forth. Hence, the search for selective MAO inhibitors (MAOIs) has become a substantial focus in current drug discovery. This review summarizes our current understanding on MAO-A/MAO-B including their structure, catalytic mechanism, and biological functions with emphases on the role of MAO-B as a potential therapeutic target for the development of medications treating neurodegenerative disorders. It also highlights the recent developments in the discovery of potential MAO-B inhibitors (MAO-BIs) belonging to diverse chemical scaffolds, arising from intensive chemical-mechanistic and computational studies documented during past 3 years (2015-2018), with emphases on their potency and selectivity. Importantly, readers will gain knowledge of various newly established MAO-BI scaffolds and their development potentials. The comprehensive information provided herein will hopefully accelerate ideas for designing novel selective MAO-BIs with superior activity profiles and critical discussions will inflict more caution in the decision-making process in the MAOIs discovery.

64 citations

Proceedings ArticleDOI
20 Apr 2018
TL;DR: In prediction of future weather condition using LSTM the neural network is trained using different combinations of weather parameters, the weather parameters used are temperature, precipitation, wind speed, pressure, dew point visibility and humidity.
Abstract: Accurate weather forecast plays a vital role in today's world as agricultural and indusrial sectors are principally dependent on weather conditions. It is also used to forecast and warm about natural disasters. Weather forecasting is determination of the right values of weather parameters and furhermore the future weather condition based on these parameters. In this study different weather parameters were collected from national climate data center then using Long-short term memory(LSTM) technique, the neural network is trained for different combinations. In prediction of future weather condition using LSTM the neural network is trained using different combinations of weather parameters, the weather parameters used are temperature, precipitation, wind speed. pressure, dew point visibility and humidity. After training of LSTM model using these parameters the prediction of future weather is done.

54 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202211
2021165
202086
201957
201868
201772