ORCID Profile
0000-0002-0740-8573
Current Organisation
Jamia Hamdard
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Publisher: CSIRO Publishing
Date: 2003
DOI: 10.1071/AR02157
Abstract: Efforts to improve the yield and quality of cultivated chickpea (Cicer arietinum L.) are constrained by a low level of intraspecific genetic ersity. Increased genetic ersity can be achieved via the hybridisation of the cultivated species with the unimproved 'wild' relatives from within the 43 species of the Cicer genus. To date, the 8 species sharing an annual growth habit and chromosome number with C. arietinum have been the primary focus of screening and introgression efforts. Screening of these species has uncovered morphological characteristics and resistance to a number of abiotic and biotic stresses that are of potential value to chickpea improvement programs. Detailed analysis of protein and DNA, karyotyping, and crossability studies have begun to elucidate the relationships between the annual Cicer species. In comparison, perennial species have received little attention due to difficulties in collection, propagation, and evaluation. This review discusses the progress towards an understanding of genetic relationships between the Cicer species, and the introgression of genes from the wild Cicer species into the cultivated species.
Publisher: IEEE
Date: 05-2017
Publisher: IEEE
Date: 10-2009
Publisher: Informa UK Limited
Date: 11-2015
DOI: 10.2147/NSA.S49052
Publisher: Informa UK Limited
Date: 28-03-2022
Publisher: Public Library of Science (PLoS)
Date: 11-06-2014
Publisher: Oxford University Press (OUP)
Date: 03-06-2021
Abstract: Borage oil that is extracted from (Borago officinalis Linn.) is a well-known medicinal plant having various medicinal benefits. In this work, an affordable, simple, reliable, rapid and easily accessible high-performance thin-layer chromatography (HPTLC) method was developed for the estimation of gamma-linolenic acid (GLA) in borage oil. HPTLC method employs thin-layer chromatography (TLC) aluminum plates precoated with silica gel (G60F254) as the stationary phase, and the mixture of hexane:toulene:glacial acetic acid (3:7:1, v/v/v) was used as the mobile phase. Densitometric analysis of the TLC plates was carried out at 200 nm. The developed method showed well-resolved spots with retention factor (Rf) value of 0.53 ± 0.04 for GLA. Various experimental conditions like saturation time for chamber, solvent phase migration and width of the band were studied intensely for selecting the optimum conditions. The method validation was performed for parameters like linearity, accuracy, specificity and precision. The values of limit of detection and limit of quantification for GLA were found to be 0.221 and 0.737 μg/band, respectively. In nutshell, the developed HPTLC method was found to be highly sensitive for the estimation of GLA in the herbal oil s les and formulations.
Publisher: Springer Science and Business Media LLC
Date: 22-02-2022
DOI: 10.1208/S12249-022-02233-9
Abstract: This study reports the formulation of mupirocin-loaded chitosan microspheres embedded in Piper betle extract containing collagen scaffold as combinational drug delivery for improved wound healing. Selection of chitosan type (molecular weight and degree of deacetylation) was carried out based on their antibacterial efficacy. The low molecular weight chitosan was selected owing to the highest antibacterial action against gram-positive as well as gram-negative bacteria. Low molecular weight chitosan-microspheres showed spherical shape with largely smooth surface morphology, 11.81% of mupirocin loading, and its controlled release profile. The XRD, DSC thermograms, and FT-IR spectral analysis revealed the mupirocin loaded in molecularly dispersed or in amorphous form, and having no chemical interactions with the chitosan matrix, respectively. The in vivo study indicates potential effect of the mupirocin, Piper betle, and chitosan in the collagen scaffold in the wound healing efficiency with approximately 90% wound healing observed at the end of 15 days of study for combinational drug-loaded chitosan microspheres-collagen scaffold-treated group. The histopathology examination further revealed tissue lined by stratified squamous epithelium, collagen deposition, fibroblastic proliferation, and absence of inflammation indicating relatively efficient wound healing once treated with combinational drug-loaded chitosan microspheres containing scaffold.
Publisher: Bentham Science Publishers Ltd.
Date: 21-11-2014
DOI: 10.2174/1871527313666141023100618
Abstract: Alzheimer's disease (AD) is a multifarious progressive neuro-degenerative state among elders. Potentiation of central cholinergic activity by using acetylcholinesterase inhibitors (AChEI) is considered as one of the major pharmacological means for the management of AD. Investigation in the past and the rest decades revealed that many drugs with anti-AD activity, including the AChEI have been discovered from natural and synthetic origin but getting success in their brain delivery is still limited. However, barriers like blood-brain barrier, blood-cerebrospinal fluid barrier and p-glycoproteins restrict the effective and safe drug delivery to the brain in patients with AD. Advancement in nanotechnology-based drug delivery systems over the last decade exemplifies the effective drug delivery and targeting to the brain with controlled rate in various diseases including AD. Till recently, erse kinds of nanomedicines for targeting of the anti-AD drugs in brain are being studied. In this review, we have highlighted the recent progress in AChEI, challenges in their effective brain delivery (physicochemical properties and biological barriers) and possible nanotechnology-based strategies that can deliver drugs across the CNS barriers during AD.
Publisher: Elsevier BV
Date: 04-2021
Publisher: Bentham Science Publishers Ltd.
Date: 12-2021
DOI: 10.2174/1381612827666210927163258
Abstract: Drug delivery to the brain has been a significant challenge in treating neurodegenerative disorders such as Alzheimer's disease due to the presence of the blood-brain barrier, which primarily obstructs the access of drugs and biomolecules into the brain. Several methods to overcome the blood-brain barrier have been employed, such as chemical disruption, surgical intervention, focused ultrasound, intranasal delivery, and the use of nanocarriers. Nanocarrier systems remain the method of choice and have shown promising results over the past decade to achieve better drug targeting. Polymeric nanocarriers and lipidic nanoparticles act as a carrier system providing better encapsulation of drugs, site-specific delivery, increased bioavailability, and sustained release of drugs. The surface modifications and functionalization of these nanocarrier systems have greatly facilitated targeted drug delivery. The safety and efficacy of these nanocarrier systems have been ascertained by several in vitro and in vivo models. In the present review, we have elaborated on recent developments of nanoparticles as a drug delivery system for Alzheimer's disease, explicitly focusing on polymeric and lipidic nanoparticles.
Publisher: Elsevier BV
Date: 10-2010
Publisher: Springer Science and Business Media LLC
Date: 03-1992
DOI: 10.1007/BF00226907
Publisher: American Chemical Society (ACS)
Date: 04-06-2010
DOI: 10.1021/CI1000532
Abstract: Intensive research has been performed on computational design of kinase inhibitors using molecular dynamics simulations, docking and quantitative structure-activity relationship (QSAR) analyses, all of which have their own limitations. In this paper, we report the application of proteochemometrics, a ligand-target modeling approach, to the recognition of stable and unstable kinase-inhibitor complexes using support vector machines (SVM) classifiers. The algorithm consists of creating topological autocorrelation descriptors for kinases and inhibitors and then development of SVM models to relate the feature vectors to the stability class (stable or unstable) of hypothetical protein-inhibitor complexes. The approach based on the autocorrelation features was compared with fragment-based approach and the former was found to outperform the later. The final classifier could recognize 82% of data to be stable or unstable using jackknife type of validation and test set prediction. Analysis of substructure classification showed a very homogeneous behavior of the model on the whole target-ligand space. The predictor is available online at gibk21.bse.kyutech.ac.jp/AUTOkinI/SVMpredictor.html.
No related grants have been discovered for Farhan Ahmad.