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Articles by Harish Dureja
Total Records ( 5 ) for Harish Dureja
  Saurabh Satija , Preeti Bansal , Harish Dureja and Munish Garg
  Present study was conducted to develop a new optimized Microwave-Assisted Extraction (MAE) method for Tinospora cordifolia in order to improve the efficiency and yield of chief bioactive compounds. Stems of the Tinospora cordifolia were subjected for extraction using MAE technique using three variable factors (extraction time, irradiation power and solvent concentration) optimized through central composite design. Berberine which was used, as marker was estimated in prepared extract by High Performance Thin Layer Chromatography (HPTLC) and compared with extracts prepared by conventional techniques like maceration and soxhlation. The results revealed that MAE of Tinospora cordifolia at 60% irradiation power, 80% ethanol concentration and at 3 min extraction time produced highest extract yield (91.3% better yield than maceration and 25.7% than soxhlation) as well as berberine content (492.8% better than maceration and 59.6% than soxhlation) as compared to extracts prepared with conventional techniques. Efficiency of the MAE method was considerably better than the conventional procedures, especially in terms of shortening extraction time (3 min as compared to 3 h for soxhlation and 7 days fort maceration), reduction of solvent used and energy consumption. The optimized microwave extraction method can provide a valuable extraction alternative of Tinospora cordifolia stem at industrial scale.
  Neeta and Harish Dureja
  Cancer is perceived as a disease of unregulated communication within cells of the body. Currently chemotherapy, radiation therapy, immunotherapy, photodynamic therapy, hormonal therapy and surgery have been used for cancer treatment. The therapeutic success rate for cancer can be tremendously improved by use of natural products such as Catharanthus roseus, Curcuma longa, Taxus bravifolia, Camptotheca acuminate etc. Boswellic acids are bioactive pentacyclic triterpenes derived from natural plant source (Boswellia serrata) represents one of the most promising anticancer agent. Various anticancer research studies and published data reported on safety of Boswellia serrata showed that boswellic acids can be used for treatment of colon cancer, pancreatic cancer, brain tumor, leukemia and prostate cancer etc. An attempt has been made in this review to highlight the treatment therapies, different Boswellia species, structural composition and role of boswellic acids in cancer therapy, safety/toxicological profile and interactions of boswellic acids.
  Vipin SHARMA , Rakesh Kumar MARWAHA and Harish DUREJA
  In the present study, chitosan membranes capable of imitating permeation characteristics of diclofenac diethylamine across animal skin were prepared using cast drying method. The effect of concentration of chitosan, concentration of cross-linking agent (NaTPP), crosslinking time was studied using Taguchi design. Taguchi design ranked concentration of chitosan as the most important factor influencing the permeation parameters of diclofenac diethylamine. The flux of the diclofenac diethylamine solution through optimized chitosan membrane (T9) was found to be comparable to that obtained across rat skin. The mathematical model developed using multilinear regression analysis can be used to formulate chitosan membranes that can mimic the desired permeation characteristics. The developed chitosan membranes can be utilized as a substitute to animal skin for in vitro permeation studies.
  Rakesh K. GOYAL , Harish DUREJA , Gajendra SINGH and Anil Kumar MADAN
  The relationship between topological indices and antitubercular activity of 5’-O- [(N-Acyl)sulfamoyl]adenosines has been investigated. A data set consisting of 31 analogues of 5’-O-[(N-Acyl)sulfamoyl]adenosines was selected for the present study. The values of numerous topostructural and topochemical indices for each of 31 differently substituted analogues of the data set were computed using an in-house computer program. Resulting data was analyzed and suitable models were developed through decision tree, random forest and moving average analysis (MAA). The goodness of the models was assessed by calculating overall accuracy of prediction, sensitivity, specificity and Mathews correlation coefficient. Pendentic eccentricity index - a novel highly discriminating, non-correlating pendenticity based topochemical descriptor - was also conceptualized and successfully utilized for the development of a model for antitubercular activity of 5’-O-[(N-Acyl)sulfamoyl]adenosines. The proposed index exhibited not only high sensitivity towards both the presence as well as relative position(s) of pendent/heteroatom(s) but also led to significant reduction in degeneracy. Random forest correctly classified the analogues into active and inactive with an accuracy of 67.74%. A decision tree was also employed for determining the importance of molecular descriptors. The decision tree learned the information from the input data with an accuracy of 100% and correctly predicted the cross-validated (10 fold) data with accuracy up to 77.4%. Statistical significance of proposed models was also investigated using intercorrelation analysis. Accuracy of prediction of proposed MAA models ranged from 90.4 to 91.6%.
  Monika GUPTA , Harish DUREJA and Anil Kumar MADAN
  The inhibition of tumor angiogenesis has become a compelling approach in the development of anticancer drugs. In the present study, topological models were developed through decision tree and moving average analysis using a data set comprising 42 analogues of 3-aminoindazoles. A total of 22 descriptors (distance based, adjacency based, pendenticity and distance-cum-adjacency based) were used. The values of all 22 topological indices for each analogue in the dataset were computed using an in-house computer program. A decision tree was constructed for the receptor tyrosine kinase KDR (kinase insert domain receptor) inhibitory activity to determine the importance of topological indices. The decision tree learned the information from the input data with an accuracy of 88%. Three independent topological models were also developed for prediction of receptor tyrosine kinase inhibitory (KDR) activity using moving average analysis. The models developed were also found to be sensitive towards the prediction of other receptor tyrosine kinases i.e. FLT3 (fms-like tyrosine kinase-3) and cKIT inhibitory activity. The accuracy of classification of single index based models using moving average analysis was found to be 88%. The performance of models was assessed by calculating precision, sensitivity, overall accuracy and Mathew’s correlation coefficient (MCC). The significance of the models was also assessed by intercorrelation analysis.
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