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   Table of Contents - Current issue
April-June 2018
Volume 8 | Issue 2
Page Nos. 53-114

Online since Tuesday, September 25, 2018

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Usnic acid-loaded bioinspired heparin modified-cellulose acetate phthalate nanoparticle(s) as an efficient carrier for site-specific delivery in lung cancer cells p. 53
Ashish Garg, Nitendra K Sahu, Awesh Kumar Yadav
Introduction: The main goal of the current study was to assess the cytotoxic influence of usnic acid (UA) after enclosement in heparin modified-cellulose acetate phthalate (HEC) nanoparticles (NPs) when targeted to lung cancer A549 cell line. Materials and Methods: HEC copolymer was manufactured by precipitation method and was substantiated by Fourier-transform infrared spectroscopy and nuclear magnetic resonance spectroscopy. HEC NPs with UA was formulated by employing HEC copolymer and later competed with UA-loaded cellulose acetate phthalate (CAP) NPs. NPs were exemplified by zeta potential, differential scanning calorimetry, particle size, atomic force microscopy, in vitro release, entrapment efficiency, X-ray diffraction , and polydispersity index. Results: Studies revealed that HEC NPs have a slower release (96.21% in 32 h) when contrasted with CAP NPs (97.36% in 8 h). In cytotoxicity analysis of A549, UA-loaded HEC NPs illustrated an immense cytotoxic potential. In addition, HEC NPs were found to be more hemocompatable in comparison to CAP NPs and plain UA. Conclusion: Decisively, on account of investigational results UA-loaded HEC NPs were percieved to be more cytotoxic against lung cancer cells than UA-loaded CAP NPs and plain UA.
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In vivo evaluation of the aromatase inhibition by 4-((1H-imidazol-1-yl) methyl)-2-(4-fluorophenyl)- 8-phenylquinoline p. 63
Navid Sedighi, Razieh Ghodsi, Gholamreza Karimi, Hossein Kamali, Farzin Hadizadeh
Objective: Some of aromatase inhibitors (AIs) are Food and Drug Administration-approved agents which are used as first-line therapy in the treatment of endocrine-responsive breast cancer. In this study, we aimed to develop new quinoline derivative with higher specificity and potency. Materials and Methods: The in vivo aromatase inhibition of these compounds was evaluated by measuring the inhibition of the androstenedione-induced uterine hypertrophy. The selectivity of aromatase inhibition has been investigated by the inhibition of adrenocorticotropic hormone stimulation on the plasma concentrations of aldosterone and cortisol. Results: Letrozole (10 μg/kg) could significantly inhibit uterine hypertrophy in positive control group that received androstenedione 30 mg/kg/day. Furthermore, quinoline derivative could decrease the androstenedione-induced uterine hypertrophy in a dose-dependent manner. Interestingly, there was no significant difference between inhibitory potency of letrozole and quinoline derivatives. High dose of letrozole could significantly decrease the serum concentration of aldosterone and cortisol as compared to control group. On the other hand, the same doses of quinoline derivative were administered; it did not show any significant effects on the serum concentration of either aldosterone or cortisol. Conclusion: This report introduced a new compound that can be considered as new lead for further investigation to explore the more potent and more selective AIs.
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Distinguishing adverse drug reactions, the noxious effects of medicines at a tertiary care hospital p. 69
Siavash Shahbazi Nia, Shadan Modaresahmadi, Armin Eisa Zaei
Introduction: Adverse drug reactions (ADRs) are unavoidable and are considered as the fourth-to-sixth leading causes of death. It makes it essential to detect and monitor the ADRs. Hence, this study was aimed to identify the agents involved in the occurrence of ADRs and to identify and monitor the ADRs occurred in inpatients of a tertiary care hospital. Materials and Methods: It was a descriptive, prospective, observational study conducted for 2 years at a tertiary care hospital in Bengaluru, India. The ADRs were detected and monitored by interviewing the patients and reviewing the laboratory tests and medical charts. All the collected data were tabulated in Microsoft Excel 2016 and analyzed for possible results. Using Naranjo scale and Hartwig and Seigel's severity assessment scale, the probability and severity of the reactions have been identified. Results: In this study, it was observed that majority of ADRs occurred in females. Patients belonging to the age group of 21–50 years old experienced higher number of ADRs than the patients in other age groups. The most commonly reported ADRs were associated with antimicrobial and cardiovascular agents. The most commonly reported ADRs were elevated liver function test (LFT) (12.2%) followed by diarrhea (9.5%). The gastrointestinal system was the most commonly affected organ system followed by fluid and electrolytes. Majority of the ADRs (55.1%) were found to be probable. In addition, the majority of the reported ADRs (84.2%) were mild. Conclusion: The results of this study provide a database of ADRs, which aids clinicians in optimized and safer use of medicines and this, in turn, might lead to an enhanced level of patient care.
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Mesalamine-loaded mucoadhesive microsphere for colon drug delivery system: Effect of process variables and in vitro characterization p. 74
Anup Patil, Pravin Pawar, Varsha Gharge, Ujjwala Doltade, Rajendra Doijad
Objective: The main objective of this study is to formulate mucoadhesive microspheres for colon drug delivery with sodium alginate (ALG) core enriched with drug. Methods: The core microspheres of ALG were prepared by modified emulsification method followed by cross-linking with different concentration of CaCl2at different stirring speed with constant drug-to-polymer ratio (1:3). The core microspheres were further coated with Eudragit S-100 using the solvent evaporation technique. Results: The microspheres (core and coated) were characterized by shape, size, surface morphology, size distribution, entrapment efficiency, and in vitro drug release studies. In vitro drug release showed that the optimized batch of core microsphere and coated microspheres exhibited 99.53% ± 0.39% and 89.22% ± 0.26%, respectively. The drug release from all formulations of mesalamine microsphere followed Higuchian Kinetics. Moreover, drug release from core and Eudragit S-100-coated microspheres followed Korsmeyer–Peppas equation with anomalous and Fickian kinetics mechanism, respectively. Stability study suggests that the degradation rate constant of mesalamine from Eudragit S-100-coated microsphere was found to be minimum 2 years shelf life of the formulation. On the basis of scanning electron microscopy, the core microspheres were formed slightly irregular in shape due to surface-attached crystals of the drug and coated mesalamine microspheres showed smooth surface and a smaller number of pores due to coating. Conclusions: It can be concluded that the appropriate combination of a pH-dependent polymer (Eudragit S-100) with a pH-independent polymer sodium ALG) was suitably adequately sustained the drug release from mesalamine microspheres.
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Development and investigation of novel solid self-nanoemulsifying system loaded with hydrochlorothiazide for the treatment of hypertension p. 83
Akhilesh Dubey, Amitha Shetty, GS Ravi, Manan Christian Kiritkumar, Prabhakara Prabhu, Srinivas Hebbar, Sally A El-Zahaby
Objective: The present study was aimed at formulating and evaluating a novel solid self-nano emulsifying drug delivery system (SNEDDS) to increase the solubility and bioavailability of hydrochlorothiazide (HCZ). Enhancing both solubility and bioavailability of drugs remain the cornerstone for achieving successful outcomes of delivery systems. Furthermore, employing nanotechnology-based formulations such as SNEDDS offers important advantage; the most important is the protection of the drug from enzymatic or chemical degradation. Materials and Methods: Liquid SNEDDS (L-SNEDDS) was prepared by adding a drug to oil, surfactant, and co-surfactant and heated up to at 60°C under continuous stirring. Solid SNEDDS (S-SNEDDS) was prepared by mixing L-SNEDDS with microcrystalline cellulose in 1:1 proportion. Results: The scanning electron microscopy showed that S-SNEDDS was spherical with an average particle size of 66.9 nm and 69.2 nm for both L-SNEDDS and S-SNEDDS, respectively. Ex vivo skin permeation study indicated that 100% drug was released from both the L-SNEDDS and S-SNEDDS formulation SF3 in 3 h. Analysis of variance test showed significant differences (Moderately significant P < 0.01) in the values when compared to a marketed product. Conclusion: The prepared S-SNEDDS helped in improving the solubility of the poorly soluble HCZ, which is a step forward toward bioavailability enhancement and thus increased therapeutic efficacy of the drug.
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An evaluation of classification algorithms for prediction of drug interactions: Identification of the best algorithm p. 92
Rita Rezaee, Reza Akbari, Milad Nasiri, Farzaneh Foroughinia, Nasrin Shokrpour
Introduction: One of the main causes of medical errors is drug interaction which occurs when a drug decreases or increases the effect of another drug. Drug interactions occur as a result of changes in pharmacodynamics, pharmacokinetics, or a combination of both. Due to the problems caused by these errors and lack of an efficient system of automatic diagnosis of drug interactions, and also since a large amount of these interactions can be prevented, we aimed to search for drug interactions in the medical texts and also classify and identify the best algorithm. Methods: A two-stage classification was used to solve the problem of unbalanced data dispersion in drug interaction classes. A subset of the most suitable features was identified for classification. In the first step of designing a binary classification, pairs of drugs which interact with each other and those which do not be separated. Then, we classified the pairs of drug interactions in one of the following four classes: effect, advice, mechanism, and int. In this study, different algorithms were used in both types of classifications, based on the type of data and expert opinion. To validate the first-stage model, we considered 90% of the data as training data and the rest were considered as the test data. To validate the second-stage model, we used the difference verification method. Weka data analysis software was also used for designing the model; then, the classification was made. Results: The results showed that the most appropriate features were mutual information (obtaining a score of 1000) and parts of speech. The efficiency of J48 algorithm in the stage of separating the drugs with and without interaction (F-measure = 0.914) and also in the multiclass stage of the bagging algorithm (F-measure = 0.915) was the highest among other algorithms. ZeroR algorithm required the shortest time to build the model (less than half a second) in both stages. Conclusion: According to the results of J48 algorithms and random forest, it can be concluded that decision tree is the most appropriate approach in the extraction and automatic classification of drug interactions, using the features derived from the text to be applied in clinical decision support system.
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Evaluation of efficacy and safety of Ayucid capsule in subjects suffering from chronic symptomatic gastroesophageal reflux disease p. 100
Sanjay M Tamoli, Shishir P Pande, Shailesh V Deshpande, Narendra B Mundhe, Mandar V Doiphode, Ganesh S Kolhe, Sachin A Upasani
Objectives: The objective of the study was to assess the efficacy and safety of Ayucid capsule and Omeprazole 20 mg in patients suffering from chronic symptomatic gastroesophageal reflux disease (GERD). Materials and Methods: It was an open-label, randomized, comparative, multicenter, prospective clinical study. Subjects in Ayucid group were advised to consume two Ayucid capsules twice daily orally before meals, and subjects in Omeprazole group were advised to consume one Omeprazole (20 mg) capsule orally before lunch for 28 days. All P values were reported based on two-sided significance test, and all the statistical tests were interpreted at 5% level of significance. Results: A total of 63 subjects (33 in Ayucid group and 30 in Omeprazole group) completed the study. At the end of the study, the number of cases of heartburn and symptom of heartburn and severity scores of acid regurgitation, dysphasia, and nausea reduced significantly (P < 0.05) in both the study groups. Significant relief in symptoms such as epigastric pain, loss of appetite, bloating of stomach, constipation, and gaseous distension was observed in both the groups. Majority of subjects showed significant (P < 0.05) reduction in GERD health-related quality of life subscores and improvement in overall efficacy in both the groups. No posttreatment significant (P > 0.05) changes were observed in safety laboratory parameters and vitals. Of the reported adverse events in the two groups, none were found to be related to the study drugs. Conclusion: Ayucid capsule is equally effective or noninferior to that of Omeprazole capsule in relieving the GERD symptoms.
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Digital health research: A scientometric assessment of global publications output during 2007–2016 p. 106
BM Gupta, SM Dhawan, KK Mueen Ahmed
Aim and Scope: To study the scientometric assessment of global publications on Digital Health Research. Methods: The paper examines digital health research covering 6981 global publications sourced from Scopus database during 2007–2016. Results: Digital health research across 109 countries registered 8.03% growth and averaged to 7.33 citations per paper. The top 10 most productive countries individually contributed 2.75% to 33.82% share to global publications output and together they accounted for 79.30% share during the period. Their international collaborative publications varied from 3% to 14.49%. Medicine is the most studied subject with largest publication share in digital health research (53.55%), followed by computer science (33.85%), engineering (24.97%), health profession (13.24%), and others. The top 20 most productive organizations and authors together contributed 12.32% and 2.99% of global publications share, respectively, and 38.91% and 3.28% of global citations share, respectively. The top 20 journals contributed 12.32% share to the global output in journals during 2007–2016. Of the total digital health research, 46 (0.65%) were highly cited papers, citations to them ranged from 100 to 1104 per paper, with 257.76 citations per paper. Conclusion: A total of 415 authors from 242 organizations contributed 46 highly cited papers which appeared in 37 journals. Four papers appeared in CA Cancer Journal of Clinicians, three papers in Annals of Internal Medicine, two papers each in European Urology, Journal of American Medical Informatics Association, New England Journal of Medicine, Pediatrics and Stroke, and one paper each in 30 other journals.
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