VIWITHAN: A STANDARDIZED ASHWAGANDHA EXTRACT AMELIORATES OVALBUMININDUCED AIRWAY-INFLAMMATION AND OXIDATIVE STRESS IN MOUSE MODEL

Objective: Withania somnifera, commonly known as Ashwagandha, Indian ginseng, has been used in Ayurvedic and indigenous medicinal preparations for various disease conditions since long time. In the present study, we investigated the protective effects of Viwithan, a standardized proprietary extract from Ashwagandha roots, against airway-inflammation and oxidative stress modulation in an ovalbumin (OVA)-induced murine model of inflammation. Methods: Allergic asthma was initiated in BALB/c mice by sensitizing with OVA on days 1 and 14, followed by intranasal challenge with OVA on days 27, 28, and 29. Mice were administered Viwithan (200 and 400 mg/kg) by oral gavage before challenge. Then, mice were evaluated for the presence of airway inflammation, production of allergen-specific cytokine response, lung pathology, and oxidative stress modulation. Results: The results showed that treatment with Viwithan attenuated OVA-induced lung inflammation in mice. Viwithan significantly attenuated inflammatory cell infiltration into the bronchoalveolar lavage fluid and markedly reduced the levels of pro-inflammatory cytokines, interleukin-10, and transforming growth factor-β1 in lung tissues. Viwithan treatment considerably reduced the lung weight in OVA-sensitized mice. Viwithan markedly attenuated the OVA-induced generation of reactive oxygen species in lung tissues. Conclusion: Together, these results suggested that Viwithan alleviates OVA-induced airway-inflammation and oxidative stress, highlighting the potential of standardized Ashwagandha extract as a useful therapeutic agent for pulmonary fibrosis management

Synthesis, antimicrobial, DNA-binding and photonuclease studies of Cobalt(III) and Nickel(II) Schiff base complexes

New metal complexes of the type M(nih)(L)](PF6)(n)center dot xAH(2)O and M(nih)(2)](PF6)center dot xH(2)O (where M = Co(III) or Ni(II), L = 1,10-phenanthroline (phen)/or 2,2' bipyridine (bpy), nih = 2-hydroxy-1-naphthaldehyde isonicotinoyl hydrazone, n = 2 or 1 and x = 3 or 2) have been synthesized and characterized by elemental analysis, magnetic, IR and H-1 NMR spectral data. The electronic and magnetic moment 2.97-3.07 B.M. data infers octahedral geometry for all the complexes. The IR data reveals that Schiff base (nih) form coordination bond with the metal ion through azomethine-nitrogen, phenolic-oxygen and carbonyl-oxygen in a tridentate fashion. In addition, DNA-binding properties of these six metal complexes were investigated using absorption spectroscopy, viscosity measurements and thermal denaturation methods. The results indicated that the nickel(II) complex strongly bind with calf-thymus DNA with intrinsic DNA binding constant K-b value of 4.9 x 10(4) M-1 for (3), 4.2 x 10(4) M-1 for (4), presumably via an intercalation mechanism compared to cobalt(III) complex with K-b value of 4.6 x 10(4) M-1 (1) and 4.1 x 10(4) M-1 (2). The DNA Photoclevage experiment shows that, the complexes act as effective DNA cleavage agent. (C) 2012 Elsevier B.V. All rights reserved

Use of Angiotensin-converting Enzyme Inhibitor Therapy and Dose-related Outcomes in Older Adults with New Heart Failure in the Community

OBJECTIVE: To evaluate the dose-related benefit of angiotensinconverting enzyme (ACE) inhibitor therapy among older adults with heart failure and to evaluate whether low-dose ACE inhibitor therapy is better than none. DESIGN: Observational cohort study. SETTING: Community-dwelling older adults in Ontario, Canada. PATIENTS/PARTICIPANTS: We identified 16,539 adults 66 years or older who survived 45 days following their first heart failure hospitalization discharge. MEASUREMENT AND MAIN RESULTS: Multivariate techniques including propensity scores were used to study the association between the dose of ACE inhibitor therapy dispensed and 3 outcomes: survival, survival or heart failure rehospitalization, and survival or all-cause hospitalization at 1 year of follow-up. Logistic regression models explored the association between initial dose dispensed and subsequent dose reduction or drug cess-ation. Overall, 10,793 (65.3%) of patients were dispensed ACE inhibitor therapy, with more than a third (3,935; 36.5%) initiated on low-dose therapy. Relative to dispensing of lowdose ACE inhibitor therapy, nonuse was associated with increased mortality (hazard ratio [HR], 1.12; 95% confidence interval [CI], 1.02 to 1.22). Dispensing medium-dose therapy provided a benefit similar to low-dose (HR, 0.94; CI, 0.86 to 1.03) and dispensing of high-dose therapy was associated with improved survival benefit (HR, 0.76; CI, 0.68 to 0.85). Relative to dispensing of low-dose ACE inhibitor therapy, dispensing high-dose conferred a benefit (HR, 0.87; CI, 0.80 to 0.95) on the composite outcome of 1-year mortality or heart failure hospitalization and the composite outcome of 1-year mortality or all-cause hospitalization (HR, 0.87; CI, 0.81 to 0.93). Relative to those dispensed low-dose ACE inhibitor therapy, those initially dispensed high-dose therapy were twice as likely to have their subsequent dose reduced or the therapy discontinued (odds ratio, 2.36; CI, 2.07 to 2.69). CONCLUSION: Our findings suggest that when possible, older adults should be titrated to the higher doses of ACE inhibitor therapy evaluated in clinical trials. If older adults cannot tolerate higher doses, then low-dose ACE inhibitor therapy is superior to none. High-dose ACE inhibitor therapy is not as well tolerated as lower doses

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset