Manipal University

About: Manipal University is a education organization based out in Manipal, Karnataka, India. It is known for research contribution in the topics: Population & Health care. The organization has 9525 authors who have published 11207 publications receiving 110687 citations.

Antimicrobial, antioxidant and in vitro anti-inflammatory activity and phytochemical screening of water extract of Wedelia trilobata (L.) Hitchc.

Abstract: The aim of the study was to evaluate antimicrobial, antioxidant and anti-inflammatory activity of dry and fresh parts of leaf, stem and flower from the water extract of Wedelia trilobata. The antimicrobial activity of water extracts of fresh and dry parts against 9 different strains of bacteria and 11 different species of fungi were determined using standard method (paper disc method). The fresh parts water extracts showed that, leaf and flower extracts were most potent inhibiting all isolates of with different zones of inhibition but did not inhibited the growth of fungi tested. All the extracts have only moderately inhibited the all fungi. The minimum microbial concentration (MMC) of the active extract was observed from fresh part extracts of leaf, flower and stem ranged from 0.4 to 5.0 mg/ml for the sensitive bacteria. In case of fungi, the minimum inhibitory concentration (MIC) of the active extracts ranged from 2.4 to 6.0 mg/ml. Together, these data suggest that the W. trilobata fresh parts extracts analyzed are potential antimicrobial candidates with a broad range of activity. Phytochemical screening of extracts showed the presence of tannins, cardiac glycosides, flavonoids, terpenoids, phenols, saponins and coumarins. Leaf and flower water have showed highest total phenolic content. In 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and ferric ion reducing antioxidant power (FRAP) method, the leaf and flower had showed free radical inhibition of 86, 83 and 1623.21, 1611.26, respectively and they also showed in vitro antiinflammatory activity by inhibiting the heat induced albumin denaturation and red blood cells membrane stabilization with 89.61 and 86.81 and 78.82, 76.65 g/ml, respectively. Proteinase activity was also significantly inhibited by the leaf (83.91 g/ml) and flower (81.17 g/ml). From the result, it is concluded that phytochemicals present in the W. trilobata extract may be responsible and can be used as antimicrobial, antioxidant and anti-inflammatory agent.

N-doped MXene derived from chitosan for the highly effective electrochemical properties as supercapacitor

Abstract: Chitosan (CS) rich in ∼ 7 wt% nitrogen is the renewable nontoxic biomass material derived from seafood waste. Chitosan is a suitable precursor to obtain N-doped materials due to the nitrogen in acetamide and amine of chitosan. In this work, the new type of N-doped MXene nanomaterials is prepared from non-toxic biological chitosan and MXene using a simple, environment-friendly method as a potential electrode for supercapacitor. The specific capacitance of 1MXene-1N reaches up to 286.28 F/g (154.59 C/g). After 10,000 charge and discharge cycles, the efficiency is always above 98%. The N-doped MXene turned out to be high electrochemistry and excellent stability due to the lone pair of electrons of the N atom and increased interlayer distance. The N-doped MXene material was prepared by high-temperature calcination.

Changes in Tinnitus Experiences During the COVID-19 Pandemic.

Abstract: Introduction: The COVID-19 pandemic has disrupted delivery of healthcare, economic activity, and affected social interactions. Identifying and supporting those most affected by the pandemic is required. The purpose of this study was to determine the impact of the pandemic on individuals with tinnitus and to identify mediating factors. Methods: This is a mixed-methods exploratory cross-sectional study, using data collected via an online survey from 3,103 individuals with tinnitus from 48 countries. The greatest representation was from North America (49%) and Europe (47%) and other countries were only marginally represented. Results: Although the study was aimed at those with pre-existing tinnitus, 7 individuals reported having COVID-19 initiated tinnitus. Having COVID-19 symptoms exacerbated tinnitus in 40% of respondents, made no change in 54%, and improved tinnitus in 6%. Other mediating factors such as the social and emotional consequences of the pandemic made pre-existing tinnitus more bothersome for 32% of the respondents, particularly for females and younger adults, better for 1%, and caused no change to tinnitus for 67%. Pre-existing tinnitus was significantly exacerbated for those self-isolating, experiencing loneliness, sleeping poorly, and with reduced levels of exercise. Increased depression, anxiety, irritability, and financial worries further significantly contributed to tinnitus being more bothersome during the pandemic period. Conclusions: These findings have implications for tinnitus management, because they highlight the diverse response both internal and external factors have on tinnitus levels. Clinical services should be mindful that tinnitus may be caused by contracting COVID-19 and pre-existing tinnitus may be exacerbated, although in the majority of respondents there was no change. Additional support should be offered where tinnitus severity has increased due to the health, social, and/or emotional effects of the COVID-19 pandemic. Tinnitus may be more bothersome for those experiencing loneliness, having fewer social interactions, and who are more anxious or worried.

Diagnosis of multiclass tachycardia beats using recurrence quantification analysis and ensemble classifiers

Abstract: Atrial Fibrillation (A-Fib), Atrial Flutter (AFL) and Ventricular Fibrillation (V-Fib) are fatal cardiac abnormalities commonly affecting people in advanced age and have indication of life-threatening condition. To detect these abnormal rhythms, Electrocardiogram (ECG) signal is most commonly visualized as a significant clinical tool. Concealed non-linearities in the ECG signal can be clearly unraveled using Recurrence Quantification Analysis (RQA) technique. In this paper, RQA features are applied for classifying four classes of ECG beats namely Normal Sinus Rhythm (NSR), A-Fib, AFL and V-Fib using ensemble classifiers. The clinically significant (p<0.05) features are ranked and fed independently to three classifiers viz. Decision Tree (DT), Random Forest (RAF) and Rotation Forest (ROF) ensemble methods to select the best classifier. The training and testing of the feature set is accomplished using 10-fold cross-validation strategy. The RQA coefficients using ROF provided an overall accuracy of 98.37% ag...