Publications by authors named "C Muthukumaran"

Introduction: Thermotolerant microbes are a group of microorganisms that survive in elevated temperatures. The thermotolerant microbes, which are found in geothermal heat zones, grow at temperatures of or above 45°C. The proteins present in such microbes are optimally active at these elevated temperatures.

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Article Synopsis
  • The study investigates the outcomes of children with heart disease and young adults with congenital heart disease who contracted COVID-19, revealing limited existing data on this topic.
  • It involved 94 patients from 24 pediatric cardiac centers in India, where a significant proportion were asymptomatic for COVID-19, yet the in-hospital mortality rate for COVID-19-positive cases was 27.1%, highlighting a drastic increase compared to COVID-negative cases.
  • Key risk factors identified for mortality included the severity of illness at admission and belonging to a lower socioeconomic class, emphasizing the need for targeted prevention and management strategies for these vulnerable populations.
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Background: COVID-19 pandemic has disrupted pediatric cardiac services across the globe. Limited data are available on the impact of COVID.19 on pediatric cardiac care in India.

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In recent years, plant based scaffold due to its inherent properties such as mechanical stability, renewability, easy mass production, inexpensiveness, biocompatibility and biodegradability with low toxic effects have received much attention in the field of bone tissue engineering. Design of good tissue compatible plant based polymer scaffold plays a vital role in biomedicine, nanomedicine and in various tissue engineering applications. The present study focused on the fabrication of a novel herbal scaffold using the medicinal plants Spinacia oleracea (SO) and Cissus quadrangularis (CQ) extracts incorporated with Alginate (Alg), Carboxy Methyl Cellulose (CMC) by lyophilization method.

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In this work, Response Surface Methodology (RSM) and Artificial Neural Network coupled with genetic algorithm (ANN-GA) have been used to develop a model and optimise the conditions for the extraction of pectin from sunflower heads. Input parameters were extraction time (10-20 min), temperature (40-60 °C), frequency (30-60 Hz), solid/liquid ratio (S/L) (1:20-1:40 g/mL) while pectin yield (PY%) was the output. Results showed that ANN-GA had a higher prediction efficiency than RSM.

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