Fungal skin infections are caused by different types of fungi among these Malassezia species is the common cause of the dermatitis in human and animals. In the present study, the skin scraping samples were collected from human and dog. The samples were inoculated into Saboraud and potato dextrose broth to achieve the fungal growth. The fungal species were isolated and characterized by colony morphology, potassium hydroxide (KOH) and lacto phenol cotton blue staining. Genomic DNA was isolated and the 28S rRNA was amplified from fungal species using the universal primers and the amplified PCR products were subjected to sequencing. The sequence analysis of 28S rRNA reveals that two sequences were similar to Malassezia globosa and one sequence is similar to Malassezia pachydermatis which causes dermatitis in human and dog, respectively. Further study was carried out to assess the antifungal activity of the silver nanoparticles synthesized through green synthesis using Azadirachta indica leaf extract and characterized by UV-Visible spectrophotometer, Transmission electron microscope (TEM), X-Ray diffraction spectrophotometer (XRD) and Fourier transform infrared spectrophotometer (FTIR). The characterized silver nanoparticles inhibit the growth of Malassezia species by forming zone of clearance. This study suggests that the silver nanoparticles could be an alternative to treat the fungal infections.

Emerging zoonotic infectious diseases like swine influenza, avian influenza and Ebola have caused massive human suffering, social upheaval and economic damage across countries and continents. There is increasing evidence that humanity’s overexploitation of nature is one of the major factors responsible for the spread. Recently, mankind is traversing a hard-pandemic time due to COVID-19 outbreak which appears to be a brutal killer. When humans infringe wild adobes for food production, it generates opportunities for infectious pathogens to leap to livestock and humans. It is the time to begin brooding about more radical measures to handle the root of this crisis. A resilient food system that puts less stress on the environment would reduce the outbreak of Emerging Infectious Diseases (EID) by reducing contact between humans and wild animals thereby restoring biodiversity. World Health Organisation (WHO) advises avoidance/judicious use of animal meat consumption during or after every outbreak. It is clearly evident that a balanced, healthy plant-based diet can help to control pandemics/epidemics not only by preventing the transmission but also by strengthening the immune system of individuals to combat the infection. This paper throws light on how the human diet is directly or indirectly linked to the emergence, spread and prognosis of various infectious diseases.

The present study aims at the development of eco-friendly antimicrobial finished Bamboo/Cotton fabrics from the herbal extracts. The herbal extracts of Syzygium aromaticum (clove) buds have been applied on to the fabrics by two methods: Direct application method and Microencapsulation Method. The antimicrobial efficacy and the wash durability are assessed using AATCC 147, AATCC 30 and EN ISO 20645 standards. Both the treatments showed good antibacterial property and the microencapsulation method showed good antifungal property too. The Direct application method showed wash durability only till 10 washes, whereas the microencapsulation method showed very good wash durability till 30 wash cycles. Analysis of the Antimicrobial Efficacy of

Background: The COVID-19 pandemic has had a significant impact on societies all over the world, leading to significant shifts in individual behavior as well as societal norms. The goal of this study was to provide an in-depth look at the many different aspects of public behavior during the COVID-19 pandemic. Methods: Demographic information, COVID-19 knowledge and awareness, prevention adherence, vaccination attitudes, and psychological well-being as a whole were all be gathered through the quantitative survey. The subjective meetings will give further bits of knowledge into the hidden inspirations, discernments, and difficulties faced by people in following general wellbeing rules. Results: To find patterns and correlations among the various variables, statistical methods like regression analysis, factor analysis, and clustering algorithms were used in the data analysis. The subjective information was investigated specifically, separating key topics and accounts that shed light on the subtleties of the public’s way of behaving during the pandemic. Conclusions: In the end, the goal of this multidimensional study was to help make decisions based on evidence and come up with plans to improve public health and lessen the impact of infectious disease outbreaks like COVID-19.