Bacterial and Fungal Contamination of Elevator Buttons in University Schools of Isfahan University of Medical Sciences, Isfahan, Iran

Optimization of the photocatalytic degradation of phenol using superparamagnetic iron oxide (Fe3O4) nanoparticles in aqueous solutions

The present work was carried out to remove phenol from aqueous medium using a photocatalytic process with superparamagnetic iron oxide nanoparticles (Fe3O4) called SPIONs. The photocatalytic process was optimized using a central composite design based on the response surface methodology. The effects of pH (3-7), UV/SPION nanoparticles ratio (1-3), contact time (30-90 minutes), and initial phenol concentration (20-80 mg L-1) on the photocatalytic process were investigated. The interaction of the process parameters and their optimal conditions were determined using CCD. The statistical data were analyzed using a one-way analysis of variance. We developed a quadratic model using a central composite design to indicate the photocatalyst impact on the decomposition of phenol. There was a close similarity between the empirical values gained for the phenol content and the predicted response values. Considering the design, optimum values of pH, phenol concentration, UV/SPION ratio, and contact time were determined to be 3, 80 mg L-1, 3, and 60 min, respectively; 94.9% of phenol was eliminated under the mentioned conditions. Since high values were obtained for the adjusted R2 (0.9786) and determination coefficient (R2 = 0.9875), the response surface methodology can describe the phenol removal by the use of the photocatalytic process. According to the one-way analysis of variance results, the quadratic model obtained by RSM is statistically significant for removing phenol. The recyclability of 92% after four consecutive cycles indicates the excellent stability of the photocatalyst for practical applications. Our research findings indicate that it is possible to employ response surface methodology as a helpful tool to optimize and modify process parameters for maximizing phenol removal from aqueous solutions and photocatalytic processes using SPIONs.

SARS-CoV-2 detection in hospital indoor environments, NW Iran

This study aimed to investigate the potential contamination of SARS-CoV-2 in indoor settled dust and surfaces of Amir Al-Muminin hospital in Maragheh, Iran. Samples were taken from surfaces and settled dust using a passive approach and particulate matter (PM) using an active approach from different hospital wards. SARS-CoV-2 was detected in 15% of settled dust samples (N = 4/26) and 10% of surface samples (3/30). SARS-CoV-2 has been detected in 13.8% and 9.1% of the dust samples collected at a distance of fewer than 1 m and more than 3 m from the patient bed, respectively. SARS-CoV-2 was found in 11% of surface samples from low-touch surfaces and 8% from high touch surfaces. The relationship between PM_2.5, PM₁₀, humidity, temperature, and positive samples of SARS-CoV-2 was investigated. A positive correlation was observed between relative humidity, PM_2.5, and positive SARS-CoV-2 samples. Principal component analysis (PCA) suggested positive correlation between positive SARS-CoV-2 samples, relative humidity, and PM_2.5. Risk assessment results indicated that the annual mean infection risk of SARS-CoV-2 for hospital staff with illness and death was 2.6 × 10^-2 and 7.7 × 10^-4 per person per year. Current findings will help reduce the permanence of viral particles in the COVID 19 tragedy and future similar pandemics e.g., novel influenza viruses.