Screening of a High-Affinity Aptamer for Aflatoxin M1 and Development of Its Colorimetric Aptasensor.

Aflatoxin M1 (AFM1), a secondary metabolite of Aspergillus spp., is highly toxic and widely present in food matrices. Therefore, the detection of AFM1 is of great importance for the protection of food safety. In this study, a five-segment sequence was designed as the initial library. Graphene oxide-SELEX (GO-SELEX) was applied to screen AFM1. After seven rounds of repeated screening, affinity and specificity assays showed that aptamer 9 was the best candidate for AFM1. The dissociation constant (Kd) of aptamer 9 was 109.10 ± 6.02 nM. To verify the efficiency and sensitivity aptamer for the detection of AFM1, a colorimetric sensor based on the aptamer was constructed. The biosensor showed good linearity in the range of AFM1 concentration of 0.5-500.0 ng/mL with a detection limit of 0.50 ng/mL. This colorimetric method was successfully used for the detection of AFM1 in milk powder samples. Its detection recovery was 92.8-105.2%. This study was conducted to provide a reference for the detection of AFM1 in food.

Impact of Meteorological factors and population size on the transmission of Micro-size respiratory droplets based Coronavirus: A brief study of highly infected cities in Pakistan

Ongoing Coronavirus epidemic (COVID-19) identified first in Wuhan, China posed huge impact on public health and economy around the globe. Both cough and sneeze based droplets or aerosols encapsulated COVID-19 particles are responsible for air borne transmission of this virus and caused unexpected escalation and high mortality worldwide. Current study intends to investigate correlation of COVID-19 epidemic with meteorological parameters particularly, temperature, rainfall, humidity, and wind speed along with population size. Data set of COVID-19 for highly infected cities of Pakistan was collected from the official website of National Institute of health (NIH). Spearmans rank (rs) correlation coefficient test employed for data analysis revealed significant correlation between temperature minimum (TM), temperature average (TA), wind speed (WS) and population size (PS) with COVID-19 pandemic. Furthermore, receiver operating characteristics (ROC) curve was used to analyze the sensitivity of TA, WS, and PS on transmission rate of COVID-19 in selected cities of Pakistan. The results obtained for sensitivity and specificity analysis for all selected parameters signifies sensitivity and direct correlation of COVID-19 transmission with temperature variation, WS and PS. Positive correlation and strong association of PS parameter with COVID-19 pandemic suggested need of more strict actions and control measures for highly populated cities. These findings will be helpful for health regulatory authorities and policymakers to take specific measures to combat COVID-19 epidemic in Pakistan.