Antiviral capacity of polypropylene/(1-Hexadecyl) trimethyl-ammonium bromide composites against COVID-19.

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, scientists from different areas are looking for alternatives to fight it. SARS-CoV-2, the cause of the infectious respiratory disease COVID-19, is mainly transmitted through direct or indirect contact with infected respiratory droplets. The integrity of the virus structure is crucial for its viability to attack human cells. Quaternary ammonium salts are characterized by having antiviral capabilities which alter or destroy the structure of the viral capsid. In this work, polypropylene (PP)/(1-Hexadecyl) trimethyl-ammonium bromide (CTAB) composites have been prepared in order to create an antiviral material. The composites were melt processed and blown to produce thin films. The CTAB content on the antiviral effect was evaluated using antibodies and serum from infected patients with the SARS-CoV-2 virus. In addition, the mechanical and thermal properties of blown films were investigated, and CTAB release kinetics from the films was followed by UV-Vis. The results indicate that the virus tends to remain less on the polymer surface by increasing the amount of CTAB in the PP matrix.

Volatile Organic Compound Exhaled Breath Sensing

This book chapter presents a broad overview of the application of nanotechnology in the biomedical area, exemplified by the application of several gas sensors (electrochemical sensors, piezoelectric sensors, optical, chemoresistive, metal oxide sensors, surface acoustic wave sensors) and focusing on the study of volatile organic compounds (VOCs) in exhaled breath for the screening of diseases of worldwide interest such as breast cancer, lung cancer, COVID-19, post COVID-19 syndrome, colorectal cancer, prostate cancer, diabetes, chronic obstructive disease, among others. This document aims to provide the state of the art in disruptive technologies based on nanosensors, especially electronic noses and the advances and perspectives in this field. The present work represents an important tool for researchers who are in the field of the development of sensing disruptive technologies for the study of VOCs in biological matrices (i.e., exhaled breath). Thus, the application of gas sensors has proven to be feasible in the biomedical area and a promising area within the diagnosis of communicable and non-communicable diseases, to be applied in POC settings, clinics, hospitals, doctors’ offices, and especially in-field applications for less-favored populations where they lack the minimum resources to achieve universal health coverage.

Health Sentinel: A mobile crowdsourcing platform for self-reported surveys provides early detection of COVID-19 clusters in San Luis Potosí, Mexico.

BACKGROUND: The Health Sentinel (Centinela de la Salud, CDS), a mobile crowdsourcing platform that includes the CDS app, was deployed to assess its utility as a tool for COVID-19 surveillance in San Luis Potosí, Mexico. METHODS: The CDS app allowed anonymized individual surveys of demographic features and COVID-19 risk of transmission and exacerbation factors from users of the San Luis Potosí Metropolitan Area (SLPMA). The platform's data processing pipeline computed and geolocalized the risk index of each user and enabled the analysis of the variables and their association. Point process analysis identified geographic clustering patterns of users at risk and these were compared with the patterns of COVID-19 cases confirmed by the State Health Services. RESULTS: A total of 1554 COVID-19 surveys were administered through the CDS app. Among the respondents, 50.4 % were men and 49.6 % women, with an average age of 33.5 years. Overall risk index frequencies were, in descending order: no-risk 77.8 %, low risk 10.6 %, respiratory symptoms 6.7 %, medium risk 1.4 %, high risk 2.0 %, very high risk 1.5 %. Comorbidity was the most frequent vulnerability category (32.4 %), followed by the inability to keep home lockdown (19.2 %). Statistically significant risk clusters identified at a spatial scale between 5 and 730 m coincided with those in neighborhoods containing substantial numbers of confirmed COVID-19 cases. CONCLUSIONS: The CDS platform enables the analysis of the sociodemographic features and spatial distribution of individual risk indexes of COVID-19 transmission and exacerbation. It is a useful epidemiological surveillance and early detection tool because it identifies statistically significant and consistent risk clusters in neighborhoods with a substantial number of confirmed COVID-19 cases.

A review of Environmental risks and vulnerability factors of indigenous populations from Latin America and the Caribbean in the face of the COVID-19.

Latin America and the Caribbean (LAC) was declared a new epicentre of the coronavirus pandemic by the World Health Organization (WHO) on 22 May 2020. As of 13 January 2021, the numbers of deaths and cases caused by COVID-19 in LAC reported are 552,000 and 17'485,000 respectively. LAC concentrates the largest percentage of indigenous populations throughout the world. In this region, poverty is persistent and particularly rural indigenous peoples hold the steepest barriers to health services and experience profound discrimination based on ethnicity, poverty, and language, compared to their non-indigenous counterparts. The information regarding the health of indigenous populations, in general, is scarce, and this problem is aggravated in the face of the COVID-19 pandemic. Therefore, the main objective of this work is to address the overall scenario of indigenous peoples in the Latin American and Caribbean region from March 2020 to January 2021, in this manner gathering information regarding health problems, economic, social, cultural and environmental factors that make indigenous populations in LAC particularly vulnerable to serious health effects from the COVID-19 pandemic, as well as compiling the mitigation strategies implemented in indigenous communities.

Comparative analysis of chemical breath-prints through olfactory technology for the discrimination between SARS-CoV-2 infected patients and controls.

BACKGROUND: We identified a global chemical pattern of volatile organic compounds in exhaled breath capable of discriminating between COVID-19 patients and controls (without infection) using an electronic nose. METHODS: The study focused on 42 SARS-CoV-2 RT-qPCR positive subjects as well as 42 negative subjects. Principal component analysis indicated a separation of the study groups and provides a cumulative percentage of explanation of the variation of 98.3%. RESULTS: The canonical analysis of principal coordinates model shows a separation by the first canonical axis CAP1 (r2 = 0.939 and 95.23% of correct classification rate), the cut-off point of 0.0089; 100% sensitivity (CI 95%:91.5-100%) and 97.6% specificity (CI 95%:87.4-99.9%). The predictive model usefulness was tested on 30 open population subjects without prior knowledge of SARS-CoV-2 RT-qPCR status. Of these 3 subjects exhibited COVID-19 suggestive breath profiles, all asymptomatic at the time, two of which were later shown to be SARS-CoV-2 RT-qPCR positive. An additional subject had a borderline breath profile and SARS-CoV-2 RT-qPCR positive. The remaining 27 subjects exhibited healthy breath profiles as well as SARS-CoV-2 RT-qPCR test results. CONCLUSIONS: In all, the use of olfactory technologies in communities with high transmission rates as well as in resource-limited settings where targeted sampling is not viable represents a practical COVID-19 screening approach capable of promptly identifying COVID-19 suspect patients and providing useful epidemiological information to guide community health strategies in the context of COVID-19.