Health effects of informal precarious workers in occupational environments with high exposure to pollutants.

The aim is to investigate and describe the health conditions of workers who are employed in precarious work settings in Mexico. Specifically, the study aims to provide insight on the health status of workers who are vulnerable due to the informal nature of their employment. Through the evaluation of three different scenarios of precarious employment (n = 110), including workers in mercury miner (workers A), brick-kilns (workers B), and quarries workers (workers C). The study analyzes clinical parameters to determine the workers' renal health condition and assesses their pulmonary function using spirometry. Multivariate analyses and Spearman correlation are performed to determine the contribution of length of service to workers' health parameters. Workers B have the highest incidence of clinical health alterations, with the highest BMI and prediabetes/diabetes index, albumin creatinine ratio, and eGFR. Moreover, pulmonary function parameters show a decrease in %FEV1/FVC in workers B and C compared to workers A, while workers A demonstrate a more significant decrease in %FEV1. Additionally, a negative correlation is observed between the length of service in precarious work settings and lung parameters (r = -0.538, p < 0.001). In conclusion, this study highlights the need to address the issue of precarious employment in Mexico by improving working conditions, access to healthcare and promoting social protection for workers, which can reduce the number of work-related illnesses and deaths and ensure the safety and health of workers.

Determination of global chemical patterns in exhaled breath for the discrimination of lung damage in postCOVID patients using olfactory technology.

The objective of this work was to evaluate the use of an electronic nose and chemometric analysis to discriminate global patterns of volatile organic compounds (VOCs) in breath of postCOVID syndrome patients with pulmonary sequelae. A cross-sectional study was performed in two groups, the group 1 were subjects recovered from COVID-19 without lung damage and the group 2 were subjects recovered from COVID-19 with impaired lung function. The VOCs analysis was executed using a Cyranose 320 electronic nose with 32 sensors, applying principal component analysis (PCA), Partial Least Square-Discriminant Analysis, random forest, canonical discriminant analysis (CAP) and the diagnostic power of the test was evaluated using the ROC (Receiver Operating Characteristic) curve. A total of 228 participants were obtained, for the postCOVID group there are 157 and 71 for the control group, the chemometric analysis results indicate in the PCA an 84% explanation of the variability between the groups, the PLS-DA indicates an observable separation between the groups and 10 sensors related to this separation, by random forest, a classification error was obtained for the control group of 0.090 and for the postCOVID group of 0.088 correct classification. The CAP model showed 83.8% of correct classification and the external validation of the model showed 80.1% of correct classification. Sensitivity and specificity reached 88.9% (73.9%-96.9%) and 96.9% (83.7%-99.9%) respectively. It is considered that this technology can be used to establish the starting point in the evaluation of lung damage in postCOVID patients with pulmonary sequelae.

Assessment of inflammatory cytokines in exhaled breath condensate and exposure to mixtures of organic pollutants in brick workers.

Brick production causes a lot of pollution in the form of dust, fumes, and toxic substances. Therefore, brick workers are highly exposed to pollutants and present a high risk of developing respiratory diseases. The objective of this research was to determine the exposure to polycyclic aromatic hydrocarbons (PAHs) and toluene in urine and evaluate the effects on health using markers of oxidative stress in exhaled breath condensate (EBC) as well as the exposure to pollutants in suspended particles of the studied area. Exposure to PAHs and toluene was evaluated using hydroxylated markers (OH) of PAHs and hippuric acid in urine, respectively. Cytokines like TNF-α, INF-y, IL-2, IL-4, IL-6, IL-8, IL-10 y GMCSF in EBC were also evaluated. PM2.5 particles were measured during an 8-h work shift. The results in brick workers presented a total OH-PAHs concentration of 97.3 µg/L and hippuric acid concentration of 0.2 g/L. The environmental concentrations of suspended particles were found within a range of 41.67-3541.6 µg/m3. The median of cytokines oscillated between 11.8 pg/mL to 1041 pg/mL. In conclusion, these results are similar to those of occupations in which there is high exposure to pollutants and populations with lung diseases. For that reason, the brick production sector requires prevention and control strategies against the pollutants emitted.

Chemometric analysis of the global pattern of volatile organic compounds in the exhaled breath of patients with COVID-19, post-COVID and healthy subjects. Proof of concept for post-COVID assessment.

The objective of this research was to evaluate the application of an electronic nose and chemometric analysis to discriminate volatile organic compounds between patients with COVID-19, post-COVID syndrome and controls in exhaled breath samples. A cross-sectional study was performed on 102 exhaled breath samples, 42 with COVID-19, 30 with the post-COVID syndrome and 30 control subjects. Breath-print analysis was performed by the Cyranose 320 electronic nose with 32 sensors. Group data were evaluated by Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA), and Support Vector Machine (SVM), and the test's diagnostic power was evaluated through a Receiver Operaring Characteristic curve(ROC curve). The results of the chemometric analysis indicate in the PCA a 97.6% (PC1 = 95.9%, PC2 = 1.0%, PC3 = 0.7%) of explanation of the variability between the groups by means of 3 PCs, the CDA presents a 100% of correct classification of the study groups, SVM a 99.4% of correct classification, finally the PLS-DA indicates an observable separation between the groups and the 12 sensors that were related. The sensitivity, specificity of post-COVID vs. controls value reached 97.6% (87.4%-99.9%) and 100% (88.4%-100%) respectively, according to the ROC curve. As a perspective, we consider that this technology, due to its simplicity, low cost and portability, can support strategies for the identification and follow-up of post-COVID patients. The proposed classification model provides the basis for evaluating post-COVID patients; therefore, further studies are required to enable the implementation of this technology to support clinical management and mitigation of effects.

Evaluation of respiratory function and biomarkers of exposure to mixtures of pollutants in brick-kilns workers from a marginalized urban area in Mexico.

Brick-kilns are polluted environments due to the use of low-quality technologies and fuels, which generates black fumes with a large number of pollutants. The objective of this research was to analyze environmental exposure and biomarkers of exposure to polycyclic aromatic hydrocarbons, metals, and respiratory health in brickmakers to assess the baseline state of contamination in a brick-kiln area of San Luis Potosi, Mexico. Lead was quantified in soil and particulate matter of 2.5 µm (PM2.5) and 10 µm (PM10) in brick-kiln areas. In brickmakers, lead was evaluated in whole blood and 10 hydroxylated metabolites of polycyclic aromatic hydrocarbons were determined in urine. Respiratory health was assessed by spirometry, exhaled breath condensate, and a COPD-PS questionnaire. Data association was performed by Spearman correlation. Environmental concentrations and biomarkers of exposure are presented as medians, for lead, it was 60.4 mg/kg, for PM10, it was 2663.1 µg/m3, and for PM2.5, it was 166.6 µg/m3. For blood lead, it was 1.06 µg/dL, and the summed concentration of OH-PAHs in urine was 16.1 µg/L. Spirometry values were 2.8 ± 0.6 L and 2.9 ± 1.3 L/s FEV1 and FEV 25-75 respectively. The correlation results indicate that the older the age of the workers is and the extensive period they have been working, their lung function is affected the most. The health vulnerability present in these occupational activities is high, so it is necessary to make visible, address these economic activities in Mexico, and apply surveillance systems based on the health of the worker.

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.

Application of chemoresistive gas sensors and chemometric analysis to differentiate the fingerprints of global volatile organic compounds from diseases. Preliminary results of COPD, lung cancer and breast cancer.

BACKGROUND: Analysis of volatile organic compounds (VOCs) in exhaled breath has been proposed as a screening method that discriminates between disease and healthy subjects, few studies evaluate whether these chemical fingerprints are specific when compared between diseases. We evaluated global VOCs and their discrimination capacity in chronic obstructive pulmonary disease (COPD), lung cancer, breast cancer and healthy subjects by chemoresistive sensors and chemometric analysis. METHODS: A cross-sectional study was conducted with the participation of 30 patients with lung cancer, 50 with breast cancer, 50 with COPD and 50 control subjects. Each participant's exhaled breath was analyzed with the electronic nose. A multivariate analysis was carried: principal component analysis (PCA) and, canonical analysis of principal coordinates (CAP). Twenty single-blind samples from the 4 study groups were evaluated by CAP. RESULTS: A separation between the groups of patients to the controls was achieved through PCA with explanations of >90% of the data and with a correct classification of 100%. In the CAP of the 4 study groups, discrimination between the diseases was obtained with 2 canonical axes with a correct general classification of 91.35%. This model was used for the prediction of the single-blind samples resulting in correct classification of 100%. CONCLUSIONS: The application of chemoresistive gas sensors and chemometric analysis can be used as a useful tool for a screening test for lung cancer, breast cancer and COPD since this equipment detects the set of VOCs present in the exhaled breath to generate a characteristic chemical fingerprint of each disease.