Environmental Epigenomics is a developing field to study the epigenetic effect on human health from exposure to environmental factors. Endocrine disrupting chemicals have been detected primarily in pharmaceutical drugs, personal care products, food additives, and food containers. Exposure to endocrine-disrupting chemicals (EDCs) has been associated with a high incidence and prevalence of many endocrine-related disorders in humans. Nevertheless, further evidence is needed to establish a correlation between exposure to EDC and human disorders. Conventional detection of EDCs is based on chemical structure and concentration sample analysis. However, substantial evidence has emerged, suggesting that cell exposure to EDCs leads to epigenetic changes, independently of its chemical structure with non-monotonic low-dose responses. Consequently, a paradigm shift in toxicology assessment of EDCs is proposed based on a comprehensive review of analytical techniques used to evaluate the epigenetic effects. Fundamental insights reported elsewhere are compared in order to establish DNA methylation analysis as a viable method for assessing endocrine disruptors beyond the conventional study approach of chemical structure and concentration analysis.

The cyclin-dependent kinase inhibitor 3 (CDKN3) gene, involved in mitosis, is upregulated in cervical cancer (CC). We investigated CDKN3 mRNA as a survival biomarker and potential therapeutic target for CC. CDKN3 mRNA was measured in 134 CC and 25 controls by quantitative PCR. A 5-year survival study was conducted in 121 of these CC patients. Furthermore, CDKN3-specific siRNAs were used to investigate whether CDKN3 is involved in proliferation, migration, and invasion in CC-derived cell lines (SiHa, CaSki, HeLa). CDKN3 mRNA was on average 6.4-fold higher in tumors than in controls (p = 8 x 10⁻⁶, Mann-Whitney). A total of 68.2% of CC patients over expressing CDKN3 gene (fold change ≥ 17) died within two years of diagnosis, independent of the clinical stage and HPV type (Hazard Ratio = 5.0, 95% CI: 2.5–10, p = 3.3 x 10⁻⁶, Cox proportional-hazards regression). In contrast, only 19.2% of the patients with lower CDKN3 expression died in the same period. In vitro inactivation of CDKN3 decreased cell proliferation on average 67%, although it had no effect on cell migration and invasion. CDKN3 mRNA may be a good survival biomarker and potential therapeutic target in CC.

Influenza has been a stationary disease in Mexico since 2009, and this causes a high cost for the national public health system, including its detection using RT-qPCR tests, treatments, and absenteeism in the workplace. Despite influenza’s relevance, the main clinical features to detect the disease defined by international institutions like the World Health Organization (WHO) and the United States Centers for Disease Control and Prevention (CDC) do not follow the same pattern in all populations. The aim of this work is to find a machine learning method to facilitate decision making in the clinical differentiation between positive and negative influenza patients, based on their symptoms and demographic features. The research sample consisted of 15480 records, including clinical and demographic data of patients with a positive/negative RT-qPCR influenza tests, from 2010 to 2020 in the public healthcare institutions of Mexico City. The performance of the methods for classifying influenza cases were evaluated with indices like accuracy, specificity, sensitivity, precision, the f1-measure and the area under the curve (AUC). Results indicate that random forest and bagging classifiers were the best supervised methods; they showed promise in supporting clinical diagnosis, especially in places where performing molecular tests might be challenging or not feasible.

Health care workers (HCW) are at high risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The incidence of SARS-CoV-2 infection in HCW has been examined in cross-sectional studies by quantitative polymerase chain reaction (qPCR) tests, which may lead to underestimating exact incidence rates. We thus investigated the incidence of SARS-CoV-2 infection in a group of HCW at a dedicated coronavirus disease 2019 (COVID-19) hospital in a six-month follow-up period. We conducted a prospective cohort study on 109 participants of both sexes working in areas of high, moderate, and low SARS-CoV-2 exposure. qPCR tests in nasopharyngeal swabs and anti-SARS-CoV-2 IgG serum antibodies were assessed at the beginning and six months later. Demographic, clinical, and laboratory parameters were analyzed according to IgG seropositivity by paired Student’s T-test or the chi-square test. The incidence rate of SARS-CoV-2 infection was considerably high in our cohort of HCW (58%), among whom 67% were asymptomatic carriers. No baseline risk factors contributed to the infection rate, including the workplace. It is still necessary to increase hospital safety procedures to prevent virus transmissibility from HCW to relatives and non-COVID-19 patients during the upcoming waves of contagion.

Background: Phase III clinical trials have documented the efficacy of the SARS-CoV-2 vaccines in preventing symptomatic COVID-19. Nonetheless, it is imperative to continue analyzing the clinical response to different vaccines in real-life studies. Our objective was to evaluate the effectiveness of five different vaccines in hospitalized patients with COVID-19 during the third COVID-19 outbreak in Mexico dominated by the Delta variant. Methods: A test-negative case–control study was performed in nine tertiary-care hospitals for COVID-19. We estimated odds ratios (OR) adjusted by variables related a priori with the likelihood of SARS-CoV-2 infection and its severity. Results: We studied 761 subjects, 371 cases, and 390 controls with a mean age of 53 years (SD, 17 years). Overall, 51% had a complete vaccination scheme, and an incomplete scheme (one dose from a scheme of two), 14%. After adjustment for age, gender, obesity, and diabetes mellitus, we found that the effectiveness of avoiding a SARS-CoV-2 infection when hospitalized with at least one vaccination dose was 71% (OR 0.29, 95% CI 0.19–0.45), that of an incomplete vaccination scheme, 67% (OR 0.33, 95% CI 0.18–0.62), and that of any complete vaccination scheme, 73% (OR 0.27, 95% CI 0.17–0.43). Conclusions: The SARS-CoV-2 vaccination program showed effectiveness in preventing SARS-CoV-2 infection in hospitalized patients during a Delta variant outbreak.

Throughout the entire coronavirus disease 19 (COVID-19) pandemic, there were disruptions in the supply chain of test materials around the world, primarily in poor- and middle-income countries. The use of 3D prints is an alternative to address swab supply shortages. In this study, the feasibility of the clinical use of 3D-printed swabs for oropharyngeal and nasopharyngeal sampling for the detection of SARS-CoV-2 infection was evaluated. For that purpose, paired samples with the 3D printed and the control swabs were taken from 42 adult patients and 10 pediatric patients, and the results obtained in the detection of SARS-CoV-2 by reverse transcription and quantitative polymerase chain reaction (RT-qPCR) were compared. Additionally, in those cases where the result was positive for SARS-CoV-2, the viral load was calculated by means of a mathematical algorithm proposed by us. For both adults and children, satisfactory results were obtained in the detection of SARS-CoV-2 by RT-qPCR; no significant differences were found in the quantification cycle values between the 3D-printed swab samples and the control samples. Furthermore, we corroborated that the 3D-printed swabs caused less discomfort and pain at the time of sampling. In conclusion, this study shows the feasibility of routinely using 3D-printed swabs for both adults and children. In this way, it is possible to maintain local and cheaper consumption along with fewer distribution difficulties.