The impacts of climate change on cyanobacterial harmful algal blooms (cHABs) are paramount, promoting the widespread distribution, intensity, and toxicity of these phenomena in major freshwater bodies across the globe. Microcystins (MCs) and nodularins (NODs) are monocyclic peptides that produce hepatotoxic effects in living organisms. Despite efforts in understanding their molecular toxicological mechanisms, we do not fully have a grasp on the human health impacts associated with these toxins derived from freshwater cHABs. We seek to provide a current update on the toxicity and epidemiology of MCs and NODs, integrating key evidence from in vitro, in vivo, and epidemiological studies. The primary objective of this work is to understand the human health impacts of MC and NOD-producing cHABs.

Children around the world are continuing to develop and suffer from chronic lung diseases such as asthma. Childhood asthma commonly presents with recurrent episodes of cough, shortness of breath, and wheezing, all of which can lead to missed school days and hospitalization admissions. The role of environmental pollutants and aeroallergens has been increasingly recognized in relation to asthma etiology. We showcase the impacts of air pollution and pollen exposures in early life on childhood asthma and allergies through an epidemiologic perspective. We also examine the effects of indoor microbial exposures such as endotoxin and glucan on allergic diseases in schoolchildren as many spend most of their time in a household or classroom setting. Findings of this work can assist in the identification of key environmental factors in critical life periods and improve clinicians’ diagnoses of asthma during early childhood.

Background: Pollen exposure in early life is shown to be associated with allergy and asthma. DNA methylation (DNAm), an epigenetic marker, potentially reacts to pollen. However, the role of at-birth DNAm between prenatal pollen grain (PPG) exposure and childhood asthma and allergic rhinitis is unknown. Methods: Data in a birth cohort study on the Isle of Wight, UK, were analyzed (n = 236). Newborn DNAm was measured in cord blood or blood spots on Guthrie cards and screened for potential association with PPG exposure using the R package ttScreening. CpGs that passed screening were further assessed for such associations via linear regressions with adjusting covariates included. Finally, DNAm at PPG-associated CpGs were evaluated for their association with asthma and allergic rhinitis using logistic regressions, adjusting for covariates. The impact of cell heterogeneity on the findings was assessed. Statistical significance was set at p < 0.05. Results: In total, 42 CpGs passed screening, with 41 remaining statistically significant after adjusting for covariates and cell types (p < 0.05). High PPG exposure was associated with lower DNAm at cg12318501 (ZNF99, β = −0.029, p = 0.032) and cg00929606 (ADM2, β = −0.023, p = 0.008), which subsequently was associated with decreased odds of asthma (OR = 0.11, 95% CI 0.02–0.53, p = 0.006; OR = 0.14, 95% CI 0.02–1.00, p = 0.049). For rhinitis, cg15790214 (HCG11) was shown to play such a role as a mediator (β = −0.027, p ≤ 0.0001; OR = 0.22, 95% CI 0.07–0.72, p = 0.01). Conclusions: The association of PPG exposure with childhood asthma and allergic rhinitis incidence is potentially mediated by DNAm at birth.

Air pollution represents an environmental health exposure associated with cardiovascular, respiratory, and neurological diseases. The temporal dynamics of key air pollutants, such as ozone (O ₃ ) and fine particulate matter (PM _2.5 ), are poorly understood, especially along the Texas industrial coastal region. This study utilizes daily time series analysis to investigate temporal trends in ambient O ₃ and PM _2.5 levels across four monitoring sites in the petrochemical-intensive city of Corpus Christi. Five years (2019–2023) of data from the U.S. Environmental Protection Agency (USEPA) on daily maximum 8-h concentrations of O ₃ (ppm) and daily mean concentration of PM _2.5 (µg/m ³ ) were used. Using classical seasonal decomposition and Autoregressive Moving Average (ARMA) modeling, we identified distinct seasonal patterns and temporal variability. Overall, O ₃ and PM _2.5 concentrations showed an inverse relationship ( ρ = -0.197; p < 0.001). Distinct seasonal patterns emerged: O ₃ peaked in spring with summer minima, while PM _2.5 demonstrated summer maxima. Both pollutants demonstrated statistically significant associations with average ambient temperature, average wind speed, and precipitation. Most notably, temperature was inversely correlated with O ₃ ( ρ = -0.373; p < 0.001) but positively with PM _2.5 concentrations ( ρ = 0.438; p < 0.001), indicating differential temperature influence. PM _2.5 also exhibited an extreme spike (70.5 μg/m ³ ) associated with a Saharan dust event in June 2020. ARMA models elucidated that elevated O₃ levels persisted daily (ARMA(1,1), p < 0.0001), while PM _2.5 oscillated (ARMA(3,4), p < 0.0001). The successful 30-day forecasting capability in this study provides essential tools for early warning systems and evidence-based air quality interventions in coastal petrochemical communities.

Purpose: This study aims to examine factors associated with asthma prevalence among Hispanic participants in the United States, focusing on access barriers, socioeconomic indicators such as education and income, and BMI. Data from the All of Us Research Program were analyzed using both traditional statistical models and interpretable machine learning algorithms. Methods: We analyzed data from the All of Us Research Program, comparing individuals with and without asthma. Logistic regression models and interpretable machine learning algorithms, including MARS (Multivariate Adaptive Regression Splines) and CIT (Conditional Inference Trees), were used to identify factors associated with asthma prevalence and their interactions. Results: The logistic regression analysis identified several variables associated with higher odds of asthma, including older age, female sex, greater access barriers, higher BMI, lower income, and higher education levels. Hispanic participants with greater access barriers had 26.3% higher odds of asthma prevalence (aPOR = 1.263, 95% CI: 1.114–1.433) compared to those without such barriers, and each unit increase in BMI was associated with a 2.9% increase in the odds of having asthma (aPOR = 1.029, 95% CI: 1.023–1.035). The MARS algorithm captured nonlinear relationships and interactions, highlighting BMI, age, sex, access barriers, income, and education as key predictors associated with asthma prevalence. Among participants younger than 60.6 years, younger age was linked with higher asthma prevalence. An interaction between age (above 21.5) and male sex indicated that the odds of asthma slightly decreased with age among males. Additionally, low-income and high BMI together were associated with elevated asthma prevalence, suggesting compounding vulnerabilities. The CIT identified BMI as the most influential variable and further stratified asthma prevalence by age, sex, education, income, and access barriers. Higher asthma prevalence was consistently observed among older females with high BMI, lower income, and greater access barriers. Conclusions: Among Hispanic participants in the All of Us Research Program, lower income combined with higher BMI and greater access barriers were significantly associated with increased odds of asthma. Males had lower odds of asthma, while older individuals showed higher asthma prevalence. These findings highlight important associations rather than causal relationships and may inform public health efforts to address asthma disparities related to weight and healthcare accessibility among Hispanic populations.

Objectives: Pollen exposure is an environmental risk factor for asthma symptoms and allergic reactions in children. However, the extent to which pollen exposure in pregnancy and early life influences the development of childhood asthma is not fully understood. We aimed to assess the associations between pollen exposure during pregnancy and early pollen exposure in the first year of life with childhood asthma at age 6 years. Methods: We assessed prenatal pollen exposure as the sum of pollen counts during 40 weeks of pregnancy and postnatal exposure as the sum of pollen counts from birth date to start of pollen season. Standardized questionnaires were used to collect data on patient demographics, asthma diagnosis, and related risk factors. Results: Increased pollen exposure during pregnancy and infancy were associated with increased odds of childhood asthma at age 6 (OR = 1.14, 95% CI 1.05-1.24, p = 0.002; OR = 1.18 95% CI 1.08-1.29, p = 0.0003, respectively). Conclusions: We conclude that higher early life (both pre- and postnatal) exposure is strongly associated with asthma development. Further studies are needed to validate these findings and to elucidate the mechanisms of early life exposures to pollen on childhood asthma etiology. Future findings could have implications for therapeutic regimens targeted at environmental triggers of asthma.