Many prey organisms adaptively respond to predation risk by inducible defenses with underlying tradeoffs in resource allocation. Cyanobacterial blooms expose zooplankton to poor food conditions, affecting the herbivores’ fitness. Given the interferences on resources allocation and life history traits, poor-quality cyanobacteria are predicted to affect the adaptive predator-induced responses in zooplankton. Here, we exposed two clones (i.e., clones SH and ZJ) of the cladoceran Daphnia mitsukuri to different combinations of fish predation cues and diets containing toxic Microcystis aeruginosa (0%–30%). D. mitsukuri matured at a small size and had elongated relative tail spine as adaptive responses to fish cues. Despite the comparable tail spine defense, fish cue-induced changes in growth and reproduction in the clone SH were more pronounced than those in the clone ZJ under no M. aeruginosa. Animals accumulated microcystin in the whole body with increasing abundance of M. aeruginosa. However, the inducible enhanced tail spine allometry was not affected, resulting in unchanged tail spine defense by Daphnia under all M. aeruginosa treatments. By contrast, M. aeruginosa remarkably decreased the adaptive maturation size and the offspring number in all animals. However, the inducible reproductive effort tended to increase or remain unchanged depending on clones associated with the constant or decreased responses of the somatic growth effort under increasing M. aeruginosa. Our results suggested that toxic M. aeruginosa did not alter the resource allocation to antipredator morphological defense but affected the somatic growth and reproduction in D. mitsukuri under fish cues. The present study highlights the different effects of toxic cyanobacteria on adaptive predator-induced responses in zooplankton, promoting the understanding for the morphological defense-mediated predator–prey interactions in eutrophic environments.

To control the spread of COVID-19, China implemented a series of lockdowns, limiting various offline interactions. This provided an opportunity to study the response of air quality to emissions control. By comparing the characteristics of pollution in the summers of 2019 and 2020, we found a significant decrease in gaseous pollutants in 2020. However, particle pollution in the summer of 2020 was more severe; PM₂.₅ levels increased from 35.8 to 44.7 μg m⁻³, and PM₁₀ increased from 51.4 to 69.0 μg m⁻³ from 2019 to 2020. The higher PM₁₀ was caused by two sandstorm events on May 11 and June 3, 2020, while the higher PM₂.₅ was the result of enhanced secondary formation processes indicated by the higher sulfate oxidation rate (SOR) and nitrate oxidation rate (NOR) in 2020. Higher SOR and NOR were attributed mainly to higher relative humidity and stronger oxidizing capacity. Analysis of PMₓ distribution showed that severe haze occurred when particles within Bin2 (size ranging 1–2.5 μm) dominated. SO₄²⁻₍₁/₂.₅₎ and SO₄²⁻₍₂.₅/₁₀₎ remained stable under different periods at 0.5 and 0.8, respectively, indicating that SO₄²⁻ existed mainly in smaller particles. Decreases in NO₃⁻₍₁/₂.₅₎ and increases in NO₃⁻₍₂.₅/₁₀₎ from clean to polluted conditions, similar to the variations in PMₓ distribution, suggest that NO₃⁻ played a role in the worsening of pollution. O₃ concentrations were higher in 2020 (108.6 μg m⁻³) than in 2019 (96.8 μg m⁻³). Marked decreases in fresh NO alleviated the titration of O₃. Furthermore, the oxidation reaction of NO₂ that produces NO₃⁻ was dominant over the photochemical reaction of NO₂ that produces O₃, making NO₂ less important for O₃ pollution. In comparison, a lower VOC/NOₓ ratio (less than 10) meant that Beijing is a VOC-limited area; this indicates that in order to alleviate O₃ pollution in Beijing, emissions of VOCs should be controlled.

Commuters are exposed to a variety of physicochemical and microbiological pollutants that can lead to adverse health effects. This study aims to evaluate the indoor air quality (IAQ) in cars, buses and trains in Lisbon, to estimate inhaled doses while commuting and to evaluate the impacts of cleaning and ventilation on the IAQ. Particulate matter with diameter lower than 1, 2.5 and 10 μm (PM₁, PM₂.₅ and PM₁₀), black carbon (BC), carbon monoxide (CO), carbon dioxide (CO₂) volatile organic compounds (VOCs), formaldehyde (CH₂O) and total airborne bacteria and fungi were measured and bacterial isolates were identified. Results showed that the type of ventilation is the main factor affecting the IAQ in vehicle cabins. Under the fan off condition, the concentration of BC was lower, but the concentration of gases such as CO₂, CO and VOC tended to accumulate rapidly. When the ventilation was used, the coarse particles were filtered originating the decrease of indoor concentrations. Commuters travelling in trains received the lowest dose for all chemical pollutants, except VOC, mainly because railways are further away from the direct vehicular emissions. Commuters travelling in cars without ventilation received the highest inhaled dose for almost all pollutants despite having the lowest travel duration. Airborne microbiota was highly affected by the occupancy of the vehicles and therefore, the fungi and bacterial loads were higher in trains and buses. Most of the isolated species were human associated bacteria and some of the most abundant species have been linked to respiratory tract infections.

Nitrous oxide (N₂O), an ozone-depleting greenhouse gas, is generally produced by soil microbes, particularly NH₃ oxidizers and denitrifiers, and emitted in large quantities after N fertilizer application in croplands. N₂O can be produced via multiple processes, and reduced, with the involvement of more diverse microbes with different physiological constraints than previously thought; therefore, there is a lack of consensus on the production processes and microbes involved under different agricultural practices. In this study, multiple approaches were applied, including N₂O isotopocule analyses, microbial gene transcript measurements, and selective inhibition assays, to revisit the involvement of NH₃ oxidizers and denitrifiers, including the previously-overlooked taxa, in N₂O emission from a cropland, and address the biological and environmental factors controlling the N₂O production processes. Then, we synthesized the results from those approaches and revealed that the overlooked denitrifying bacteria and fungi were more involved in N₂O production than the long-studied ones. We also demonstrated that the N₂O production processes and soil microbes involved were different based on fertilization practices (plowing or surface application) and fertilization types (manure or urea). In particular, we identified the following intensified activities: (1) N₂O production by overlooked denitrifying fungi after manure fertilization onto soil surface; (2) N₂O production by overlooked denitrifying bacteria and N₂O reduction by long-studied N₂O-reducing bacteria after manure fertilization into the plowed layer; and (3) N₂O production by NH₃-oxidizing bacteria and overlooked denitrifying bacteria and fungi when urea fertilization was applied into the plowed layer. We finally propose the conceptual scheme of N flow after fertilization based on distinct physiological constraints among the diverse NH₃ oxidizers and denitrifiers, which will help us understand the environmental context-dependent N₂O emission processes.

Prothioconazole (PTC), a popular agricultural fungicide, and its main metabolite prothioconazole-desthio (PTCd) are receiving great attention due to their toxicological effects in the non-target organisms. This study investigated their dosage-dependent (1 and 5 mg/kg BW/day) toxicological effects on oxidative stress and metabolic profiles of liver and kidney tissues using male mice. PTC and PTCd significantly inhibited the growth phenotype including body weights gain, liver and kidney indices. Furthermore, these effects were deeply investigated using the biomarkers of oxidative stress, and metabolomics. Notably, these effects were dose and tissue-dependent. Specifically, the more serious impacts involving oxidative stress and metabolic disorders were observed in the high concentration treatment groups. Also, the liver tissue was more severely affected than the kidney tissue. Lastly, the change in oxidative stress biomarkers and metabolomics profile revealed that PTCd induced more severe toxic effects than the parent compound PTC. In brief, these results indicate that exposure to PTC and PTCd could cause potential health risks in mammals.

Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O₃, NO₂, NO, PM₂.₅, and PM₁₀, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error ∼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution.

Spatial variation of the levels of polycyclic aromatic hydrocarbons (PAHs) was evaluated within an urban-industrial district where the main anthropogenic pressures are a 15 MW biomass power plant (BPP) and road traffic. The use of a high-density lichen transplant network and wind quantitative relationships made it possible to perform a hierarchical analysis of contamination. Combined uni-bi and multivariate statistical analyses of the resulting databases revealed a dual pattern. In its surroundings (local scale), the BPP affected the bioaccumulation of fluoranthene, pyrene and total PAHs, although a confounding effect of traffic (mostly petrol/gasoline engines) was evident. Spatial variation of the rate of diesel vehicles showed a significant association with that of acenaphthylene, acenaphthene, fluorene, anthracene and naphthalene. The series of high-speed wind values suggests that wind promotes diffusion rather than dispersion of the monitored PAHs. At the whole study area scale, the BPP was a source of acenaphthylene and acenaphthene, while diesel vehicles were a source of acenaphthylene. PAHs contamination strongly promotes oxidative stress (a threefold increase vs pre-exposure levels) in lichen transplants, suggesting a marked polluting effect of anthropogenic sources especially at the expense of the mycobiont. The proposed monitoring approach could improve the apportionment of the different contributions of point and linear anthropogenic sources of PAHs, mitigating the reciprocal biases affecting their spatial patterns.

Wetlands can improve water quality, but they are also recognized as important sources of greenhouse gases (GHG) such as nitrous oxide (N₂O) and methane (CH₄). Emissions of these gases from wetland ecosystems, especially those in headwaters, are poorly understood. Here, we determined monthly concentrations of dissolved N₂O and CH₄ in a headwater stream of the Taihu Lake basin of China that contains both wetland and non-wetland reaches. Daily GHG dynamics in the wetland reach were also investigated. Riverine N₂O and CH₄ concentrations generally varied within 10–30 nmol L⁻¹ and 0.1–1.5 μmol L⁻¹, respectively. CH₄ saturation levels in the wetland reach were about seven times higher than those in the non-wetland reach, but there was no difference in N₂O saturation. In the wetland reach, saturation levels of CH₄ peaked in July, coincident with a dip in N₂O saturation to levels below its saturated solubility. This underscores that hotspots of CH₄ production and sinks for N₂O can occur occasionally in wetlands in mid-summer, when vegetative growth and microbial activities are high. Diurnal measurements indicated that CH₄ saturation in water flows passing through the wetlands from midnight through the early morning can surge to levels 10 times higher than those detected at other times of the day. Simultaneously, saturation levels of N₂O decreased by 75%, indicating a net consumption of N₂O. Changes in nutrient supply determined by upstream inflows, as well as dissolved oxygen, pH, and other environmental factors mediated by the wetlands, correlate with the differentiated behavior of N₂O and CH₄ production in wetlands. Additional work will be necessary to confirm the roles of these factors in regulating GHG emissions in riverine wetlands.

This systematic review and meta-analysis aimed to investigate the association between air pollution and DNA methylation in adults from published observational studies. PubMed, Web of Science and Embase databases were systematically searched for available studies on the association between air pollution and DNA methylation published up to March 9, 2021. Three DNA methylation approaches were considered: global methylation, candidate-gene, and epigenome-wide association studies (EWAS). Meta-analysis was used to summarize the combined estimates for the association between air pollutants and global DNA methylation levels. Heterogeneity was assessed with the Cochran Q test and quantified with the I² statistic. In total, 38 articles were included in this study: 16 using global methylation, 18 using candidate genes, and 11 using EWAS, with 7 studies using more than one approach. Meta-analysis revealed an imprecise but inverse association between exposure to PM₂.₅ and global DNA methylation (for each 10-μg/m³ PM₂.₅, combined estimate: 0.39; 95% confidence interval: 0.97 - 0.19). The candidate-gene results were consistent for the ERCC3 and SOX2 genes, suggesting hypermethylation in ERCC3 associated with benzene and that in SOX2 associated with PM₂.₅ exposure. EWAS identified 201 CpG sites and 148 differentially methylated regions that showed differential methylation associated with air pollution. Among the 307 genes investigated in 11 EWAS, a locus in nucleoredoxin gene was found to be positively associated with PM₂.₅ in two studies. Current meta-analysis indicates that PM₂.₅ is imprecisely and inversely associated with DNA methylation. The candidate-gene results consistently suggest hypermethylation in ERCC3 associated with benzene exposure and that in SOX2 associated with PM₂.₅ exposure. The Kyoto Encyclopedia of Genes and Genomes (KEGG) network analyses revealed that these genes were associated with African trypanosomiasis, Malaria, Antifolate resistance, Graft-versus-host disease, and so on. More evidence is needed to clarify the association between air pollution and DNA methylation.