The effects of catalytic hydrothermal (HT) pretreatment on animal manure followed by the addition of hydrochar on the nutrients recovery have not yet been investigated using a combination of chemical, microscopic, and spectroscopic techniques. Therefore, a catalytic HT process was employed to pretreat swine manure without additives (manure-HT) and with H₂O₂ addition (manure-HT- H₂O₂) to improve the conversion efficiency of labile or organic phosphorus (P) to inorganic phase. Then, a Ca–Al layered double hydroxide hydrochar (Ca/Al LDH@HC) derived from corn cob biomass was synthesized and applied to enhance P sorption. Scanning electron microscopy (SEM), and three-dimensional excitation emission matrix (3D-EEM), X-ray photoelectron spectroscopy (XPS), P k-edge X-ray absorption near edge structure (XANES), were used to elucidate the mechanisms of P release and capture. The H₂O₂ assisted HT treatment significantly enhanced the release of inorganic P (251.4 mg/L) as compared to the untreated manure (57.2 mg/L). The 3D-EEM analysis indicated that the labile or organic P was transformed and solubilized efficiently along with the deconstruction of manure components after the H₂O₂ assisted HT pretreatment. Application of Ca/Al LDH@HC improved the removal efficiency of P from the derived P-rich HT liquid. This sorption process was conformed to the pseudo-second-order model, suggesting that chemisorption was the primary mechanism. The results of SEM and P k-edge XANES exhibited that Ca, as the dominated metal component, could act as a reaction site for the formation of phosphate precipitation. These results provide critical findings about recovering P from manure waste, which is useful for biowastes management and nutrients utilization, and mitigating unintended P loss and potential environmental risks.

Arsenic (As) and cadmium (Cd), two major carcinogenic heavy metals, enters into human food chain by the consumption of rice or rice-based food products. Both As and Cd disturb plant-nutrient homeostasis and hence, reduces plant growth and crop productivity. In the present study, As/Cd modulated responses were studied in non-basmati (IR-64) and basmati (PB-1) rice varieties, at physiological, biochemical and transcriptional levels. At the seedling stage, PB-1 was found more sensitive than IR-64, in terms of root biomass; however, their shoot phenotype was comparable under As and Cd stress conditions. The ionomic data revealed significant nutrient deficiencies in As/Cd treated-roots. The principal component analysis identified NH₄⁺ as As-associated key macronutrient; while, NH₄⁺/NO₃⁻ and K⁺ was majorly associated with Cd mediated response, in both IR-64 and PB-1. Using a panel of 21 transporter gene expression, the extent of nutritional deficiency was ranked in the order of PB-1(As)<IR-64(As)<PB-1(Cd)<IR-64(Cd). A feed-forward model is proposed to explain nutrient deficiency induced de-regulation of gene expression, as observed under Cd-treated IR-64 plants, which was also validated at the level of sulphur metabolism related enzymes. Using urea supplementation, as nitrogen-fertilizer, significant mitigation was observed under As stress, as indicated by 1.018- and 0.794-fold increase in shoot biomass in IR-64 and PB-1, respectively compared to that of control. However, no significant amelioration was observed in response to supplementation of urea under Cd or potassium under As/Cd stress conditions. Thus, the study pinpointed the relative significance of various macronutrients in regulating As- and Cd-tolerance and will help in designing suitable strategies for mitigating As and/or Cd stress conditions.

Predicting the occurrence of algal blooms is of great importance in managing water quality. Moreover, the demand for predictive models, which are essential tools for understanding the drivers of algal blooms, is increasing with global warming. However, modeling cyanobacteria dynamics is a challenging task. We developed a multivariate Chain-Bernoulli-based prediction model to effectively forecast the monthly sequences of algal blooms considering hydro-environmental predictors (water temperature, total phosphorus, total nitrogen, and water velocity) at a network of stations. The proposed model effectively predicts the risk of harmful algal blooms, according to performance measures based on categorical metrics of a contingency table. More specifically, the model performance assessed by the LOO cross-validation and the skill score for the POD and CSI during the calibration period was over 0.8; FAR and MR were less than 0.15. We also explore the relationship between hydro-environmental predictors and algal blooms (based on cyanobacteria cell count) to understand the dynamics of algal blooms and the relative contribution of each potential predictor. A support vector machine is applied to delineate a plane separating the presence and absence of algal bloom occurrences determined by stochastic simulations using different combinations of predictors. The multivariate Chain-Bernoulli-based prediction model proposed here offers effective, scenario-based, and strategic options and remedies (e.g., controlling the governing environmental predictors) to relieve or reduce increases in cyanobacteria concentration and enable the development of water quality management and planning in river systems.

Single-chemical thresholds cannot comprehensively evaluate the risk of chemical mixture exposure in indoor air. Moreover, a large number of researches have focused on short-term and high-concentration co-exposure scenarios related to different species, based on diverse endpoints, which hampers the application and improvement of existing risk evaluation models of chemical mixture exposures. More importantly, current risk evaluation models are not user-friendly for construction practitioners who do not have sufficient toxicological knowledge. Therefore, in this study, an inhalation experiment system and a hazard index (HI) were developed to investigate the risks associated with low-concentration and long-term inhalation exposure scenarios of formaldehyde and benzene, individually and combined, based on Drosophila melanogaster mortality. The results showed that the system exhibited good reproducibility in providing stable exposure concentrations during D. melanogaster life cycle. Furthermore, in a range of experimental concentrations, the interaction between formaldehyde and benzene was additive or synergistic, which was concentration- and ratio-dependent. This study is of great significance in harmonising and providing toxicity data under long-term and low-concentration exposure scenarios, which is beneficial for establishing a new user-friendly risk evaluation model for indoor chemical mixture exposures. It should be noted that the proposed HI value could indicate the hazard degrees of long-term inhalation exposures of formaldehyde and benzene, individually and combined, to D. melanogaster. However, the applicability of this index requires further experiments to evaluate the exposure risks of other volatile organic compounds (VOCs) to D. melanogaster.

Climate changes and metal contamination are pervasive stressors for soil ecosystems. Mercury (Hg), one of the most toxic metals, has been reported to interact with temperature. However, compared to aquatic biota, little is known about how temperature affects Hg toxicity and bioaccumulation to soil organisms. Here, toxicity and bioaccumulation experiments were replicated at 15 °C, 20 °C, and 25 °C to understand how sub-optimal temperatures affect the toxicokinetics and toxicodynamics of Hg via soil. Genotoxicity and energy reserves were also assessed to disclose potential trade-offs in life-history traits. Results underpin the complexity of temperature-Hg interactions. Survival was determined mainly by toxicokinetics, but toxicodynamics also played a significant role in defining survival probability during early stages. The processes determining survival probability were faster at 25 °C: General Unified Threshold of Survival (GUTS) model identified an earlier/steeper decline in survival, compared to 20 °C or 15 °C, but it also approached the threshold faster. Despite potentiation of Hg genotoxicity, temperature promoted faster detoxification, either increasing toxicokinetics rates or damage repair mechanisms. This metabolism-driven increase in detoxification led to higher depletion of energy reserves and likely triggered stress response pathways. This work emphasized the need for comprehensive experimental approaches that can integrate the multiple processes involved in temperature-metal interactions.

Freshwater ecosystems are recognized as non-negligible sources of plastic contamination for the marine environment that is the final acceptor of 53 thousand tons of plastic per year. In this context, microplastic particles are well known to directly pose a great threat to freshwater organisms, they also indirectly affect the aquatic ecosystem by adsorbing and acting as a vector for the transport of other pollutants (“Trojan horse effect”). Polystyrene is one of the most widely produced plastics on a global scale, and it is among the most abundant microplastic particles found in freshwaters. Nevertheless, to date few studies have focused on the eco-genotoxic effects on freshwater organisms caused by polystyrene microplastic particles (PS-MPs) in combination with other pollutants such as pharmaceuticals and pesticides. The aim of this study is to investigate chronic and sub-chronic effects of the microplastic polystyrene beads (PS-MP, 1.0 μm) both as individual xenobiotic and in combination (binary/ternary mixtures) with the acicloguanosine antiviral drug acyclovir (AC), and the neonicotinoid broad-spectrum insecticide imidacloprid (IMD) in one of the most sensitive non-target organisms of the freshwater food chain: the cladoceran crustacean Ceriodaphnia dubia. Considering that the individually selected xenobiotics have different modes of action and/or different biological sites, the Bliss independence was used as reference model for this research. Basically, when C. dubia neonates were exposed for 24 h to the mixtures during Comet assay, mostly an antagonistic genotoxic effect was observed. When neonates were exposed to the mixtures for 7 days, mostly an additive chronic toxic effect occurred at concentrations very close or even overlapping to the environmental ones ranging from units to tens of ng/L for PS-MPs, from tenths/hundredths to units of μg/L for AC and from units to hundreds of μg/L for IMD, revealing great environmental concern.

We aimed to explore the effects of mixtures of lead and various metals on blood pressure (BP) and the odds of pre-hypertension (systolic blood pressure (SBP) 120–139 mmHg, and/or diastolic blood pressure (DBP) 80–89 mmHg) and hypertension (SBP/DBP ≥140/90 mmHg) among Chinese adults in a cross-sectional study. This study included 11,037 adults aged 18 years or older from the 2017–2018 China National Human Biomonitoring. Average BP and 13 metals (lead, antimony, arsenic, cadmium, mercury, thallium, chromium, cobalt, molybdenum, manganese, nickel, selenium, and tin) in blood and urine were measured and lifestyle and demographic data were collected. Weighted multiple linear regressions were used to estimate associations of metals with BP in both single and multiple metal models. Weighted quantile sum (WQS) regression was performed to assess the relationship between metal mixture levels and BP. In the single metal model, after adjusting for potential confounding factors, the blood lead levels in the highest quartile were associated with the greater odds of both pre-hypertension (odds ratio (OR): 1.56, 95% CI: 1.22–1.99) and hypertension (OR:1.75, 95% CI: 1.28–2.40) when compared with the lowest quartile. We also found that blood arsenic levels were associated with increased odds of pre-hypertension (OR:1.31, 95% CI:1.00–1.74), while urinary molybdenum levels were associated with lower odds of hypertension (OR:0.68, 95% CI:0.50–0.93). No significant associations were found for the other 10 metals. WQS regression analysis showed that metal mixture levels in blood were significantly associated with higher SBP (β = 1.56, P < 0.05) and DBP (β = 1.56, P < 0.05), with the largest contributor being lead (49.9% and 66.8%, respectively). The finding suggests that exposure to mixtures of metals as measured in blood were positively associated with BP, and that lead exposure may play a critical role in hypertension development.

Epidemiological studies have demonstrated a strong association of ambient fine particulate matter (PM₂.₅) exposure with the increasing mortality by ischemic heart disease (IHD), but the involved mechanisms remain poorly understood. Herein, we found that the chronic exposure of real ambient PM₂.₅ led to the upregulation of hypoxia-inducible factor-1 alpha (HIF-1α) protein in the myocardium of mice, accompanied by obvious myocardial injury and hypertrophy. Further data from the hypoxia-ischemia cellular model indicated that PM₂.₅-induced HIF-1α accumulation was responsible for the promotion of myocardial hypoxia injury. Moreover, the declined ATP level due to the HIF-1α-mediated energy metabolism remodeling from β-oxidation to glycolysis had a critical role in the PM₂.₅-increased myocardial hypoxia injury. The in-depth analysis delineated that PM₂.₅ exposure decreased the binding of prolyl hydroxylase domain 2 (PHD2) and HIF-1α and subsequent ubiquitin protease levels, thereby leading to the accumulation of HIF-1α. Meanwhile, factor-inhibiting HIF1 (FIH1) expression was down-regulated by PM₂.₅, resulting in the enhanced translocation of HIF-1α to the nucleus. Overall, our study provides valuable insight into the regulatory role of oxygen sensor-mediated HIF-1α stabilization and translocation in PM-exacerbated myocardial hypoxia injury, we suggest this adds significantly to understanding the mechanisms of haze particles-caused burden of cardiovascular disease.