Journal of Environmental Health Science and Engineering最新文献

Biomarkers of susceptibility are indicative of an individual’s capacity to react to particular exposures, whereas toxicodynamic models elucidate the correlation between exposure and response. In this article, a novel methodology is presented for the evaluation of modifying factors in the field of toxicology. The proposed approach involves the integration of biomarkers of susceptibility with toxicodynamic models. Through the integration of these two methodologies, scientists are able to gain a more comprehensive understanding of the impact of modifying factors, such as genetic polymorphisms or epigenetic profiles, on an individual’s reaction to toxic substances. This methodology has the potential to facilitate a more thorough evaluation of the hazards linked to the contact with combinations of chemicals and the cumulative effects of such exposures. The utilization of biomarkers in the evaluation of exposure for risk assessment is progressively incorporating the examination of susceptibility factors alongside exposure factors. This may involve the identification of a particular genetic polymorphism for a metabolic enzyme. The integration of ecotoxicological tests with models is crucial for achieving a comprehensive assessment. This approach exhibits the potential to enhance our comprehension of disease causation and facilitate the identification of populations that may exhibit an elevated susceptibility to disease.

In recent years, excessive amounts of drugs such as antibiotics have been used to combat COVID-19 and newly discovered viruses. This has led to the production and release of significant amounts of drugs and their metabolites as toxic pollutants in aquatic systems. Therefore, pharmaceutical wastes must be removed efficiently before entering the environment and entering water sources. In this research, Ni/Al-LDH@ZIF-8 nanocomposite was synthesized from layered double hydroxides and metal-organic frameworks and used to remove the antibiotic sarafloxacin (SRF) in the aqueous medium. The work aimed to develop the performance and combine the features of the adsorbent compounds such as high surface area, adjustable porosity, and low-density structure. Different methods implemented to analyze the nanocomposite, such as Fourier transform infrared spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and energy dispersive X-ray spectroscopy. The experiment utilized the central composite design to evaluate statistics and the response level method to optimize the factors affecting the absorption process. The initial concentration of SRF, adsorbent dose, pH, and contact time were considered in this experiment. The results showed an increase in the removal efficiency of SRF to 97%. Statistical studies showed that the optimal adsorption conditions are as follows: initial concentration of SRF 40 mg·L^–1, pH 6.3, adsorbent dose of Ni/Al-LDH@ZIF-8 49 mg, and contact time of 44 min. According to the model of isotherms parameters, the adsorption process is more consistence with the Freundlich model with the absorption capacity of 79.7 mg·g⁻¹. The pseudo-second-order model described the adsorption kinetics data.

Graphical abstract

Background

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are persistent organic pollutants in the environment. While some studies suggest that PFASs may contribute to cancer development, the link between PFAS exposure and cancer risk remains debated.

Methods

This dose-response meta-analysis explores the relationship between PFASs and cancer. It employs odds ratio (OR) and standardized mean difference (SMD), along with their 95% confidence interval (CI), to assess the effects of PFASs on cancer risk. Relevant studies were sourced from Web of Science, PubMed, Embase, Medline, and CNKI databases. The dose-response relationship was assessed by the fixed-effects model and least-squares regression.

Results

Forty studies, involving a total of 748,188 participants, were included in this meta-analysis. Out of these, 13 studies were specifically analyzed for the dose-response relationship. Findings revealed that exposure to PFASs, especially PFDA, significantly raises the risk of genitourinary cancers, and PFDA exposure shows a dose-dependent increase in overall and breast cancer risk. Additionally, PFOS exposure is associated with an increased cancer risk, and elevated PFOA levels were significantly observed in breast cancer patients.

Conclusions

The findings suggest that PFAS exposure is a potential cancer risk factor, with the carcinogenic potential of PFDA being dose-dependent.

Analyzing municipal wastewater for the presence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) helps to evaluate the efficacy of treatment systems in mitigating virus-related health risks. This research investigates wastewater treatment plants’ (WWTPs) performance in the reduction of SARS-CoV-2 from municipal wastewater in Tehran, Iran. SARS-CoV-2 RNA was measured within sewers, at the inlets, and after the primary and secondary treatment stages of three main WWTPs. Within sewers, the average virus titer stood at 58,600 gc/L, while at WWTP inlets, it measured 38,136 gc/L. A substantial 67% reduction in virus titer was observed at the inlets, accompanied by a 2-log reduction post-primary treatment. Remarkably, the biological treatment process resulted in complete virus elimination across all plants. Additionally, a notable positive correlation (r > 0.8) was observed between temperature and virus titer in wastewater. Using wastewater-based epidemiology (WBE) technique and the estimated SARS-CoV-2 RNA shedding rates, the infection prevalence among populations served by WWTPs found to be between 0.128% to 0.577%. In conclusion, this research not only advances our understanding of SARS-CoV-2 dynamics within wastewater treatment systems but also provides practical insights for enhancing treatment efficiency and implementing the feasibility of WBE strategies in Tehran. These implications contribute to the broader efforts to protect public health and mitigate the impact of future viral outbreaks.

Graphical abstract

This paper represents the reviews of recent advancements in different physicochemical methods for disinfecting contaminated surfaces, which are considered to be responsible for transmitting different bacterial, viral, and fungal infectious diseases. Surface disinfection can be achieved by applying chemicals, UV-based processes, ionization radiation (gamma-ray, X-ray and electron beam), application of self-disinfecting surfaces, no-touch room disinfection methods, and robotic disinfection methods for built-in settings. Application of different chemicals, such as alcohols, hydrogen peroxide, peracetic acid, quaternary ammonium salts, phenol, and iodine solution, are common and economical. However, the process is time-consuming and less efficient. The use of UVC light (wavelength: 200–280 nm, generated by low vapor mercury lamps or pulse xenon light) has gained much attention for disinfecting fomites worldwide. In recent times, the combination of UV and H₂O₂, based on the principle of the advanced oxidation process, has been applied for disinfecting inanimate surfaces. The process is very efficient and faster than chemical and UV processes. Heavy metals like copper, silver, zinc, and other metals can inactivate microbes and are used for surface modification to produce self-disinfecting surfaces and used in healthcare facilities. In combination with UVB (280–315 nm) and UVA (315–400 nm), titanium oxide has been utilized for disinfecting contaminated surfaces. Ionization radiation, one of the advanced methods, can be used in disinfecting medical devices and drugs. Post-COVID-19 pandemic, the no-touch and robotic disinfection methods utilizing chemicals or UVC lights have received much importance in built-in settings. Among these methods, surface disinfection by applying chemicals by fogging/vaporization and UV radiation methods has been widely reported in the literature compared to other methods.

Wastewater-based epidemiology (WBE) is considered an innovative and promising tool for estimating community exposure to a wide range of chemical and biological compounds by analyzing wastewater. Despite scholars' interest in WBE studies, there are uncertainties and limitations associated with this approach. This current review focuses on the feasibility of the WBE approach in assessing environmental pollutants, including pesticides, heavy metals, phthalates, bisphenols, and personal care products (PCPs). Limitations and challenges of WBE studies are initially discussed, and then future perspectives, gaps, and recommendations are presented in this review. One of the key limitations of this approach is the selection and identification of appropriate biomarkers in studies. Selecting biomarkers considering the basic requirements of a human exposure biomarker is the most important criterion for validating this new approach. Assessing the stability of biomarkers in wastewater is crucial for reliable comparisons of substance consumption in the population. However, directly analyzing wastewater does not provide a clear picture of biomarker stability. This uncertainty affects the reliability of temporal and spatial comparisons. Various uncertainties also arise from different steps involved in WBE. These uncertainties include sewage sampling, exogenous sources, analytical measurements, back-calculation, and estimation of the population under investigation. Further research is necessary to ensure that measured pollutant levels accurately reflect human excretion. Utilizing data from WBE can support healthcare policy in assessing exposure to environmental pollutants in the general population. Moreover, WBE seems to be a valuable tool for biomarkers that indicate healthy conditions, lifestyle, disease identification, and exposure to pollutants. Although this approach has the potential to serve as a biomonitoring tool in large communities, it is necessary to monitor more metabolites from wastewater to enhance future studies.

Purpose

More than 20 genetically modified (GM) food crops including rice have been approved in many countries. GM rice and derived products have not yet been approved in India so they are considered as unauthorized genetically modified organisms (GMOs) in the country. Therefore it is important to track whether the rice containing food items, available in the marketplace are GMO-free.

Methods

A pilot study was conducted to check the GM status of 30 samples of packed rice grains and processed food products with rice as an ingredient, using polymerase chain reaction (PCR) assays targeting Cauliflower Mosaic Virus 35 S promoter (P-35 S), nopaline synthase terminator (T-nos), phosphinothricin-N-acetyltransferase (pat) and cry1Ac gene, which could cover screening for all the globally approved GM rice events.

Results

Based on the results, none of the samples tested were found positive for P-35 S, T-nos, pat and cry1Ac.

Conclusion

The unauthorized presence of GM rice ingredients was not detected in the samples tested. Such studies may further be conducted for the testing of GM ingredients derived from cereals other than rice in the food products imported from the country where GM events of respective cereal crop are approved, as a part of regulatory requirement.

Adsorption of heavy metals on stream sediments has important implications for the fate and transport of contaminants in subsurface ecosystems. Lead (Pb) is a potentially hazardous heavy metal that is found in high amounts in anthropogenic environments, especially aquatic ecosystems. The key mechanisms for distributing this metal in the environment are adsorption and desorption in stream to sediment, and vice versa. Therefore, this work is mainly focused on the study of the influence of amorphous Fe/Al-oxyhydroxides and soil organic matter (SOM) on the adsorption of Pb onto natural stream sediment. Spiking adsorption experiments were carried out with four types of samples namely, untreated dried sediment, Fe/Al-oxyhydroxides depleted sediment, SOM depleted sediment and both Fe/Al as well as SOM depleted sediment in the pH range of 3.0 to 8.0. The results showed that Pb adsorption was reduced by up to 45% in amorphous Fe/Al-oxyhydroxide depleted sediment at pH 4.0 to 6.0, whereas a similar adsorption reduction was observed in SOM depleted sediment at pH 6.5 to 7.5. Maximum Pb adsorption was reduced by up to 75% in both amorphous Fe/Al-oxyhydroxides and SOM depleted sediment samples at pH ranges ranging from 3.0 to 7.0. Furthermore, it was shown that SOM was most significant at pH 6.5, while Fe/Al-oxyhydroxides were more important when pH was > 6.5 for the Pb adsorption in natural stream sediment.

The present study evaluated the performance of multiwalled carbon nanotube (MWCNT)@MgAl-layered double hydroxide (LDH) nanoparticles loaded on poly-2 aminothiazole (PAT)/chitosan (CS) matrix (CPML) to remove Cd²⁺ ions from aqueous solution. The removal efficiency of modified CS/PAT with MWCNT@MgAl-LDHs was increased significantly compared to pure CS/PAT. The influence of heavy metal ion concentration, pH, temperature, adsorbent dosage, and contact time on the adsorption was examined. The optimum conditions for the adsorption of Cd²⁺ ions were 25 ⁰C with the adsorbent dosage of 0.06 g and initial concentration for adsorption of the Cd²⁺ 100 mg/L at pH = 8. The maximum adsorption capacity was measured to be 1106.19 mg/g. The values of thermodynamic parameters namely Gibbs free energy (ΔG°), entropy change (ΔS°), and enthalpy change (ΔH°) indicated the feasibility, spontaneity and the endothermic nature of the adsorption process, respectively. The pseudo-second-order kinetics and the Langmuir model were selected as the best models for the adsorption process. Also, CPML nanocomposite (NC) was successfully tested for p-nitrophenol (p-NP) reduction in the presence of NaBH₄. The reaction was nearly completed in 6 min. The fabricated CPML-NC could be reused for three consecutive cycles.

Society's support upon chemicals over the last few decades has led to their increased production, application and discharge into the environment. Wastewater treatment plants (WWTPs) contain a multitude of these chemicals such us; pharmaceutical compounds (PCs). Often, their biodegradability by activated sludge microorganisms is significant for their elimination during wastewater treatment. In this paper the focus is laid on two PCs carbamazepine (CBZ) and diclofenac (DCF) and their main transformation products (TPs). Laboratory degradation tests with these two pharmaceuticals using activated sludge as inoculum under aerobic conditions were performed and microbial metabolites were analyzed by liquid chromatography-mass spectrometry (LC/MS-MS). In two different Mixed liquid Suspended Solids (MLSS) concentrations the biodegradability by activated sludge of CBZ and DCF were evaluated. Also, this article proposes a decision support system to optimize the prediction process of this type of pharmacological compounds. A study and analysis of the techniques of Support Vector Machine, Random Forest, Decision Trees and Multilayer Perceptron Network is carried out to select the most reliable and accurate predictor for the decision system. There are not significant differences in the removal of DCF with 30 mg MLSS/L and 60 mg MLSS/L. DCF was better removed than CBZ in all experiments studied. The TP detected in the samples were mainly 4-OH-DCF for DCF and 10, 11 EPOXICBZ for CBZ. The results show that the best models are obtained with Random Forest and Multilayer Perceptron Network techniques, with a model fit of more than 95% for both carbamazepine and diclofenac metabolites. Obtaining a root means square errors of 0.80 µg/L for the metabolite 4-OH-DCF for DCF with the technique Random Forest and a root means square errors of 1.13 µg/L for the metabolite 10, 11 EPOXICBZ for CBZ with the Multilayer Perceptron Network technique.