Entry pathways determined the effects of MPs on sludge anaerobic digestion system: The views of methane production and antibiotic resistance genes fates.

Sludge is one of the primary reservoirs of microplastics (MPs), and the effects of MPs on subsequent sludge treatment raised attention. Given the entry pathways, MPs would exhibit different properties, but the entry pathway-dependent effect of MPs on sludge treatment performance and the fates of antibiotic resistance genes (ARGs), another high-risk emerging contaminant, were seldom documented. Herein, MPs with two predominant entry pathways, including wastewater-derived (WW-derived) and anaerobic digestion-introduced (AD-introduced), were used to investigate the effects on AD performance and ARGs abundances. The results indicated that WW-derived MPs, namely the MPs accumulated in sludge during the wastewater treatment process, exhibited significant inhibition on methane production by 22.8%-71.6%, while the AD-introduced MPs, being introduced in the sludge AD process, slightly increased the methane yield by 4.7%-17.1%. Meanwhile, MPs were responsible for promoting transmission of target ARGs, and polyethylene terephthalate MPs (PET-MPs) showed a greater promotion effect (0.0154-0.0936) than polyamide MPs (PA-MPs) (0.0013-0.0724). Compared to size, entry pathways and types played more vital roles on MPs influences. Investigation on mechanisms based on microbial community structure revealed characteristics (aging degree and types) of MPs determined the differences of AD performance and ARGs fates. WW-derived MPs with longer aging period and higher aging degree would release toxics and decrease the activities of microorganisms, resulting in the negative impact on AD performance. However, AD-introduced MPs with short aging period exhibited marginal impacts on AD performance. Furthermore, the co-occurrent network analysis suggested that the variations of potential host bacteria induced by MPs with different types and aging degree attributed to the dissemination of ARGs. Distinctively from most previous studies, the MPs with different sizes did not show remarkable effects on AD performance and ARGs fates. Our findings benefited the understanding of realistic environmental behavior and effect of MPs with different sources.

Advancing chronic toxicity risk assessment in freshwater ecology by molecular characterization-based machine learning.

The continuously increased production of various chemicals and their release into environments have raised potential negative effects on ecological health. However, traditional labor-intensive assessment methods cannot effectively and rapidly evaluate these hazards, especially for chronic risk. In this study, machine learning (ML) was employed to construct quantitative structure-activity relationship (QSAR) models, enabling the prediction of chronic toxicity to aquatic organisms by leveraging the molecular characteristics of pollutants, namely, the molecular descriptors, fingerprints, and graphs. The limited dataset size hindered the notable advantages of the graph attention network (GAT) model for the molecular graphs. Considering computational efficiency and performance (R2 = 0.78; RMSE = 0.77), XGBoost (XGB) was used for reliable QSAR-ML models predicting chronic toxicity using small- or medium-sized tabular data and the molecular descriptors. Further kernel density estimation analysis confirmed the high accuracy of the model for pollutant concentrations ranging from 10-3 to 102 mg/L, effectively aligning with most environmental scenarios. Model interpretation showed SlogP and exposure duration as the primary influential factors. SlogP, representing the distribution coefficient of a molecule between lipophilic and hydrophilic environments, had a negative effect on the toxicity outcomes. Additionally, the exposure duration played a crucial role in determining the chronic toxicity. Finally, the chronic toxicity data of bisphenol A validated the robustness and reliability of the model established in this research. Our study provided a robust and feasible methodology for chronic ecological risk evaluation of various types of pollutants and could facilitate and increase the use of ML applications in environmental fields.

From air to airway: Dynamics and risk of inhalable bacteria in municipal solid waste treatment systems.

Municipal solid waste treatment (MSWT) system emits a cocktail of microorganisms that jeopardize environmental and public health. However, the dynamics and risks of airborne microbiota associated with MSWT are poorly understood. Here, we analyzed the bacterial community of inhalable air particulates (PM10, n = 71) and the potentially exposed on-site workers' throat swabs (n = 30) along with waste treatment chain in Shanghai, the largest city of China. Overall, the airborne bacteria varied largely in composition and abundance during the treatment (P < 0.05), especially in winter. Compared to the air conditions, MSWT-sources that contributed to 15 ∼ 70% of airborne bacteria more heavily influenced the PM10-laden bacterial communities (PLS-SEM, ß = 0.40, P < 0.05). Moreover, our year-span analysis found PM10 as an important media spreading pathogens (104 ∼ 108 copies/day) into on-site workers. The machine-learning identified Lactobacillus and Streptococcus as pharynx-niched featured biomarker in summer and Rhodococcus and Capnocytophaga in winter (RandomForest, ntree = 500, mtry = 10, cross = 10, OOB = 0%), which closely related to their airborne counterparts (Procrustes test, P < 0.05), suggesting that MSWT a dynamic hotspot of airborne bacteria with the pronounced inhalable risks to the neighboring communities.

The crystalline structure transition and hydrogen bonds shift determining enhanced enzymatic digestibility of cellulose treated by ultrasonication.

Global energy issue raised the necessity to develop second-generation biofuels, and biorefinery of cellulosic biomass becomes a promising solution. Various pretreatments were used to overcome the cellulose nature of recalcitrance and improve the enzymatic digestibility, but the lack of mechanism understanding hindered the development of efficient and cost-effective technologies of cellulose utilization. Using structure-based analysis, we demonstrate that the improved hydrolysis efficiency caused by ultrasonication was ascribed to the changed cellulose properties rather than the increased dissolubility. Further, isothermal titration calorimetry (ITC) analysis suggested that enzymatic digestion of cellulose is an entropically favored reaction driven by hydrophobic forces other than an enthalpically favored reaction. The changes in cellulose properties and thermodynamic paramenters due to ultrasonication accounted for the improved accessibility. Ultrasonication-treated cellulose showed porous, rough and disordered morphology, accompanying with the loss of crystalline structure. Despite the unaffected unit cell structure, ultrasonication expanded the crystalline lattice by increasing grain sizes and average cross-sectional area, resulting in the transformation from cellulose I to cellulose II, with the decreased crystallinity, better hydrophilicity and increased enzymatic bioaccessibility. Furthermore, FTIR combined with two-dimensional correlation spectroscopy (2D-CoS) verified that the sequential shift of hydroxyl group and intramolecular/intermolecular hydrogen bonds, the functional groups governing cellulose crystal structure and stability, accounted for the ultrasonication-induced transition of cellulose crystalline structure. This study provides a comprehensive picture of cellulose structure and property response caused by mechanistic treatments and will open up avenues to develop novel pretreatments for efficient utilization.

The role of pretreatments in handling antibiotic resistance genes in anaerobic sludge digestion - A review.

Sludge is among the most important reservoirs of antibiotic resistance genes (ARGs), which would cause potential environmental risks with the sludge utilization. Currently, anaerobic digestion (AD) is effective to simultaneously realize the resource recovery and pollutants removal, including antibiotic resistance genes (ARGs), and various pretreatments are used to enhance the performance. Recently, plentiful publications have focused on the effects of pretreatment on ARGs removal, but the contradictory results are often obtained, and a comprehensive understanding of the research progress and mechanisms is essential. This study summarizes various pretreatment techniques for improving AD efficiency and ARGs reduction, investigates promising performance in ARGs removal when pretreatments combined with AD, and analyzes the potential mechanisms accounting for ARGs fates. The results showed that although thermal hydrolysis pretreatment showed the best performance in ARGs reduction during the pretreatment process, the significant rebound of ARGs would occur in the subsequent AD process. Conversely, ozone pretreatment and alkali pretreatment had no significant effect on ARGs abundance in the pretreatment stage, but could enhance ARGs removal by 15.6-24.3 % in the subsequent AD. Considering the efficiency and economic effectiveness, free nitrous acid pretreatment would be a promising and feasible option, which could enhance methane yield and ARGs removal by up to 27 % and 74.5 %, respectively. Currently, the factors determining ARGs fates during pretreatment and AD processes included the shift of microbial community, mobile genetic elements (MGEs), and environmental factors. A comprehensive understanding of the relationship between the fate of ARGs and pretreatment technologies could be helpful for systematically evaluating various pretreatments and facilitating the development of emerging and effective pretreatment techniques. Moreover, given the effectiveness, economic efficiency and environmental safety, we called for the applications of modern analysis approaches such as metagenomic and machine learning on the optimization of pretreatment conditions and revealing underlying mechanisms.

The Investigation on Nosocomial Infection of Acinetobacter baumannii and the Clinical Analysis of Sequential Therapy of Cefoperazone/Sulbactam Sodium for Intracranial Infection.

Background: Intracranial infection is a serious complication after neurosurgery. According to a survey, the incidence of intracranial infection is about 2.2%-2.6%, and patients with severe symptoms may even pose a threat to their life safety. Objective: To explore the risk factors for intracranial infection caused by Acinetobacter baumannii after surgery and the clinical effect of sequential therapy of cefoperazone/sulbactam sodium. Methods: In this study, a retrospective study was used. In this case-control study, 48 cases of intracranial Acinetobacter baumannii infection after neurosurgery in our hospital from January 2016 to December 2021 were selected as the infection group, and 96 patients without intracranial infection after surgery during the same period were selected as the control group to study all kinds of related factors and analyze the risk factors for intracranial Acinetobacter baumannii infection; in addition, in accordance with the therapeutic regimen for anti-infection, the infection group was divided into the tigecycline group (patients with tigecycline therapy in this group) and the combined group (patients with tigecycline combined with cefoperazone/sulbactam sequential therapy), with 24 cases in each group in order to compare the therapeutic effects of the two groups. Results: Logistic regression factor model results show that increasing age of patients, surgical treatment for intracranial tumor or craniocerebral trauma, postoperative drainage time (≥3 days), and postoperative hospital stay (≥10 days) were the risk factors for postoperative intracranial infection of Acinetobacter baumannii in neurosurgical patients (P < 0.05), and postoperative prophylactic antibiotic treatment can reduce the incidence of intracranial infection (P < 0.05). The cerebrospinal fluid nucleated cell count, serum CRP, and serum PCT in the combined group 72 h after treatment were lower than those in the tigecycline group, and the difference was statistically significant (P < 0.05). Compared with the clinical efficacy after 72-hour treatment, the cure rate and effective rate in the combined treatment group were 83.33% and 16.67%, respectively, and those in the tigecycline group were 54.17% and 33.33%, respectively. The invalid interest rate was 12.50%, and the combined treatment group was superior to the tigecycline group (P < 0.05). Conclusion: For patients with craniocerebral surgery, targeted preventive interventions should be carried out for the risk factors that may lead to intracranial Acinetobacter baumannii infection. The clinical effect of tigecycline combined with cefoperazone and sulbactam sodium sequentially in the treatment of intracranial Acinetobacter baumannii infection is better.