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Emerging contaminants such as engineered nanoparticles (ENPs), pharmaceuticals and personal care products (PPCPs) are of great concern because of their wide distribution and incomplete removal in conventional wastewater and soil treatment processes. The production and usage of ENPs and PPCPs inevitably result in their coexistence in different environmental media, thus posing various risks to organisms in aquatic and terrestrial ecosystems. However, the existing literature on the physicochemical interactions between ENPs and PPCPs and their effects on organisms is rather limited. Therefore, this paper summarized the ecotoxicity of combined ENPs and PPCPs by discussing: (1) the interactions between ENPs and PPCPs, including processes such as aggregation, adsorption, transformation, and desorption, considering the influence of environmental factors like pH, ionic strength, dissolved organic matter, and temperature; (2) the effects of these interactions on bioaccumulation, bioavailability and biotoxicity in organisms at different trophic levels; (3) the impacted of ENPs and PPCPs on cellular-level biological process. This review elucidated the potential ecological hazards associated with the interaction of ENPs and PPCPs, and serves as a foundation for future investigations into the ecotoxicity and mode of action of ENPs, PPCPs, and their co-occurring metabolites.

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Harmful Algal Blooms (HABs) have caused damage to the marine environment in Isla San Pedro in the Gulf of Corcovado, Chile. While rising water temperature and artificial eutrophication are the most discussed topics as a cause, marine bacteria is a recent attractive parameter as an algal bloom driver. This study monitored algal and bacterial compositions in the water of Isla San Pedro for one year using microscopy and 16S rRNA metabarcoding analysis, along with physicochemical parameters. The collected data were analyzed with various statistical tools to understand how the particle-associated bacteria (PA) and the free-living (FL) bacteria were possibly involved in algal blooms. Both FL and PA fractions maintained a stable bacterial composition: the FL fraction was dominated by Proteobacteria (α-Proteobacteria and γ-Proteobacteria), and Cyanobacteria dominated the PA fraction. The two fractions contained equivalent bacterial taxonomic richness (c.a. 8,000 Operational Taxonomic Units) and shared more than 50% of OTU; however, roughly 20% was exclusive to each fraction. The four most abundant algal genera in the Isla San Pedro water were Thalassiosira, Skeletonema, Chaetoceros, and Pseudo-nitzchia. Statistical analysis identified that the bacterial species Polycyclovorans algicola was correlated with Pseudo-nitzschia spp., and our monitoring data recorded a sudden increase of particle-associated Polycyclovorans algicola shortly after the increase of Pseudo-nitzschia, suggesting that P. algicola may have regression effect on Pseudo-nitzschia spp. The study also investigated the physicochemical parameter effect on algal-bacterial interactions. Oxygen concentration and chlorophyll-a showed a strong correlation with both FL and PA bacteria despite their assemblage differences, suggesting that the two groups had different mechanisms for interacting with algal species.

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Single nanomaterials and nanohybrids (NHs) can inhibit microbial processes in wastewater treatment, especially nitrification. While existing studies focus on short-term and acute exposures of single nanomaterials on wastewater microbial community growth and function, long-term, low-exposure, and emerging NHs need to be examined. These NHs have distinctly different physicochemical properties than their parent nanomaterials and, therefore, may exert previously unknown effects onto wastewater microbial communities. This study systematically investigated long-term [∼6 solid residence time [(SRT)] exposure effects of a widely used carbon-metal NH (rGO-nZVI = 1:2 and 1:0.2, mass ratio) and compared these effects to their single-parent nanomaterials (i.e., rGO and nZVI) in nitrifying sequencing batch reactors. nZVI and NH-dosed reactors showed relatively unaffected microbial communities compared to control, whereas rGO showed a significantly different (p = 0.022) and less diverse community. nZVI promoted a diverse community and significantly higher (p < 0.05) biomass growth under steady-state conditions. While long-term chronic exposure (10 mg·L-1) of single nanomaterials and NHs had limited impact on long-term nutrient recovery, functionally, the reactors dosed with higher iron content, that is, nZVI and rGO-nZVI (1:2), promoted faster NH4+-N removal due to higher biomass growth and upregulation of amoA genes at the transcript level, respectively. The transmission electron microscopy images and scanning electron microscopy─energy-dispersive X-ray spectroscopy analysis revealed high incorporation of iron in nZVI-dosed biomass, which promoted higher cellular growth and a diverse community. Overall, this study shows that NHs have unique effects on microbial community growth and function that cannot be predicted from parent materials alone.

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BACKGROUND: Identifying protein functional sites (PFSs) and, particularly, the physicochemical interactions at these sites is critical to understanding protein functions and the biochemical reactions involved. Several knowledge-based methods have been developed for the prediction of PFSs; however, accurate methods for predicting the physicochemical interactions associated with PFSs are still lacking. RESULTS: In this paper, we present a sequence-based method for the prediction of physicochemical interactions at PFSs. The method is based on a functional site and physicochemical interaction-annotated domain profile database, called fiDPD, which was built using protein domains found in the Protein Data Bank. This method was applied to 13 target proteins from the very recent Critical Assessment of Structure Prediction (CASP10/11), and our calculations gave a Matthews correlation coefficient (MCC) value of 0.66 for PFS prediction and an 80% recall in the prediction of the associated physicochemical interactions. CONCLUSIONS: Our results show that, in addition to the PFSs, the physical interactions at these sites are also conserved in the evolution of proteins. This work provides a valuable sequence-based tool for rational drug design and side-effect assessment. The method is freely available and can be accessed at http://202.119.249.49 .

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A comprehensive 8-drug metabolic cocktail was designed to simultaneously target 6 Cytochrome P450 enzymes and 2 membrane transporters. This study aimed to assess the pre-absorption risk of this new metabolic cocktail which contained metoprolol, caffeine, midazolam, pravastatin, flurbiprofen, omeprazole, digoxin and montelukast. This paper describes a systematic approach to understand whether the co-administration of the 8 selected drug products, i.e., the physical mixing of these products in the human gastro-intestinal environment, will create any issue that may interfere with the individual drug dissolution which in turns modify the total amount or timing of their availability for absorption. The evaluation consisted of two steps. An initial evaluation was based on theoretical understanding of the physicochemical properties of the drugs and the gastro intestinal environment, followed by in vitro dissolution tests. The results indicated that the designer 8-drug cocktail has acceptable pre-absorption compatibility when dosed simultaneously, and recommended the progression of the cocktail into clinical validation study.

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This study proposed a novel approach for quantitative evaluation of the physicochemical interactions between a particle and rough surface. The approach adopts the composite Simpson's rule to numerically calculate the double integrals in the surface element integration of these physicochemical interactions. The calculation could be achieved by a MATLAB program based on this approach. This approach was then applied to assess the physicochemical interactions between rough membrane surface and sludge foulants in a submerged membrane bioreactor (MBR). The results showed that, as compared with smooth membrane surface, rough membrane surface had a much lower strength of interactions with sludge foulants. Meanwhile, membrane surface morphology significantly affected the strength and properties of the interactions. This study showed that the newly developed approach was feasible, and could serve as a primary tool for investigating membrane fouling in MBRs.

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