The identification of transformation products (TPs) is essential for profiling the potential risk of pharmaceuticals in wastewater. Nevertheless, numerous interfering features in high resolution mass spectrometry (HRMS) data from environmental samples make it difficult to screen candidate TPs and elucidate their structures by nontarget analysis" for improved clarity and readability. Here, molecular networking was introduced to address this issue. To connect nodes representing TPs and pharmaceuticals within a cluster of molecular networking correctly, crucial parameters (cosine similarity (CS) and minimum matched fragmentation ions (MMFI)) were optimized for the first time based on 54 reference standards. Then, the robustness and improved performance of this method for pharmaceutical TP identification were demonstrated using wastewater samples from both laboratory experiments and full-scale wastewater treatment plants (WWTPs). Results suggested that values of 0.5 for CS and 2 for MMFI were optimal parameters for the identification of pharmaceutical TPs by molecular networking. Experimental results of wastewater samples demonstrated that molecular networking reduced false positive candidate TPs by over 10 times compared to existing nontarget strategies. In addition, by using the information of edges in molecular networking, a total of 13 diclofenac TPs were identified and 3 of them were newly found. Results of wastewater samples from full-scale WWTPs further demonstrated that molecular networking enabled the identification of 21 pharmaceutical TPs from massive features and 8 of them were newly discovered. This study highlights the effectiveness of molecular networking in rapidly screening candidate TP features and assisting in structure identification, thereby facilitating the discovery of novel TPs and supporting subsequent risk assessment in wastewater.

To enable sulfur dioxide (SO₂) reduction in blackberry winemaking, this study investigated fermentations at two initial pH values (2.40, 2.95) supplemented with 0, 25, and 50 mg·L⁻¹ SO₂, with systematic assessment of fermentation kinetics, microbial communities, metabolite profiles, and sensory quality. The 25 mg·L⁻¹ SO₂ treatment did not significantly alter fermentation efficiency or microbial diversity, and maintained highly consistent species composition across groups. Remarkably, this 25 mg·L⁻¹ dose achieved higher ester levels and improved sweetness, yielding better overall flavor than both the control and 50 mg·L⁻¹ groups. Blackberry must’s intrinsic high acidity, rich polyphenols, and added sugar confer robust antimicrobial activity, permitting significant SO₂ cutbacks without quality deterioration. This work provides a scientific basis for producing low‑SO₂, health‑oriented fruit wines.

Understanding how complex organic contaminant mixtures change in composition, structure, and transformation behavior across wastewater treatment plants (WWTPs) is essential for improving pollutant control. However, stage-resolved knowledge of these processes remains limited. Here, we integrated non-targeted screening, paired mass distance (PMD) reactomics, CANOPUS-based structural annotation, and MS2Tox-based toxicity prediction to characterize compositional changes, dominant transformation behaviors, and toxicity implications throughout a full-scale anaerobic-anoxic-oxic (A/A/O) treatment and disinfection process through wastewater sampling in a WWTP. Across the treatments, chemical features progressively shifted toward lower molecular weight and higher hydrophilicity. Structural classification revealed the common pollutants (organic acids and derivatives, benzenoids, lipids and lipid-like molecules) and specific pollutants present in each unit. Reactomics revealed that methylation and dehydrogenation/oxidation were the most frequent transformation types, and each unit exhibited several distinct reaction types (e.g., stage-specific alkylation/dealkylation reactions during disinfection). Further correlating structure and reaction types reveal that pollutant transformations in wastewater are characterized by small mass shifts and generally retained the structural category of the reactant. Subsequently, toxicity prediction results suggested that most compounds exhibited no (65%) to low (31.6%) toxicity in WWTP. Biological treatment was associated with more predicted detoxification events, whereas chlorination disinfection showed more predicted toxicity-increase events that were frequently associated with alkylation-/methylation-related PMD signals. This study provides a stage-resolved interpretation of contaminant transformation across WWTP treatment units by linking feature attenuation, structural redistribution, PMD-derived reaction signatures, and MS2Tox-predicted toxicity shifts.

Background: Cyanidin 3-O-glucoside (C3G) is the most abundant anthocyanin in nature. However, the copigmentation of organic acids with C3G has not been analyzed. In this study, the contents of organic acids and C3G in blackberry wine were determined, and the copigmentation between them was investigated. Results: The addition of organic acids did not significantly change the molecular weight of the compounds in the solution. Regarding the copigmentation of organic acids with C3G, the organic acids altered the solution polarity. This led to the rotation of the B ₋ ring plane of C3G, restored the shielding color intensity, and enhanced the color rendering strength of the C3G solution. Hydrophobic and hydrogen bonding forces are the main intermolecular forces that affect their copigmentation. This study enriched copigmentation of organic acids on anthocyanins. Moreover, it provides a reference to produce high-quality fruit wine and reduce environmental pollution caused by perishable fruits.

Cardiovascular pharmaceuticals were extensively detected and generally coexist with their transformation products (TPs) in wastewater. However, knowledges on TPs and transformation processes for cardiovascular pharmaceuticals remained largely unclear. To fill this knowledge gap, nontarget screening combined with batch experiments were employed to reveal the transformation of five cardiovascular pharmaceuticals (atenolol, metoprolol, propranolol, bezafibrate and candesartan) in aerobic activated sludge. The removal rate constants per unit of biomass ranged from 0.0105 to 0.0571 L g SS-1 h-1 for five cardiovascular pharmaceuticals. Atenolol and bezafibrate exhibited more excellent removal efficiency (over 99 %) than other three cardiovascular pharmaceuticals. Subsequently, 33 TPs were tentatively identified and 16 of them were not reported in previous studies. Based on identified TPs, transformation pathways of five cardiovascular pharmaceuticals were proposed, which suggested acetylation, ammoniation, carboxylation, dealkylation, decarboxylation, dihydroxylation, demethylation, epoxidation, formylation, hydrogenation, hydrolysis, hydroxylation, methylation and oxidation were involved in the transformation of cardiovascular pharmaceuticals in wastewater. Notably, N- dealkylation at the site of secondary and tertiary amine, acetylation at the site of primary amine and dehydrogenation at the site of linear alkyl were summarized as the specific transformation patterns across different cardiovascular pharmaceuticals. Furthermore, the predicted results suggested that about 30 % TPs have higher persistence and bioaccumulation than parent compounds while about 40 % TPs harbored higher toxicity than parent compounds of cardiovascular pharmaceuticals. Collectively, this study unveiled the fate and transformation pathways of five cardiovascular pharmaceuticals and summarized the specific transformation patterns for them in aerobic activated sludge, which is theoretically useful to effectively remove pharmaceuticals from wastewater.

Assessing the pharmaceutical removal potential in wastewater treatment plants (WWTPs) is critical for risk management, but remains technically challenging. In this study, a machine learning (ML)-based framework was developed to predict pharmaceutical removability using over 4000 spatiotemporal measurements of 80 pharmaceuticals across 17 full-scale WWTPs. Modified quantum chemistry (QC) descriptors, which couple electronic properties with treatment processes, were integrated with conventional molecular descriptors and WWTP parameters for modeling. The developed classification model achieved satisfactory predictive performance with an accuracy of 0.81 and demonstrated robust generalizability in external validation. Model interpretation revealed that site-specific electronic features significantly improved predictive performance, with the modified electrophilicity index emerging as the dominant driving factor of pharmaceutical removability in WWTPs. Pharmaceuticals with high molecular stability and low electro-surface activity tended to exhibit low removability, particularly under conditions of high site-specific electrophilicity and lower temperatures. Scenario-dependent predictions from the model provide valuable guidance for optimizing treatment strategies. Specifically, pharmaceuticals such as carbamazepine, diazepam, and citalopram exhibited higher predicted amenability to chemical treatment, whereas mifepristone, erythromycin, and sulfacetamide were more likely to be effectively removed under biological processes. Extended sludge and hydraulic retention time, along with optimized influent loading, were expected to further enhance the removal of persistent pharmaceuticals. This study offers predictive insights into pharmaceutical removal potential through the developed ML model and provides scientific support for pharmaceutical management in WWTPs.

Transformation products (TPs) of pharmaceuticals have raised great concerns due to the extensive detection and potentially higher concentration and toxicity than parents. However, the related knowledge on TPs of pharmaceuticals in wastewater were limited. To fill this gap, suspect screening workflow was developed to identify TPs from 28 pharmaceuticals in 12 wastewater treatment plants (WWTPs) located in Yangtze River Delta region of China. Based on the developed suspect lists included structural information and predicted retention time for 1643 TPs, 67 TPs were successfully identified at confidence levels of ≥3 and 61.12 % of them originated from non-steroidal anti-inflammatory drugs. Subsequently, target screening revealed that 4‑hydroxy-diclofenac, diclofenac-benzoic acid, N-demethylation tramadol, 10,11-dihydro-10-dihydroxycarbamazepine and 10,11-dihydro-10,11-epoxycarbamazepine exhibited high concentration up to μg/L in WWTPs. Comparatively, the cumulative concentration of TPs was higher than parents of pharmaceuticals in effluent of WWTPs. In addition, the predicted results revealed that 29.85 %, 82.09 % and 19.91 % TPs have higher toxicity, persistence and bioaccumulation than parents. Furthermore, diclofenac-benzoic acid and 10,11-dihydro-10,11-epoxycarbamazepine exhibited higher eco-risks than their corresponding parents and N-demethylation tramadol was found to be with moderated eco-risks in effluent of WWTRPs. Collectively, the present study provides holistic information on TPs for 28 pharmaceuticals in wastewater and highlights the importance for TPs of pharmaceuticals in WWTPs from the aspect of concentration, toxicity and eco-risks. In the future, not only parents, but also TPs of pharmaceuticals should be effectively managed and attenuated in wastewater.

Native mass spectrometry (nMS) is a cutting-edge technique that leverages electrospray ionization MS (ESI-MS) to investigate large biomolecules and their complexes in solution. The goal of nMS is to retain the native structural features and interactions of the analytes during the transition to the gas phase, providing insights into their natural conformations. In biopharmaceutical development, nMS serves as a powerful tool for analyzing complex protein heterogeneity, allowing for the examination of non-covalently bonded assemblies in a state that closely resembles their natural folded form. Herein, we present an imaged capillary isoelectric focusing-MS (icIEF-MS) workflow to characterize cysteine-linked antibody-drug conjugate (ADC) under native conditions. Two ADCs were analyzed: a latest generation cysteine-linked ADC polatuzumab vedotin and the first FDA-approved cysteine-linked ADC brentuximab vedotin. This workflow benefits from a recently developed icIEF system that is MS-friendly and capable of directly coupling to a high-sensitivity MS instrument. Results show that the icIEF separation is influenced by both drug payloads and the post-translational modifications (PTMs), which are then promptly identified by MS. Overall, this native icIEF-MS method demonstrates the potential to understand and control the critical quality attributes (CQAs) that are essential for the safe and effective use of ADCs.

The haze of blackberry wine has seriously affected consumers' purchase intention, thus restricting the development of the blackberry wine industry. This study explored the relationship between the haze mechanism of different fruit wines and the changes in protein and polyphenol contents of blackberry wine after aging. The role of metal ions in haze formation was analyzed. Experimental results show that metal ions are important factors in the formation of haze in blackberry wine. They act as an intermediary between proteins and polyphenols to promote haze formation. This study provides the first analysis of the formation mechanism of blackberry wine haze and theoretical reference for controlling and reducing the formation of haze.

Efforts in water ecosystem conservation require an understanding of causative factors and removal efficacies associated with mixture toxicity during wastewater treatment. This study conducts a comprehensive investigation into the interplay between wastewater estrogenic activity and 30 estrogen-like endocrine disrupting chemicals (EEDCs) across 12 municipal wastewater treatment plants (WWTPs) spanning four seasons in China. Results reveal substantial estrogenic activity in all WWTPs and potential endocrine-disrupting risks in over 37.5 % of final effluent samples, with heightened effects during colder seasons. While phthalates are the predominant EEDCs (concentrations ranging from 86.39 %) for both estrogenic activity and major EEDCs (phthalates and estrogens), with the secondary and tertiary treatment segments contributing 88.59 ± 8.12 % and 11.41 ± 8.12 %, respectively. Among various secondary treatment processes, the anaerobic/anoxic/oxic-membrane bioreactor (A/A/O-MBR) excels in removing both estrogenic activity and EEDCs. In tertiary treatment, removal efficiencies increase with the inclusion of components involving physical, chemical, and biological removal principles. Furthermore, correlation and multiple liner regression analysis establish a significant (p < 0.05) positive association between solid retention time (SRT) and removal efficiencies of estrogenic activity and EEDCs within WWTPs. This study provides valuable insights from the perspective of prioritizing key pollutants, the necessity of integrating more efficient secondary and tertiary treatment processes, along with adjustments to operational parameters like SRT, to mitigate estrogenic activity in municipal WWTPs. This contribution aids in managing endocrine-disrupting risks in wastewater as part of ecological conservation efforts.

The extensive detection of antidepressants in wastewater has raised increasing concerns for human beings. During biological wastewater treatment processes, antidepressants cannot be completely removed and mineralized, which caused the formation of transformation products (TPs). To date, knowledges on TPs that participated in the transformation processes of antidepressants were scarce. To fill this gap, molecular networking nontarget screening based on lab-scale batch assays were employed to explore the removal and transformation of five antidepressants (amitriptyline (AMI), clomipramine (CLO), duloxetine (DUL), nortriptyline (NOR) and paroxetine (PAR)). The removal rate constants per unit of biomass (kbio) of the five antidepressants were found to range from 0.29 to 0.56 L/(gMLSS*d). Comparatively, clomipramine was removed more slowly than other antidepressants, which attributed to its lower electrophilic properties. Subsequently, 22 TPs were tentatively identified, among which 19 ones were newly found in the present study. The proposed transformation pathways indicated that demethylation, N-formylation, N-acetylation, N-succinylation, N-hydroxylation, dealkylation, hydrolysis and nitrosation participated in the transformation of antidepressants in wastewater. Particularly, Nacylation and N-hydroxylation were found as characteristics reactions for antidepressants in wastewater and these reactions consistently occurred at the site of amino functional group, where high electrophilic activity was the dominant causes for the observed characteristics reactions. In silico results revealed that TPs formed during biological wastewater treatment generally had lower toxicity, lower bioaccumulation and higher bioavailability than their parent compounds. Collectively, the present study provides insights into the transformation processes of antidepressants in wastewater, indicating that characteristic transformation reactions occur across different antidepressants, which is theoretically useful to effectively remove pharmaceuticals from wastewater.

With the global implementation of wastewater reuse, accurately assessing the soil ecological risk of chiral pollutants from wastewater necessitates a comprehensive understanding of their enantioselective toxicity to soil animals. Ibuprofen (IBU) is the most prevalent chiral pharmaceutical in municipal wastewater. However, its enantioselective toxicity toward soil animals and the underlying mechanism remain largely unknown. In this study, the toxicity of IBU enantiomers, S-IBU and R-IBU, to earthworms was evaluated at environmentally relevant concentrations (10 and 100 μg/L), simulating wastewater reuse for irrigation. The results demonstrated that IBU adversely affects the growth, reproduction, regeneration, defense systems, and metabolic processes of earthworms, with S-IBU exhibiting stronger toxic effects than R-IBU. The bioavailability assessment revealed that S-IBU was more readily absorbed by earthworms and converted to its enantiomer within earthworms than R-IBU. This is consistent with molecular docking results showing that S-IBU had stronger affinities for functional proteins associated with xenobiotic transport and transformation. The findings of this study highlight that S-IBU poses a higher risk than R-IBU to soil organisms under wastewater reuse scenarios and that the chirality of chemical pollutants in wastewater deserves more attention when implementing wastewater reuse. In addition, our study underscores that the differences in bioavailability and bioactivity may account for the enantioselective toxicity of chiral pollutants.

The inefficient biodegradation and incomplete mineralization of nitrogenous heterocyclic compounds (NHCs) have emerged as a pressing environmental concern. The top-down design offers potential solutions to this issue by targeting improvements in community function, but the ecological linkages between selection strength and the structure and function of desired microbiomes remain elusive. Herein, the integration of metagenomics, culture-based approach, non-targeted metabolite screening and enzymatic verification experiments revealed the effect of enrichment concentration on the top-down designed benzothiazole (BTH, a typical NHC)-degrading consortia. Significant differences were observed for the degradation efficiency and community structure under varying BTH selections. Notably, the enriched consortia at high concentrations of BTH were dominated by genus Rhodococcus, possessing higher degradation rates. Moreover, the isolate Rhodococcus pyridinivorans Rho48 displayed excellent efficiencies in BTH removal (98 %) and mineralization (∼ 60 %) through the hydroxylation and cleavage of thiazole and benzene rings, where cytochrome P450 enzyme was firstly reported to participate in BTH conversion. The functional annotation of 460 recovered genomes from the enriched consortia revealed diverse interspecific cooperation patterns that accounted for the BTH mineralization, particularly Nakamurella and Micropruina under low selection strength, and Rhodococcus and Marmoricola under high selection strength. This study highlights the significance of selection strength in top-down design of synthetic microbiomes for degrading refractory organic pollutants, providing valuable guidance for designing functionally optimized microbiomes used in environmental engineering.

This study investigated the spatiotemporal distribution of 17 pharmaceuticals in wastewater treatment plants (WWTPs) from 17 provinces across China, and explored structural insights into their removal in full-scale wastewater treatment processes by quantum chemistry. Briefly, 10 pharmaceuticals were detected in above 85 % of samples, of which ibuprofen and sulfamethoxazole dominated with concentrations up to the μg/L level. Seasonally, concentrations of psychoactive drugs (PDs) were 1.3-2.6 times higher in summer than in other seasons. Spatially, higher average concentrations were detected in northern WWTPs, and regions with similar economic levels exhibited similar contamination patterns. Pharmaceutical removal in WWTPs ranged from 41.4 % (carbamazepine) to 87.2 % (sulfamethizole), with the secondary treatment segment, especially aerobic treatment units, maintaining an important position. Molecular structural mechanisms behind these removal performances were further revealed. Firstly, we demonstrated a significant association of pharmaceutical overall removal with electrophilicity index (ωcubic) as well as the lowest unoccupied molecular orbital energy (ELUMO). Highly electrophilic pharmaceuticals may persist in WWTPs and their sensitivity to electron exchange reactions accounted for the discrepant removal. In terms of treatment segments, pharmaceuticals with reaction sites masked in molecular structure, such as ibuprofen and venlafaxine, showed a propensity for tertiary treatment suitability. Furthermore, enzymes of aerobic units exhibited excellent docking affinity to pharmaceutical molecules with an average affinity of -7.2 kcal/mol, and hydrogen-bond interactions played an important factor in promoting biodegradation. Our results emphasize the necessity of assessing pharmaceutical contamination on a larger spatiotemporal scale. Moreover, the structural insights into removal phenomena offer scientific molecular-level justification for the design and optimization of pharmaceutical treatment technologies in WWTPs.

The application of deep learning (DL) models for screening environmental estrogens (EEs) for the sound management of chemicals has garnered significant attention. However, the currently available DL model for screening EEs lacks both a transparent decision-making process and effective applicability domain (AD) characterization, making the reliability of its prediction results uncertain and limiting its practical applications. To address this issue, a graph neural network (GNN) model was developed to screen EEs, achieving accuracy rates of 88.9% and 92.5% on the internal and external test sets, respectively. The decision-making process of the GNN model was explored through the network-like similarity graphs (NSGs) based on the model features (FT). We discovered that the accuracy of the predictions is dependent on the feature distribution of compounds in NSGs. An AD characterization method called AD(FT) was proposed, which excludes predictions falling outside of the model's prediction range, leading to a 15% improvement in the F1 score of the GNN model. The GNN model with the AD method may serve as an efficient tool for screening EEs, identifying 800 potential EEs in the Inventory of Existing Chemical Substances of China. Additionally, this study offers new insights into comprehending the decision-making process of DL models.

The construction of novel heterojunction engineering is more favorable for boosting the photocatalytic performance of composite catalysts for emerging contaminants removal. Herein, a spherical-like Mo2C/ZnIn2S4 heterojunction was fabricated via a facile hydrothermal route and then applied as efficient photocatalyst for degrading tetracycline. Benefiting from benign hetero-interface contact and large specific surface area, the prepared catalyst exhibited superior adsorption and photocatalytic activity for contaminants degradation under visible irradiation. Combining with radicals quenching tests and electron spin resonance characterization, the radicals and photo-generated holes were found to be mainly responsible for tetracycline degradation. Moreover, the results of the main degradation intermediates suggested that hydroxylation, dehydration, demethylation, deamination and hydrogenation reduction play major role in degradation processes. The predicted toxicity of degradation intermediates presented that 8 products may cause eco-toxicity. This work provides a facile route for designing spherical-like heterostructured catalysts and sheds lights on sewage remediation by a synergistic adsorption/photocatalysis strategy.

Metal ions could affect the stability of fruit wine. However, their influence on the stability of blackberry wine (BBW) has not been studied. In this study, the influence of iron, copper, chromium and nickel on the stability of BBW was analyzed. The influence of iron ions on BBW and its main pigment cyanidin-3-O-glucoside (C3G) was analyzed by comparing chromaticity, fluorescence, and component. The mechanism by which iron ions cause C3G discoloration was further studied. After 15 days of aging, the stability of BBW added with 1 mmol/L copper, chromium, and nickel powder showed no significant change. However, BBW changed in color from red to blue after adding the same concentration of iron powder. This result could be attributed to the interaction with iron ions after a part of C3G was converted into delphinidin 3-O-glucoside (D3G). The higher hue of blue was obtained when the molar concentration ratio of iron ion to D3G was 4:1. This study was the first to observe and analyze the iron-induced color change in BBW. The research results provide a theoretical basis for guiding the wine brewers to avoid the color change of blackberry wine by controlling the source and concentration of iron ions in the brewing process.

Wastewater treatment plants (WWTPs) are the major sources of contaminants discharged into downstream water bodies. Profiling the contaminants in effluent of WWTPs is crucial to assess the potential eco-risks toward downstream organisms. To this end, this study investigated the contaminants in effluent of 10 WWTPs locating in 10 cities of Yangtze River delta region of China by suspected screening analysis. Further, the persistence, bioaccumulation, toxicity (PBT) and the characteristics sub-structures of PBT-like chemicals were analyzed. Totally, 704 chemicals including 155 chemical products, 31 food additives, 52 natural substances, 112 personal care products, 123 pesticides, 192 pharmaceuticals, 17 hormones and 22 others were found. The results of PBT analysis suggested that 42 chemicals (5.97% among the detected chemicals in WWTPs) were with PBT property. Among them, 31 contaminants were not reported previously. 9 characteristics sub-structures (N-methyleneisobutylamine, 1-naphthaldehyde, 2,3,3-trimethylcyclohexene, cyclohexanol, N-sec-butyl-n-propylamine, (5E)-2,6-dimethylocta-1,5-diene, 2-ethylphenol, pentadecane and 6-methoxyhexane) were found for PBT-like chemicals. The sub-structures of highly linear alkyl partially explained the significantly higher PBT score for personal care products. Present study provides fundamental information on PBT properties of contaminants in effluent of WWTPs, which will benefit to prioritize contaminants with high concerns in effluent of WWTPs.