The Effects of Tremella fuciformis Polysaccharide on the Physicochemical, Multiscale Structure and Digestive Properties of Cyperus esculentus Starch.

In this study, we have investigated the effects of Tremella fuciformis polysaccharide (TP) on the pasting, rheological, structural and in vitro digestive properties of Cyperus esculentus starch (CS). The results showed that the addition of TP significantly changed the pasting characteristics of CS, increased the pasting temperature and pasting viscosity, inhibited pasting, reduced the exudation of straight-chain starch and was positively correlated with the amount of TP added. The addition of the appropriate amount of TP could increase its apparent viscosity and enhance its viscoelasticity. The composite system of CS/TP exhibited higher short-range ordered structure and solid dense structure, which protected the crystal structure of CS, but was related to the amount of TP added. In addition, the introduction of TP not only decreased the in vitro digestion rate of CS and increased the content of slow-digestible starch (SDS) and resistant starch (RS), but also reduced the degree of digestion. Correlation studies established that TP could improve the viscoelasticity, relative crystallinity and short-range order of the CS/TP composite gel, maintain the integrity of the starch granule and crystalline structure, reduce the degree of starch pasting and strengthen the gel network structure of CS, which could help to lower the digestibility of CS.

Leaching hazards of tire wear particles in hydrothermal treatment of sludge: Exploring molecular composition, transformation mechanism, and ecological effects of tire wear particle-derived compounds.

Tire wear particles (TWPs) are considered a significant contributor of microplastics (MPs) in the sludge during heavy rainfall events. Numerous studies have shown that hydrothermal treatment (HT) of sludge can accelerate the leaching of MP-derived compound into hydrothermal liquid, thus impairing the performance of subsequent anaerobic digestion and the quality of the hydrothermal liquid fertilizer. However, the leaching behavior of TWPs in the HT of sludge remains inadequately explored. This study examined the molecular composition of TWP-derived compounds and transformation pathways of representative tire-related additives under different hydrothermal temperatures using liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with mass difference analysis. The acute toxicity and phytotoxicity of TWP leachates were assessed using Vibrio qinghaiensis Q67 and rice hydroponics experiments. The results indicated that elevating the hydrothermal temperature not only amplified the leaching behavior of TWPs but also enhanced the chemical complexity of the TWP leachate. Utilizing both suspect and non-target screenings, a total of 144 compounds were identified as additives, including N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6-PPD), hexa(methoxymethyl)melamine (HMMM), dibutyl phthalate (DBP). These additives underwent various reactions, such as desaturation, acetylation, and other reactions, leading to the formation of different transformation products (TPs). Moreover, certain additives, including caprolactam and 2,2,6,6-tetramethyl-4-piperidinol, demonstrated the potential to form conjugate products with amino acids or Maillard products. Meanwhile, TWP-derived compounds showed significant acute toxicity and detrimental effects on plant growth. This study systematically investigated the environmental fate of TWPs and their derived compounds during the HT of sludge, offering novel insights into the intricate interactions between the micropollutants and dissolved organic matter (DOM) in sludge.

A multi-scale feature fusion neural network for multi-class disease classification on the maize leaf images.

Maize is a globally important cereal crop, however, maize leaf disease is one of the most common and devastating diseases that afflict it. Artificial intelligence methods face challenges in identifying and classifying maize leaf diseases due to variations in image quality, similarity among diseases, disease severity, limited dataset availability, and limited interpretability. To address these challenges, we propose a residual-based multi-scale network (MResNet) for classifying multi-type maize leaf diseases from maize images. MResNet consists of two residual subnets with different scales, enabling the model to detect diseases in maize leaf images at different scales. We further utilize a hybrid feature weight optimization method to optimize and fuse the feature mapping weights of two subnets. We validate MResNet on a maize leaf diseases dataset. MResNet achieves 97.45% accuracy. The performance of MResNet surpasses other state-of-the-art methods. Various experiments and two additional datasets confirm the generalization performance of our model. Furthermore, thermodynamic diagram analysis increases the interpretability of the model. This study provides technical support for the disease classification of agricultural plants.

Surface Adsorption and Photoinduced Degradation: A Study of Spinel Ferrite Nanomaterials for Removal of a Model Organic Pollutant from Water.

Spinel oxide nanocrystals are attractive materials for photoinduced advanced oxidation processes that degrade organic pollutants in water due to their chemical stability and tunability, visible light absorption, and magnetic recoverability. However, a systematic understanding of the structural and chemical factors that control the reactivity of specific spinel oxide nanocrystal materials toward photoinduced degradation processes is lacking. This Perspective illustrates these knowledge gaps through an investigation into the impacts of surface chemistry and composition of spinel ferrite nanocrystals of formula MFe2O4 (M = Mg, Fe, Co, Ni, Cu, Zn) on their ability to remove a model organic pollutant (methyl orange (MO)) from water. We identify two mechanisms by which the nanocrystals remove MO from water: (i) surface adsorption and (ii) photoinduced degradation under visible light irradiation in the presence of hydrogen peroxide via the photo-Fenton reaction. Nanocrystals that do not contain any surface ligands are more effective at removing MO from water than nanocrystals that contain surface ligands, despite our observation that the ligand-less nanocrystals do not form stable colloidal dispersions in water, while ligand-coated nanocrystals are colloidally stable. For many of the spinel ferrite compositions studied here, the fraction of methyl orange removal via adsorption to the nanocrystal surface in the absence of photoexcitation is larger than the fraction removed under irradiation. Our data indicate that the composition-dependent surface charge of the nanocrystals controls the degree of surface adsorption of the charged MO molecule. Overall, these results demonstrate that careful consideration of the impacts of surface chemistry on the behavior of spinel ferrite nanocrystals is required to accurately assess and subsequently understand their activity toward the photoinduced degradation of organic molecules.

Solid-liquid redistribution and degradation of antibiotics during hydrothermal treatment of sewage sludge: Interaction between biopolymers and antibiotics.

Waste activated sludge serves an important reservoir for antibiotics within wastewater treatment plants, and understanding the occurrence and evolution of antibiotics during sludge treatment is crucial to mitigate the potential risks of subsequent resource utilization of sludge. This study explores the degradation and transformation mechanisms of three typical antibiotics, oxytetracycline (OTC), ofloxacin (OFL), and azithromycin (AZI) during sludge hydrothermal treatment (HT), and investigates the influence of biopolymers transformation on the fate of these antibiotics. The findings indicate that HT induces a shift of antibiotics from solid-phase adsorption to liquid-phase dissolution in the initial temperature range of 25-90 °C, underscoring this phase's critical role in preparing antibiotics for subsequent degradation phases. Proteins (PN) and humic acids emerge as crucial for antibiotic binding, facilitating their redistribution within sludge. Specifically, the binding capacity sequence of biopolymers to antibiotics is as follows: OFL>OTC>AZI, highlighting that OFL-biopolymers display stronger electrostatic attraction, more available adsorption sites, and more stable binding strength. Furthermore, antibiotic degradation mainly occurs above 90 °C, with AZI being the most temperature-sensitive, degrading 92.97% at 180 °C, followed by OTC (91.26%) and OFL (52.51%). Concurrently, the degradation products of biopolymers compete for active sites to form novel amino acid-antibiotic conjugates, which inhibits the further degradation of antibiotics. These findings illuminate the effects of biopolymers evolution on intricate dynamics of antibiotics fate in sludge HT and are helpful to optimize the sludge HT process for effective antibiotics abatement.

Mariculture waters as yet another hotbed for the creation and transfer of new antibiotic-resistant pathogenome.

With the rapid growth of aquaculture globally, large amounts of antibiotics have been used to treat aquatic disease, which may accelerate induction and spread of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in aquaculture environments. Herein, metagenomic and 16S rRNA analyses were used to analyze the potentials and co-occurrence patterns of pathogenome (culturable and unculturable pathogens), antibiotic resistome (ARGs), and mobilome (mobile genetic elements (MGEs)) from mariculture waters near 5000 km coast of South China. Total 207 species of pathogens were identified, with only 10 culturable species. Furthermore, more pathogen species were detected in mariculture waters than those in coastal waters, and mariculture waters were prone to become reservoirs of unculturable pathogens. In addition, 913 subtypes of 21 ARG types were also identified, with multidrug resistance genes as the majority. MGEs including plasmids, integrons, transposons, and insertion sequences were abundantly present in mariculture waters. The co-occurrence network pattern between pathogenome, antibiotic resistome, and mobilome suggested that most of pathogens may be potential multidrug resistant hosts, possibly due to high frequency of horizontal gene transfer. These findings increase our understanding of mariculture waters as reservoirs of antibiotic resistome and mobilome, and as yet another hotbed for creation and transfer of new antibiotic-resistant pathogenome.

Polypeptide N-Acetylgalactosaminyl transferase 14 is a novel mediator in pancreatic ß-cell function and growth.

Polypeptide N-Acetylgalactosaminyl transferase 14 (GALNT14) plays important roles in cancer progression and chemotherapy response. Here, we show that GALNT14 is highly expressed in pancreatic ß cells and regulates ß cell function and growth. We found that the expression level of Ganlt14 was significantly decreased in the primary islets from three rodent type-2 diabetic models. Single-Cell sequencing defined that Galnt14 was mainly expressed in ß cells of mouse islets. Galnt14 knockout (G14KO) INS-1 cell line, constructed by using CRISPR/Cas9 technology were growth normal, but showed blunt shape, and increased basal insulin secretion. Combined proteomics and glycoproteomics demonstrated that G14KO altered cell-to-cell junctions, communication, and adhesion. Insulin receptor (IR) and IGF1-1R were indirectly confirmed for GALNT14 substrates, contributed to diminished IGF1-induced p-AKT levels and cell growth in G14KO cells. Overall, this study uncovers that GALNT14 is a novel modulator in regulating ß cells biology, providing a missing link of ß cells O-glycosylation to diabetes development.

Response mechanisms of resistance in L-form bacteria to different target antibiotics: Implications from oxidative stress to metabolism.

Due to the specific action on bacterial cell wall, ß-lactam antibiotics have gained widespread usage as they exhibit a high degree of specificity in targeting bacteria, but causing minimal toxicity to host cells. Under antibiotic pressure, bacteria may opt to shed their cell walls and transform into L-form state as a means to evade the antibiotic effects. In this study, we explored and identified diverse optimal conditions for both Gram-negative bacteria (E. coli DH5α (CTX)) and Gram-positive bacteria (B. subtilis ATCC6633), which were induced to L-form bacteria using lysozyme (0.5 ppm) and meropenem (64 ppm). Notably, when bacteria transformed into L-form state, both bacterial strains showed varying degrees of increased resistance to antibiotics polymyxin E, meropenem, rifampicin, and tetracycline. E. coli DH5α (CTX) exhibited the most significant enhancement in resistance to tetracycline, with a 128-fold increase, while B. subtilis ATCC6633 showed a 32-fold increase in resistance to tetracycline and polymyxin E. Furthermore, L-form bacteria maintained their normal metabolic activity, combined with enhanced oxidative stress, served as an adaptive strategy promoting the sustained survival of L-form bacteria. This study provided a theoretical basis for comprehending antibiotic resistance mechanisms, developing innovative treatment strategies, and confronting global antibiotic resistance challenges.

Joint global and local interpretation method for CIN status classification in breast cancer.

Breast cancer is among the cancer types with the highest numbers of new cases. The study of this disease from a microscopic perspective has been a prominent research topic. Previous studies have shown that microRNAs (miRNAs) are closely linked to chromosomal instability (CIN). Correctly predicting CIN status from miRNAs can help to improve the survival of breast cancer patients. In this study, a joint global and local interpretation method called GL_XGBoost is proposed for predicting CIN status in breast cancer. GL_XGBoost integrates the eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP) methods. XGBoost is used to predict CIN status from miRNA data, whereas SHAP is used to select miRNA features that have strong relationships with CIN. Furthermore, SHAP's rich visualization strategies enhance the interpretability of the entire model at the global and local levels. The performance of GL_XGBoost is validated on the TCGA-BRCA dataset, and it is shown to have an accuracy of 78.57% and an area under the curve value of 0.87. Rich visual analysis is used to explain the relationships between miRNAs and CIN status from different perspectives. Our study demonstrates an intuitive way of exploring the relationship between CIN and cancer from a microscopic perspective.

Low-abundance proteins-based label-free SERS approach for high precision detection of liver cancer with different stages.

BACKGROUND: Surface-enhanced Raman scattering (SERS) technology have unique advantages of rapid, simple, and highly sensitive in the detection of serum, it can be used for the detection of liver cancer. However, some protein biomarkers in body fluids are often present at ultra-low concentrations and severely interfered with by the high-abundance proteins (HAPs), which will affect the detection of specificity and accuracy in cancer screening based on the SERS immunoassay. Clearly, there is a need for an unlabeled SERS method based on low abundance proteins, which is rapid, noninvasive, and capable of high precision detection and screening of liver cancer. RESULTS: Serum samples were collected from 60 patients with liver cancer (27 patients with stage T1 and T2 liver cancer, 33 patients with stage T3 and T4 liver cancer) and 40 healthy volunteers. Herein, immunoglobulin and albumin were separated by immune sorption and Cohn ethanol fractionation. Then, the low abundance protein (LAPs) was enriched, and high-quality SERS spectral signals were detected and obtained. Finally, combined with the principal component analysis-linear discriminant analysis (PCA-LDA) algorithm, the SERS spectrum of early liver cancer (T1-T2) and advanced liver cancer (T3-T4) could be well distinguished from normal people, and the accuracy rate was 98.5% and 100%, respectively. Moreover, SERS technology based on serum LAPs extraction combined with the partial least square-support vector machine (PLS-SVM) successfully realized the classification and prediction of normal volunteers and liver cancer patients with different tumor (T) stages, and the diagnostic accuracy of PLS-SVM reached 87.5% in the unknown testing set. SIGNIFICANCE: The experimental results show that the serum LAPs SERS detection combined with multivariate statistical algorithms can be used for effectively distinguishing liver cancer patients from healthy volunteers, and even achieved the screening of early liver cancer with high accuracy (T1 and T2 stage). These results showed that serum LAPs SERS detection combined with a multivariate statistical diagnostic algorithm has certain application potential in early cancer screening.

Revealing Hydrogen Spillover on 1T/2H MoS2 Heterostructures for an Enhanced Hydrogen Evolution Reaction by Scanning Electrochemical Microscopy.

The in situ characterization of the heterostructure active sites during the hydrogen evolution reaction (HER) process and the direct elucidation of the corresponding catalytic structure-activity relationships are essential for understanding the catalytic mechanism and designing catalysts with optimized activity. Hence, exploring the underlying reasons behind the exceptional catalytic performance necessitates a detailed analysis. Herein, we employed scanning electrochemical microscopy (SECM) to in situ image the topography and local electrocatalytic activity of 1T/2H MoS2 heterostructures on mixed-phase molybdenum disulfide (MoS2) with 20 nm spatial resolution. Our measurements provide direct data about HER activity, enabling us to differentiate the superior catalytic performance of 1T/2H MoS2 heterostructures compared to other active sites on the MoS2 surface. Combining this spatially resolved electrochemical information with density functional theory calculations and numerical simulations enables us to reveal the existence of hydrogen spillover from the 1T MoS2 surface to 1T/2H MoS2 heterostructures. Furthermore, it has been verified that hydrogen spillover can significantly enhance the electrocatalytic activity of the heterostructures, in addition to its strong electronic interaction. This study not only contributes to the future investigation of electrochemical processes at nanoscale active sites on structurally complex electrocatalysts but also provides new design strategies for improving the catalytic activity of 2D electrocatalysts.

Lactobacilli-derived adjuvants combined with immunoinformatics-driven multi-epitope antigens based approach protects against Clostridium perfringens in a mouse model.

Clostridium perfringens is ubiquitously distributed and capable of secreting toxins, posing a significant threat to animal health. Infections caused by Clostridium perfringens, such as Necrotic Enteritis (NE), result in substantial economic losses to the livestock industry annually. However, there is no effective commercial vaccine available. Hence, we set out to propose an effective approach for multi-epitope subunit vaccine construction utilizing biomolecules. We utilized immunoinformatics to design a novel multi-epitope antigen against C. perfringens (CPMEA). Furthermore, we innovated novel bacterium-like particles (BLPs) through thermal acid treatment of various Lactobacillus strains and selected BLP23017 among them. Then, we detailed the structure of CPMEA and BLPs and utilized them to prepare a multi-epitope vaccine. Here, we showed that our vaccine provided full protection against C. perfringens infection after a single dose in a mouse model. Additionally, BLP23017 notably augmented the secretion of secretory immunoglobulin A (sIgA) and enhanced antibody production. We conclude that our vaccine possess safety and high efficacy, making it an excellent candidate for preventing C. perfringens infection. Moreover, we demonstrate our approach to vaccine construction and the preparation of BLP23017 with distinct advantages may contribute to the prevention of a wider array of diseases and the novel vaccine development.

Na-Ru bimetallic functional sites promote photo-driven CO2 directed conversion into CH4.

Recently, there has been a significant increase in interest in using photocatalysis for the energy conversion of polluting gases. In this research, sodium and ruthenium bimetallic functional sites co-modified bismuth tungstate (Ru/Na-Bi2WO6) nanoflower photocatalyst was synthesized via the hydrothermal method. The CO2 reduction products on the Bi2WO6 substrate were CO (1.66 µmol/g/h, 68 %) and CH4 (0.78 µmol/g/h, 32 %). After optimization, a significant change in the CO2 products of the Bi2WO6-based composite material was observed, with CO (0.61 µmol/g/h, 3.6 %) and CH4 (16.1 µmol/g/h, 96.4 %). Results showed that the dominance of CH4 as the main product in the Ru/Na-BWO system is attributed to the effective doping of Na, which generates impurity energy levels composed of oxygen vacancies, lowering the conduction band position of Bi2WO6, thereby suppressing CO generation, and enhancing CH4 selectivity by changing the CO2 activation pathway. The remarkable performance is ascribed to the synergized adsorption and activation of CO2 by the tandem Na+ sites and Ru0 sites. Specifically, the doped Na+ sites play a major role in promoting the adsorption CO2 molecules, while the Ru0 sites play a dominant role in facilitating the activation of the intermediates.

A multivariate analysis of microplastics in soils along the headwaters of Yangtze river on the Tibetan Plateau.

Microplastics (MPs) are among the most widespread anthropogenic pollutants of natural environments, while limited research has focused on the fate of MPs in soils along the Plateau rivers. In this study, we investigated MPs in soils along the source areas of the Yangtze River on the Qinghai-Tibet Plateau. The results showed mean MP abundance values of (89.4 ± 51.0) and (64.4 ± 24.5) items/kg of dry soils around the tributary and mainstream areas, respectively. Film, transparent colors, and polyethylene were common shape, color, and compositions, respectively. The correlation analysis and PCA revealed that MP abundance was related to soil heavy metals (Cr and Ni) and nutrients (TOC and TP) (p < 0.05). Structural equation modeling also revealed that population density was the dominant driving factor contributing to MPs, with a total effect coefficient of 0.45. In addition, the conditional fragmentation model further distinguished the differences in MP sources from upstream to downstream along the Jinsha River. The significant sources of MPs in the bare land and grasslands from the upper reaches of the Jinsha River included traffic, tourism, and atmospheric transport. In contrast, MP transport during farming activities mainly contributed to MPs in the agricultural soil in the lower reaches.

Sentiment analysis of video danmakus based on MIBE-RoBERTa-FF-BiLSTM.

Danmakus are user-generated comments that overlay on videos, enabling real-time interactions between viewers and video content. The emotional orientation of danmakus can reflect the attitudes and opinions of viewers on video segments, which can help video platforms optimize video content recommendation and evaluate users' abnormal emotion levels. Aiming at the problems of low transferability of traditional sentiment analysis methods in the danmaku domain, low accuracy of danmaku text segmentation, poor consistency of sentiment annotation, and insufficient semantic feature extraction, this paper proposes a video danmaku sentiment analysis method based on MIBE-RoBERTa-FF-BiLSTM. This paper constructs a "Bilibili Must-Watch List and Top Video Danmaku Sentiment Dataset" by ourselves, covering 10,000 positive and negative sentiment danmaku texts of 18 themes. A new word recognition algorithm based on mutual information (MI) and branch entropy (BE) is used to discover 2610 irregular network popular new words from trigrams to heptagrams in the dataset, forming a domain lexicon. The Maslow's hierarchy of needs theory is applied to guide the consistent sentiment annotation. The domain lexicon is integrated into the feature fusion layer of the RoBERTa-FF-BiLSTM model to fully learn the semantic features of word information, character information, and context information of danmaku texts and perform sentiment classification. Comparative experiments on the dataset show that the model proposed in this paper has the best comprehensive performance among the mainstream models for video danmaku text sentiment classification, with an F1 value of 94.06%, and its accuracy and robustness are also better than other models. The limitations of this paper are that the construction of the domain lexicon still requires manual participation and review, the semantic information of danmaku video content and the positive case preference are ignored.

Inhibitory effect of microplastics derived organic matters on humification reaction of organics in sewage sludge under alkali-hydrothermal treatment.

Alkali-hydrothermal treatment (AHT) of sewage sludge is often used to recover value-added dissolved organic matters (DOM) enriched with artificial humic acids (HA). Microplastics (MPs), as emerging contaminants in sewage sludge, can leach organic compounds (MP-DOM) during AHT, which potentially impact the characteristics of thermally treated sludge's DOM. This study employed spectroscopy and Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR-MS) to explore the impacts of MPs on DOM composition and transformation during AHT. The biological effects of DOM were also investigated by hydroponic experiments. The results showed that the leaching of MP-DOM led to a substantial increase in DOC content of DOM of thermally treated sludge. Conversely, the HA content significantly decreased in the presence of MPs, resulting in a decline of plant growth facilitation degree. FT-ICR-MS analysis revealed that the reduction in HA content was characterized by a notable decline in the abundance of O6-7 and N1-3O6-7 molecules. Reactomics results indicated that the leaching of MP-DOM inhibited the Maillard reaction but bolstered oxidation reactions. The inhibition of Maillard reaction, resulting in a decrease in crucial precursors (dicarbonyl compounds, ketoses, and deoxyglucosone), was responsible for the decrease of HA content. The primary mechanism responsible for inhibiting the Maillard reaction was the consumption of reactive amino reactants through two pathways. Firstly, the leaching of organic acids in MP-DOM caused decrease of sludge pH, leading to the protonation of amino groups. Secondly, the lipid-like compounds in MP-DOM underwent oxidation (-2H+O), producing fatty aldehydes that consumed the reactive amino reactants. These discoveries offer enhanced insights into the specific contribution of MPs to the composition, transformation, bioactivity of DOM during AHT process.

Ocular Biometry Features and Their Relationship with Anterior and Posterior Segment Lengths among a Myopia Population in Northern China.

Objectives: The study aims to explore the ocular biometry of a myopic population in Northern China, focusing specifically on anterior and posterior segment lengths. Methods: This is a cross-sectional study. The medical records of 3458 myopic patients who underwent refractive surgery were evaluated. Axial length (AL), anterior chamber depth (ACD), lens thickness (LT) and other biometric parameters were measured using the IOL Master 700. The study determined the anterior segment length (ASL = ACD + LT), the posterior segment length (PSL = AL - ASL) and the ratio of ASL to PSL (ASL/PSL). Results: This study included 3458 eyes from 3458 myopic patients (1171 men and 2287 women). The mean age was 27.38 ± 6.88, ranging from 16 to 48 years old. The mean ASL was 7.35 ± 0.27 mm, and the mean PSL was 18.39 ± 1.18 mm. The ASL and PSL trends demonstrate an age-related increase for both genders, with notable gender-specific variations. Across most age groups, males typically exhibited higher ASLs and PSLs than females, with the exception of the 35-40 and 40-45 age groups. The ASL and PSL consistently increased with a rising AL. The AL strongly correlates with the PSL and negatively correlates with the ASL/PSL ratio. The ACD and LT moderately correlate with the ASL, but an increased LT does not imply a longer posterior segment. The CCT and SE show little correlation with axial eye parameters. Conclusions: Among Chinese myopic patients, a longer ASL and PSL were correlated with older age and the male gender. The AL strongly correlates positively with the PSL and negatively correlates with the ASL/PSL ratio. An elongation of the posterior segment may primarily account for an eyeball's lengthening.

Corrigendum to "3D-printed tri-element-doped hydroxyapatite/ polycaprolactone composite scaffolds with antibacterial potential for osteosarcoma therapy and bone regeneration" [Bioact. Mater. 31 (January 2024) 18-37].

[This corrects the article DOI: 10.1016/j.bioactmat.2023.07.004.].

Exposure of Danio rerio to environmental sulfamethoxazole may contribute to neurobehavioral abnormalities via gut microbiome disturbance.

The neurotoxic effects and mechanisms of low-dose and long-term sulfamethoxazole (SMZ) exposure remain unknown. This study exposed zebrafish to environmental SMZ concentrations and observed behavioral outcomes. SMZ exposure increased hyperactivity and altered the transcript levels of 17 genes associated with neurological function. It impaired intestinal function by reducing the number of intestinal goblet cells and lipid content. Metabolomic results indicated that the contents of several lipids and amino acids in the gut were altered, which might affect the expression levels of neurological function-related genes. Metagenomic results demonstrated that SMZ exposure substantially altered the composition of the gut microbiome. Zebrafish receiving a transplanted fecal microbiome from the SMZ group were also found to exhibit abnormal behavior, suggesting that the gut microbiome is an important target for SMZ exposure-induced neurobehavioral abnormalities. Multi-omics correlation analysis revealed that gut micrometabolic function was related to differential gut metabolite levels, which may affect neurological function through the gut-brain-axis. Reduced abundance of Lefsonia and Microbacterium was strongly correlated with intestinal metabolic function and may be the key bacterial genera in neurobehavioral changes. This study confirms for the first time that SMZ-induced neurotoxicity in zebrafish is closely mediated by alterations in the gut microbiome.