Asymmetric chitosan-derivative/carboxymethylcellulose layer-by-layer film combining antimicrobial and vascular regeneration for the repair of infected wounds.

Bacterially infected wounds are a serious threat to patients' lives and health, and multifunctional dressings with antimicrobial properties and healing promotion are urgently needed. Thus, we used the cationic and anionic properties of chitosan (CS)-nerol (N) derivative (CSN) and carboxymethylcellulose (CMC) to prepare asymmetric layer-by-layer self-assembled (LBL) composite films (CSN-CMC LBL films) with antibacterial and healing properties using a spin-coating method. SEM images showed that the CSN-CMC LBL films had completely different degrees of roughness at the bottom (hydrophilic layer) and at the top (hydrophobic layer), with the roughness at the top increasing as the number of layers increased. The CSN and CMC were used to prepare asymmetric LBL films via the electrostatic attraction of -COO- and NH3+. In addition, adhesion and water contact angle tests showed that the CSN-CMC LBL films had enhanced tissue adhesion and good hydrophobicity. These materials had excellent antimicrobial activity and good biocompatibility. Importantly, the animal infection model results showed that CSN-CMC-8 LBL films effectively eliminated the infection in vivo, inhibited inflammation, promoted vascular regeneration, accelerated the epithelialization process, and achieved high quality healing. Overall, the CSN-CMC LBL films in this study showed considerable potential for application in infected wound healing.

Chasing the heat: Unraveling urban hyperlocal air temperature mapping with mobile sensing and machine learning.

Many cities face unprecedented high temperatures with increasing extreme events. Heatwaves pose significant health risks, including cardiovascular diseases, heatstroke, and dehydration. Mapping urban near-surface air temperature (Tair) is crucial for understanding thermal exposure and addressing climate change. Previous studies relied on satellite-derived land surface temperature (LST) and stationary monitoring, but high spaio-temporal Tair mapping is still a challenge. This study optimized a mobile sensing scheme using an electric bicycle platform with environmental and image sensors, and deep learning captured local-scale urban factors. A spatio-temporal data fusion model that consisted of three parts, temporal trend extraction, locality analysis, and neighborhood effect analysis, generated hyperlocal Tair maps. The Results from Beijing demonstrated the effectiveness of the framework, achieving the lowest MAE of 0.02 °C. Optimized data collection and the new model achieved accurate temperature predictions and thermal exposure assessment. Efficiency enhanced sensing strategy was also proposed. The study highlights local-scale factors and spatio-temporal dependencies in addressing heatwaves and climate change impacts in urban areas.

An optimized multi-technique based analytical platform for identification, characterization and quantification of nanoplastics in water.

Nanoplastics (NPs) have been identified as an emerging concern for the environment and our food chains in recent years. Monitoring the concentration and size of nanoplastics is essential to assess the potential risks that nanoplastic particles may pose. In this study, we presented a multi-technique based analytical platform to identify, characterize and quantify nanoplastics in water samples through a combination of sample pre-concentration, asymmetric flow field-flow fractionation coupled with multi-angle light scattering (AF4-MALS) and pyrolysis-GC/MS (Py-GC/MS). Models for predicting NPs concentration and particle number in unknown samples were established and validated using NPs standards of known size and AF4-MALS response. Py-GC/MS was applied for further identification of polymer type and quantification of mass concentration. Filtration conditions for pre-concentration were optimized to ensure a high recovery rate with minimal effect on original particle size. The addition of 0.05% SDS prior to filtration, using controlled filtration procedures, effectively improved the recovery. Furthermore, this study demonstrates the application of the analytical platform for the characterization and quantification of different nanoparticles (e.g. spiked PMMA and PS NPs) in the size range 60 nm-350 nm with detection limits down to 0.01 ppm in water samples. The established analytical platform can fill an analytical gap by offering a solution for quantifying size-resolved mass concentrations of nanoplastics and providing comprehensive data on size distribution, particle number and mass quantification with high sensitivity for detection.

Determination and Characterization of Gold Nanoparticles in Liquor Using Asymmetric Flow Field-Flow Fractionation Hyphenated with Inductively Coupled Plasma Mass Spectrometry.

The EU has approved the usage of gold as a food additive (E175) and it has been applied in numerous foods for coloring and decoration purposes. Different from the general assumption that edible gold is mainly present in the form of flakes or external coating in foods, this work demonstrated that gold nanoparticles (Au NPs) can be released from gold flakes and extracted under optimized conditions. To support future risk assessment associated with the exposure of Au NPs to human health, an effective approach was established in this study for both size characterization and mass determination of Au NPs released in a commercial gold-containing liquor using Asymmetric Flow Field-flow Fractionation (AF4) hyphenated with Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Our results showed that no Au NPs were detected in the original liquor product and only after ultrasonication for several minutes did Au NPs occur in the ultrasound-treated liquor. Particularly, Au NPs released in the liquor can be well extracted after 100-fold enrichment of gold flakes and the subsequent ultrasonication for 25 min. Size characterization of Au NPs was conducted by AF4-ICP-MS under calibration with Au NP standards. The gold particle sizes detected ranged from 8.3-398.0 nm and the dominant size of the released Au NPs was around 123.7 nm in the processed liquor. The mass concentration of gold particles determined in the liquor sample with gold flakes concentrated and subsequently sonicated was 48.1 µg L-1 by pre-channel calibration and the overall detection recoveries ranged over 82-95%. For the comparison control samples without ultrasonication, there was no detection of Au NPs. The established method was demonstrated to be useful for monitoring Au NPs in liquor and is possibly applied to other similar foodstuffs.

The detection, characterization, and quantification of dominant degradation products of nisin A and Z in selected dairy products by liquid chromatography-high-resolution mass spectrometry technique.

Nisin, a bacteriocin produced through fermentation using bacterium Lactococcus lactis, has several commercial variants such as nisin A and nisin Z. Nisin serves as a natural preservative with antimicrobial properties in various food products, including dairy and beverages, for extending product shelf life. The efficacy and safety of nisin A as a bacteriocin has been well characterized. However, there is limited evidence regarding the efficacy, stability, and safety of nisin Z as a food preservative, as it has not undergone comprehensive regulatory reviews. In this work, we studied the stability of nisin A and Z in a selection of yogurt drinks and found nisin to be unstable, particularly in fruit-flavored yogurt drinks. Both nisin A and Z could experience significant degradation leading to the nisin parent ion peaks dropping below detectable level before the product's expiry date. Compared with nisin A, the formation of oxidized metabolite nisin Z+O appeared to be the predominant reaction for nisin Z. These findings highlight the need for further scientific research to understand the behavior of nisin Z under different application conditions, which is crucial for assessing the efficacy and safety of nisin Z under these conditions. One potential application of this knowledge is to optimize the formulation of yogurt-based drinks to stabilize nisin Z and sustain its biopreservative function throughout the product's shelf life. Additionally, the current study shows that for the testing of the presence of nisin A or nisin Z, it is imperative to cover both the parent and the main degradant(s) of nisin. This is especially true for nisin Z, for which the regulatory approval status may vary in different markets. As such, the confirmative identification of nisin Z and its key metabolites in commercial products would be essential.

Optimizing the extraction of active components from Salvia miltiorrhiza by combination of machine learning models and intelligent optimization algorithms and its correlation analysis of antioxidant activity.

We extracted Sal B and TIIA from Salvia miltiorrhiza using enzymatic-assisted ethanol extraction. ACONN predicted optimal process conditions. Enzymolysis and alcohol extraction were used, optimizing conditions and evaluating antioxidant activity. ACONN analyzed data and ACO optimized conditions. Lab verification comprehensively evaluated the conditions. The correlation between Sal B, TIIA, and their antioxidant activities was examined. Weights of 0.5739 and 0.4260 evaluated Sal B and TIIA. ACONN had a 97.46% fitting degree. Optimized extraction conditions improved yield and quality, yielding a comprehensive evaluation value of 27.69 with 4.46% average errors. This approach enhances extraction and compound quality. Antioxidant activity strongly correlated with component yield, influenced by extraction conditions. ACONN-optimized extraction improved Sal B and TIIA yield and quality, with potential as natural antioxidants. Integrating machine learning and optimization algorithms in industrial extraction enhances efficiency and environmental preservation.

Proteoform-Resolved Profiling of Plasminogen Activation Reveals Novel Abundant Phosphorylation Site and Primary N-Terminal Cleavage Site.

Plasminogen (Plg), the zymogen of plasmin (Plm), is a glycoprotein involved in fibrinolysis and a wide variety of other physiological processes. Plg dysregulation has been implicated in a range of diseases. Classically, human Plg is categorized into two types, supposedly having different functional features, based on the presence (type I) or absence (type II) of a single N-linked glycan. Using high-resolution native mass spectrometry, we uncovered that the proteoform profiles of human Plg (and Plm) are substantially more extensive than this simple binary classification. In samples derived from human plasma, we identified up to 14 distinct proteoforms of Plg, including a novel highly stoichiometric phosphorylation site at Ser339. To elucidate the potential functional effects of these post-translational modifications, we performed proteoform-resolved kinetic analyses of the Plg-to-Plm conversion using several canonical activators. This conversion is thought to involve at least two independent cleavage events: one to remove the N-terminal peptide and another to release the active catalytic site. Our analyses reveal that these processes are not independent but are instead tightly regulated and occur in a step-wise manner. Notably, N-terminal cleavage at the canonical site (Lys77) does not occur directly from intact Plg. Instead, an activation intermediate corresponding to cleavage at Arg68 is initially produced, which only then is further processed to the canonical Lys77 product. Based on our results, we propose a refined categorization for human Plg proteoforms. In addition, we reveal that the proteoform profile of human Plg is more extensive than that of rat Plg, which lacks, for instance, the here-described phosphorylation at Ser339.

Fast and scalable production of crosslinked polyimide aerogel fibers for ultrathin thermoregulating clothes.

Polyimide aerogel fibers hold promise for intelligent thermal management fabrics, but their scalable production faces challenges due to the sluggish gelation kinetics and the weak backbone strength. Herein, a strategy is developed for fast and scalable fabrication of crosslinked polyimide (CPI) aerogel fibers by wet-spinning and ambient pressure drying via UV-enhanced dynamic gelation strategy. This strategy enables fast sol-gel transition of photosensitive polyimide, resulting in a strongly-crosslinked gel skeleton that effectively maintains the fiber shape and porous nanostructure. Continuous production of CPI aerogel fibers (length of hundreds of meters) with high specific modulus (390.9 kN m kg-1) can be achieved within 7 h, more efficiently than previous methods (>48 h). Moreover, the CPI aerogel fabric demonstrates almost the same thermal insulating performance as down, but is about 1/8 the thickness of down. The strategy opens a promisingly wide-space for fast and scalable fabrication of ultrathin fabrics for personal thermal management.

Revealing spatial multimodal heterogeneity in tissues with SpaTrio.

Capturing and depicting the multimodal tissue information of tissues at the spatial scale remains a significant challenge owing to technical limitations in single-cell multi-omics and spatial transcriptomics sequencing. Here, we developed a computational method called SpaTrio that can build spatial multi-omics data by integrating these two datasets through probabilistic alignment and enabling further analysis of gene regulation and cellular interactions. We benchmarked SpaTrio using simulation datasets and demonstrated its accuracy and robustness. Next, we evaluated SpaTrio on biological datasets and showed that it could detect topological patterns of cells and modalities. SpaTrio has also been applied to multiple sets of actual data to uncover spatially multimodal heterogeneity, understand the spatiotemporal regulation of gene expression, and resolve multimodal communication among cells. Our data demonstrated that SpaTrio could accurately map single cells and reconstruct the spatial distribution of various biomolecules, providing valuable multimodal insights into spatial biology.

Discovery of novel neutral glycosphingolipids in cereal crops: rapid profiling using reversed-phased HPLC-ESI-QqTOF with parallel reaction monitoring.

This study explores the sphingolipid class of oligohexosylceramides (OHCs), a rarely studied group, in barley (Hordeum vulgare L.) through a new lipidomics approach. Profiling identified 45 OHCs in barley (Hordeum vulgare L.), elucidating their fatty acid (FA), long-chain base (LCB) and sugar residue compositions; and was accomplished by monophasic extraction followed by reverse-phased high performance liquid chromatography electrospray ionisation quadrupole-time-of-flight tandem mass spectrometry (HPLC-ESI-QqTOF-MS/MS) employing parallel reaction monitoring (PRM). Results revealed unknown ceramide species and highlighted distinctive FA and LCB compositions when compared to other sphingolipid classes. Structurally, the OHCs featured predominantly trihydroxy LCBs associated with hydroxylated FAs and oligohexosyl residues consisting of two-five glucose units in a linear 1 → 4 linkage. A survey found OHCs in tissues of major cereal crops while noting their absence in conventional dicot model plants. This study found salinity stress had only minor effects on the OHC profile in barley roots, leaving questions about their precise functions in plant biology unanswered.

Double Network Physical Crosslinked Hydrogel for Healing Skin Wounds: New Formulation Based on Polysaccharides and Zn2.

Developing convenient, efficient, and natural wound dressings remain the foremost strategy for treating skin wounds. Thus, we innovatively combined the semi-dissolved acidified sol-gel conversion method with the internal gelation method to fabricate SA (sodium alginate)/CS (chitosan)/Zn2+ physically cross-linked double network hydrogel and named it SA/CS/Zn2+ PDH. The characterization results demonstrated that increased Zn2+ content led to hydrogels with improved physical and chemical properties, such as rheology, water retention, and swelling capacity. Moreover, the hydrogels exhibited favorable antibacterial properties and biocompatibility. Notably, the establishment of an in vitro pro-healing wound model further confirmed that the hydrogel had a superior ability to repair wounds and promote skin regeneration. In future, as a natural biomaterial with antimicrobial properties, it has the potential to promote wound healing.

Elucidating dynamic cell lineages and gene networks in time-course single cell differentiation.

Single cell RNA sequencing (scRNA-seq) technologies provide researchers with an unprecedented opportunity to exploit cell heterogeneity. For example, the sequenced cells belong to various cell lineages, which may have different cell fates in stem and progenitor cells. Those cells may differentiate into various mature cell types in a cell differentiation process. To trace the behavior of cell differentiation, researchers reconstruct cell lineages and predict cell fates by ordering cells chronologically into a trajectory with a pseudo-time. However, in scRNA-seq experiments, there are no cell-to-cell correspondences along with the time to reconstruct the cell lineages, which creates a significant challenge for cell lineage tracing and cell fate prediction. Therefore, methods that can accurately reconstruct the dynamic cell lineages and predict cell fates are highly desirable. In this article, we develop an innovative machine-learning framework called Cell Smoothing Transformation (CellST) to elucidate the dynamic cell fate paths and construct gene networks in cell differentiation processes. Unlike the existing methods that construct one single bulk cell trajectory, CellST builds cell trajectories and tracks behaviors for each individual cell. Additionally, CellST can predict cell fates even for less frequent cell types. Based on the individual cell fate trajectories, CellST can further construct dynamic gene networks to model gene-gene relationships along the cell differentiation process and discover critical genes that potentially regulate cells into various mature cell types.

Single-cell RNA sequencing reveals enhanced antitumor immunity after combined application of PD-1 inhibitor and Shenmai injection in non-small cell lung cancer.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have altered the clinical management of non-small cell lung cancer (NSCLC). However, the low response rate, severe immune-related adverse events (irAEs), and hyperprogressive disease following ICIs monotherapy require attention. Combination therapy may overcome these limitations and traditional Chinese medicine with immunomodulatory effects provides a promising approach. Shenmai injection (SMI) is a clinically effective adjuvant treatment for cancer with chemotherapy and radiotherapy. Therefore, the combined effects and mechanisms of SMI and programmed death-1 (PD-1) inhibitor against NSCLC was focused on this study. METHODS: A Lewis lung carcinoma mouse model and a lung squamous cell carcinoma humanized mouse model were used to investigate the combined efficacy and safety of SMI and PD-1 inhibitor. The synergistic mechanisms of the combination therapy against NSCLC were explored using single-cell RNA sequencing. Validation experiments were performed using immunofluorescence analysis, in vitro experiment, and bulk transcriptomic datasets. RESULTS: In both models, combination therapy alleviated tumor growth and prolonged survival without increasing irAEs. The GZMAhigh and XCL1high natural killer (NK) cell subclusters with cytotoxic and chemokine signatures increased in the combination therapy, while malignant cells from combination therapy were mainly in the apoptotic state, suggesting that mediating tumor cell apoptosis through NK cells is the main synergistic mechanisms of combination therapy. In vitro experiment confirmed that combination therapy increased secretion of Granzyme A by NK cells. Moreover, we discovered that PD-1 inhibitor and SMI combination blocked inhibitory receptors on NK and T cells and restores their antitumoral activity in NSCLC better than PD-1 inhibitor monotherapy, and immune and stromal cells exhibited a decrease of angiogenic features and attenuated cancer metabolism reprogramming in microenvironment of combination therapy. CONCLUSIONS: This study demonstrated that SMI reprograms tumor immune microenvironment mainly by inducing NK cells infiltration and synergizes with PD-1 inhibitor against NSCLC, suggested that targeting NK cells may be an important strategy for combining with ICIs. Video Abstract.

Marine-Derived Bioactive Peptides Self-Assembled Multifunctional Materials: Antioxidant and Wound Healing.

Peptide self-assembling materials have received significant attention from researchers in recent years, emerging as a popular field in biological, environmental, medical, and other new materials studies. In this study, we utilized controllable enzymatic hydrolysis technology (animal proteases) to obtain supramolecular peptide self-assembling materials (CAPs) from the Pacific oyster (Crassostrea gigas). We conducted physicochemical analyses to explore the pro-healing mechanisms of CAPs on skin wounds in both in vitro and in vivo experiments through a topical application. The results demonstrated that CAPs exhibit a pH-responsive behavior for self-assembly and consist of peptides ranging from 550 to 2300 Da in molecular weight, with peptide chain lengths of mainly 11-16 amino acids. In vitro experiments indicated that CAPs display a procoagulant effect, free radical scavenging activity, and promote the proliferation of HaCaTs (112.74% and 127.61%). Moreover, our in vivo experiments demonstrated that CAPs possess the ability to mitigate inflammation, boost fibroblast proliferation, and promote revascularization, which accelerates the epithelialization process. Consequently, a balanced collagen I/III ratio in the repaired tissue and the promotion of hair follicle regeneration were observed. With these remarkable findings, CAPs can be regarded as a natural and secure treatment option with high efficacy for skin wound healing. The potential of CAPs to be further developed for traceless skin wound healing is an exciting area for future research and development.

A novel water-soluble chitosan grafted with nerol: Synthesis, characterization and biological activity.

In order to improve the antibacterial activity of chitosan and change its solubility, a novel water-soluble chitosan (CS)-nerol (N) derivative (CS-N) was prepared via Schiff base reaction and grafting reaction. FT-IR, NMR, XRD, TGA and SEM were used to characterize the structure and physicochemical properties, and in vitro antibacterial, antioxidant, and cellular assays were used to test for bioactivity and safety. The results revealed that the C6 hydroxyl group of CS was substituted with N, with a degree of substitution of 38 % for CS-N. Furthermore, compared to CS, CS-N demonstrated superior antibacterial activity against Escherichia coli and Staphylococcus aureus, as well as significant DPPH and ABTS free radical scavenging activity. Most importantly, CS-N did not harm HaCaT cells. In conclusion, this study provides a promising strategy for the design of chitosan derivatives with significant potential for application in pharmaceutical, food and cosmetic applications.

3D Printed Integrated Gradient-Conductive MXene/CNT/Polyimide Aerogel Frames for Electromagnetic Interference Shielding with Ultra-Low Reflection.

Construction of advanced electromagnetic interference (EMI) shielding materials with miniaturized, programmable structure and low reflection are promising but challenging. Herein, an integrated transition-metal carbides/carbon nanotube/polyimide (gradient-conductive MXene/CNT/PI, GCMCP) aerogel frame with hierarchical porous structure and gradient-conductivity has been constructed to achieve EMI shielding with ultra-low reflection. The gradient-conductive structures are obtained by continuous 3D printing of MXene/CNT/poly (amic acid) inks with different CNT contents, where the slightly conductive top layer serves as EM absorption layer and the highly conductive bottom layer as reflection layer. In addition, the hierarchical porous structure could extend the EM dissipation path and dissipate EM by multiple reflections. Consequently, the GCMCP aerogel frames exhibit an excellent average EMI shielding efficiency (68.2 dB) and low reflection (R = 0.23). Furthermore, the GCMCP aerogel frames with miniaturized and programmable structures can be used as EMI shielding gaskets and effectively block wireless power transmission, which shows a prosperous application prospect in defense industry and aerospace.

Blocking AMPK ß1 myristoylation enhances AMPK activity and protects mice from high-fat diet-induced obesity and hepatic steatosis.

AMP-activated protein kinase (AMPK) is a master regulator of cellular energy homeostasis and a therapeutic target for metabolic diseases. Co/post-translational N-myristoylation of glycine-2 (Gly2) of the AMPK ß subunit has been suggested to regulate the distribution of the kinase between the cytosol and membranes through a "myristoyl switch" mechanism. However, the relevance of AMPK myristoylation for metabolic signaling in cells and in vivo is unclear. Here, we generated knockin mice with a Gly2-to-alanine point mutation of AMPKß1 (ß1-G2A). We demonstrate that non-myristoylated AMPKß1 has reduced stability but is associated with increased kinase activity and phosphorylation of the Thr172 activation site in the AMPK α subunit. Using proximity ligation assays, we show that loss of ß1 myristoylation impedes colocalization of the phosphatase PPM1A/B with AMPK in cells. Mice carrying the ß1-G2A mutation have improved metabolic health with reduced adiposity, hepatic lipid accumulation, and insulin resistance under conditions of high-fat diet-induced obesity.

Impact of a long-term high-fructose diet on systemic metabolic profiles of mice.

Evidence is mounting that chronic high-fructose diets (HFrD) can lead to metabolic abnormalities and cause a variety of diseases. However, the underlying mechanism by which long-term high fructose intake influencing systemic metabolism remains unclarified. This study, therefore, attempted to investigate the impact of a high-fructose diet on metabolic profile. Four-week-old male C57BL/6 mice were fed with 15% fructose solution as their only source of water for 8 weeks. Afterward, gas chromatography-mass spectrometry (GC-MS) was employed to investigate the comprehensive metabolic profile of serum, muscle, liver, heart, white adipose, brain, and kidney tissues, and multivariate analyses including principal component analysis (PCA) and orthogonal partial least squared-discriminant analysis (OPLS-DA) were applied to screen for differential metabolite expression between the HFrD and control groups. Furthermore, the MetaboAnalyst 5.0 (http://www.metaboanalyst.ca) and Kyoto Encyclopedia of Genes and Genomes database (KEGG; http://www.kegg.jp) were employed to portray a detailed metabolic network. This study identified 62 metabolites related to HFrD and 10 disturbed metabolic pathways. The results indicated that high fructose intake mainly influenced amino acid metabolism and biosynthesis (glycine, serine, and threonine metabolism; aspartate, and glutamate metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis, and arginine biosynthesis pathways), glutathione metabolism, sphingolipid metabolism, and glyoxylate and dicarboxylate metabolism in serum, whereas these pathways were suppressed in the brain. Starch and sucrose metabolism in muscle was also disrupted. These results elucidate the effects of long-term high fructose consumption on the metabolic profiles of various tissues and provide new insight for the identification of potential metabolic biomarkers and pathways disrupted by high fructose.

A GC-MS-based untargeted metabolomics approach for comprehensive metabolic profiling of vancomycin-induced toxicity in mice.

Background: Vancomycin is a glycopeptide antibiotic that is commonly used for severe drug-resistant infections treatment. Application of vancomycin frequently leads to severe ototoxicity, hepatotoxicity, and nephrotoxicity; however, the comprehensive metabolic analysis of vancomycin-induced toxicity is lacking. Purpose: This study attempted to investigate the metabolic changes after vancomycin administration in mice. Methods: Experimental mice (n = 9) received continuous intraperitoneal injection of vancomycin (400 mg/kg) every day for 7 days, and mice in control group (n = 9) were treated with the same amount of normal saline. Pathological changes of the kidney were examined using haematoxylin and eosin (HE) staining. A gas chromatography-mass spectrometry (GC-MS) approach was used to identify discriminant metabolites in serum and various organs including the heart, liver, kidney, spleen, cerebral cortex, hippocampus, inner ear, lung, and intestine. The potential metabolites were identified using orthogonal partial least squares discrimination analysis (OPLS-DA). Subsequently, the MetaboAnalyst 5.0 (http://www.metaboanalyst.ca) and Kyoto Encyclopedia of Genes and Genomes database (KEGG, http://www.kegg.jp) were employed to depict the metabolic pathways. Results: Compared with the control group, the vancomycin induced 13, 17, 27, 22, 16, 10, 17, 11, 10, and 7 differential metabolites in the serum, liver, kidney, heart, cerebral cortex, lung, spleen, intestine, hippocampus, and inner ear, respectively. Further pathway analyses identified that amino acids metabolism, fatty acids biosynthesis, energy metabolism, and lipid metabolism were disrupted after VCM exposure. Conclusion: Vancomycin affects the metabolism in various organs in mice, which provides new insights for identification of vancomycin-induced toxicity, and facilitate to better understanding of the metabolic pathogenesis of vancomycin.