Methylisothiazolinone pollution inhibited root stem cells and regeneration through auxin transport modification in Arabidopsis thaliana.

Methylisothiazolinone (MIT) is a widely used preservative and biocide to prevent product degradation, yet its potential impact on plant growth remains poorly understood. In this study, we investigated MIT's toxic effects on Arabidopsis thaliana root growth. Exposure to MIT significantly inhibited Arabidopsis root growth, associated with reduced root meristem size and root meristem cell numbers. We explored the polar auxin transport pathway and stem cell regulation as key factors in root meristem function. Our findings demonstrated that MIT suppressed the expression of the auxin efflux carrier PIN1 and major root stem cell regulators (PLT1, PLT2, SHR, and SCR). Additionally, MIT hindered root regeneration by downregulating the quiescent center (QC) marker WOX5. Transcriptome analysis revealed MIT-induced alterations in gene expression related to oxidative stress, with physiological experiments confirming elevated reactive oxygen species (ROS) levels and increased cell death in root tips at concentrations exceeding 50 µM. In summary, this study provides critical insights into MIT's toxicity on plant root development and regeneration, primarily linked to modifications in polar auxin transport and downregulation of genes associated with root stem cell regulation.

Histone lactylation dynamics: Unlocking the triad of metabolism, epigenetics, and immune regulation in metastatic cascade of pancreatic cancer.

Cancer cells rewire metabolism to sculpt the immune tumor microenvironment (TME) and propel tumor advancement, which intricately tied to post-translational modifications. Histone lactylation has emerged as a novel player in modulating protein functions, whereas little is known about its pathological role in pancreatic ductal adenocarcinoma (PDAC) progression. Employing a multi-omics approach encompassing bulk and single-cell RNA sequencing, metabolomics, ATAC-seq, and CUT&Tag methodologies, we unveiled the potential of histone lactylation in prognostic prediction, patient stratification and TME characterization. Notably, "LDHA-H4K12la-immuno-genes" axis has introduced a novel node into the regulatory framework of "metabolism-epigenetics-immunity," shedding new light on the landscape of PDAC progression. Furthermore, the heightened interplay between cancer cells and immune counterparts via Nectin-2 in liver metastasis with elevated HLS unraveled a positive feedback loop in driving immune evasion. Simultaneously, immune cells exhibited altered HLS and autonomous functionality across the metastatic cascade. Consequently, the exploration of innovative combination strategies targeting the metabolism-epigenetics-immunity axis holds promise in curbing distant metastasis and improving survival prospects for individuals grappling with challenges of PDAC.

The Protective Efficacy of a SARS-CoV-2 Vaccine Candidate B.1.351V against Several Variant Challenges in K18-hACE2 Mice.

The emergence of SARS-CoV-2 variants of concern (VOCs) with increased transmissibility and partial resistance to neutralization by antibodies has been observed globally. There is an urgent need for an effective vaccine to combat these variants. Our study demonstrated that the B.1.351 variant inactivated vaccine candidate (B.1.351V) generated strong binding and neutralizing antibody responses in BALB/c mice against the B.1.351 virus and other SARS-CoV-2 variants after two doses within 28 days. Immunized K18-hACE2 mice also exhibited elevated levels of live virus-neutralizing antibodies against various SARS-CoV-2 viruses. Following infection with these viruses, K18-hACE2 mice displayed a stable body weight, a high survival rate, minimal virus copies in lung tissue, and no lung damage compared to the control group. These findings indicate that B.1.351V offered protection against infection with multiple SARS-CoV-2 variants in mice, providing insights for the development of a vaccine targeting SARS-CoV-2 VOCs for human use.

The significant role of amino acid metabolic reprogramming in cancer.

Amino acid metabolism plays a pivotal role in tumor microenvironment, influencing various aspects of cancer progression. The metabolic reprogramming of amino acids in tumor cells is intricately linked to protein synthesis, nucleotide synthesis, modulation of signaling pathways, regulation of tumor cell metabolism, maintenance of oxidative stress homeostasis, and epigenetic modifications. Furthermore, the dysregulation of amino acid metabolism also impacts tumor microenvironment and tumor immunity. Amino acids can act as signaling molecules that modulate immune cell function and immune tolerance within the tumor microenvironment, reshaping the anti-tumor immune response and promoting immune evasion by cancer cells. Moreover, amino acid metabolism can influence the behavior of stromal cells, such as cancer-associated fibroblasts, regulate ECM remodeling and promote angiogenesis, thereby facilitating tumor growth and metastasis. Understanding the intricate interplay between amino acid metabolism and the tumor microenvironment is of crucial significance. Expanding our knowledge of the multifaceted roles of amino acid metabolism in tumor microenvironment holds significant promise for the development of more effective cancer therapies aimed at disrupting the metabolic dependencies of cancer cells and modulating the tumor microenvironment to enhance anti-tumor immune responses and inhibit tumor progression.

Human Equilibrative Nucleoside Transporter 1: Novel Biomarker and Prognostic Indicator for Patients with Gemcitabine-Treated Pancreatic Cancer.

Aim: This article aimed to find appropriate pancreatic cancer (PC) patients to treat with Gemcitabine with better survival outcomes by detecting hENT1 levels. Methods: We collected surgical pathological tissues from PC patients who received radical surgery in our hospital from September 2004 to December 2014. A total of 375 PC tissues and paired adjacent nontumor tissues were employed for the construction of 4 tissue microarrays (TMAs). The quality of the 4 TMAs was examined by HE staining. We performed immunohistochemistry analysis to evaluate hENT1 expression in the TMAs. Moreover, we detected hENT1 expression level and proved the role of hENT1 in cell proliferation, drug resistance, migration and invasion in vivo and vitro. Results: The results indicated that low hENT1 expression indicated a significantly poor outcome in PC patients, including shortened DFS (21.6±2.8 months versus 36.9±4.0 months, p<0.001) and OS (33.6±3.9 versus 39.6±3.9, p=0.004). Meanwhile, patients in stage I/II of TNM stage had a longer OS (40.2±3.4 versus 15.4±1.7, p=0.002) and DFS (31.0±3.1 versus 12.4±1.9, p=0.016) than patients in stage III/IV. Patients in M0 stage had a longer OS (39.7±3.4 versus 16.2±1.9, p=0.026) and DFS(30.7±3.0 versus 11.8±2.2, p=0.031) than patients in M1 stage, and patients with tumors not invading the capsule had a better DFS than those with tumor invasion into the capsule (30.8±3.0 versus 12.6±2.3, p=0.053). Patients with preoperative CA19-9 values ≤467 U/mL have longer DFS than that of patients who had preoperative CA19-9 values >467 U/mL (37.9±4.1 versus 22.9±4.0, p=0.04). In the subgroup analysis, a high hENT1 expression level was related to a longer OS(39.4±4.0 versus 31.5±3.9, p=0.001) and DFS(35.7±4.0 versus 20.6±2.7; p<0.0001) in the Gemcitabine subgroup. Conclusion: PC patients with high hENT1 expression have a better survival outcomes when receiving Gemcitabine. hENT1 expression can be a great prognostic indicator for PC patients to receive Gemcitabine treatment.

Systematic identification and functional analysis of root meristem growth factors (RGFs) reveals role of PgRGF1 in modulation of root development and ginsenoside production in Panax ginseng.

Panax ginseng C.A. Mey., known for its medicinal and dietary supplement properties, primarily contains pharmacologically active ginsenosides. However, the regulatory mechanisms linking ginseng root development with ginsenoside biosynthesis are still unclear. Root meristem growth factors (RGFs) are crucial for regulating plant root growth. In our study, we identified five ginseng RGF peptide sequences from the ginseng genome and transcriptome libraries. We treated Arabidopsis and ginseng adventitious roots with exogenous Panax ginseng RGFs (PgRGFs) to assess their activities. Our results demonstrate that PgRGF1 influences gravitropic responses and reduces lateral root formation in Arabidopsis. PgRGF1 has been found to restrict the number and length of ginseng adventitious root branches in ginseng. Given the medicinal properties of ginseng, We determined the ginsenoside content and performed transcriptomic analysis of PgRGF1-treated ginseng adventitious roots. Specifically, the total ginsenoside content in ginseng adventitious roots decreased by 19.98 % and 63.71 % following treatments with 1 µM and 10 µM PgRGF1, respectively, compared to the control. The results revealed that PgRGF1 affects the accumulation of ginsenosides by regulating the expression of genes associated with auxin transportation and ginsenoside biosynthesis. These findings suggest that PgRGF1, as a peptide hormone regulator in ginseng, can modulate adventitious root growth and ginsenoside accumulation.

How to choose a design thinking method for teaching the design of localization: A two-dimension linguistic fuzzy model with two-tuples.

There are many different types of scientific design thinking methods, but it is necessary to evaluate the applicability of the methods to the components of the design teaching curriculum in universities. Therefore, this study assesses the applicability of design thinking in terms of "design practice" and "locality" based on the local design education philosophy and the characteristics of the students and courses. A two-dimensional linguistic fuzzy model with two-tuples was proposed, and the assessment values of 36 experts were statistically analysed using the Delphi, triangular fuzzy number, Euclidean distance, two-dimension linguistic label (2DLL), and two-dimensional linguistic weighted arithmetic aggregation (2DLWAA) methods. The results highlighted the 12 categories of design thinking methods that are most applicable to teaching and learning, indicating the basic views of university design faculty on the application of design thinking methods. Finally, the new design teaching methods have been validated and constructed through years of teaching practice, and have some reference value for teaching design courses in universities.

Aromatic-Carbonyl Interactions as an Emerging Type of Non-Covalent Interactions.

Aromatic-carbonyl (Ar···C═O) interactions, attractive interactions between the arene plane and the carbon atom of carbonyl, are in the infancy as one type of new supramolecular bonding forces. Here the study and functionalization of aromatic-carbonyl interactions in solution is reported. A combination of aromatic-carbonyl interactions and dynamic covalent chemistry provided a versatile avenue. The stabilizing role and mechanism of arene-aldehyde/imine interactions are elucidated through crystal structures, NMR studies, and computational evidence. The movement of imine exchange equilibria further allowed the quantification of the interplay between arene-aldehyde/imine interactions and dynamic imine chemistry, with solvent effects offering another handle and matching the electrostatic feature of the interactions. Moreover, arene-aldehyde/imine interactions enabled the reversal of kinetic and thermodynamic selectivity and sorting of dynamic covalent libraries. To show the functional utility diverse modulation of fluorescence signals is realized with arene-aldehyde/imine interactions. The results should find applications in many aspects, including molecular recognition, assemblies, catalysis, and intelligent materials.

The study on mechanical model considering optimal self-adaption in the bottleneck area.

It aims to solve the problem that the evacuation state of pedestrians depicted by the traditional social force model in a crowded multiexit scenario has a relatively large difference with the actual state, especially the 'optimal path' considered by the self-driving force is the problem of shortest path, and the multiexit evacuation mode depicted by the 'herd behavior' is the local optimum problem. Through in-depth analysis of actual evacuation data of pedestrians and causes of problem, a new crowd evacuation optimization model is established in order to effectively improve the simulation accuracy of crowd evacuation in a multi-exit environment. The model obtains the direction of motion of pedestrians using a field model, fully considers the factors such as exit distance, distribution of pedestrians and regional crowding degree, makes a global optimization for the self-driving force in the social force model using a centralized and distributed network model, and makes a local optimization for it using an elephant herding algorithm, so as to establish a new evacuation optimization method for optimal self-adaption in the bottleneck area. The performance status is compared between the improved social force model and the new model by experiments, and the key factors that affect the new model are analyzed in an in-depth manner. The results show that the new model can optimize the optimal path choice at the early stage of evacuation and improve the evacuation efficiency of pedestrians at the late stage, so as to ensure relatively even distribution of pedestrians at each exit, and also make the simulated evacuation process be more real; and the improvement in overall evacuation efficiency is greater when the number of pedestrians to be evacuated is larger. Therefore, the new model provides a method to solve the phenomenon of disorder in overall pedestrian evacuation due to excessive crowd density during the process of multi-exit evacuation.

Photoswitchable Cascades for Allosteric and Bidirectional Control over Covalent Bonds and Assemblies.

Studies of complex systems and emerging properties to mimic biosystems are at the forefront of chemical research. Dynamic multistep cascades, especially those exhibiting allosteric regulation, are challenging. Herein, we demonstrate a versatile platform of photoswitchable covalent cascades toward remote and bidirectional control of reversible covalent bonds and ensuing assemblies. The relay of a photochromic switch, keto-enol equilibrium, and ring-chain equilibrium allows light-mediated reversible allosteric structural changes. The accompanying distinct reactivity further enables photoswitchable dynamic covalent bonding and release of substrates bidirectionally through alternating two wavelengths of light, essentially realizing light-mediated signaling cycles. The downfall of energy by covalent bond formation/scission upon photochemical reactions offers the driving force for the controlled direction of the cascade. To show the molecular diversity, photoswitchable on-demand assembly/disassembly of covalent polymers, including structurally reconfigurable polymers, was realized. This work achieves photoswitchable allosteric regulation of covalent architectures within dynamic multistep cascades, which has rarely been reported before. The results resemble allosteric control within biological signaling networks and should set the stage for many endeavors, such as dynamic assemblies, molecular motors, responsive polymers, and intelligent materials.

Comprehensive analysis of bulk and single-cell transcriptomic data reveals a novel signature associated with endoplasmic reticulum stress, lipid metabolism, and liver metastasis in pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with high probability of recurrence and distant metastasis. Liver metastasis is the predominant metastatic mode developed in most pancreatic cancer cases, which seriously affects the overall survival rate of patients. Abnormally activated endoplasmic reticulum stress and lipid metabolism reprogramming are closely related to tumor growth and metastasis. This study aims to construct a prognostic model based on endoplasmic reticulum stress and lipid metabolism for pancreatic cancer, and further explore its correlation with tumor immunity and the possibility of immunotherapy. METHODS: Transcriptomic and clinical data are acquired from TCGA, ICGC, and GEO databases. Potential prognostic genes were screened by consistent clustering and WGCNA methods, and the whole cohort was randomly divided into training and testing groups. The prognostic model was constructed by machine learning method in the training cohort and verified in the test, TCGA and ICGC cohorts. The clinical application of this model and its relationship with tumor immunity were analyzed, and the relationship between endoplasmic reticulum stress and intercellular communication was further explored. RESULTS: A total of 92 characteristic genes related to endoplasmic reticulum stress, lipid metabolism and liver metastasis were identified in pancreatic cancer. We established and validated a prognostic model for pancreatic cancer with 7 signatures, including ADH1C, APOE, RAP1GAP, NPC1L1, P4HB, SOD2, and TNFSF10. This model is considered to be an independent prognosticator and is a more accurate predictor of overall survival than age, gender, and stage. TIDE score was increased in high-risk group, while the infiltration levels of CD8+ T cells and M1 macrophages were decreased. The number and intensity of intercellular communication were increased in the high ER stress group. CONCLUSIONS: We constructed and validated a novel prognostic model for pancreatic cancer, which can also be used as an instrumental variable to predict the prognosis and immune microenvironment. In addition, this study revealed the effect of ER stress on cell-cell communication in the tumor microenvironment.

Neighboring Effects of Sulfur Oxidation State on Dynamic Covalent Bonds and Assemblies.

The impact of a varied sulfur oxidation state (sulfide, sulfoxide, and sulfone) on imine dynamic covalent chemistry is presented. The role of noncovalent interactions, including chalcogen bonds and CH hydrogen bonds, on aldehyde/imine structures and imine exchange reactions was elucidated through experimental and computational evidence. The change in the sulfur oxidation state and diamine linkage further allowed the regulation of imine macrocycles, providing a platform for controlling molecular assemblies.

An exposome atlas of serum reveals the risk of chronic diseases in the Chinese population.

Although adverse environmental exposures are considered a major cause of chronic diseases, current studies provide limited information on real-world chemical exposures and related risks. For this study, we collected serum samples from 5696 healthy people and patients, including those with 12 chronic diseases, in China and completed serum biomonitoring including 267 chemicals via gas and liquid chromatography-tandem mass spectrometry. Seventy-four highly frequently detected exposures were used for exposure characterization and risk analysis. The results show that region is the most critical factor influencing human exposure levels, followed by age. Organochlorine pesticides and perfluoroalkyl substances are associated with multiple chronic diseases, and some of them exceed safe ranges. Multi-exposure models reveal significant risk effects of exposure on hyperlipidemia, metabolic syndrome and hyperuricemia. Overall, this study provides a comprehensive human serum exposome atlas and disease risk information, which can guide subsequent in-depth cause-and-effect studies between environmental exposures and human health.

Multiple control of azoquinoline based molecular photoswitches.

Multi-addressable molecular switches with high sophistication are creating intensive interest, but are challenging to control. Herein, we incorporated ring-chain dynamic covalent sites into azoquinoline scaffolds for the construction of multi-responsive and multi-state switching systems. The manipulation of ring-chain equilibrium by acid/base and dynamic covalent reactions with primary/secondary amines allowed the regulation of E/Z photoisomerization. Moreover, the carboxyl and quinoline motifs provided recognition handles for the chelation of metal ions and turning off photoswitching, with otherwise inaccessible Z-isomer complexes obtained via the change of stimulation sequence. Particularly, the distinct metal binding behaviors of primary amine and secondary amine products offered a facile way for modulating E/Z switching and dynamic covalent reactivity. As a result, multiple control of azoarene photoswitches was accomplished, including light, pH, metal ions, and amine nucleophiles, with interplay between diverse stimuli further enabling addressable multi-state switching within reaction networks. The underlying structural and mechanistic insights were elucidated, paving the way for the creation of complex switching systems, molecular assemblies, and intelligent materials.

[Risk analysis of serum chemical residues for metabolic associated fatty liver disease based on exposome-lipidome wide association study].

Metabolic associated fatty liver disease (MAFLD) is a common liver disease with a prevalence of up to 25%; it not only adversely affects human health but also aggravates the economic burden of society. An increasing number of studies have suggested that the occurrence of chronic noncommunicable diseases is affected by both environmental exposures and genetic factors. Research has also shown that environmental pollution may increase the risk of MAFLD and promote its occurrence and development. However, the relationship between these concepts, as well as the underlying exposure effects and mechanism, remains incompletely understood. Lipidomics, a branch of metabolomics that studies lipid disorders, can help researchers investigate abnormal lipid metabolites in various disease states. Lipidome-exposome wide association studies are a promising paradigm for investigating the health effects of cumulative environmental exposures on biological responses, and could provide new ideas for determining the associations between metabolic and lipid changes and disease risk caused by chemical-pollutant exposure. Hence, in this study, targeted exposomics and nontargeted lipidomics studies based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) were used to characterize exogenous chemical pollutants and endogenous lipid metabolites in the sera of patients with MAFLD and healthy subjects. The results demonstrated that fipronil sulfone, malathion dicarboxylic acid, and monocyclohexyl phthalate may be positively associated with the disease risk of patients diagnosed as simple fatty liver disease (hereafter referred to as MAFLD(0)). Moreover, fipronil sulfone, acesulfame potassium, perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluoroundecanoic acid (PFUnDA), 4-hydroxybenzophenone, and 3,5-di-tert-butyl-4-hydroxybenzoic acid (DBPOB) may be positively associated with the disease risk of patients diagnosed as fatty liver complicated by single or multiple metabolic disorders. Association analysis was carried out to explore the lipid metabolites induced by chemical residues. Triglyceride (TG) and diglyceride (DG) were significantly increased in MAFLD and MAFLD(0). The numbers of carbons of significantly changed DGs and TGs were mainly in the ranges of 32-40 and 35-60, respectively, and both were mainly characterized by changes in polyunsaturated lipids. Most of the lipid-effect markers were positively correlated with chemical residues and associated with increased disease risk. Our research provides a scientific basis for studies on the association and mechanism between serum chemical-pollutant residues and disease outcomes.

Epigenetic regulation in cancer.

Epigenetic modifications are defined as heritable changes in gene activity that do not involve changes in the underlying DNA sequence. The oncogenic process is driven by the accumulation of alterations that impact genome's structure and function. Genetic mutations, which directly disrupt the DNA sequence, are complemented by epigenetic modifications that modulate gene expression, thereby facilitating the acquisition of malignant characteristics. Principals among these epigenetic changes are shifts in DNA methylation and histone mark patterns, which promote tumor development and metastasis. Notably, the reversible nature of epigenetic alterations, as opposed to the permanence of genetic changes, positions the epigenetic machinery as a prime target in the discovery of novel therapeutics. Our review delves into the complexities of epigenetic regulation, exploring its profound effects on tumor initiation, metastatic behavior, metabolic pathways, and the tumor microenvironment. We place a particular emphasis on the dysregulation at each level of epigenetic modulation, including but not limited to, the aberrations in enzymes responsible for DNA methylation and histone modification, subunit loss or fusions in chromatin remodeling complexes, and the disturbances in higher-order chromatin structure. Finally, we also evaluate therapeutic approaches that leverage the growing understanding of chromatin dysregulation, offering new avenues for cancer treatment.

Crosstalk between metabolic remodeling and epigenetic reprogramming: A new perspective on pancreatic cancer.

Pancreatic cancer is a highly malignant solid tumor with a poor prognosis and a high mortality rate. Thus, exploring the mechanisms underlying the development and progression of pancreatic cancer is critical for identifying targets for diagnosis and treatment. Two important hallmarks of cancer-metabolic remodeling and epigenetic reprogramming-are interconnected and closely linked to regulate one another, creating a complex interaction landscape that is implicated in tumorigenesis, invasive metastasis, and immune escape. For example, metabolites can be involved in the regulation of epigenetic enzymes as substrates or cofactors, and alterations in epigenetic modifications can in turn regulate the expression of metabolic enzymes. The crosstalk between metabolic remodeling and epigenetic reprogramming in pancreatic cancer has gained considerable attention. Here, we review the emerging data with a focus on the reciprocal regulation of metabolic remodeling and epigenetic reprogramming. We aim to highlight how these mechanisms could be applied to develop better therapeutic strategies.

[New advances in exposomics-analysis methods and research paradigms based on chromatography-mass spectrometry].

The occurrence and development of human diseases are influenced by both genetic and environmental factors. Research models that describe disease occurrence only from the perspective of genetics present certain limitations. In recent years, effects of environment factors on the occurrence and development of diseases have attracted extensive attentions. Exposomics focuses on the measurement of all exposure factors in an individual's life and how these factors are related to disease development. Exposomics provides new ideas to promote studies on the relationship between human health and environmental factors. Environmental exposures are characterized with different physical and chemical properties, as well as very low concentrations in vivo, which contribute great challenges in the comprehensive measurement of chemical residues in the human body. Chromatography-mass spectrometry-based technologies combine the high-efficiency separation ability of chromatography with the high resolution and sensitive detection characteristics of mass spectrometry; the combination of these techniques can achieve the high-coverage, high-throughput, and sensitive detection of environmental exposures, thus providing a powerful tool for measuring chemical exposures. Exposomics-analysis methods based on chromatography-mass spectrometry mainly include targeted quantitative analysis, suspect screening, and non-targeted screening. To explore the relationship between environmental exposure and the occurrence and development of diseases, researchers have developed research paradigms, including exposome wide association study, mixed-exposure study, exposomics and multi-omics (genome, transcriptome, proteome, metabolome)-association study, and so on. The emergence of these methods has brought about unprecedented developments in exposomics studies. In this manuscript, analytical methods based on chromatography-mass spectrometry, exposomics research paradigms, and their relevant prospects are reviewed.

Screening and identification of unknown chemical contaminants in food based on liquid chromatography-high-resolution mass spectrometry and machine learning.

Unknown or unexpected chemical contaminants and/or their transformation products in food that may be harmful to humans need to be discovered for comprehensive safety evaluation. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is a powerful tool for detecting chemical contaminants in food samples. However, identifying all of peaks in LC-HRMS is not possible, but if class information is known in advance, further identification will become easier. In this work, a novel MS2 spectra classification-driven screening strategy was constructed based on LC-HRMS and machine learning. First, the classification model was developed based on machine learning algorithm using class information and experimental MS2 data of chemical contaminants and other non-contaminants. By using the developed artificial neural network classification model, in total 32 classes of pesticides, veterinary drugs and mycotoxins were classified with good prediction accuracy and low false-positive rate. Based on the classification model, a screening procedure was developed in which the classes of unknown features in LC-HRMS were first predicted through the classification model, and then their structures were identified under the guidance of class information. Finally, the developed strategy was tentatively applied to the analysis of pork and aquatic products, and 8 chemical contaminants and 11 transformation products belonging to 8 classes were found. This strategy enables screening of unknown chemical contaminants and transformation products in complex food matrices.