Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective To establish a high-throughput non-targeted screening and prioritization method for emerging pollutants(EPs)in sewage using direct injection high-resolution mass spectrometry(HRMS).Methods The sewage samples were filtered by membrane filter and directly subjected to the liquid chromatography-time-of-flight mass spectrometer based on a method modified from our previous study.A C18 chromatographic column was applied for a gradient elution separation,and accurate mass and mass spectral fragment information were obtained through the MS full scan mode and MS/MS DIA data collection mode.After peak detection and alignment,the features from the raw data through open source software MZmine 3,and then high-throughput screening strategies such as MassBank and PubChem databases were used for compound annotation.Finally,the candidate features were confirmed with chemical standards by compared their retention time and mass spectrum fragmentation ion peaks.Results 13 EPs were identified,including 7 industrial chemicals,4 pharmaceuticals,1 pesticide and 1 metabolite.High detection rates were observed for metformin(86.2％),2-hydroxybenzothiazole(79.3％),1,2-benzisothiazole-3-one(72.4％),and 1,2-benzisothiazole-3-one(72.4％).The quantitative concentration range of EPs was 1.37～19.05 ng/mL,with the high concentrations observed for melamine(19.05 ng/mL)and furosemide(18.49 ng/mL).Ecological risk assessment identified 1,2-benzisothiazol-3-one,4-aminoacetophenone,creatinine,2-hydroxybenzothiazole,and furosemide as key pollutants.Conclusion This direct injection coupled with HRMS workflow enables efficient non-targeted screening and prioritization of emerging EPs in sewage samples,highlighting five ecotoxicologically critical EPs.The methodology enhances environmental monitoring capabilities and provide critical technical support for interdisciplinary research such as environmental forensics and health risk assessment.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective To establish a high-throughput non-targeted screening and prioritization method for emerging pollutants(EPs)in sewage using direct injection high-resolution mass spectrometry(HRMS).Methods The sewage samples were filtered by membrane filter and directly subjected to the liquid chromatography-time-of-flight mass spectrometer based on a method modified from our previous study.A C18 chromatographic column was applied for a gradient elution separation,and accurate mass and mass spectral fragment information were obtained through the MS full scan mode and MS/MS DIA data collection mode.After peak detection and alignment,the features from the raw data through open source software MZmine 3,and then high-throughput screening strategies such as MassBank and PubChem databases were used for compound annotation.Finally,the candidate features were confirmed with chemical standards by compared their retention time and mass spectrum fragmentation ion peaks.Results 13 EPs were identified,including 7 industrial chemicals,4 pharmaceuticals,1 pesticide and 1 metabolite.High detection rates were observed for metformin(86.2％),2-hydroxybenzothiazole(79.3％),1,2-benzisothiazole-3-one(72.4％),and 1,2-benzisothiazole-3-one(72.4％).The quantitative concentration range of EPs was 1.37～19.05 ng/mL,with the high concentrations observed for melamine(19.05 ng/mL)and furosemide(18.49 ng/mL).Ecological risk assessment identified 1,2-benzisothiazol-3-one,4-aminoacetophenone,creatinine,2-hydroxybenzothiazole,and furosemide as key pollutants.Conclusion This direct injection coupled with HRMS workflow enables efficient non-targeted screening and prioritization of emerging EPs in sewage samples,highlighting five ecotoxicologically critical EPs.The methodology enhances environmental monitoring capabilities and provide critical technical support for interdisciplinary research such as environmental forensics and health risk assessment.

Objective To establish a simultaneous detection approach for 34 emerging contaminants(ECs)in tap water by liquid chromatography-tandem mass spectrometry(HPLC-MS/MS).Human health risk assessment was performed according to the detection results from 43 tap water samples.Methods Tap water samples were concentrated and extracted by solid phase extraction,and then blown to near dry by nitrogen at 40℃.The sample extracts were dissolved in methanol-water solution(95:5,VN)to 0.5 mL for analyzing.Agilent Jet Stream Electrospray Ionization(AJS ESI)and the multiple reaction monitoring(MRM)mode were performed for MS to acquire the data of 34 ECs.A database including precursor ion,product ion and retention times was established accordingly.Results The average linear correlation coefficients(r)of 34 kinds of ECs was 0.995 9.The limits of detection were 0.01～0.60 ng/L and the recoveries were between 60.7％and 119.8％.The intra-group precisions were between 0.05％～9.89％and the intra-day precisions were between 0.20％～14.40％for the spiked samples.The method was applied to analyze 43 tap water samples and a total of 15 ECs were detected.According to the results,the detection rate of caffeine was the highest(84％),and the concentration range was ND～74.42 ng/L.Among all the ECs detected,1,2,3-benzotriazole had the highest concentration(ND～361.15 ng/L),where detection rate was 44％.Humans may be exposed to these ECs by drinking the tap water.The human health risk assessments of 12 kinds of ECs were carried out,however,the estimated risk was negligible(risk quotient＜0.01).Conclusion The method is simple,highly sensitive and selective,and could meet the detection needs of ECs at trace level in tap water.There was no human health risk posed for ECs identified in 43 tap water samples analyzed by this method.

Objective Metabolomics was used to analyze the changes of metabolites in the plasma of Fenpropathrin-contaminated rats to find potential biomarkers for forensic identification of Fenpropathrin poisoning.Methods SD rats in the two experimental groups were given 20.5 mg/kg and 41 mg/kg doses of fenpropathrin respectively by gavage.The rats in the control group were given equivalent volume of normal saline.The angular vein blood of rats was collected 24 hours after gavage,and endogenous small molecule metabolites in plasma were investigated by ultra-performance liquid chromatography-time-of-flight mass spectrometry(UPLC-TOF-MS).The data was processed by SIMCA14.1.The differential metabolites in plasma of fenpropathrin-infected rats were screened out according to the Variable Importance in Projection(VIP)and p<0.05 in the OPLS-DA model.Finally,the pathways were analyzed.Results There were significant differences in plasma metabolite levels between the control group and the experimental group,and 17 biomarkers were selected to identify whether the rats had received fenpropathrin,which mainly affected purine metabolism,Alanine,aspartate and glutamate metabolism,arginine biosynthesis,biosynthesis of unsaturated fatty acids and pyrimidine metabolism.Conclusion Fenpropathrin can change the composition of metabolites in rats,and the differential markers screened can provide supportive forensic evidence for cases related to deltamethrin poisoning.

Objective Olanzapine has a significant effect in the treatment of mental illness,so its use has been increasing year by year,and poisoning cases have occurred from time to time.Weight gain is a common side effect,and predicting it can be used as a warning to reduce the occurrence of olanzapine poisoning.In this paper,we screened out the differential metabolites between the olanzapine administration rats whose body weight significantly increased and no significantly changed weight.,therefore established an early diagnosis model for predicting olanzapine-induced weight gain in rats.Methods Thirty rats were randomly divided into the control group and olanzapine administration group,which were given continuously gavage with gthe normal saline and olanzapine for 28 days respectively.Blood was taken from the medial canthal vein on the first day after administration,and serum was collected for metabolomics analysis.The olanzapine group was divided into weight gain group and weight unchanged group by comparing with control group.The metabolic group data of the two groups were compared and the differential compounds were screened out between the two groups,Further then an early diagnosis model was established.Results There were 26 differential compounds between the weight gain group and the weight unchanged group after olanzapine administration for 28 days,including 10 lipids,which were involved in the metabolism of α-linolenic acid,the biosynthesis of unsaturated fatty acids,the biosynthesis of primary bile acids,and the synthesis of steroid hormones.Combined with the random forest algorithm,a early diagnosis model was established and the accurate rate was 80％.Conclusion Olanzapine administration would cause changes in the metabolome of rats,mostly concentrated in lipids,and the model based on 26 differential metabolites could be a candidate method for the early forensic determination of olanzapine poisoning.

Objective Based on ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-QTOF-MS/MS),a nontarget screening strategy was adopted in analyzing and identifying emerging pollutants(EPs)in tap water across the country,and studying its spatial and temporal distribution characteristics.Methods After extracting tap water samples by solid phase extraction,mobile phases(0.1%aqueous formic acid and methanol solutions)was used to elute the sample on a C18 chromatographic column.The nontarget screening strategy was used to acquire the MS information in full scan mode.We extracted and analyzed the chromatographic and mass spectral peaks,then searched the spectral library to compare the exact mass numbers,and the secondary MS/MS spectra fragment ion information was compared one by one.Finally,the retention time and the mass spectrum data of candidate EPs were identified and analyzed with the data of standard samples.then quantified by the internal standard method.Results A total of 135 EPs were initially screened from tap water across the country and 24 with high chromatographic peak response were finally selected and verified by standard products,including 6 pharmaceuticals,13 pesticides,3 industrial compounds and 2 food additives.Nine of them showed detection rates of more than 60%,such as canrenone,medroxyprogesterone,hydrocortisone acetate,etc.The concentrations of detected pollutants range from ND 422.63 ng/L.And the four contaminants with higher average concentrations were canrenone,medroxyprogesterone,hydrocortisone acetate and tris(2-butoxyethyl)phosphate.Conclusion In this study,a nontarget strategy based on UPLC-QTOF-MS/MS was adopted to screen potential unknown pollutants with no-standards,and explored the overall contamination status of tap water samples.This contributed to more comprehensive understanding of the EPs distribution,and provided technical support for monitoring the EPs in tap water.

Objective Olanzapine has a significant effect in the treatment of mental illness,so its use has been increasing year by year,and poisoning cases have occurred from time to time.Weight gain is a common side effect,and predicting it can be used as a warning to reduce the occurrence of olanzapine poisoning.In this paper,we screened out the differential metabolites between the olanzapine administration rats whose body weight significantly increased and no significantly changed weight.,therefore established an early diagnosis model for predicting olanzapine-induced weight gain in rats.Methods Thirty rats were randomly divided into the control group and olanzapine administration group,which were given continuously gavage with gthe normal saline and olanzapine for 28 days respectively.Blood was taken from the medial canthal vein on the first day after administration,and serum was collected for metabolomics analysis.The olanzapine group was divided into weight gain group and weight unchanged group by comparing with control group.The metabolic group data of the two groups were compared and the differential compounds were screened out between the two groups,Further then an early diagnosis model was established.Results There were 26 differential compounds between the weight gain group and the weight unchanged group after olanzapine administration for 28 days,including 10 lipids,which were involved in the metabolism of α-linolenic acid,the biosynthesis of unsaturated fatty acids,the biosynthesis of primary bile acids,and the synthesis of steroid hormones.Combined with the random forest algorithm,a early diagnosis model was established and the accurate rate was 80％.Conclusion Olanzapine administration would cause changes in the metabolome of rats,mostly concentrated in lipids,and the model based on 26 differential metabolites could be a candidate method for the early forensic determination of olanzapine poisoning.

Objective Based on ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-QTOF-MS/MS),a nontarget screening strategy was adopted in analyzing and identifying emerging pollutants(EPs)in tap water across the country,and studying its spatial and temporal distribution characteristics.Methods After extracting tap water samples by solid phase extraction,mobile phases(0.1%aqueous formic acid and methanol solutions)was used to elute the sample on a C18 chromatographic column.The nontarget screening strategy was used to acquire the MS information in full scan mode.We extracted and analyzed the chromatographic and mass spectral peaks,then searched the spectral library to compare the exact mass numbers,and the secondary MS/MS spectra fragment ion information was compared one by one.Finally,the retention time and the mass spectrum data of candidate EPs were identified and analyzed with the data of standard samples.then quantified by the internal standard method.Results A total of 135 EPs were initially screened from tap water across the country and 24 with high chromatographic peak response were finally selected and verified by standard products,including 6 pharmaceuticals,13 pesticides,3 industrial compounds and 2 food additives.Nine of them showed detection rates of more than 60%,such as canrenone,medroxyprogesterone,hydrocortisone acetate,etc.The concentrations of detected pollutants range from ND 422.63 ng/L.And the four contaminants with higher average concentrations were canrenone,medroxyprogesterone,hydrocortisone acetate and tris(2-butoxyethyl)phosphate.Conclusion In this study,a nontarget strategy based on UPLC-QTOF-MS/MS was adopted to screen potential unknown pollutants with no-standards,and explored the overall contamination status of tap water samples.This contributed to more comprehensive understanding of the EPs distribution,and provided technical support for monitoring the EPs in tap water.