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 investigate the value of intravoxel incoherent motion diffusion-weighted imaging(IVIM-DWI)in predicting the clinical and pathological features of prostate cancer(PCa).Methods We recruited 47 patients who underwent bpMRI combined with IVIM-DWI in our hospital from July 2022 to October 2023 and pathologically confirmed with PCa.Among these cases,20 were transitional zone PCa(TZ-PCa),and 27 were peripheral zone PCa(PZ-PCa).According to the International Society of Urological Pathology(ISUP)risk grades,the patients were divided into high-risk group(ISUP≥3)and low-risk group(ISUP≤2).Differences in the risk levels between TZ-PCa group and PZ-PCa group were compared.Factors including age,total prostate-specific antigen(tPSA),diffusion coefficient(D)value,pseudo diffusion coefficient(D*)value,perfusion fraction(F)value,and apparent diffusion coefficient(ADC)as independent variables were compared between the two groups.Binary logistic regression analysis was further used to identify the factors associated with high or low risk of PCa.Receiver operation characteristic(ROC)curves were plotted to evaluate the diagnostic efficacy of PSA,D value,anatomical zones,and the combined model of PSA+D value+anatomical zones in predicting the risk level of PCa.Results The risk level was higher in PZ-PCa group than in TZ-PCa group(P=0.015).Binary logistic regression analysis showed that the tPSA level in the high-risk group of PCa was higher than that in the low-risk group(OR=1.026,95％CI:1.004-1.049,P=0.014),but the Dmean value was lower than that in the low-risk group(OR=0.993,95％CI:0.987-0.999,P=0.034).PCa in the high-risk group was more distributed in the peripheral zone(OR=5.250,95％CI:1.468-18.772,P=0.023).The diagnostic efficacy of the combined model(AUC=0.887,95％CI:0.787-0.987)was higher than that of tPSA,Dmean,or anatomical partitioning alone(P=0.001,0.043,and 0.003,respectively).Conclusion PZ-PCa has a higher risk level than TZ-PCa.Combining bpMRI localization of anatomical zones with PSA and D value provides the highest efficacy in predicting the risk level of PCa,which can potentially support the development of precise and personalized clinical diagnosis and treatment strategies for PCa.

Objective To investigate the value of intravoxel incoherent motion diffusion-weighted imaging(IVIM-DWI)in predicting the clinical and pathological features of prostate cancer(PCa).Methods We recruited 47 patients who underwent bpMRI combined with IVIM-DWI in our hospital from July 2022 to October 2023 and pathologically confirmed with PCa.Among these cases,20 were transitional zone PCa(TZ-PCa),and 27 were peripheral zone PCa(PZ-PCa).According to the International Society of Urological Pathology(ISUP)risk grades,the patients were divided into high-risk group(ISUP≥3)and low-risk group(ISUP≤2).Differences in the risk levels between TZ-PCa group and PZ-PCa group were compared.Factors including age,total prostate-specific antigen(tPSA),diffusion coefficient(D)value,pseudo diffusion coefficient(D*)value,perfusion fraction(F)value,and apparent diffusion coefficient(ADC)as independent variables were compared between the two groups.Binary logistic regression analysis was further used to identify the factors associated with high or low risk of PCa.Receiver operation characteristic(ROC)curves were plotted to evaluate the diagnostic efficacy of PSA,D value,anatomical zones,and the combined model of PSA+D value+anatomical zones in predicting the risk level of PCa.Results The risk level was higher in PZ-PCa group than in TZ-PCa group(P=0.015).Binary logistic regression analysis showed that the tPSA level in the high-risk group of PCa was higher than that in the low-risk group(OR=1.026,95％CI:1.004-1.049,P=0.014),but the Dmean value was lower than that in the low-risk group(OR=0.993,95％CI:0.987-0.999,P=0.034).PCa in the high-risk group was more distributed in the peripheral zone(OR=5.250,95％CI:1.468-18.772,P=0.023).The diagnostic efficacy of the combined model(AUC=0.887,95％CI:0.787-0.987)was higher than that of tPSA,Dmean,or anatomical partitioning alone(P=0.001,0.043,and 0.003,respectively).Conclusion PZ-PCa has a higher risk level than TZ-PCa.Combining bpMRI localization of anatomical zones with PSA and D value provides the highest efficacy in predicting the risk level of PCa,which can potentially support the development of precise and personalized clinical diagnosis and treatment strategies for PCa.

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 To establish an analytical method of LC-MS/MS based on micro-segmentation analysis of multiple hairs,verify the detection of 20 benzodiazepines in 1mm hair,and finally use it for case detection analysis.Methods 5 hairs were cut into 1mm long segments each,and the corresponding segments were immersed and sonicated in an extract containing dithiothreitol,methanol,etc.Mobile phase A was 0.1%formic acid in water,and mobile phase B was acetonitrile.Data were collected using electrospray ion source positive ion mode in multiple reaction monitoring mode.Results The 20 benzodiazepines in multiple hairs had a good linear relationship(r>0.99),detection limit of 0.2～5 pg/mm,minimum quantification limit of 0.5 to 20 pg/mm,the intro-day and inter-day precisions of 2.03%to 13.81%,the intro-day and inter-day accuracies of 87.98%～111.29%,matrix effect of 71.15%～110.43%,and extraction recovery of 69.34%to 99.94%.Using this method,hair samples were analyzed in volunteers taking a single dose of clonazepam for 20 days,and the detected location of clonazepam in 15 hairs was located in segment 6～11 from the hair root,with the concentration range of 1.06～3.45 pg/mm.By this method,the hair of the victims suspected of having taken sleeping pills in the case was analyzed.In 15 hairs,clonazepam was detected in segments 9～13 of the hair root.The quantitative results were 1.07～19.06 pg/mm.The experimental results were basically consistent with the medication time of the victim.Conclusion The micro-segmentation analysis technique of multiple hairs can be applied to the investigation of drug-assisted crime cases,and can roughly estimate the medication time.

Objective To establish an ultra-high performance liquid chromatography(UPLC)fingerprint and multi-index content determination method of Siraitiae fructus standard decoction.Methods 15 batches of Siraitiae fructus from different producing areas were collected,Siraitiae fructus standard decoction was prepared according to Technical Requirements for Quality Control and Standardization of Traditional Chinese Medicine Formula Granules,and the extract rate was calculated.UPLC was used to establish the fingerprint of 15 batches of Siraitiae fructus standard decoction and determine the contents of 11-O-mogroside V,kaempferitrin and mogroside V,which were the main effective components.The chemometrics analysis was used to evaluate the quality of Siraitiae fructus standard decoction and find possible quality markers.Results The extraction rate of 15 batches Siraitiae fructus standard decoction ranged from 24.79％to 34.95％.There were 16 common peaks in the fingerprint,and 4 components were identified.The Siraitiae fructus standard decoction was divided into 2 categories by chemometrics analysis,among which samples from Liuzhou,Guangxi were in one category and samples from Guilin,Guangxi were in another category.Seven differential markers were screened out under the condition of variable importance projection value,and the order was as follows:peak 8＞peak 7＞peak 5＞peak 12(kaempferitrin)＞peak 1＞peak 13＞peak 4.The contents of kaempferitrin,11-O-mogroside V and mogroside V in samples from Guilin,Guangxi were slightly higher than those in samples from Liuzhou,Guangxi.Conclusion The UPLC fingerprint and content determination method established in this study are feasible,which can provide a basis for the quality evaluation of Siraitiae fructus.The results of principal component analysis show that kaempferol is likely to become a quality marker of Siraitiae fructus.