ObjectiveTo investigate the mechanisms by which the combination of berberine （BBR） and baicalin （BAI） ameliorates type 2 diabetes mellitus （T2DM） due to internal accumulation of dampness-heat from the perspectives of gut microbiota and metabolomics. MethodsAntibiotics were used to induce pseudo-sterile mice. Thirty pseudo-sterile mice were randomized into a normal fecal microbiota transplantation group （n=10） and a T2DM （syndrome of internal accumulation of dampness-heat） fecal microbiota transplantation group （n=20）. The mice were then administrated with suspensions of fecal microbiota from healthy volunteers and a patient with T2DM due to internal accumulation of dampness-heat by gavage， respectively. Each mouse received 200 µL suspension every other day for a total of 15 times to reshape the gut microbiota. The T2DM model mice were then assigned into a model group （n=8） and a BBR-BAI group （n=11）. BBR was administrated at a dose of 200 mg·kg^-1， and BAI was administrated in a ratio of BBR-BAI 10∶1 based on preliminary research findings. The administration lasted for 8 consecutive weeks. Fasting blood glucose （FBG）， glycated hemoglobin （HbA1c）， insulin （INS）， triglycerides （TG）， total cholesterol （CHOL）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， and alanine aminotransferase （ALT） levels were measured to evaluate the effects of the BBR-BAI combination on glucose and lipid metabolism and liver function in T2DM mice. Hematoxylin-eosin staining was employed to observe pathological changes in the colon tissue. The expression of claudin-1， zonula occludens-1 （ZO-1）， and occludin in the colon tissue was determined by Western blot. Real-time quantitative polymerase chain reaction（Real-time PCR） was employed to assess the levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in the colon tissue. The fecal microbiota composition and differential metabolites were analyzed by 16S rRNA sequencing and ultra-high performance liquid chromatography-quadrupole-time of flight tandem mass spectrometry （UPLC-Q-TOF-MS）， respectively. ResultsThe BBR-BAI combination lowered the FBG， HbA1c， and INS levels （P<0.05， P<0.01） and alleviated insulin resistance （P<0.01） in T2DM mice. Additionally， BBR-BAI elevated the levels of ZO-1， occludin， and claudin-1 （P<0.05， P<0.01） and down-regulated the expression levels of TNF-α， IL-1β， and IL-6 in the colon （P<0.05， P<0.01）. The results of 16S rRNA sequencing showed that BBR-BAI increased the relative abundance of Ligilactobacillus， Phascolarctobacterium， and Akkermansia （P<0.05）， while significantly decreasing the relative abundance of Alistipes， Odoribacter， and Colidextribacter （P<0.05）. UPLC-Q-TOF-MS identified 28 differential metabolites， which were primarily involved in arachidonic acid metabolism and α-linolenic acid metabolism. ConclusionBBR-BAI can ameliorate T2DM due to internal accumulation of dampness-heat by modulating the relative abundance of various bacterial genera in the gut microbiota and the expression of fecal metabolites.

ObjectiveTo explore the mechanism of action of Wendantang on ApoE^-/- hyperlipidemic mice using non-targeted metabolomics technology. MethodsMale C57BL/6J mice served as the normal control group （n=6）， and they were fed with regular chow， while male ApoE^-/- mice constituted the high-fat group （n=30）， and they were fed with a 60% high-fat diet. After 11 weeks of model establishment， the mice in the high-fat group were randomly divided into the model group， simvastatin group （3.3 mg·kg^-1）， and high-dose， medium-dose， and low-dose groups of Wendantang （26， 13， 6.5 g·kg^-1， respectively， in terms of crude drug amount）， with six mice in each group. The normal control group and the model group were gavaged with an equivalent volume of normal saline， and all groups continued to be fed their respective diets， receiving daily medication for 10 weeks with weekly body weight measurements. Serum levels of total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， free fatty acids （NEFA）， blood glucose （GLU）， alanine aminotransferase （ALT）， and aspartate aminotransferase （AST） were detected in the mice. Pathological changes in liver tissue were observed using hematoxylin-eosin （HE） staining， and ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF-MS/MS） was employed for metabolomic analysis of mouse liver tissue. ResultsCompared to the normal control group， the model group exhibited significantly increased body weight， blood lipid levels， and liver function （P<0.05， P<0.01）， with disordered liver tissue structure， swollen hepatocytes， and accompanying vacuolar fatty degeneration and inflammatory cell infiltration. Compared to the model group， the simvastatin group and Wendantang groups showed significantly reduced body weight， TG， NEFA， GLU， ALT， and AST levels （P<0.05， P<0.01）， with a significant increase in HDL-C levels （P<0.05， P<0.01）， demonstrating a dose-dependent effect. The lesion of the liver tissue section was obviously improved after administration， tending towards a normal liver tissue morphology. Analysis of liver metabolites revealed 86 differential metabolites between the normal control group and the model group， with the high-dose group of Wendantang able to regulate 56 of these metabolites. Twenty-two differential metabolites associated with hyperlipidemia were identified， mainly including chenodeoxycholic acid， hyocholic acid， taurine， glycocholic acid， dihydroceramide， hydroxy sphingomyelin C14∶1， arachidonic acid， and linoleic acid， enriching 22 metabolic pathways， with 4 being the most significant （P<0.05）， namely primary bile acid biosynthesis， sphingolipid metabolism， unsaturated fatty acid biosynthesis， and linoleic acid metabolism pathways. ConclusionWendantang can improve blood lipid levels and liver function in ApoE^-/- hyperlipidemic mice， which may be related to the regulation of primary bile acid biosynthesis， sphingolipid metabolism， unsaturated fatty acid biosynthesis， and linoleic acid metabolism pathways.

Objective To analyze changes in intestinal microbiota composition and metabolites in mice with nitrous oxide poisoning using 16S rDNA sequencing and metabolomics,and to examine correlations between gut microbes and metabolites in order to explore the mechanisms of nitrous oxide poisoning.Methods C57BL/6 mice were randomly divided into a control group and a nitrous oxide poisoning group(n=6).The poisoning group was exposed to 90,000 ppm nitrous oxide twice daily for 1 h over 28 days,while the control group was exposed to air.Fecal samples were collected 24 h after the last exposure.16S rDNA sequencing was used to analyze structural differences in microbial communities and identify significantly different taxa.Metabolomics analysis was performed to detect changes in fecal metabolites and identify differential metabolites.Correlation analysis was conducted between differential microbiota and metabolites.Results 16S rDNA sequencing showed that the poisoning group had increased microbial abundance compared with controls,while species diversity remained unchanged.Significant differences were observed in gut microbiota structure between groups.Metabolomics identified 112 differential metabolites related to nitrous oxide poisoning,mainly involving the cAMP signaling pathway and sphingolipid metabolism.Spearman correlation analysis revealed a strong association between differential microbiota and differential metabolites.Conclusion Nitrous oxide poisoning alters the structure and metabolic profiles of intestinal microbiota.Changes in microbial abundance affect multiple metabolic pathways,which may be related to damage to the nervous and hematological systems.These findings provide a basis for further research on the mechanisms of nitrous oxide poisoning and for clinical treatment.

Objective Piperazine derivatives are a group of emerging psychoactive substances with excitatory and hallucinogenic effects on the central nervous system.This study established a high-performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)screening method for the detection of 40 piperazine compounds in urine.Methods A 200 μL urine sample(spiked with an internal standard at 1 ng/mL)was subjected to liquid-liquid extraction with ethyl acetate.After nitrogen evaporation,the residue was redissolved in 200 μL methanol and injected for analysis.Separation was performed on a Waters Acquity UPLC? HSS T3 column(100 mm × 2.1 mm,1.8 μm).The mobile phase consisted of(A)20 mmol/L ammonium acetate buffer containing 0.1％formic acid and 5％acetonitrile,and(B)acetonitrile.Gradient elution was applied,and detection was carried out in multiple reaction monitoring(MRM)mode.Quantification was achieved using an internal standard calibration curve.Results The 40 piperazine substances demonstrated good linearity within the range of 1-50 ng/mL,with correlation coefficients of 0.995-0.998.The extraction recovery ranged from 51.51％to 104.1％.Intra-day precision was below 5％,while inter-day precision ranged from 1.61％to 10.17％.Accuracy was between-7.84％and 8.77％.The limits of detection were 0.2-1 ng/mL,and the limit of quantification was 1 ng/mL.Conclusion The proposed method requires only a small sample volume,exhibits high sensitivity,selectivity,and stability,and offers short run times.It is suitable for the qualitative and quantitative determination of piperazine derivatives in urine in forensic toxicology practice.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

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 gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.