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.

Bone tissue engineering(BTE)is expected to be used as an autologous bone graft substitute for bone defects,and in the se-lection of BTE scaffold materials,collagen(Col)and hydroxyapatite(HA)have attracted attention due to their unique biomimetic ad-vantages.Collagen/hydroxyapatite(CHA)composite scaffolds made by combining the two have been shown to have excellent biocompat-ibility and bone-enhancing potential in various in vitro,in vivo,and clinical studies.With the development of three-dimensional(3D)printing technology in the field of tissue engineering,bone scaffolds constructed using 3D printing methods have been shown to possess superior clinical potential.This review describes new advances in 3D printed CHA composite scaffolds and introduces the application of 3D printed CHA scaffolds in oral and maxillofacial bone regenerative repair.

Depression,as a severe psychological and psychiatric disorder,significantly impairs the long-term physical and mental health of patients.Current depression detection methods are plagued by strong subjectivity,limited techniques,and inadequate intelligence.Previous studies have mostly relied on single-modal signal analysis,making it difficult to comprehensively reflect the multidimensional characteristics of depression.Based on the independently developed intelligent depression detection system,wearable devices are used to collect prefrontal dual-lead EEG signals,PPG signals,and single-lead ECG signals.Data from 30 patients with depression and 40 healthy controls are collected and analyzed.A multimodal depression recognition model named RBLF-Net is proposed,which integrates spatiotemporal features,weighted attention,and random forests to utilize the multi-signal features for depression recognition.The model exhibits superior performance in the five-fold cross-validation,achieving a classification accuracy of 81.43%,a precision of 81.02%,and a recall rate of 81.25%,outperforming other comparative models,and thus providing an intelligent analysis approach for depression recognition from the perspective of multi-modal fusion.

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 analyze the epidemiological characteristics and immune effects of pertussis in Jiangxi Province from 2020 to 2023 and provide a reference basis for preventing and controlling pertussis in Jiangxi Province.Methods:The annual pertussis incidence data and population data of Jiangxi Province in the same period were derived from the China Disease Prevention and Control Information System, the population data for 2020 were derived from the seventh population census data of Jiangxi Province, and pertussis cases with PV immunization history were derived from the immunization program information system of Jiangxi Province. Descriptive epidemiological methods were used to analyze pertussis epidemic characteristics and PV immunization history in Jiangxi Province from 2020 to 2023. An expert modeler was used to construct the best time series model and perform seasonal decomposition. The chi-square test and Cochran-Armitage trend test were used for statistical analysis. Excel 2013 and SPSS 27.0 software were used for statistical analysis.Results:A total of 886 cases of pertussis were reported in Jiangxi Province from 2020 to 2023, with an average annual reported incidence rate of 0.49/100 000, showing a linear upward trend ( Z=121.80, P<0.001). The Winters' additive model was optimal to fit the monthly data with stable seasonality (Ljung-Box statistic Q=10.56, P=0.78), the average number of reported cases in August was higher than the annual average of 5.12. The top three cities with reported incidence rates were Pingxiang (1.11/100 000), Yichun (1.10/100 000), and Nanchang (0.73/100 000). The highest age composition of cases was in the under 1-year-old group (373 cases,42.10%). Under 1-year-old group, 5-9-years-old group, and ≥10-years-old group all showed an increasing trend in reported incidence year by year (all P<0.001), and the reported incidence rate of under 1-year-old group increased from 12.42/100 000 in 2020 to 48.85/100 000 in 2023. A total of 545 cases (61.51%) had a history of PV immunization. Four doses PV immunization was the main ones (44.92%, 398 cases) and the median ( Q1, Q3) interval from the last vaccination to onset was 4 (1,5) years. Conclusions:The reported incidence of pertussis in Jiangxi Province increased from 2020 to 2023. The cases are mainly concentrated in the under 1-year-old group. The rates of PV vaccination in pertussis cases was low, with more number of vaccine breakthrough infection cases with 4-doses PV vaccination. It has been suggested to continue doing the following: strengthening pertussis surveillance, improving the timeliness of pertussis vaccination, implementing the fifth dose as soon as possible for children over 6-year-old, strengthening the studies of vaccine breakthrough infection case, and optimizing the population immunity strategy of pertussis.

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 explore the influence of value orientation brief therapy (VBT) on anxiety and depression symptoms, social function, coping style and self-acceptance level of major depressive disorder adolescents with anxious distress.Methods:From June 2021 to June 2022, seventy adolescent major depressive disorder patients with anxious distress were included in the study, who were randomly divided into study group(35 people, 31 people completed)and control group (35 people, 30 people completed). The study group was given routine treatment combined with VBT, while the control group was given routine treatment only. Before and after treatment, Hamilton anxiety scale(HAMA), Hamilton depression scale (HAMD), social disability screening schedule (SDSS), coping style questionnaire(CSQ) and self-acceptance questionnaire (SAQ) were used to evaluate the two groups, and SPSS 26.0 software was used to statistically analyze the data of the two groups. Paired sample t-test was used for intra-group comparison, and independent sample t-test was used for inter-group comparison. Results:After 6 weeks of treatment, the scores of HAMA((6.03±3.58) vs (14.03±7.06), t=5.55, P<0.01), HAMD((8.77±5.52 ) vs (16.50±7.59), t=4.56, P<0.01)and SDSS((4.23±1.50) vs (6.63±0.96), t=7.43, P<0.01)in the study group were significantly lower than those in the control group, the differences were statistically significant. The scores of self-acceptance((19.23±1.33) vs (13.47±1.46), t=-16.12, P<0.01)and self-evaluation ((19.87±2.87) vs (12.77±1.68), t=-11.75, P<0.01) in the SAQ scale and the scores of problem-solving((8.71±2.30) vs (6.23±3.45), t=3.31, P<0.05) and rationalization ((6.20±3.11) vs (4.67±2.43), t=2.13, P<0.05) in the CSQ questionnaire were significantly higher than those in the control group, the differences were statistically significant. The total effective rate of the study group(90.3%(28/31) vs 66.7%(20/30), χ2=5.09, P<0.05) was significantly higher than that of the control group, the difference was statistically significant. Conclusion:The effect of routine treatment combined with VBT is better, which can effectively improve anxiety and depression symptoms, social function and coping style, and enhance self-acceptance and self-evaluation in adolescent major depressive disorder patients, which is worthy of clinical application.

Purpose Based on a variety of combinations of cranial MR Dixon images,the deep learning method is used to generate CT images,and the reconstruction efficiency is evaluated by comparing with the corresponding CT images.Materials and Methods A total of 77 cranial CT and MR images were collected retrospectively in Ruijin Hospital,Shanghai Jiaotong University School of Medicine from June to December 2021.The U-Net neural network was used for network training,with 62 cases in the training set and 15 cases in the test set.CT image reconstruction was performed using four kinds of Dixon images and a total of seven models among the various combinations.Mean absolute error,mean squared error,Pearson correlation coefficient and skull area Dice similarity coefficient were used to evaluate the image reconstruction efficiency.Results The generated CT images of the various Dixon image combination models showed strong correlation with the corresponding CT images(R>0.75,P<0.05),and the CT images reconstructed by the four-channel model had the closest value to the actual CT images[mean absolute error=147.516±30.802,mean squared error=(8.648±3.403)×104],the highest correlation coefficient(R=0.796±0.055),and the highest similarity coefficient in the cranial region(Dice similarity coefficient=0.800±0.036).Conclusion Deep learning training through Dixon images can be used to generate CT images,and the combination of four kinds of Dixon contrast images can improve the CT image reconstruction efficiency.