Sepsis remains a challenge in critical care worldwide，with intestinal microbiome dysbiosis implicated in its onset，progression，and organ dysfunction. Germ-free （GF） and human microbiota-colonized animals，by eliminating confounding from resident microbiota and combining induction methods such as CLP/LPS/live-bacterial challenge with fecal microbiota transplantation （FMT） and mono- or combined colonization，enable causal tests and dissection of microbiota-host interactions and drug mechanisms. This review summarizes the application of GF and related models in sepsis research. At the immune level，TLR-related signaling and pathogen community-induced suppression of IRF3-dependent defense affect innate immunity and pathogen clearance. At the barrier level，reprogramming of tight junction proteins and increased permeability drive gut-derived amplification. At the metabolic level，short-chain fatty acids and bile acids function as metabolic valves influencing GPR/HDAC signaling. At the epigenetic level，EZH2 and histone deacetylation emerge as druggable targets. We further synthesize anti-sepsis evidence for traditional Chinese medicine （TCM），mainly from conventional animals and clinical studies，discussing how formulae （e.g.，Xuebijing，Shenfu，and Huanglian Jiedu Tang） and active constituents （e.g.，berberine，luteolin，ginsenosides，and resveratrol） may act through microbiota-related and direct host pathways，with FMT/metabolite replenishment enabling further causal testing. Finally，we propose a closed-loop GF-humanized-clinical stratification paradigm for integrated evaluation of microecology，epigenetics，immunity，and organ outcomes，providing a translational path for precision prevention and treatment based on TCM and the microbiome.

OBJECTIVE To construct a classification prediction model for vancomycin blood concentration， and to optimize its precision dosing strategies. METHODS Patient records meeting inclusion criteria were extracted from the Medical Information Mart for Intensive Care database. Following data cleaning and preprocessing， a final cohort of 9 902 patient was analyzed. Feature selection was performed through correlation analysis and the Boruta feature selection algorithm. Vancomycin blood concentrations were discretized into three categories based on clinical therapeutic windows： low （＜10 μg/mL）， intermediate （10-20 μg/mL）， and high （≥20 μg/mL）. Six machine learning algorithms were employed to construct classification models： tabular prior-data fitted network （TabPFN）， logistic regression （LR）， random forest （RF）， extreme gradient boosting （XGBoost）， support vector machine （SVM）， K-nearest neighbors （KNN）. Model performance was evaluated using 10-fold cross-validation （10-CV）， with primary metrics including： accuracy， balanced accuracy， precision macro， recall macro， macro F1， area under the receiver operating characteristic curve （OvR-AUC）. Shapley Additive Explanations （SHAP） was adopted to analyze the direction and magnitude of the impact that different features had on the model’s predictive outcomes. RESULTS The results showed that the RF and TabPFN models performed the best （with accuracy of 0.741 4 and 0.737 7， and OvR-AUC of 0.907 0 and 0.895 8， respectively）. XGBoost model exhibited moderate performance， while LR， SVM， and KNN models demonstrated relatively poor performance. Confusion matrix heatmap analysis revealed that both RF and TabPFN achieved higher accuracy in predicting high- concentration cases but exhibited slightly lower performance in the low and medium concentration categories. Bootstrap with 10-CV revealed that the RF model demonstrated stable performance across various evaluation metrics （accuracy： 0.741 4； balanced accuracy： 0.740 3； precision macro： 0.732 1； recall macro： 0.736 0； macro F1： 0.736 0； OvR-AUC： 0.907 0）， indicating good classification performance and generalization ability. SHAP analysis revealed that creatinine， urea nitrogen， daily cumulative dose and administration frequency of vancomycin， which were key predictors， had a significant impact on the prediction results. CONCLUSIONS RF and TabPFN models demonstrate certain advantages in the classification prediction of vancomycin trough blood concentrations； however， their performance in the low to moderate concentration categories still requires improvement.

Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

OBJECTIVE To investigate the distribution and drug resistance of pathogens isolated from the children with bloodstream infection in pediatric intensive care unit(PICU)so as to provide guidance for empirical clinical treatment of infections.METHODS Based on the Pediatric Intensive Care Database(PIC,http://pic.nbscn.org),the etiological data were collected from the PICU children of Children's Hospital,Zhejiang University School of Medicine by R software in 2010-2019 and were retrospectively analyzed.The species,distribution and drug resist-ance of the pathogens isolated from the children were observed.RESULTS Totally 991 strains of pathogens were isolated,727(73.36％)of which were gram-positive bacteria,213(21.49％)were gram-negative bacteria,and 51(5.15％)were fungi.Staphylococcus epidermidis(320 strains,32.29％)was the predominant species of the gram-positive bacteria,followed by Staphylococcus hominis(118 strains,11.91％),Staphylococcus capitis(55 strains,5.55％)and Enterococcus faecium(Group D,33 strains,3.33％);Klebsiella pneumoniae(59 strains,5.95％),Escherichia coli(58 strains,5.85％),Acinetobacter baumannii(25 strains,2.52％)and Pseudo-monas aeruginosa(18 strains,1.82％)were the major species of gram-negative bacteria.The analysis of drug re-sistance showed that the gram-positive bacteria were generally resistant to β lactams and maintained sensitive to vancomycin and linezolid;the gram-negative bacteria showed high drug resistance rates,especially,A.baumannii and P.aeruginosa,showed multi-drug resistance.CONCLUSIONS The gram-positive bacteria are dominant among the pathogens isolated from the PICU children with bloodstream infections.The empirical treatment should be performed based on the distribution and drug resistance data of the pathogens,and sensitive drugs should be cho-sen for optimization of the treatment regimen.

OBJECTIVE To investigate the distribution and drug resistance of pathogens isolated from the children with bloodstream infection in pediatric intensive care unit(PICU)so as to provide guidance for empirical clinical treatment of infections.METHODS Based on the Pediatric Intensive Care Database(PIC,http://pic.nbscn.org),the etiological data were collected from the PICU children of Children's Hospital,Zhejiang University School of Medicine by R software in 2010-2019 and were retrospectively analyzed.The species,distribution and drug resist-ance of the pathogens isolated from the children were observed.RESULTS Totally 991 strains of pathogens were isolated,727(73.36％)of which were gram-positive bacteria,213(21.49％)were gram-negative bacteria,and 51(5.15％)were fungi.Staphylococcus epidermidis(320 strains,32.29％)was the predominant species of the gram-positive bacteria,followed by Staphylococcus hominis(118 strains,11.91％),Staphylococcus capitis(55 strains,5.55％)and Enterococcus faecium(Group D,33 strains,3.33％);Klebsiella pneumoniae(59 strains,5.95％),Escherichia coli(58 strains,5.85％),Acinetobacter baumannii(25 strains,2.52％)and Pseudo-monas aeruginosa(18 strains,1.82％)were the major species of gram-negative bacteria.The analysis of drug re-sistance showed that the gram-positive bacteria were generally resistant to β lactams and maintained sensitive to vancomycin and linezolid;the gram-negative bacteria showed high drug resistance rates,especially,A.baumannii and P.aeruginosa,showed multi-drug resistance.CONCLUSIONS The gram-positive bacteria are dominant among the pathogens isolated from the PICU children with bloodstream infections.The empirical treatment should be performed based on the distribution and drug resistance data of the pathogens,and sensitive drugs should be cho-sen for optimization of the treatment regimen.

Objective To establish biparameter MRI stepwiese discriminant models based on T2WI and diffusion-weighted imaging(DWI),and to observe their value for detecting clinically significant prostate cancer(CSPCa)in transitional zone.Methods Totally 224 patients with pathologically confirmed prostatic transitional zone lesions were retrospectively collected and divided into CSPCa group(n=81)and non-CSPCa group(n=143)according to pathological results and Gleason scores.Single factor and stepwise discriminant analysis were used to analyze T2WI and DWI manifestations of lesions in both groups,so as to screen the independent impact factors for distinguishing CSPCa from non-CSPCa.Discriminant functions models for CSPCa and non-CSPCa were established,respectively,and the diagnostic efficiency of models were verified using cross-verification method,while correct discriminant rate≥80％was considered as having differential diagnostic value.Results The maximum diameter,boundary,DWI signal of lesions,prostate capsule being complete or not,as well as the minimum apparent diffusion coefficient were all independent impact factors for distinguishing CSPCa from non-CSPCa,and the discriminant function models for CSPCa and non-CSPCa were established based on the above factors,respectively,with correct discrimination rates of discriminant function model for CSPCa and non-CSPCa of 90.11％and 88.81％,respectively,and the overall correct discrimination rate of 89.31％.Conclusion Biparameter MRI stepwise discriminant models could be used to detect CSPCa in transitional zone.

Objective To establish biparameter MRI stepwiese discriminant models based on T2WI and diffusion-weighted imaging(DWI),and to observe their value for detecting clinically significant prostate cancer(CSPCa)in transitional zone.Methods Totally 224 patients with pathologically confirmed prostatic transitional zone lesions were retrospectively collected and divided into CSPCa group(n=81)and non-CSPCa group(n=143)according to pathological results and Gleason scores.Single factor and stepwise discriminant analysis were used to analyze T2WI and DWI manifestations of lesions in both groups,so as to screen the independent impact factors for distinguishing CSPCa from non-CSPCa.Discriminant functions models for CSPCa and non-CSPCa were established,respectively,and the diagnostic efficiency of models were verified using cross-verification method,while correct discriminant rate≥80％was considered as having differential diagnostic value.Results The maximum diameter,boundary,DWI signal of lesions,prostate capsule being complete or not,as well as the minimum apparent diffusion coefficient were all independent impact factors for distinguishing CSPCa from non-CSPCa,and the discriminant function models for CSPCa and non-CSPCa were established based on the above factors,respectively,with correct discrimination rates of discriminant function model for CSPCa and non-CSPCa of 90.11％and 88.81％,respectively,and the overall correct discrimination rate of 89.31％.Conclusion Biparameter MRI stepwise discriminant models could be used to detect CSPCa in transitional zone.

Patients with acute heart failure (AHF) often experience dyspnea, and monitoring and quantifying their breathing patterns can provide reference information for disease and prognosis assessment. In this study, 39 AHF patients and 24 healthy subjects were included. Nighttime chest-abdominal respiratory signals were collected using wearable devices, and the differences in nocturnal breathing patterns between the two groups were quantitatively analyzed. Compared with the healthy group, the AHF group showed a higher mean breathing rate (BR_mean) [(21.03 ± 3.84) beat/min vs. (15.95 ± 3.08) beat/min, P < 0.001], and larger R_RSBI_cv [70.96% (54.34%-104.28)% vs. 58.48% (45.34%-65.95)%, P = 0.005], greater AB_ratio_cv [(22.52 ± 7.14)% vs. (17.10 ± 6.83)%, P = 0.004], and smaller SampEn (0.67 ± 0.37 vs. 1.01 ± 0.29, P < 0.001). Additionally, the mean inspiratory time (TI_mean) and expiration time (TE_mean) were shorter, TI_cv and TE_cv were greater. Furthermore, the LBI_cv was greater, while SD1 and SD2 on the Poincare plot were larger in the AHF group, all of which showed statistically significant differences. Logistic regression calibration revealed that the TI_mean reduction was a risk factor for AHF. The BR_ mean demonstrated the strongest ability to distinguish between the two groups, with an area under the curve (AUC) of 0.846. Parameters such as breathing period, amplitude, coordination, and nonlinear parameters effectively quantify abnormal breathing patterns in AHF patients. Specifically, the reduction in TI_mean serves as a risk factor for AHF, while the BR_mean distinguishes between the two groups. These findings have the potential to provide new information for the assessment of AHF patients.
Humans ; Heart Failure/diagnosis* ; Prognosis ; Respiration ; Wearable Electronic Devices ; Acute Disease

【Objective】 To evaluate the efficacy and safety of plasma-derived human coagulation factor Ⅷ (FⅧ) in the treatment of patients with hemophilia A. 【Methods】 A multi-center and open, SAT(single-arm trials) clinical study was conducted. A total of 54 subjects with hemophilia A were enrolled in 5 research centers. FⅧ was injected according to the subjects' weight, severity of disease and other factors, and the transfusion efficiency of FⅧ activity at 10 min after the first infusion of the first bleeding event was taken as the main efficacy indexes. The improvement scores of bleeding symptoms and signs within 24 h after the first infusion of the first bleeding event were the secondary efficacy indexes. The pathogenic microbial indexes and FⅧ inhibitors were detected on 90(th) and 180(th) day after treatment. 【Results】 The transfusion efficiency of FⅧ activity of 54 subjects at 10 min after the first infusion was 171.9% on average, with median of 169.5%, both higher than the target value of 100%. Within 24 h after the first infusion, the improvement of bleeding symptoms and signs of the subjects were scored, among which 19 cases (35.2%) were "obvious", 35 cases (64.8%) were "good", and the total clinical effective rate reached 100%. Five subjects (9.3%) had six drug-related adverse events. On 90(th) and 180(th) day after treatment, hepatitis B surface antigen, hepatitis C antibody, HIV antibody, treponema pallidum antibody and FⅧ inhibitors were detected, and no negative to positive cases were found. 【Conclusion】 After infusion, the FⅧ preparation can significantly improve the FⅧ activity level in hemophilia A patients in a short period of time, which has high infusion efficiency and can achieve better treatment efficacy, and can also effectively control and relieve bleeding symptoms and signs, with good overall safety.

Objective To investigate the clinical effect of No ha la hu(Mongolian medicine abdominal massage)combined with Ni ru ha(Mongolian medicine enema)in the treatment of incomplete intestinal obstruction.Methods A total of 80 patients with incomplete intestinal obstruction admitted to the department of emergency and critical care medicine of Inner Mongolia International Mongolian Hospital from April 2020 to April 2022 were selected as the study objects,they were randomly divided into control group and observation group,40 cases in each group.The control group was treated with routine modern medicine,and the observation group was treated with mongolian medicine No ha la hu combined with Ni ru ha on the basis of routine treatment.Specific methods:the patient supine position,both lower limbs flexion,natural calm breathing,the doctor stands on the patient's right side,applies a little butter to the palm of his hand,rub hands,massages the abdomen with the middle finger and ring finger at acupoints such as ileocecal point,small intestine point,small intestine point,small intestine point and lower clockwise direction point.Massage the abdomen with the palm for about 20 minutes,once a day for 3 days.No ha la hu was given after the treatment of Ni ru ha(Rhubarb 250 g,Cold water stone 150 g,Sanai 100 g,Facial alkali 100 g,Hyacinth 50 g,Terminalia chebula 50 g),the patients should lie on the left side,raise the buttocks about 10 cm,insert the enema into the rectum 15-20 cm,take the Mongolian medicine Liuweian powder 12 g and warm water 50-100 mL for enema,once a day for 3 days.The difference of relieving time of abdominal pain and distension,time of exhaustion,time of fasting,and time of hospital stay between the two groups were compared,and the clinical effect was observed.Results Relieving time of abdominal pain,abdominal distension,time of exhaust and time of hospital stay in the observation group were significantly shorter than those in the control group[abdominal pain relief time(hours):5.3±1.8 vs.8.1±1.6,abdominal distension relief time(hours):3.2±1.5 vs.6.5±1.9,time of exhaust(days):2.6±1.7 vs.4.1±2.1,hospital stay(days):8.3±2.9 vs.10.1±2.1,all P<0.05],time of fasting in the observation group were shorter than those in the control group(days:2.9±0.5 vs.3.1±0.6,the difference was not statistically significant(all P>0.05).The effective rate of the observation group was significantly higher than that of the control group[92.5％(37/40)vs.75.0％(30/40),P<0.05].Conclusion On the basis of routine treatment of western medicine,the treatment of incomplete intestinal obstruction by Mongolian medicine No ha la hu combined with Ni ru ha is more effective,which can effectively restore gastrointestinal function,relieve abdominal pain and other symptoms,and shorten the time of exhaust.