Objective: We aimed to explore the mechanism of Pizhan Powder in regulating the Wnt4/β-catenin signaling pathway to promote wound healing in mice with chronic skin ulcer. Methods: Male BALB/c mice were divided into blank, model, Pizhan Powder, Pizhan powder removed bark medications, bark medications, inhibitor, and Pizhan Powder + inhibitor groups using the random number table method, with six mice per group. Except for the blank group, chronic skin ulcer wound models were prepared in the other groups by implanting foreign bodies. The blank control group received no treatment, whereas the wounds of the model group were cleaned with furacilin solution. The Pizhan Powder, Pizhan Powder removed bark medications, and bark medications groups were each administered 0.1 g of the corresponding medication on the skin wounds. The inhibitor group received an intraperitoneal injection of 3-(4-methylphenylsulfonamido) benzoic acid methyl ester (MSAB) at a dosage of 10 mg/kg. The Pizhan Powder + inhibitor group was administered 0.1 g of Pizhan Powder on the skin wound, and an intraperitoneal injection of MSAB was also administered (10 mg/kg). These treatments were administered once a day for 14 consecutive days. Wound healing was observed on the first, third, seventh, and 14th day of treatment; hematoxylin and eosin staining was used to observe the pathological changes of ulcerated skin; keratin 10 (CK10), keratin 14 (CK14), cell proliferation nuclear antigen (Ki-67), α-smooth muscle actin (α-SMA), and β-catenin expression in wounds was observed through immunofluorescence; Western blotting was used to detect the expression of signaling pathway-related proteins (Wnt4 and β-catenin). Results: Compared to the model group, the Pizhan Powder group showed a reduced wound area and an increased wound healing rate (P<0.05) and elevated CK10, CK14, Ki-67, α-SMA, β-catenin, and Wnt4 protein expressions (P<0.05). Compared to the Pizhan Powder group, the wound healing rate of the bark medications and Pizhan Powder removed bark medications groups was reduced (P<0.05). The wound healing rate and the fluorescence expression of CK10, CK14, Ki-67, and α-SMA in the Pizhan Powder removed bark medications group were lower than that in the bark medications group (P<0.05). Compared to the Pizhan Powder group, the wound healing rate of the Pizhan Powder + inhibitor group was reduced, and CK10, CK14, Ki-67, α-SMA, β-catenin and Wnt4 protein expression were lower (P<0.05). Conclusion Pizhan Powder promotes wound healing in chronic skin ulcers of mice by regulating the Wnt4/β-catenin signaling pathway. The bark medications (buffalo hide, white mulberry root-bark, and Chinese wolfberry root-bark) play a crucial role, representing a concrete application of the traditional Chinese medicine theory of " treating skin with skin.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective To analyze the incidence of venous thromboembolism(VTE)in pulmonary patients and explore the assessment and prevention of the risk of pneumonia accompanied VTE.Methods The patients with pneumonia were divided into control group(simple pneumonia)and treatment group(with VTE)according to the condition of VTE.Demographic data,blood routine,coagulation index,liver and kidney function index and blood gas index were collected.Statistical methods like chi square test,t-test and nonparametric rank sum test were applied to compare the differences between the two groups.Finally,the nomogram was established according to the logistic regression results and the receiver operating characteristic(ROC)curve was calculated.Results 106 cases in control group and 29 cases in treatment group.Univariate analysis showed that age,D-dimer,fibrinogen degradation products,white blood cell count,neutrophil count,albumin-globulin ratio were statistically significant(P＜0.05).Multivariate logistic regression analysis suggests that age[odds ratio(OR)=1.052],D-dimer(OR=2.339),and albumin/globulin(OR=0.042)are independent affecting factors for VTE in pneumonia patients.A nomogram was developed and ROC was calculated,the area under curve(AUC)was 0.754.Conclusion High age,elevated D-dimer and decreased albumin/globulin are independent risk factors for VTE in pneumonia patients.More over,the established prediction model has good accuracy.

Metabolic associated fatty liver disease (MAFLD) has become a prevalent chronic liver disease worldwide because of lifestyle and dietary changes. Gut microbiota and its metabolites have been shown to play a critical role in the pathogenesis of MAFLD. Understanding of the function of gut microbiota and its metabolites in MAFLD may help to elucidate pathological mechanisms, identify diagnostic markers, and develop drugs or probiotics for the treatment of MAFLD. Here we review the pathogenesis of MAFLD by gut microbiota and its metabolites and discuss the feasibility of treating MAFLD from the perspective of gut microbes.
Gastrointestinal Microbiome ; Fatty Liver/microbiology* ; Humans

Objective:To retrieve and summarize the evidence of indications for extubation in neurosurgical tracheotomy patients, so as to provide reference for promoting timely and safe extubation of neurosurgical tracheotomy patients.Methods:Evidence-based problems were identified according to the population, intervention, professional, outcome, setting, type of evidence (PIPOST) model. According to the "6S" classification model of the evidence-based retrieval database, all evidences of extubation indications of neurosurgical tracheotomy patients in the database, guideline website and professional institution website were systematically retrieved, including clinical guidelines, systematic review, expert consensus, evidence summary and clinical decision-making. The search period was from the establishment of the database to May 31, 2022. Two researchers independently evaluated the quality of the included article and extracted evidence.Results:A total of 12 articles were included, including four guidelines, four systematic reviews, two expert consensuses, one evidence summary, and one clinical decision-making. A total of 18 pieces of best evidence for extubation indications of neurosurgical tracheotomy patients were summarized, including 7 themes: disease condition, consciousness and autonomous activity, respiratory function, cough function, swallowing function, airway condition, multidisciplinary team and equipment support.Conclusions:The extubation of neurosurgical tracheotomy patients should consider many factors. The summary of evidence has a certain degree of scientific and practical significance, which can provide evidence-based basis for medical and nursing staff to apply evidence in a targeted manner.

Orally inhaled drug products (OIDPs) play a great role in the pharmacological treatment of chronic obstructive pulmonary disease (COPD) and asthma. There is an unmet clinical need for OIDPs. Pharmacodynamics-Bioequivalence studies (PD-BE) are recommended by several national guidelines as important research methods for bioequivalence study of OIDPs. It can effectively bridge the gap between in vitro studies and PK-BE studies in evaluating the efficacy and safety consistency of generic drugs with the original drugs. There are two research methods for PD-BE, using a diastolic model or an excitation model. The different methods use different metrics to evaluate efficacy. The more commonly used metrics include Forced Expiratory Volume in the First Second (FEV1), Specific Airway Conductance (sGaw), Peripheral Airway Resistance (R5-20), and stimulant concentration/dose (PC20/PD20). PD-BE studies using FEV1 as an efficacy metric is also recommended by the FDA (Food and Drug Administration), EMA (European Medicines Agency) and NMPA (National Medical Products Administration) guidelines and is widely accepted by investigators. In such PD-BE studies, the trial protocols for different OIDPs drugs are relatively consistent in terms of trial design, trial data processing, and equivalence evaluation criteria, while there are detailed differences in terms of target population, single/multiple dosing, dose administration, and collection site design. This paper reviews the progress of PD-BE studies in the bioequivalence evaluation of OIDPs by combining national guidelines and PD-BE-related studies of OIDPs published in the last five years, with a view to providing important theoretical information for PD-BE studies of OIDPs.

PURPOSE: The International Study Group on Pancreatic Fistula's definition of postoperative pancreatic fistula (POPF) has recently been updated. This study aimed to identify risk factors for POPF in patients having pancreaticoduodenectomy (PD) and to generate a nomogram to predict POPF. METHODS: Data on 298 patients who underwent PD from March 2012 to October 2017 was retrospectively reviewed and POPF statuses were redefined. A nomogram was constructed using data from 220 patients and validated using the remaining 78 patients. Independent risk factors for POPF were identified using univariate and multivariate analyses. A predictive nomogram was established based on the independent risk factors and was compared with existing models. RESULTS: Texture of the pancreas, size of the main pancreatic duct, portal vein invasion, and definitive pathology were the identified risk factors. The nomogram had a C-index of 0.793 and was internally validated. The nomogram performed better (C-index of 0.816) than the other most cited models (C-indexes of 0.728 and 0.735) in the validation cohort. In addition, the nomogram can assign patients into low- (less than 10%), intermediate- (10% to 30%), and high-risk (equal or higher than 30%) groups to facilitate personalized management. CONCLUSION The nomogram accurately predicted POPF in patients having PD.

Objective To test the effects of human-computer interaction intelligent compression package for heparin injection in patients with orthopedic surgery.Methods From July 2015 to June 2016,108 patients with orthopedic surgery were enrolled in the study,and were divided into the experimental group (54 cases) and the control group(54 cases) by random number table.The experimental group was given heparin injection with human-computer interaction intelligent compression package for 3 min,while the control group was given manual compression for 3 min.We evaluated the incidence and severity of subcutaneous hemorrhage and nurses' operating time of two groups.Results The incidence of subcutaneous hemorrhage was 3.9％ in the experimental group,12.4％ in the control group(P＜0.05).The operating time was(100.4±8.7 s) for the experimental group and(233.8±15.3 s) for the control group (P＜0.01).Conclusion Using human-computer interaction intelligent compression package can reduce the incidence of subcutaneous hemorrhage.It can also reduce the working hours of nurses and optimize human resources.