Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

This study explored the mechanism of Xiangsha Liujunzi Decoction(XSLJZD) in the treatment of functional dyspepsia(FD) based on inositol-requiring enzyme 1(IRE1)/apoptosis signal-regulating kinase 1(ASK1)/c-Jun N-terminal kinase(JNK) pathway-mediated autophagy in interstitial cells of Cajal(ICC). Forty-eight SPF-grade male SD suckling rats were randomly divided into a blank group and a modeling group, and the integrated modeling method(iodoacetamide gavage + disturbance of hunger and satiety + swimming exhaustion) was used to replicate the FD rat model. After the model replications were successfully completed, the rats were divided into a model group, high-dose, medium-dose, and low-dose groups of XSLJZD(12, 6, and 3 g·kg~(-1)·d~(-1)), and a positive drug group(mosapride of 1.35 mg·kg~(-1)·d~(-1)), and the intervention lasted for 14 days. The gastric emptying rate and intestinal propulsion rate of rats in each group were measured. The histopathological changes in the gastric sinus tissue of rats in each group were observed by hematoxylin-eosin(HE) staining. The ultrastructure of ICC was observed by transmission electron microscopy. The immunofluorescence double staining technique was used to detect the protein expression of phospho-IRE1(p-IRE1), TNF receptor associated factors 2(TRAF2), phospho-ASK1(p-ASK1), phospho-JNK(p-JNK), p62, and Beclin1 in ICC of gastric sinus tissue of rats in each group. Western blot was used to detect the related protein expression of gastric sinus tissue of rats in each group. Compared with those in the blank group, the rats in the model group showed decreased body weight, gastric emptying rate, and intestinal propulsion rate, and transmission electron microscopy revealed damage to the endoplasmic reticulum structure and increased autophagosomes in ICC. Immunofluorescence staining revealed that the ICC of gastric sinus tissue showed a significant elevation of p-IRE1, TRAF2, p-ASK1, p-JNK, and Beclin1 proteins and a significant reduction of p62 protein. Western blot revealed that the expression levels of relevant proteins in gastric sinus tissue were consistent with those of proteins in ICC. Compared with the model group, the body weight of rats in the high-dose and medium-dose groups of XSLJZD was increased, and the gastric emptying rate and intestinal propulsion rate were increased. Transmission electron microscopy observed amelioration of structural damage to the endoplasmic reticulum of ICC and reduction of autophagosomes, and the p-IRE1, TRAF2, p-ASK1, p-JNK, and Beclin1 proteins in the ICC of gastric sinus tissue were significantly decreased. The p62 protein was significantly increased. Western blot revealed that the expression levels of relevant proteins in gastric sinus tissue were consistent with those of proteins in ICC. XSLJZD can effectively treat FD, and its specific mechanism may be related to the inhibition of the expression of molecules related to the endoplasmic reticulum stress IRE1/ASK1/JNK pathway in ICC and the improvement of autophagy to promote gastric motility in ICC.
Animals ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Autophagy/drug effects* ; Rats ; Rats, Sprague-Dawley ; Interstitial Cells of Cajal/metabolism* ; Dyspepsia/physiopathology* ; Protein Serine-Threonine Kinases/genetics* ; MAP Kinase Kinase Kinase 5/genetics* ; MAP Kinase Signaling System/drug effects* ; Humans ; Endoribonucleases/genetics* ; Multienzyme Complexes

Objective： To analyze the symptoms, diagnosis and treatment of upper urinary tract calculi patients combined with mild and moderate benign prostatic hyperplasia (BPH) after ureteral stent implantation. Methods： One hundred and six BPH patients who were hospitalized for upper urinary tract calculi and had ureteral stents retained from January 2019 to December 2022 were selected and divided into 2 weeks group and 4 weeks group according to the time of removal of ureteral stents after surgery. Their general clinical data were analyzed and compared. International Prostatic Symptom Scale (IPSS), postoperative ureteral Stent Symptom Questionnaire (USSQ), and incidence of adverse events after ureteral stent removal were recorded before and after removal. Results： The scores of IPSS were significantly increased in all patients, and symptoms in urinary tract had improved significantly after discharge (P<0.05). Compared with the 2 weeks group, the USSQ score of the 4 weeks group was significantly increased (P<0.05). And no significant adverse event was observed in the 2 weeks group after the removal of ureteral sten. Conclusion： IPSS score and USSQ score increased significantly during stent implantation in BPH patients with lithiasis. And complications increased significantly over time. Following thorough clinical assessment, early ureteral stent removal demonstrates both safety and efficacy, representing an optimal therapeutic approach in selected cases.
Humans ; Male ; Prostatic Hyperplasia/surgery* ; Stents ; Ureter/surgery* ; Aged ; Middle Aged ; Urinary Calculi/surgery* ; Ureteral Calculi/surgery*

Cardamonin, a natural flavonoid compound, exhibits potential anti-aging properties, yet its precise mechanisms still remain unclear. In this study, we established cellular senescence models using bleomycin and H2O2 and treated the cells with varying concentrations of cardamonin to investigate its anti-senescence effects and underlying mechanisms. Senescence-associated β-galactosidase (SA-β-gal) staining was employed to assess senescent phenotypes, while immunofluorescence was used to detect DNA damage levels. Intracellular reactive oxygen species (ROS) levels were measured using the DCFH-DA probe, and Western blot was performed to analyze the expression of p53, p21, collagen, α-smooth muscle actin (α-SMA), mechanistic target of rapamycin (mTOR), and p-mTOR. To further validate the mechanistic target, MHY1485 was utilized to activate the mTOR pathway and evaluate its regulatory impact on senescence phenotypes. The results demonstrated that cardamonin significantly alleviated bleomycin- and H2O2-induced cellular senescence. Mechanistic studies revealed that cardamonin reduced ROS accumulation and suppressed mTOR phosphorylation. Notably, MHY1485-mediated activation of the mTOR pathway reversed senescence and fibrotic phenotypes, providing reciprocal validation of the target mechanism. In conclusion, cardamonin mitigates cellular senescence by targeting the mTOR-ROS axis, offering a promising therapeutic strategy for anti-aging interventions and the treatment of idiopathic pulmonary fibrosis (IPF).

Air Pollution/analysis* ; Environmental Exposure/analysis* ; China/epidemiology* ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; Environmental Monitoring

The development of chemoresistance which results in a poor prognosis often renders current treatments for colorectal cancer(CRC).In this study,we identified reduced microvessel density(MVD)and vascular immaturity resulting from endothelial apoptosis as therapeutic targets for overcoming chemoresistance.We focused on the effect of metformin on MVD,vascular maturity,and endothelial apoptosis of CRCs with a non-angiogenic phenotype,and further investigated its effect in overcoming chemoresistance.In situ transplanted cancer models were established to compare MVD,endothelial apoptosis and vascular maturity,and function in tumors from metformin-and vehicle-treated mice.An in vitro co-culture system was used to observe the effects of metformin on tumor cell-induced endothelial apoptosis.Transcriptome sequencing was performed for genetic screening.Non-angiogenic CRC developed inde-pendently of angiogenesis and was characterized by vascular leakage,immaturity,reduced MVD,and non-hypoxia.This phenomenon had also been observed in human CRC.Furthermore,non-angiogenic CRCs showed a worse response to chemotherapeutic drugs in vivo than in vitro.By suppressing endo-thelial apoptosis,metformin sensitized non-angiogenic CRCs to chemo-drugs via elevation of MVD and improvement of vascular maturity.Further results showed that endothelial apoptosis was induced by tumor cells via activation of caspase signaling,which was abrogated by metformin administration.These findings provide pre-clinical evidence for the involvement of endothelial apoptosis and subsequent vascular immaturity in the chemoresistance of non-angiogenic CRC.By suppressing endothelial apoptosis,metformin restores vascular maturity and function and sensitizes CRC to chemotherapeutic drugs via a vascular mechanism.

Objective:To develop and validate the models based on mixed enhanced computed tomography (CT) radiomics and deep learning features, and evaluate the efficacy for differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC) before surgery.Methods:The clinical data of 201 patients with surgically resected and histopathologically confirmed PASC (PASC group) and 332 patients with surgically resected histopathologically confirmed PDAC (PDAC group) who underwent enhanced CT within 1 month before surgery in the First Affiliated Hospital of Naval Medical University from January 2011 to December 2020 were retrospectively collected. The patients were chronologically divided into a training set (treated between January 2011 and January 2018, 156 patients with PASC and 241 patients with PDAC) and a validation set (treated between February 2018 and December 2020, 45 patients with PASC and 91 patients with PDAC) according to the international consensus on the predictive model. The nnU-Net model was used for pancreatic tumor automatic segmentation, the clinical and CT images were evaluated, and radiomics features and deep learning features during portal vein phase were extracted; then the features were dimensionally reduced and screened. Binary logistic analysis was performed to develop the clinical, radiomics and deep learning models in the training set. The models' performances were determined by area under the ROC curve (AUC), sensitivity, specificity, accuracy, and decision curve analysis (DCA).Results:Significant differences were observed in tumor size, ring-enhancement, upstream pancreatic parenchymal atrophy and cystic degeneration of tumor both in PASC and PDAC group in the training and validation set (all P value <0.05). The multivariable logistic regression analysis showed the tumor size, ring-enhancement, dilation of the common bile duct and upstream pancreatic parenchymal atrophy were associated with PASC significantly in the clinical model. The ring-enhancement, dilation of the common bile duct, upstream pancreatic parenchymal atrophy and radiomics score were associated with PASC significantly in the radiomics model. The ring-enhancement, upstream pancreatic parenchymal atrophy and deep learning score were associated with PASC significantly in the deep learning model. The diagnostic efficacy of the deep learning model was highest, and the AUC, sensitivity, specificity, and accuracy of the deep learning model was 0.86 (95% CI 0.82-0.90), 75.00%, 84.23%, and 80.60% and those of clinical and radiomics models were 0.81 (95% CI 0.76-0.85), 62.18%, 85.89%, 76.57% and 0.84 (95% CI 0.80-0.88), 73.08%, 82.16%, 78.59% in the training set. In the validation set, the area AUC, sensitivity, specificity, and accuracy of deep learning model were 0.78 (95% CI 0.67-0.84), 68.89%, 78.02% and 75.00%, those of clinical and radiomics were 0.72 (95% CI 0.63-0.81), 77.78%, 59.34%, 65.44% and 0.75 (95% CI 0.66-0.84), 86.67%, 56.04%, 66.18%. The DCA in the training and validation sets showed that if the threshold probabilities were >0.05 and >0.1, respectively, using the deep learning model to distinguish PASC from PDAC was more beneficial for the patients than the treat-all-patients as having PDAC scheme or the treat-all-patients as having PASC scheme. Conclusions:The deep learning model based on CT automatic image segmentation of pancreatic neoplasm could effectively differentiate PASC from PDAC, and provide a new non-invasive method for confirming PASC before surgery.