Intervertebral disc degeneration （IVDD） is the core cause of chronic low back pain， which severely impairs patients’ quality of life and imposes a heavy social and medical burden. The hypoxia-pyroptosis-inflammation cascade mediated by hypoxia-inducible factor-1α （HIF-1α） is the core pathological mechanism driving the initiation and progression of IVDD. Natural active ingredients derived from traditional Chinese medicine （TCM） have become a research hotspot in the field of IVDD prevention and treatment due to their advantages of multi-target effects， favorable efficacy， and low toxicity. This paper systematically reviews the mechanism of HIF-1α-mediated hypoxia-pyroptosis-inflammation cascade in degenerative nucleus pulposus tissue and the intervention of related active ingredients. It is found that natural active ingredients such as baicalein， curcumin and resveratrol can intervene in the HIF-1α-mediated pathological cascade through four core links to delay IVDD progression： targeting the HIF-1α oxygen sensing pathway to block the initiation of pyroptosis cascade， inhibiting NOD-like receptor protein 3 inflammasome activation to cut off the cascade amplification of inflammatory signals， intervening in the Gasdermin D-mediated pyroptosis execution stage to protect cell membrane integrity， and regulating extracellular matrix metabolism to reconstruct intervertebral disc homeostasis.

Objective To observe the changes in the serum level of tumor necrosis factor-α(TNF-α)during pegylated interferon-alpha(PEG-IFN-α)treatment in inactive HBsAg carriers(IHCs),to investigate the association between the dynamic changes of TNF-α and HBsAg clearance,and to assess the value of TNF-α as a potential biomarker for predicting the therapeutic efficacy of PEG-IFN-α.Methods A prospective study was conducted among 455 IHCs who attended our hospital from January 2018 to March 2023,and they were divided into treatment group and IHC control group.The 210 IHCs in the treatment group voluntarily received PEG-IFNα-2b treatment for 48 weeks,followed by follow-up for 24 weeks,and the 245 IHCs in the IHC control group were followed up for 72 weeks without treatment.The serum level of TNF-α was measured at baseline(week 0)and at weeks 12,24,48,and 72,and at week 72,the treatment group was further divided into HBsAg clearance group and non-clearance group.The serum level of TNF-α at different time points was compared between groups.The logistic regression analysis was used to assess the value of TNF-α in predicting HBsAg clearance.The t-test was used for comparison of normally distributed continuous data between two groups,and a one-way analysis of variance used for comparison between multiple groups;the repeated measures analysis of variance was used for comparison of normally distributed repeated measurement data within each group and between groups;the chi-square test or the Fisher's exact test was used for comparison of categorical data between groups.Univariate and multivariate logistic regression analyses were used to investigate the predictive factors for HBsAg clearance,and the receiver operating characteristic(ROC)curve was used to determine the cut-off value of TNF-α in predicting HBsAg clearance.Results At week 72,compared with the IHC control group,the treatment group had significantly higher HBsAg clearance rate(46.2%vs 1.2%,χ2=133.333,P<0.001)and seroconversion rate(34.8%vs 0.8%,χ2=94.650,P<0.001).The HBsAg clearance group and the non-clearance group had a significant increase in the serum level of TNF-α during treatment,which gradually returned to the baseline level after drug withdrawal(F=351.733 and 76.434,both P<0.001).Comparisons between groups showed that the HBsAg clearance group had the highest serum level of TNF-α at weeks 12,24,and 48,followed by the non-clearance group and the IHC control group(all P<0.001).The multivariate logistic regression analysis showed that baseline HBsAg level(odds ratio[OR]=0.329,95%confidence interval[CI]:0.189-0.571,P<0.001),baseline HBV DNA<20 IU/mL(OR=1.414,95%CI:1.057-1.787,P=0.045),ALT≥2×upper limit of normal at week 12(OR=1.127,95%CI:1.028-1.722,P=0.043),TNF-α level at week 12(OR=1.336,95%CI:1.018-1.754,P=0.037),and TNF-α level at week 24(OR=1.879,95%CI:1.477-2.391,P<0.001)were independent predictive factors for HBsAg clearance.The ROC analysis showed that TNF-α level at week 12 had an area under the ROC curve(AUC)of 0.846(95%CI:0.814-0.889)in predicting HBsAg clearance at week 72,with a sensitivity of 76.3%and a specificity of 81.0%,while TNF-α level at week 24 had an AUC of 0.912(95%CI:0.758-0.972),with a sensitivity of 81.4%and a specificity of 96.2%.Conclusion PEG-IFN-α can increase the serum level of TNF-α in IHCs,and the serum level of TNF-α at weeks 12 and 24 can effectively predict HBsAg clearance induced by PEG-IFN-α.

Objective To investigate the value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced MRI radiomics and signal intensity in hepatobiliary phase(HBP)in predicting the pathological differentiation degree of hep-atocellular carcinoma(HCC).Methods The clinical and imaging data of 224 patients pathologically confirmed with HCC were col-lected.All patients were randomly divided into test group(68 cases)and training group(156 cases)at a ratio of 7︰3.The ITK-SNAP software was used to delineate region of interest(ROI)on arterial phase(AP),portal venous phase(PVP)and HBP,the radiomics features of the tumor tissues were extracted and the radiomics models were established using the FAE software.Logistic regression analysis was used to determine the clinical independent predictors associated with the pathological differentiation degree of HCC and to construct clinical model and clinical-radiomics model.Receiver operating characteristic(ROC)curve was plotted for each model and the area under the curve(AUC)was calculated to compare the diagnostic efficacy of the models.Results Age,alpha-fetoprotein(AFP),and r-glutamyltransferase(r-GT)were independent risk factors for predicting the degree of pathological differentiation of HCC.The AUC of the clinical-radiomics model in the training group and test group were 0.825 and 0.779,respectively,which were higher than those of the radiomics model(0.812 and 0.771)and the clinical model(0.687 and 0.666).Conclusion Gd-EOB-DTPA enhanced MRI radiomics have certain value in predicting the degree of pathological differentiation of HCC,while the predictive value of the signal intensity on HBP and the signal intensity ratio(SIR)on HBP is limited.

Simultaneous management of intestinal mucosal barrier dysfunction and gut microbiota dysregulation represents a significant challenge in the treatment of inflammatory bowel disease (IBD). Herein, we report a novel system that integrates multi-enzyme mimicking cerium single-atom nanocatalysts (CeSACs) with Lactobacillus reuteri probiotics (LR@CeSACs) for multipronged management of IBD. In this system, CeSACs demonstrate robust multi-enzyme activities across a broad pH range, effectively scavenging elevated reactive oxygen species, downregulating pro-inflammatory cytokines, and suppressing the expression of fibrosis-related genes. Moreover, probiotics promote the targeting and retention of the CeSACs for sustained catalytic antioxidant therapy. In turn, the inflammation relief enabled by CeSACs promotes bacterial viability, allowing for the rapid reshaping of intestinal barrier function and the restoration of gut microbiota. Therefore, LR@CeSACs exhibit excellent catalytic anti-inflammatory and anti-fibrotic therapeutic effects, as well as a certain prophylactic effect, as demonstrated in several murine models.

Objective:To investigate the value of habitat radiomic features based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in establishing a predictive model for cytokeratin 19 (CK19) expression in hepatocellular carcinoma (HCC) and to evaluate its role in prognostic risk stratification.Methods:This multicenter case-control study retrospectively enrolled 489 patients with pathologically confirmed HCC who underwent Gd-EOB-DTPA-enhanced MRI between June 2016 and June 2024. Among them, 346 patients from the First Affiliated Hospital of Soochow University were divided into a training cohort ( n=245) and an internal test cohort ( n=101) via stratified sampling at a 7∶3 ratio. And 143 patients from Nantong Third Hospital Affiliated to Nantong University served as an external validation cohort. The training cohort included 53 CK19-positive and 192 CK19-negative patients. The internal test cohort included 21 CK19-positive and 80 CK19-negative patients. The external validation cohort included 30 CK19-positive and 113 CK19-negative patients. Univariate logistic regression analysis was performed to identify potential factors associated with CK19 expression, and a clinical-radiologic model was constructed. The k-means clustering algorithm was applied to segment target HCC lesions into 3 subregions. Radiomic features were extracted and selected from these habitat subregions. Habitat radiomics models were constructed for the arterial phase (AP), portal venous phase, hepatobiliary phase (HBP), and combined phases (CP). Multivariate logistic regression analysis identified independent clinical and radiologic predictors of CK19 expression, and the optimal habitat model score was integrated to build a clinical-radiologic-habitat combined model. The area under the receiver operating characteristic curve (AUC) was used to evaluate model predictive performance. Recurrence-free survival (RFS) was analyzed using the Kaplan-Meier method and the differences in survival curves were compared with the log-rank test. Results:Univariate logistic regression analysis revealed that alpha-fetoprotein (AFP) ( OR=2.629, 95% CI 1.412-4.896, P=0.002), AP enhancement ( OR=3.636, 95% CI 1.642-8.052, P=0.001), AP peritumoral enhancement ( OR=2.219, 95% CI 1.084-4.542, P=0.029), and HBP peritumoral hypointensity ( OR=2.010, 95% CI 1.004-4.021, P=0.049) were potential factors associated with CK19 expression, which were incorporated into the clinical-radiologic model. In the internal and external validation cohorts, the AUC of the clinical-radiologic model was 0.690 (95% CI 0.590-0.778) and 0.650 (95% CI 0.565-0.727), respectively. The habitat radiomics model based on CP images demonstrated the highest performance. It achieved AUC of 0.729 (95% CI 0.622-0.836) and 0.725 (95% CI 0.607-0.842) in the internal and external validation cohorts, respectively. Multivariate analysis identified AFP ( OR=2.494, 95% CI 1.163-5.348, P=0.019), AP enhancement ( OR=5.230, 95% CI 1.868-14.643, P=0.002) and habitat radiomics model score ( OR=4.105, 95% CI 2.643-6.368, P<0.001) as independent predictors of CK19 positivity. Based on these factors, a combined clinical-radiologic-habitat combined model was established. The clinical-radiologic-habitat combined model achieved AUCs of 0.767 (95% CI 0.671-0.846) and 0.730 (95% CI 0.649-0.801) in the internal and external validation cohorts, respectively. Significant differences in RFS were observed between the CK19-positive group (25.1 month) and CK19-negative group (51.0 month) as predicted by the clinical-radiologic-habitat model ( χ2=4.17, P=0.041). Conclusion:The clinical-radiologic-habitat combined model based on Gd-EOB-DTPA-enhanced MRI habitat radiomics demonstrates good predictive performance for CK19 expression in HCC and offers valuable prognostic stratification for clinical practice.

Objective:To explore the value of the deep learning model based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI in preoperatively predicting vessels completely encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC).Methods:This study adopted a case-control design to retrospectively analyze 420 patients with HCC confirmed by postoperative pathology who underwent Gd-EOB-DTPA enhanced MRI between June 2016 and March 2023. A total of 420 patients were divided into a training set ( n=305) from the First Affiliated Hospital of Soochow University and an external validation set ( n=115) from Affiliated Nantong Hospital 3 of Nantong University. Based on postoperative pathological findings, patients were stratified into VETC-positive and VETC-negative groups. The training set comprised 161 VETC-positive cases and 144 VETC-negative cases, while the external validation set included 55 VETC-positive cases and 60 VETC-negative cases. Tumor regions of interest in arterial, portal venous, and hepatobiliary phases were manually delineated using ITK-SNAP software. Pre-trained Vgg19, Densenet121, and Vision Transformer (ViT) models were employed for transfer learning, extracting deep learning features from each image. Feature data were processed using FAE software, and 12 logistic regression models (arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase models) were constructed to select the optimal deep learning model. Independent predictors in clinical characteristics were identified through univariate and multivariate logistic analyses to establish a clinical model for predicting VETC pattern. Subsequently, a clinical-deep learning fusion model was developed by integrating these clinical predictors with the optimal deep learning features. Model performance in predicting VETC-positive HCC was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Results:In the external validation set, the area under the curve (AUC) of the Vgg19 model in the arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase, respectively were 0.799,0.756,0.789,0.821, which were higher than those of Densenet121 (AUC: 0.544,0.581,0.544,0.583) and ViT (AUC: 0.740,0.752,0.785,0.767) model. The three-phase combined Vgg19 model achieved the highest AUC of 0.821 (95% CI 0.746-0.897). Multivariate logistic regression identified alpha-fetoprotein level ( OR=1.826,95% CI 1.069-3.120, P=0.028) and tumor diameter ( OR=1.329,95% CI 1.206-1.466, P<0.001) as independent predictors of VETC-positive HCC, forming the clinical model with an AUC of 0.789 (95% CI 0.703-0.859). The clinical-deep learning fusion model further achieved the AUC of 0.825 (95% CI 0.749-0.900). Calibration curves confirmed high concordance between predicted and actual probabilities for the three-phase Vgg19 model, while DCA revealed greater net clinical benefit for the combined Vgg19 and fusion models compared with the clinical model alone. Conclusions:The deep learning model based on Gd-EOB-DTPA enhanced MRI can be used to predict VETC of HCC preoperatively, among which the three-phase combined Vgg19 model and the clinical-deep learning model provide high predictive value.

Objective To develop a machine learning(ML)-based prediction model for assessing the therapeutic effects of resveratrol(RES)on the pathological damage of acute pancreatitis(AP),and to optimize RES administration strategies for AP through validation using an animal model.Methods AAn ML-based prediction model was constructed using published data.Interpretability analysis was applied to identify high-efficacy zones within the parameter space of administration dose and frequency,which was followed by rigorous screening to select the optimal dosing strategy that balanced therapeutic efficacy and experimental feasibility.A total of 32 C57BL/6 mice were randomly assigned to 4 groups(n=8 per group),including a control group(Ctrl),an AP model group induced by caerulein(CER)and referred to as CER-AP,a treatment group receiving RES via intraperitoneal injection(RES i.p.),and a treatment group receiving RES via intragastric gavage(RES i.g.).The Ctrl group received intraperitoneal injection of normal saline.The CER-AP and the treatment groups were induced with 10 intraperitoneal injections of CER at 50 μg/kg.RES was administered to the RES i.p.and RES i.g.groups according to the optimal dose and timing predicted by the ML model.Blood and tissue samples were collected 12 hours after the experiment started.Results The gradient boosting decision tree model,optimized via Hyperopt,yielded the best performance,predicting that the optimal dose and administration frequency were 19.992 mg/kg and 3.828 times,respectively.Accordingly,a regimen of 20 mg/kg RES,administered four times,was used in the animal experiments.Compared with the Ctrl group,the CER-AP group exhibited higher pancreatic pathology scores and elevated levels of serum amylase,lipase,pancreatic myeloperoxidase,and trypsin,with all differences reaching statistical significance(all P<0.05).The administration of 20 mg/kg RES via both intraperitoneal injection and intragastric gavage mitigated pancreatic inflammatory cell infiltration and necrosis,improved the overall pathology score,and reduced serum amylase,lipase,and pancreatic myeloperoxidase levels to varying degrees(all P<0.05).Conclusion A regimen of 20 mg/kg RES administered four times effectively alleviates the severity of CER-induced AP.The therapeutic benefits appear to arise from a multi-target regulatory network that simultaneously suppresses inflammatory cascades,mitigates oxidative stress,and reduces apoptosis,thereby reducing pancreatic tissue damage and systemic inflammatory responses.

Objective To investigate the influencing factors for low anterior resection syndrome(LARS)at one year after ileostomy reversal in patients who have undergone radical resection for rectal cancer,and to inform clinical interventions.Methods A retrospective cohort study was conducted on 312 patients who successfully underwent ileostomy reversal after radical resection for rectal cancer between January 2023 and January 2024 at 3 tertiary hospitals in Chongqing.Based on LARS scores at 1-year after stoma reversal,they were divided into a LARS group(score≥21)and a non-LARS group(score≤20).Clinical data were collected from the medical record system,including age,body mass index(BMI),sex,tumor size,tumor distance from the anal verge,T stage,N stage,date of low anterior resection,neoadjuvant therapy,postoperative chemotherapy,anastomotic leakage,and date of ileostomy reversal.Univariate analysis was used to screen potential influencing factors,and variables with P<0.2 were included in a multivariate logistic regression model.Binary stepwise regression analysis was applied to further analyze significant influencing factors for LARS at 1 year after ileostomy reversal.Results In the cohort,there were 127 patients assigned into the LARS group and 185 into the non-LARS group.The incidence of LARS at 1 year after ileostomy reversal was 40.70%,with mild cases accounting for 21.79%and severe ones for 18.91%,and a mean LARS score of 14.52±11.64.Multivariate logistic regression analysis showed that neoadjuvant therapy(yes vs no:OR=1.830,95%CI:1.088～3.089;P=0.023),tumor distance from anal verge≤5 cm(vs>5 cm:OR=2.044,95%CI:1.249～3.374;P=0.005),occurrence of anastomotic leakage(yes vs no:OR=7.470,95%CI:2.247～34.102;P=0.003),time to reversal(≥181 d vs 91～180 d:OR=2.297,95%CI:1.363～3.917;P=0.002),and N stage(N1～N2 vs N0:OR=1.650,95%CI:1.009～2.717;P=0.047)were significant influencing factors for LARS at 1 year after ileostomy reversal.Conclusion Our results suggest that anastomotic leakage,time to reversal≥181 d,tumor distance from anal verge≤5 cm,neoadjuvant therapy,and N stage N1～N2 are associated with the occurrence of LARS at 1 year after ileostomy reversal in patients following radical resection of rectal cancer.Clinical healthcare providers should implement early intervention and long-term follow-up for patients with high-risk factors both before and after stoma reversal.

There is a substantial unmet need for treatments in the field of pediatric rare diseases, and investigator initiated trial(IIT) provide a critical pathway for testing and developing new drugs or treatment strategies. However, healthcare institutions, when conducting such research, must address compliance risks related to project approval, contract management, data protection, and conflict of interest management. This study aims to analyze the particularities and challenges of IIT in pediatric rare diseases, review relevant regulations and regulatory requirements, and provide healthcare institutions with a reference framework for compliance risk management to maximize the benefits of IIT. Based on literature review, analysis of laws and regulations, practical work experience, and frameworks from other institutions, we summarize the unique aspects of pediatric rare disease IIT in terms of participant characteristics, innovative technologies, and organizational structures.On this basis, targeted compliance management recommendations are proposed, which include establishing a risk rating and full-cycle risk monitoring mechanism, a consent and ethical review mechanism tailored to pediatric participants, a robust contract management mechanism, a comprehensive data security management mechanism, and a multidisciplinary team and multi-channel compensation mechanism. The study concludes that healthcare institutions, funders, and other collaborating entities should implement compliance management in line with the characteristics of IIT to ensure the safety and effectiveness of research and facilitate innovation and development in the treatment of pediatric rare diseases.

Objective:To explore the clinical distribution characteristics and changes of common inhalant allergens and food allergens in all outpatient and inpatient children visiting Shanghai Children′s Hospital from 2020 to 2024, and to provide a basis for the diagnosis, treatment and prevention of allergic diseases in children.Methods:A retrospective cohort study was conducted to retrospectively enroll all outpatient and inpatient children who visited Shanghai Children′s Hospital and underwent serum allergen-specific IgE (sIgE) antibody testing from January 2020 to August 2024, and the characteristics and changing trends of allergens in the past 5 years were analyzed. A total of 127 310 tests were included. There were 76 776 male tests (60.31%) and 50 534 female tests (39.69%). There were 27 392 tests (21.52%) aged 0-3 years (infant group), 51 596 tests (40.53%) aged 4-6 years (preschool group), 44 574 tests (35.01%) aged 7-12 years (school-age group), and 3 748 tests (2.94%) aged 13-18 years (adolescent group). The χ2 test was used for statistical analysis. Results:The difference in total positivity rate between different years was statistically significant ( χ2=2 907.478, P<0.001). The positive rates of inhalant allergens such as house dust, Dermatophagoides pteronyssinus/ Dermatophagoides farinae, cockroach, cat dander, mugwort, Humulus scandens, mold fungi mix, and food allergens such as beef and mutton increased significantly with age (The χ2 values were 649.496, 3 414.686, 303.247, 1 277.408, 40.477, 189.952, 600.737, 203.198, and 15.301, respectively, and the P values were <0.001, <0.001, <0.001, <0.001, <0.001, <0.001,<0.001,<0.001, and 0.002, respectively). The positive rates of inhalant allergen such as Ambrosia elatior (1.59%) and food allergens such as egg white (17.36%), milk (30.48%), shrimp (8.27%), crab (8.13%), codfish (2.61%), salmon (0.66%), mytilus edulis (2.89%), lobster/scallop (5.27%), cashew nuts (5.09%), peanuts (3.54%), and soybean (1.73%) were highest at the age of 0-3 years and decreased significantly with age (The χ2 values were 10.365, 2 407.443, 139.085, 872.548, 870.245, 106.823, 47.674, 47.244, 559.422, 369.800, 384.788, 153.660, respectively, and the P values were 0.016, 0.000,<0.001,<0.001,<0.001,<0.001,<0.001,<0.001,<0.001,<0.001,<0.001,<0.001, respectively). Inhaled allergens mainly have a greater impact on children with respiratory-related diseases such as allergic rhinitis and asthma, while food allergens mainly have a greater impact on children with atopic dermatitis/eczema. The positive rate of sIgE of various allergens in the allergic rhinitis combined asthma group were higher than that of allergic rhinitis alone, and the sIgE positive rate of total allergens and inhaled allergens was significantly higher than that of allergic rhinitis alone ( χ2=20.851, 39.155, the P values were both<0.001). Among them, the sIgE positive rate of Ambrosia elatior and cashew nuts showed significant difference ( χ2=5.044, 8.420, P=0.025, 0.004); and the sIgE positive rate of Dermatophagoides pteronyssinus/ Dermatophagoides farinae, cat dander, grass pollens mix and mold fungi mix had extremely significant difference ( χ2=26.409, 25.990, 21.283, 16.411, the P values were all <0.001). The inhaled allergens and food allergens with the highest positive rates in the 5 years were Dermatophagoides pteronyssinus/ Dermatophagoides farinae (56.21%) and milk (47.47%), and as time went by, the positive rates gradually decreased. There is a moderate correlation between the three allergens of Ambrosia elatior, Amaranthus retroflexus, and tree pollens mix (0.55, 0.70, 0.63), and there is a moderate correlation between mango and tree pollens mix (0.50). Conclusion:Dermatophagoides pteronyssinus/ Dermatophagoides farinae, cat dander, dog dander, egg white, and milk may be important allergens for children in Shanghai City from 2020 to 2024. The positive rates vary among different genders, age groups, and disease groups, but the positive rates of Dermatophagoides pteronyssinus/ Dermatophagoides farinae, milk and cat dander allergens remain in the top three.