Objective To explore the application value of three mainstream large language models in the diagnosis, differential diagnosis, and treatment decision support of the primary diseases related to pediatric liver transplantation. Methods Seventy-nine cases of pediatric liver transplantation-related diseases diagnosed through pathological or clinical follow-up data were collected from Renji Hospital, Shanghai Jiao Tong University School of Medicine or published high-quality case reports. These cases covered 25 types of primary diseases such as cholestatic liver disease, metabolic diseases, and tumors. Standardized prompts were used to input the case information into the DeepSeek-R1, ChatGPT-4o and Grok-3 models, and the accuracy of their preliminary diagnosis and differential diagnosis based on basic clinical data was evaluated. The final diagnosis accuracy and the response time after supplementary examination were also assessed, as well as the completeness and rationality of their analysis of disease treatment principles. Results In the initial diagnosis and differential diagnosis stage, the comprehensive accuracy of DeepSeek-R1 was the highest [72.1%, 95% confidence interval (CI) 61.4% - 80.8%], and there was a statistically significant difference in the comprehensive accuracy of the three models for initial diagnosis (P = 0.008). After adding further examination information, the final diagnosis accuracy of the three models increased, with DeepSeek-R1 at 88.6% (95% CI 79.7% - 93.9%), ChatGPT-4o at 87.3% (95% CI 78.2% - 93.0%), and Grok-3 at 78.5% (95% CI 68.2% - 86.1%). There was no statistically significant difference among the three models (P = 0.05). The scores given by experts for the treatment principles showed good consistency (Kappa = 0.769). In addition, the response time of ChatGPT-4o is shorter than that of the other two models [(24 ± 7) s]. Conclusions Large language models demonstrate good efficacy in the diagnosis and treatment decision-making process of various pediatric liver diseases, have a good application prospect for auxiliary diagnosis and decision support, and are expected to help improve the accuracy and efficiency of clinical diagnosis and treatment of pediatric liver transplantation-related primary diseases.

Renal hilar tumors pose significant surgical challenges due to their proximity to major renal vessels and the collecting system. In robot-assisted partial nephrectomy, although both anterior and posterior lip tumors are considered renal hilar tumors, their operative difficulty and complication profiles differ markedly owing to distinct anatomical relationships and vascular adjacency. Anterior lip tumors, often involving tributaries of the renal vein, carry a relatively higher risk of intraoperative and postoperative bleeding. In contrast, posterior lip tumors, closer to the renal artery, are more likely to prolong warm ischemia time, thereby increasing the risk of postoperative renal impairment. Regarding urine leakage, although anterior lip tumors are theoretically closer to the collecting system and may pose a slightly elevated risk, precision reconstruction strategies—such as lip reconstruction based on sinus space anatomy—can effectively mitigate this risk. However, the specific difference in urine leakage risk between anterior and posterior lip tumors warrants further investigation. Both anterior and posterior lip tumors of the kidney can achieve low positive surgical margin rates in experienced centers. Complication risks are affected by multiple factors, including tumor anatomical complexity, warm ischemia time, and surgeon experience. Notably, R.E.N.A.L. score＞8 is associated with significantly increased complication risks. Preoperative meticulous imaging evaluation, selection of an appropriate surgical approach based on tumor location, controlled warm ischemia time, and application of delicate suturing and reconstruction techniques are essential strategies to reduce complications.

The imaging features of intracranial melanoma are similar to those of other intracranial tumors, and a definite diagnosis often cannot be made solely based on imaging examinations. Although molecular pathology can detect gene mutations and protein markers of intracranial melanoma, its diagnostic specificity is limited due to the cross-expression of markers. Studies have shown that the combined application of imaging and molecular pathology can obviously improve the diagnosis sensitivity and specificity of intracranial melanoma, and by integrating the morphological and molecular characteristics of the melanoma, this combined application can optimize individualized treatment strategies and play important roles in surgical planning, targeted therapy selection, and therapeutic efficacy detection. This article reviews the research progress on the synergistic role of imaging and molecular pathology in the diagnosis and targeted therapy of intracranial melanoma, with the aim of providing a reference for diagnosis and treatment of intracranial melanoma.

AIM:To investigate the regulatory role and molecular mechanisms of the p62-NIMA(never in mi-tosis gene A)-related kinase 7(NEK7)-gasdermin D(GSDMD)-mediated pyroptosis axis in a mouse model of gouty arthri-tis.METHODS:C57BL/6 mice were randomly divided into control group,model group,and colchicine group(n=5 per group).Conditional knockout mouse models of p62,GSDMD,and p62-GSDMD were constructed and assigned to p62-/-group,GSDMD-/-group,and p62-/--GSDMD-/-group,respectively(n=5 per group).The gouty arthritis model was in-duced by monosodium urate crystal injection into the ankle joint in all groups except control.The colchicine group re-ceived oral colchicine pretreatment for 3 days prior to MSU injection,continuing for 5 days total.Ankle joint swelling was measured using a vernier caliper at 0,6,12,24,and 48 hours post-injection.Serum levels of p62,GSDMD,caspase-1,interleukin-1β(IL-1β),and IL-18 were quantified by ELISA.Immunohistochemistry staining was performed to assess nu-cleotide-binding oligomerization domain-like receptor protein 3(NLRP3),apoptosis-associated speck-like protein contain-ing a caspase recruitment domain(ASC),cleaved caspase-1,and IL-1β expression in joint tissues.Western blot was con-ducted to detect protein expression of p62,GSDMD,NLRP3,ASC,cleaved caspase-1,and IL-1β in mouse ankle joints,while RT-qPCR was used to measure mRNA expression of p62,NEK7,GSDMD,NLRP3,caspase-1 and IL-1β.RE-SULTS:Serum p62 levels and p62 protein and mRNA expression in ankle joints were significantly elevated in the model group.Following p62 gene knockout,the protein expression of NLRP3,ASC,caspase-1,and IL-1β in ankle joints showed a marked increase.Both GSDMD-/-and p62-/--GSDMD-/-groups exhibited attenuated ankle joint swelling,reduced serum levels of caspase-1,IL-1β,and IL-18,along with downregulated expression of p62,NLRP3,ASC,caspase-1,and IL-1β at both mRNA and protein levels in ankle joints.The NEK7 mRNA expression was similarly suppressed in these groups.CONCLUSION:Our findings demonstrate that MSU crystals activate macrophages through the coordinated action of p62,NEK7,and GSDMD,triggering NLRP3 inflammasome-mediated pyroptosis and ultimately promoting joint inflammation in gout mice.The p62-NEK7-GSDMD axis represents a critical regulatory mechanism in the canonical pyrop-tosis signaling pathway.

The imaging features of intracranial melanoma are similar to those of other intracranial tumors, and a definite diagnosis often cannot be made solely based on imaging examinations. Although molecular pathology can detect gene mutations and protein markers of intracranial melanoma, its diagnostic specificity is limited due to the cross-expression of markers. Studies have shown that the combined application of imaging and molecular pathology can obviously improve the diagnosis sensitivity and specificity of intracranial melanoma, and by integrating the morphological and molecular characteristics of the melanoma, this combined application can optimize individualized treatment strategies and play important roles in surgical planning, targeted therapy selection, and therapeutic efficacy detection. This article reviews the research progress on the synergistic role of imaging and molecular pathology in the diagnosis and targeted therapy of intracranial melanoma, with the aim of providing a reference for diagnosis and treatment of intracranial melanoma.

Objective:To analyze the association between daily physical activity patterns and dyslipidemia among people receiving physical examination aged 40-65 years.Methods:This cross-sectional study consecutively enrolled 864 participants aged 40-65 years and met the inclusion and exclusion criteria who underwent health check-ups at the Physical Examination Center of Fuquan First People′s Hospital from March to November in 2022. The data of general characteristics, physical activity, physical examination findings, and lipid profiles were collected. The daily physical activity patterns were identified using K-means clustering analysis. The unconditional binary logistic regression was employed to explore the associations between these activity patterns and dyslipidemia, followed by subgroup analyses.Results:The physical activity of the 864 study participants (517 males and 347 females) included in the analysis was divided into 4 patterns (G1: low physical activity; G2: active commuting; G3: housework; G4: leisure exercise). Using G1 as a reference, after adjusting for confounders, G4 was negatively associated with low high density lipoprotein cholesterol (HDL-C) ( OR=0.37, 95% CI: 0.14-1.00) ( P=0.05). In the male, G3 was negatively associated with dyslipidemia ( OR=0.44, 95% CI: 0.21-0.93) and low HDL-C ( OR=0.25, 95% CI: 0.10-0.68) (both P<0.05). In the subjects aged 50 years and above, G2 was negatively associated with dyslipidemia ( OR=0.52, 95% CI: 0.30-0.90), hypertriglyceridemia ( OR=0.50, 95% CI: 0.28-0.90) and low HDL-C ( OR=0.47, 95% CI: 0.24-0.91) (all P<0.05). In those who never or occasionally stayed up late, G2 was negatively associated with hypertriglyceridemia ( OR=0.31, 95% CI: 0.13-0.75) ( P<0.05); in those who stayed up late often, G4 was negatively associated with dyslipidemia ( OR=0.33, 95% CI: 0.13-0.85) and low HDL-C ( OR=0.19, 95% CI: 0.04-0.84) (both P<0.05). In the centrally obese population, G2 was negatively associated with dyslipidemia ( OR=0.55, 95% CI: 0.35-0.88) and hypertriglyceridemia ( OR=0.54, 95% CI: 0.33-0.86) (both P<0.05). Conclusions:Association between different physical activity patterns and dyslipidemia varied among adults aged 40-65 years undergoing health check-ups. Leisure-time exercise is associated with a reduced risk of dyslipidemia, while household activities also emerges as a beneficial factor linked to lower dyslipidemia risk particularly in the male population.

Objective:To explore the value of the vesical imaging-reporting and data system (VI-RADS) score based on multiparametric MRI (mpMRI) combined with quantitative tumor MRI parameters in assessing the muscle invasion of bladder cancer.Methods:The study was a case-control study. The data of 87 bladder cancer patients confirmed by pathology who underwent mpMRI of the bladder were retrospectively collected from the First Medical Center of Chinese PLA General Hospital between January 2019 and April 2023 The pathological findings were used as the gold standard to categorize them into the muscle invasive bladder cancer (MIBC) group (29 cases) and non-muscle invasive bladder cancer (NMIBC) group (58 cases). Quantitative parameters were measured based on preoperative mpMRI images, including the length of tumor bladder wall contact, the perpendicular distance between the bladder tumor and the tangent of the bladder wall, the maximal diameter of the bladder tumor, and the volume of the bladder tumor. Bladder cancer was classified according to the VI-RADS scoring criteria. The Mann-Whitney U test was used for intergroup comparisons. Multivariate logistic regression analysis was performed to obtain the independent risk factors related to muscle invasion of bladder cancer and to establish the model. The receiver operating characteristic curves were analyzed for MRI quantitative parameters and logistic regression models, and area under the curve (AUC) comparisons were performed using the DeLong test. Results:The differences in tumor bladder wall contact length, perpendicular distance from the tumor to the tangent line of the bladder wall, maximum diameter, bladder tumor volume, and the VI-RADS scores were statistically significant between the MIBC group and the NMIBC group ( P<0.05). Multifactorial logistic regression analysis showed that tumor bladder wall contact length ( OR=21.07, 95% CI 3.56-124.89, P=0.001) and VI-RADS score ( OR=11.90, 95% CI 3.53-40.12, P<0.001) were the independent risk factors for evaluating the muscle invasion of bladder cancer. The difference between the VI-RADS score and the tumor bladder wall contact length for assessing muscular infiltration of bladder cancer had AUCs of 0.802 (95% CI 0.704-0.899) and 0.759 (95% CI 0.652-0.865). The combined model of VI-RADS score combined with tumor bladder wall contact length had an AUC of 0.891 (95% CI 0.812-0.970), which was higher than the diagnostic efficacy of applying tumor bladder wall contact length or VI-RADS score alone ( Z=3.05, 2.37, P=0.002, 0.018). Conclusion:Tumor contact length with the bladder wall is an independent risk factor for assessing muscle invasion of bladder cancer and the combination of VI-RADS score may enhances diagnostic accuracy.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To explore the value of the vesical imaging-reporting and data system (VI-RADS) score based on multiparametric MRI (mpMRI) combined with quantitative tumor MRI parameters in assessing the muscle invasion of bladder cancer.Methods:The study was a case-control study. The data of 87 bladder cancer patients confirmed by pathology who underwent mpMRI of the bladder were retrospectively collected from the First Medical Center of Chinese PLA General Hospital between January 2019 and April 2023 The pathological findings were used as the gold standard to categorize them into the muscle invasive bladder cancer (MIBC) group (29 cases) and non-muscle invasive bladder cancer (NMIBC) group (58 cases). Quantitative parameters were measured based on preoperative mpMRI images, including the length of tumor bladder wall contact, the perpendicular distance between the bladder tumor and the tangent of the bladder wall, the maximal diameter of the bladder tumor, and the volume of the bladder tumor. Bladder cancer was classified according to the VI-RADS scoring criteria. The Mann-Whitney U test was used for intergroup comparisons. Multivariate logistic regression analysis was performed to obtain the independent risk factors related to muscle invasion of bladder cancer and to establish the model. The receiver operating characteristic curves were analyzed for MRI quantitative parameters and logistic regression models, and area under the curve (AUC) comparisons were performed using the DeLong test. Results:The differences in tumor bladder wall contact length, perpendicular distance from the tumor to the tangent line of the bladder wall, maximum diameter, bladder tumor volume, and the VI-RADS scores were statistically significant between the MIBC group and the NMIBC group ( P<0.05). Multifactorial logistic regression analysis showed that tumor bladder wall contact length ( OR=21.07, 95% CI 3.56-124.89, P=0.001) and VI-RADS score ( OR=11.90, 95% CI 3.53-40.12, P<0.001) were the independent risk factors for evaluating the muscle invasion of bladder cancer. The difference between the VI-RADS score and the tumor bladder wall contact length for assessing muscular infiltration of bladder cancer had AUCs of 0.802 (95% CI 0.704-0.899) and 0.759 (95% CI 0.652-0.865). The combined model of VI-RADS score combined with tumor bladder wall contact length had an AUC of 0.891 (95% CI 0.812-0.970), which was higher than the diagnostic efficacy of applying tumor bladder wall contact length or VI-RADS score alone ( Z=3.05, 2.37, P=0.002, 0.018). Conclusion:Tumor contact length with the bladder wall is an independent risk factor for assessing muscle invasion of bladder cancer and the combination of VI-RADS score may enhances diagnostic accuracy.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.