Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.

ObjectiveTo investigate the effect of 1，25（OH）₂D₃ on the level of peroxisome proliferator-activated receptor-γ （PPAR-γ） in the liver， the phenotype of hepatic macrophages， and liver inflammation in a rat model of nonalcoholic steatohepatitis （NASH）， as well as the mechanism of 1，25（OH）₂D₃ improving liver inflammation. MethodsAfter 1 week of adaptive feeding， 24 specific pathogen-free Wistar rats were randomly divided into normal group ［choline-supplemented L-amino acid-defined （CSAA） diet］， normal+1，25（OH）₂D₃ group ［CSAA diet+1，25（OH）₂D₃］， model group ［choline-deficient L-amino acid-defined diet （CDAA） diet］， and model+1，25（OH）₂D₃ group ［CDAA diet+1，25（OH）₂D₃］， with 6 rats in each group. The dose of 1，25（OH）₂D₃ was 5 μg/kg for intraperitoneal injection twice a week for 12 weeks. The serum levels of aspartate aminotransferase （AST） and alanine aminotransferase （ALT） were measured， liver histopathology was observed， and SAF score was assessed. M1 hepatic macrophages and M2 hepatic macrophages were measured to analyze in the change in the phenotype of hepatic macrophages， and ELISA was used to measure the levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， and interleukin-10 （IL-10） in liver tissue， and qPCR was used to measure the mRNA level of PPAR-γ. The two-factor analysis of variance was use for comparison between groups， and the least significant difference t-test was used for further comparison； the Pearson method was used for correlation analysis. ResultsCompared with the normal group， the model rats with CDAA diet-induced NASH had significant increases in the serum levels of AST and ALT （P=0.019 and P<0.001）， the SAF score of liver histopathology （P<0.001）， the level of M1 hepatic macrophages （P<0.001）， and the ratio of M1 and M2 hepatic macrophages （P<0.001）， as well as a significant increase in the level of TNF-α （P<0.001） and a significant reduction in the level of IL-4 in liver tissue （P=0.025）. The 1，25（OH）₂D₃ group had significant reductions in the serum levels of ALT （P<0.001）， the SAF score of liver histopathology （P<0.001）， the level of M1 hepatic macrophages （P<0.001）， and the ratio of M1 and M2 hepatic macrophages （P=0.001）， the level of IL-1β （P<0.001） and a significant increase in the level of M2 hepatic macrophages （P=0.017）， the level of IL-10 （P=0.039）， the level of IL-4 （P<0.001）， the level of PPAR-γ （P=0.016）. There were significant interactions between CDAA diet-induced NASH model and 1，25（OH）₂D₃ in serum the levels of AST and ALT （P=0.007 and P=0.008）， the SAF scores of liver histopathology （P<0.001）， the level of M1 hepatic macrophages （P<0.001）， the level of M2 hepatic macrophages （P=0.008）， the ratio of M1 and M2 of hepatic macrophages （P=0.005）， the level of TNF-α （P<0.001）， the level of IL-10 （P=0.038）， the level of IL-4 （P<0.001） and the level of PPAR-γ （P=0.009）. The correlation analysis showed that PPAR-γ was negatively correlated with the ratio of M1 and M2 hepatic macrophages （r=-0.415， P=0.044） and was positively correlated with M2 hepatic macrophages （r=0.435， P=0.033）， IL-10 （r=0.433， P=0.035）， and IL-4 （r=0.532， P=0.007）. ConclusionThis study shows that 1，25（OH）₂D₃ improves liver inflammation in NASH by activating PPAR-γ to regulate the phenotypic transformation of hepatic macrophages.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

Due to the inherently complex anatomical structure and physiological charac-teristics of the biliary system, biliary surgery faces considerable challenges in key stages such as preoperative planning, intraoperative identification, and postoperative management. These challenges contribute to a persistently high incidence of complications, severely affecting patient prognosis and overall survival. In recent years, with the continued advancement of interdisciplinary integration between medicine and engineering, intelligent digital technologies, centered on digital medicine, big data, and medical artificial intelligence, have been increasingly applied in the field of biliary surgery, offering new solutions to these longstanding problems. The authors systematically review recent advances and clinical applications of intelligent digital technologies in biliary surgery, and explore the evolution from clinical needs to technological innovation and practical implementation. The aim is to facilitate the transition of biliary surgery from an experience-based approach to an intelligent and precision-driven paradigm, thereby improving surgical safety and patient outcomes.

Objective:To investigate the factors associated with prolonged QTc interval in long-term hospitalized patients with schizophrenia, and to develop and validate a predictive model.Methods:A cross-sectional study was conducted involving 215 long-term hospitalized patients with schizophrenia at Xianyang Hospital, Yan'an University from January to December 2023. The incidence of prolonged QTc intervals among the patients was analyzed. Univariate and multivariate analyses of the factors associated with prolonged QTc intervals were performed. A mathematical model was developed to predict prolonged QTc intervals in long-term hospitalized patients with schizophrenia, and the predictive performance of the model was evaluated.Results:Among the 215 patients, 42 exhibited prolonged QTc intervals, with an incidence rate of 19.53%. Univariate analysis revealed statistically significant differences between the groups with and without prolonged QTc in terms of age, gender, body mass index, categories of antipsychotic medication used, fasting blood glucose, and potassium levels ( t = -5.66, χ2 = 29.03, t = -2.01, χ2 = 10.96, t = -5.78, t = 5.92, all P < 0.05). Multivariate logistic regression analysis indicated that age, gender, fasting blood glucose, and potassium levels were independent factors affecting QTc interval prolongation ( OR = 1.097, 10.221, 2.449, 0.014, all P < 0.05). The goodness-of-fit of the logistic regression model was validated to be satisfactory (Hosmer-Lemeshow χ2 = 14.56, P > 0.05). A risk nomogram model based on the variables from the multivariate analysis had a C-index of 0.713. Receiver operating characteristic curve analysis was performed using the independent influential factors and their P values from the logistic regression model to predict the probability of QTc interval prolongation. The area under the curve values were 0.762, 0.725, 0.730, 0.792, and 0.920, respectively. Conclusions:The incidence of prolonged QTc interval is relatively high in long-term hospitalized patients with schizophrenia. Female gender, older age, hyperglycemia, and hypokalemia are all associated with prolonged QTc intervals. The mathematical model developed based on these factors demonstrates good predictive performance for QTc interval prolongation.