BACKGROUND:Radiotherapy significantly improves survival rates in patients with various malignant tumors.However,with prolonged post-treatment survival,many patients face the risk of radiation-related cardiac toxicity.This is especially true after chest radiotherapy,where the risk of radiation-induced heart disease significantly increases,becoming one of the most severe complications affecting prognosis survival.OBJECTIVE:To identify diagnostic markers of endothelial cellular senescence in radiation-induced heart disease through systematic transcriptomic analysis.METHODS:Firstly,genes associated with cellular senescence were screened from the CellAge database and intersected with the transcriptomic training dataset of a mouse model of radiation-induced heart disease to identify differentially expressed senescence-related genes.Secondly,weighted gene co-expression network analysis and machine learning were used to identify key hub genes that play critical roles in radiation-induced heart disease.The expression of these genes was validated using a dataset of radiation-induced endothelial injury.Additionally,the quanTlseq method was employed to assess the immune infiltration status related to radiation-induced heart disease.The expression levels of key genes and their association with survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy were explored through the analysis of The Cancer Genome Atlas database.RESULTS AND CONCLUSION:(1)Systematic transcriptomic analysis identified CCND1 as the core gene of endothelial cellular senescence in radiation-induced heart disease,and this finding was validated in the mouse model of radiation-induced heart disease.(2)The diagnostic model constructed from these data indicated that CCND1 had high specificity and sensitivity for diagnosing radiation-induced heart disease.(3)Immune infiltration analysis revealed significant immune response dysregulation in the mouse model of radiation-induced heart disease,and CCND1 was closely related to various immune cells.(4)Kaplan-Meier survival analysis showed that CCND1 was associated with poorer disease-specific survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy.This study systematically uncovers,for the first time,the pivotal role of CCND1 in endothelial cell senescence associated with radiation-induced heart disease.CCND1,a gene integral to cell cycle regulation,can induce cellular senescence when abnormally expressed.Furthermore,the findings highlight its potential as an early diagnostic marker.

BACKGROUND:Radiotherapy significantly improves survival rates in patients with various malignant tumors.However,with prolonged post-treatment survival,many patients face the risk of radiation-related cardiac toxicity.This is especially true after chest radiotherapy,where the risk of radiation-induced heart disease significantly increases,becoming one of the most severe complications affecting prognosis survival.OBJECTIVE:To identify diagnostic markers of endothelial cellular senescence in radiation-induced heart disease through systematic transcriptomic analysis.METHODS:Firstly,genes associated with cellular senescence were screened from the CellAge database and intersected with the transcriptomic training dataset of a mouse model of radiation-induced heart disease to identify differentially expressed senescence-related genes.Secondly,weighted gene co-expression network analysis and machine learning were used to identify key hub genes that play critical roles in radiation-induced heart disease.The expression of these genes was validated using a dataset of radiation-induced endothelial injury.Additionally,the quanTlseq method was employed to assess the immune infiltration status related to radiation-induced heart disease.The expression levels of key genes and their association with survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy were explored through the analysis of The Cancer Genome Atlas database.RESULTS AND CONCLUSION:(1)Systematic transcriptomic analysis identified CCND1 as the core gene of endothelial cellular senescence in radiation-induced heart disease,and this finding was validated in the mouse model of radiation-induced heart disease.(2)The diagnostic model constructed from these data indicated that CCND1 had high specificity and sensitivity for diagnosing radiation-induced heart disease.(3)Immune infiltration analysis revealed significant immune response dysregulation in the mouse model of radiation-induced heart disease,and CCND1 was closely related to various immune cells.(4)Kaplan-Meier survival analysis showed that CCND1 was associated with poorer disease-specific survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy.This study systematically uncovers,for the first time,the pivotal role of CCND1 in endothelial cell senescence associated with radiation-induced heart disease.CCND1,a gene integral to cell cycle regulation,can induce cellular senescence when abnormally expressed.Furthermore,the findings highlight its potential as an early diagnostic marker.

Objective To systematically evaluate the differences in outcomes between functional mitral regurgitation (FMR) and degenerative mitral regurgitation (DMR) in patients treated with transcatheter edge-to-edge repair (TEER) using the MitraClip device. Methods A systematic literature search was conducted in PubMed, Embase, the Cochrane Library, Web of Science, the CNKI, Wanfang Database, VIP Database, and the CBM from their inception to January 2024. Two researchers independently performed study selection, data extraction, and risk of bias assessment. The quality of cohort studies was evaluated using the Newcastle-Ottawa Scale (NOS). A meta-analysis was performed using Stata 18.0 software. Results A total of 13 cohort studies involving 6 402 patients were included, comprising 4 161 patients in the FMR group and 2 241 in the DMR group. All included studies had NOS scores of ≥6 points. The meta-analysis revealed that compared to the DMR group, the FMR group had a higher 1-year all-cause mortality rate [OR=1.53, 95%CI (1.30, 1.81), P＜0.01] and a higher 1-year rehospitalization rate for heart failure [OR=1.90, 95%CI (1.60, 2.26), P＜0.01]. Conversely, the FMR group had a lower post-procedural mean transmitral gradient [SMD=–0.47, 95%CI (–0.65, –0.30), P＜0.01] and a lower rate of subsequent mitral valve surgery [OR=0.41, 95%CI (0.20, 0.83), P=0.01]. Conclusion Following MitraClip therapy, patients with FMR exhibit favorable short-term outcomes, but their mid- to long-term outcomes are inferior to those of patients with DMR. When determining the treatment strategy with MitraClip, the specific etiology of mitral regurgitation should be considered for a more accurate prediction of therapeutic efficacy and prognosis.

The core pathogenesis of attention deficit hyperactivity disorder （ADHD） lies in deficiency， stasis and stagnation. Deficiency arises from kidney essence depletion and spleen dysfunction in transportation and transformation， leading to inadequate nourishment of the marrow sea. Stasis caused by qi deficiency leads to obstruction in channels and collaterals， resulting in obstructed marrow transport. Stagnation is associated with the excess of the five minds transforming into fire， which scorches the brain orifices and leads to loss of control over marrow utilisation. Based on this， a "supplementation-unblocking-regulation" therapeutic approach is proposed. For deficiency， the focus is on supplementing kidney and fortifying spleen， and replenishing the marrow sea. For stasis， the priority is to unblock and open the orifices， and clear the marrow channels. For stagnation， the core is to clear fire and contain the mind， regulate and restore vital activity. In clinical practice， it is necessary to identify the primary and secondary pathogenic mechanisms and apply dynamic， combined treatment， integrating Chinese herbal medicine， acupuncture， and guiding exercises throughout the process， aiming to provide a reference for the diagnosis and treatment of ADHD with traditional Chinese medical.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

OBJECTIVE To compare the risk of pneumonitis and interstitial lung disease （ILD） associated with different antibody-drug conjugates （ADC） in the treatment of breast cancer. METHODS CNKI， VIP， PubMed， Embase and other Chinese and English databases， and ClinicalTrials.gov were searched from the inception to June 15， 2025. Randomized controlled trials （RCT） about pneumonitis and ILD associated with ADC （T-DM1， T-DXd， SG， Dato-DXd， SHR-A1811，ARX788， and T-Duo） in the treatment of breast cancer were included. After literature screening， data extraction， and quality assessment， a network meta-analysis was conducted using Stata 17.0 software， and the surface under the cumulative ranking curve（SUCRA） of all interventions were ranked. RESULTS A total of 19 RCTs involving 10 556 patients were included. The overall incidence of pneumonitis with ARX788 and T-DXd was significantly higher than that with T-DM1， T-DM1 plus TPC（T-DM1combined with pertuzumab or atezolizumab）， TPC（treatment of primary care）， and SG （ P ＜0.05）， for grade 1-2 pneumonitis， ARX788 and T-DXd showed significantly higher incidence than T-DM1， T-DM1 plus TPC， and TPC （ P ＜0.05）. For both indicators， ARX788 and T-Duo were ranked as the top two by SUCRA. For the incidence of grade ≥3 pneumonitis， T-DXd and T-DM1 were significantly higher than SG （ P ＜0.05）， T-Duo and Dato-DXd were ranked as the top two by SUCRA. For overall incidence of ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， TPC， and SG （ P ＜0.05）， for the incidence of grade 1-2 ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， and TPC （ P ＜0.05）， for the incidence of grade ≥3 ILD， ARX788 was significantly higher than TPC （ P ＜0.05）. For three indicators above， ARX788 and T-DXd combined with pertuzumab were ranked as the top two by SUCRA. CONCLUSIONS Compared with other ADCs， ARX788 and T-Duo are associated with a higher risk of pneumonitis and ILD in patients with breast cancer.

Background/Aims: Pancreatic stenting reduces post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP) and aids in cannulation in difficult cases. However, conservative endoscopists may stop at this step, resulting in suboptimal outcomes. This study assessed the efficacy of transpancreatic precut sphincterotomy (TPS) as a rescue procedure following pancreatic stenting. Methods: Between March 2013 and November 2018, 82 patients underwent pancreatic stenting at our institution prior to successful biliary cannulation. TPS was introduced in April 2016, and patients were divided into Before TPS and After TPS groups. The outcomes included cannulation success, PEP incidence, and predictors of TPS conversion. Results: There were 43 and 39 patients in the Before TPS and After TPS groups, respectively. Twenty-two patients (56.4%) underwent conversion to TPS in the After TPS group. The After TPS group had a higher bile duct cannulation rate (89.7% vs. 72.1%) than the Before TPS group, but this difference was not statistically significant (p=0.054). Multivariate analysis showed that age >50 years (odds ratio [OR], 0.181; p=0.021) and being in the After TPS group (OR, 0.712; p=0.039) were independently associated with reduced PEP risk. Haraldsson Type 2 and Type 4 papillae carried a relatively high TPS conversion rate. Conclusions A stepwise cannulation strategy that incorporates TPS after pancreatic stenting minimizes the need for advanced techniques and improves PEP outcomes.

Background: To investigate directional deviations between pilot holes and final pedicle screw trajectories in freehand placement and analyze risk factors for misplacement. While pedicle screws are widely used in thoracolumbosacral surgery, directional deviations between pilot holes and final screw trajectories remain understudied as potential risk factors for misplacement. Methods: Thirty-three patients undergoing posterior fixation were prospectively enrolled. Inertial measurement units (IMUs) tracked the spatial positions of pedicle finders and screwdrivers via custom software. Surgeons (n = 6) were stratified into senior, middle, and junior groups. Analyzed variables included the use of tapping, surgeon experience, spinal deformity status, screw tip morphology, and surgical parameters. Results: Among 198 implanted screws (6.00 ± 2.88/patient), all exhibited trajectory deviations (8.12° ± 3.47°). Tapping significantly reduced deviations (7.23° ± 3.23° vs. 8.87° ± 3.31°, p < 0.01). Senior surgeons achieved smaller deviations (7.34° ± 3.33°) than the middle group (8.60° ± 3.51°, p = 0.039) and junior group (8.68° ± 3.49°, p = 0.022). Multivariate analysis confirmed tapping (p = 0.001) and senior experience (p = 0.023) as protective factors. No significant associations emerged for spinal deformity (8.43° ± 3.73° vs. 7.97° ± 3.35°, p = 0.377), screw tip type (cylindrical, 8.43° ± 3.26° vs. tapered, 8.07 ± 3.51°; p = 0.637), obesity, or surgical position parameters. Conclusions Freehand pedicle screw placement consistently produces trajectory deviations from pilot holes, and surgeon experience and tapping are modifiable protective factors. The IMU-based tracking system enables quantitative surgical motion analysis, suggesting its utility for training optimization and technique standardization.