Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

Objective To introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.

BACKGROUND:The surgical treatment of severe lumbar fractures is mainly based on posterior short-segment fixation,and different pedicle screw fixation methods have differences in biomechanical properties.OBJECTIVE:To simulate three different screw fixation techniques in the treatment of severe L1 vertebral fractures using three-dimensional finite element technology,and to compare and analyze the biomechanical characteristics of the upper and lower intervertebral discs,fractured vertebrae,and internal fixation devices during the simulated spinal movement.METHODS:A three-dimensional model of the T11-L3 spine was established to simulate severely unstable fracture of the lumbar 1 vertebral body using the designed three pedicle screw fixation methods:Model A with 4 traditional pedicle screws(2 in each T12 and L2),model B with 4 Universal Spine System pedicle screws(2 in each T12 and L2),and Model C were bilateral intermediate fixation with 6 pedicle screws(2 in each of T12,L1,and L2).Restraint and load were applied to simulate the maximum stress and maximum displacement of the internal fixation,the displacement of the L1 vertebral body,and stress on the intervertebral discs superior and inferior to the injured vertebra during the anterior flexion,posterior extension,left-sided bending,right-sided bending and left-right rotation of the lumbar spine.RESULTS AND CONCLUSION:(1)The maximum displacement and motion range of the lumbar 1 vertebra with Model C in flexion and extension,left bending,right bending,left rotation,and right rotation were lowest in the tested motion states;the maximum stress of the screws and connecting rods was the smallest;and the maximum stress of intervertebral discs superior and inferior to the injured vertebra was the smallest.This was followed by the Model B,while the maximum displacement and motion range of the lumbar 1 vertebra and the stress and displacement of the screw connecting rod in the Model A were highest,but it showed the worst biomechanical stability and was more prone to adjacent segment degeneration.(2)These results show that bilateral intermediate fixation with six pedicle screws during the treatment of severe lumbar fractures is more dispersed in internal fixator stress and exhibits the least displacement and motion range of the vertebral pedicle screws and rods compared with four universal spinal system pedicle screws and four traditional pedicle screws.Thus,it can effectively reduce the occurrence of internal fixation failure and the adjacent segment degeneration.

BACKGROUND:The surgical treatment of severe lumbar fractures is mainly based on posterior short-segment fixation,and different pedicle screw fixation methods have differences in biomechanical properties.OBJECTIVE:To simulate three different screw fixation techniques in the treatment of severe L1 vertebral fractures using three-dimensional finite element technology,and to compare and analyze the biomechanical characteristics of the upper and lower intervertebral discs,fractured vertebrae,and internal fixation devices during the simulated spinal movement.METHODS:A three-dimensional model of the T11-L3 spine was established to simulate severely unstable fracture of the lumbar 1 vertebral body using the designed three pedicle screw fixation methods:Model A with 4 traditional pedicle screws(2 in each T12 and L2),model B with 4 Universal Spine System pedicle screws(2 in each T12 and L2),and Model C were bilateral intermediate fixation with 6 pedicle screws(2 in each of T12,L1,and L2).Restraint and load were applied to simulate the maximum stress and maximum displacement of the internal fixation,the displacement of the L1 vertebral body,and stress on the intervertebral discs superior and inferior to the injured vertebra during the anterior flexion,posterior extension,left-sided bending,right-sided bending and left-right rotation of the lumbar spine.RESULTS AND CONCLUSION:(1)The maximum displacement and motion range of the lumbar 1 vertebra with Model C in flexion and extension,left bending,right bending,left rotation,and right rotation were lowest in the tested motion states;the maximum stress of the screws and connecting rods was the smallest;and the maximum stress of intervertebral discs superior and inferior to the injured vertebra was the smallest.This was followed by the Model B,while the maximum displacement and motion range of the lumbar 1 vertebra and the stress and displacement of the screw connecting rod in the Model A were highest,but it showed the worst biomechanical stability and was more prone to adjacent segment degeneration.(2)These results show that bilateral intermediate fixation with six pedicle screws during the treatment of severe lumbar fractures is more dispersed in internal fixator stress and exhibits the least displacement and motion range of the vertebral pedicle screws and rods compared with four universal spinal system pedicle screws and four traditional pedicle screws.Thus,it can effectively reduce the occurrence of internal fixation failure and the adjacent segment degeneration.

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.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To compare the clinical efficacy of typeⅡhybrid surgery versus Sun’s surgery in treating acute Stanford A aortic dissection. Methods A retrospective analysis was conducted on the clinical data of patients with acute Stanford A aortic dissection who were treated at the Central Hospital of Wuhan affiliated to Tongji Medical College, Huazhong University of Science and Technology from 2016 to 2022. According to the surgical method, patients were divided into a typeⅡhybrid group and a Sun’s surgery group, and the clinical efficacy of the two groups was compared. Results A total of 52 patients were included, with 22 in the typeⅡhybrid surgery group and 30 in the Sun’s surgery group. The typeⅡhybrid group consisted of 18 males and 4 females, with an average age of (58.18±6.00) years, while the Sun’s surgery group consisted of 22 males and 8 females, with an average age of (53.03±11.89) years. All surgeries were successfully completed. There were 4 (13.3%) perioperative deaths in the Sun’s surgery group, including 2 patients of multiple organ failure, 1 patient of paraplegia, and 1 patient of uncontrollable postoperative bleeding. There was 1 (4.5%) perioperative death in the typeⅡhybrid surgery group, who was suspected of acute coronary syndrome and took a loading dose of dual antiplatelet drugs preoperatively. The patient underwent secondary thoracotomy for hemostasis, was re-cannulated during the operation, and finally died of circulatory failure after implantation of intra-aortic balloon pumping. There was no statistical difference in perioperative mortality between the two groups (P=0.381). Compared with the Sun’s surgery group, the typeⅡhybrid surgery group had shorter cardiopulmonary bypass time [153.00 (135.00, 185.25) min vs. 182.50 (166.50, 196.75) min, P=0.013], aortic cross-clamping time [77.00 (70.50, 92.00) min vs. 102.50 (93.50, 109.75) min, P<0.001], postoperative ICU stay [4.00 (2.83, 6.00) days vs. 8.00 (6.38, 11.78) days, P<0.001], postoperative ventilator support time [72.00 (29.50, 93.25) h vs. 87.65 (39.13, 139.13) h, P=0.138], less intraoperative blood loss [(1586.82±209.41) mL vs. (1 806.00±292.62) mL, P=0.004], postoperative 24 h drainage volume [612.50 (507.50, 762.50) mL vs. 687.50 (518.75, 993.75) mL, P=0.409], and shorter postoperative hospital stay [18.00 (13.00, 20.25) days vs. 22.00 (17.00, 29.25) days, P=0.013]. There was no statistically significant difference in the incidence of other early postoperative complications such as secondary thoracotomy for hemostasis, tracheotomy, renal dysfunction requiring dialysis, stroke, and paraplegia between the two groups (P>0.05). Conclusion For patients with acute Stanford A aortic dissection, typeⅡhybrid surgery is safe and effective; compared with traditional Sun’s surgery, typeⅡhybrid surgery has relatively less trauma, lower incidence of complications, satisfactory short-term results, and further research is needed on long-term prognosis.

OBJECTIVE To investigate the effects of calcitriol on sepsis-induced immunosuppression and its potential mechanism. METHODS A sepsis-induced immunosuppression mice model was established using cecal ligation and puncture （CLP）. The 7-day survival rate， serum levels of tumor necrosis factor- α （TNF- α）， interleukin-6 （IL-6）， and IL-1β were determined in sham operation group， CLP group and calcitriol group （1 μg/kg）； the morphological changes of lung tissue in mice were observed. Lipopolysaccharide （LPS） tolerance macrophage models （representing sepsis-induced immunosuppression） were established using mice macrophage cell line RAW264.7 cells. The levels of TNF-α and IL-6 in cell supernatants as well as mRNA expressions of IL-1β， nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 （NLRP3）， IL-18 and caspase-1 were assessed in culture medium group， LPS group， LPS tolerance group， and calcitriol （5 μmol/L） group. The following parameters were measured： propidium iodide （PI）-positive cell ratio， caspase-1 activity， lactate dehydrogenase （LDH） release， and Ca2+ levels. RESULTS Compared with CLP group， 7-day survival rate and serum levels of TNF-α， IL-6 and IL-1β were increased significantly in calcitriol group （P＜0.05）. Additionally， pulmonary tissue damage was markedly attenuated in calcitriol group. Compared with LPS tolerance group， the levels of TNF-α and IL-6 in cell supernatants， mRNA expressions of IL- 1β， NLRP3， IL-18 and caspase-1， PI-positive cell ratio， caspase-1 activity， LDH release， and Ca2+ levels were all increased significantly in calcitriol group （P＜0.05）. CONCLUSIONS Calcitriol can reverse sepsis-induced immunosuppression， and the mechanism of action may be E-mail：yarfwy@163.com achieved by the binding of calcitriol to vitamin D receptor，which promotes the release of Ca2+ from the endoplasmic reticulum， thereby driving the NLRP3/caspase-1-mediated pyroptosis pathway.

Breast milk is the optimal natural food for newborns. However， some newborns cannot receive maternal breast milk due to reasons such as mother-infant separation or insufficient lactation. The establishment of human milk banks （HMB） can effectively address these issues， thereby increasing the breastfeeding rate among hospitalized newborns and improving their quality of survival. However， HMB in China is still in the development and improvement stage. Its implementation involves a series of ethical issues， such as informed consent， privacy protection， economic incentives， quality and safety， and fair resource distribution， which hinder HMB’s widespread promotion. Therefore， discussing the ethical dilemmas faced by the widespread establishment of HMB in China’s hospitals and analyzing coping strategies are crucial for improving the breastfeeding rate of newborns. This paper deeply analyzed and sorted out the ethical issues and challenges currently faced by HMB in China， and proposed corresponding strategies， including “ensuring informed consent and voluntary participation of both donors and recipients，” “protecting the privacy of donors and recipients，” “establishing an ethics-based moral incentive and social support system，” “strictly controlling quality and safety issues”， and “developing fair and rational policies，” aiming to provide a reference solution for addressing ethical concerns in the establishment and operation of HMB.