Medical artificial intelligence （AI） is a new type of application formed by the combination of machine learning， computer vision， natural language processing， and other technologies with clinical medical treatment. With the continuous iteration and development of relevant technologies， medical AI has shown great potential in improving the efficiency of diagnosis and treatment， and service quality， but it also increases the possibility of triggering ethical issues. Ethical issues resulting from the clinical application of medical AI were analyzed， including the lack of algorithmic interpretability and transparency of medical AI， leading to information asymmetry and cognitive discrepancies； the concerning status of security and privacy protection of medical data； and the complex and unclear division of responsibilities due to the collaborative participation of multiple subjects in the clinical application of medical AI， resulting in increased difficulty in the identification of medical accidents and clarification of responsibilities. The paper proposed the principles of not harming patients’ interests， physician’s subjectivity， fairness and inclusiveness， and rapid response. It also explored the strategies and implementation paths for responding to the ethical issues of medical AI from multiple perspectives， including standardizing the environment and processes， clarifying responsibility attribution， continuously assessing the impact of data protection， guaranteeing data security， ensuring model transparency and interpretability， carrying out multi-subject collaboration， as well as the principles of being driven by ethical values and adhering to the “human health-centeredness.” It aimed to provide guidance for the healthy development of medical AI， ensuring technological progress while effectively managing and mitigating accompanying ethical risks， thereby promoting the benign development of medical AI technology and better serving the healthcare industry and patients.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

Pancreatic cancers (PCs) is a common malignant tumor with poor prognosis in the digestive system. Its main treatment methods include surgery, radiotherapy, chemotherapy, and targeted therapy. The early diagnosis rate of hidden onset of PCs is low, and most patients have already lost the opportunity to undergo surgery when diagnosed with PCs. Chemotherapy is still the main treatment for advanced PCs, but the use of chemotherapy drugs in PCs can easily lead to drug resistance. The most significant feature that distinguishes PCs from other tumors is its rich and dense matrix, which not only hinders drug penetration but also impedes the infiltration of immune cells. The above reasons have led to a very low survival rate of PCs patients. Therefore, drug delivery systems are very important in the diagnosis and treatment of PCs. They can improve drug delivery, enhance biological barrier penetration, reduce side effects, and combine multiple treatment methods. Therefore, the treatment prospects of PCs are very broad. Currently, drug delivery systems widely applied in PCs primarily include nanodrug delivery systems, tumor microenvironment-targeted drug delivery system, immunotherapy drug delivery system, gene therapy drug delivery system, and combination therapy drug delivery system that synergize multiple therapeutic modalities. Emerging drug delivery systems (DDSs) have revolutionized PCs treatment by addressing these challenges through multiple mechanisms. Nanoformulations improve drug solubility, prolong circulation time, and reduce systemic toxicity via passive/active targeting. Smart DDSs responsive to PCs-specific stimuli enable extracellular matrix degradation, tumor-associated fibroblasts reprogramming, and vascular normalization to enhance drug accessibility. Last but not least, carrier systems loaded with myeloid-derived suppressor cell inhibitors or T cell activators can reverse immunosuppression and potentiate immunotherapy efficacy. Advanced platforms co-deliver chemotherapeutics with immunomodulators, gene-editing tools, or sonodynamic agents to achieve synergistic antitumor effects. These platforms aim to address critical challenges in PCs treatment, such as enhancing drug bioavailability, overcoming stromal barriers, reprogramming immunosuppressive niches, and achieving multi-mechanistic antitumor effects. This article provides a systematic summary and prospective analysis of the current development status, latest cutting-edge advances, opportunities, and challenges of the above-mentioned drug delivery systems in the field of PCs therapy.

Objective To compare the long-term prognosis of elderly patients with stageⅠnon-small cell lung cancer (NSCLC) after lobectomy or segmentectomy. Methods Data of elderly patients with stageⅠNSCLC between 2010 and 2020 were collected from the SEER database. According to the resection method, patients were divided into a lobectomy group and a segmentectomy group. The overall survival (OS) and lung cancer-specific survival (LCSS) of the two groups were compared by propensity score matching (lobectomy : segmentectomy=2 : 1). Results A total of 9990 patients were included, including 5840 (58.46%) females and 4150 (41.54%) males, with an average age of (70.48±6.47) years. Among them, 9029 patients were in the lobectomy group and 961 patients were in the segmentectomy group. After propensity score matching, a total of 2883 patients were matched, including 1 922 patients in the lobectomy group and 961 patients in the segmentectomy group. There was no statistical difference in baseline data between the two groups (P>0.05). The 10-year OS rate and LCSS rate of the lobectomy group were higher than those of the segmentectomy group (OS: 51.15% vs. 38.35%, P<0.01; LCSS: 79.68% vs. 71.52%, P<0.01). Subgroup analysis showed that the survival advantage of lobectomy was found in patients aged 60-<70 years and ≥80 years; for patients 70-<80 years, there was no statistical difference in OS or LCSS between the two surgical methods (P>0.05). In addition, for patients with tumor diameter ≤2 cm (stages ⅠA1-ⅠA2), lymph node dissection number≥10, and receiving adjuvant radiotherapy/chemotherapy, segmentectomy could also achieve a similar prognosis as lobectomy. Conclusion Overall, for elderly patients with stage ⅠNSCLC, lobectomy can achieve better OS and LCSS. However, individual differences, tumor characteristics, and perioperative treatment plans should be considered comprehensively to determine the surgical method for elderly patients with stageⅠNSCLC.

Objective To investigate the clinical value of 3.0 T functional magnetic resonance imaging in evaluating postoperative recurrence and treatment efficacy of glioma. Methods A retrospective analysis was conducted on the general clinical data of 67 patients who underwent glioma surgery at the Second Affiliated Hospital of Xingtai Medical University. All patients received chemotherapy for more than one month post-surgery. Recurrence of glioma was diagnosed based on secondary surgery or pathological biopsy results as the gold standard. From 3 to 6 months post-surgery, computerized tomography was used to measure cerebral blood volume (CBV), three-dimensional arterial spin labeling was used to measure cerebral blood flow (CBF) and relative CBF (rCBF), and diffusion-weighted imaging with and without contrast enhancement was used to measure apparent diffusion coefficient (ADC). Data were analyzed using SPSS 26.0 statistical software, and the t test or χ² test was used for inter-group comparisons based on data type. The receiver operating characteristic (ROC) curve was applied to evaluate the value of CBV, rCBF, and ADC in assessing postoperative recurrence and treatment efficacy of glioma. Results Patients with high-grade gliomas showed significantly higher CBV and rCBF and significantly lower ADC compared to those with low-grade gliomas (P < 0.05). The area under the ROC curve (AUC) of CBV, rCBF, and ADC in combination for grading glioma was 0.960, which was higher than those of individual indicators (0.790, 0.955, and 0.795, P < 0.05). The recurrence group had significantly higher CBV and rCBF and lower ADC compared to the non-recurrence group (P < 0.05). The AUC of CBV, rCBF, and ADC in combination for predicting postoperative glioma recurrence was 0.965, which was significantly higher than those of individual indicators (0.729, 0.929, and 0.941, P < 0.05). CBV and rCBF were lower and ADC was higher in the effective treatment group than in the ineffective treatment group (P < 0.05). The AUC of CBV, rCBF, and ADC in combination for evaluating glioma treatment efficacy was 0.985, which was higher than those of individual indicators (0.842, 0.898, and 0.961, P < 0.05). Conclusion The CBV, rCBF, and ADC in combination has shown high diagnostic accuracy and predictive efficacy in the evaluation of postoperative recurrence and treatment efficacy of glioma, which has important clinical application value.

[摘 要] 目的：探索外周免疫功能状态与肺癌转移的关联，筛选可用于肺癌转移“正虚”评估的外周血免疫标志物。方法：回顾性分析2023年3月至2025年4月期间上海中医药大学附属市中医医院收治的肺癌患者治疗前的外周血免疫标志物，根据是否存在远处转移，将患者分为无转移组与转移组，比较两组间免疫细胞和细胞因子的表达差异。将单因素分析P < 0.05的外周血免疫指标纳入多因素二元Logistic回归模型，以识别肺癌转移的独立预测因素。结果：共纳入193例肺癌患者（无转移组101例，转移组92例），两组在性别、年龄、吸烟史、饮酒史、病理类型间的差异均无统计学意义（均P > 0.05）。单因素分析显示，无转移组与转移组间有多项免疫指标存在显著差异（均P < 0.05），包括：淋巴细胞计数，CD3+、CD4+、CD8+ T、CD19+ B细胞及CD3-CD16+56+ NK细胞绝对计数，Treg细胞、CD8+CD28+ Treg细胞、G-MDSC和CD3-CD16+CD56+dim NK细胞百分率，以及细胞因子IL-1β、IL-6和IL-10水平。将差异性指标行二元Logistic回归分析，提示外周血中Treg细胞和CD8+CD28+ Treg细胞百分率是肺癌发生远处转移的独立预测因素[OR = 1.193, 95% CI（1.047, 1.36）, P < 0.01; OR = 0.978, 95% CI（0.957, 0.999）, P < 0.05]。结论：外周血免疫功能紊乱是肺癌转移“正虚”的生物学基础，本研究以量化指标证实外周免疫功能状态与肺癌转移的相关性，为“正虚伏毒”和“肿瘤转移态”理论提供了实证。