目的 探究磁共振成像三维快速自旋回波序列（CUBE）序列在眼眶肿瘤及肿瘤样病变中的诊断价值。方法 选取2023年5月—2025年6月郑州市第二人民医院收治的眼眶肿瘤及肿瘤样病变患者89例为研究对象，依据病理诊断结果分为眼眶肿瘤组（43例）及肿瘤样病变组（46例）。分别采用病理检查及磁共振成像CUBE序列对研究对象进行检测。比较眼眶肿瘤组与肿瘤样病变组的资料。采用Kappa检验比较病理金标准与磁共振成像CUBE序列鉴别诊断的一致性。采用2×2列联表分析磁共振成像CUBE鉴别眼眶肿瘤及肿瘤样病变的诊断效能。结果 病理鉴别诊断结果与磁共振成像CUBE序列结果比较，差异无统计学意义（P＞0.05）。眼眶肿瘤组与肿瘤样病变组的资料比较，差异无统计学意义（P＞0.05）。Kappa检验发现，磁共振成像CUBE序列鉴别眼眶肿瘤与肿瘤样病变与病理金标准比较的Kappa值为0.820，一致性较高（P＜0.05）。磁共振成像CUBE序列鉴别眼眶肿瘤及肿瘤样病变的灵敏度为88.37%，特异度为93.48%，准确度为91.01%，误诊率为6.52%，漏诊率为11.63%，约登指数为81.85%，阳性预测概率为92.68%，阴性预测概率为89.58%。结论 磁共振成像CUBE序列鉴别诊断成人眼眶肿瘤及肿瘤样病变与病理诊断结果的一致性较高。

     Objective To investigate the diagnostic value of the three-dimensional fast spin echo sequence（CUBE）in magnetic resonance imaging for orbital tumors and tumor-like lesions．Methods From May 2023 to June 2025，89 patients with orbital tumors and tumor like lesions were included as the study subjects．Based on pathological diagnosis results，they were separated into orbital tumor group（43 cases）and tumor like lesion group（46 cases）．The pathological examination and magnetic resonance imaging CUBE sequence were used to scan the study subjects．The data were compared between the orbital tumor group and the tumor like lesion group．Kappa test was used to compare the consistency of differential diagnosis between pathological gold standard and magnetic resonance imaging CUBE sequence．A 2×2 contingency table was uesd to analyze the diagnostic performance of magnetic resonance imaging CUBE in differentiating orbital tumors and tumor-like lesions．Results The difference between the pathological differential diagnosis results and the magnetic resonance imaging CUBE sequence was not statistically significant（P＞0.05）．The data comparison between the orbital tumor group and the tumor like lesion group showed no statistical difference（P＞0.05）．The Kappa test found that the Kappa value of 0.820 for differentiating orbital tumors from tumor like lesions using the magnetic resonance imaging CUBE sequence compared to the pathological gold standard was highly consistent（P＜0.05）．The sensitivity，specificity，accuracy，misdiagnosis rate，missed diagnosis rate，Youden index，positive predictive probability，and negative predictive probability of magnetic resonance imaging CUBE sequence in differentiating orbital tumors and tumor like lesions were 88.37%，93.48%，91.01%，6.52%，11.63%，81.85%，92.68% and 89.58%，respectively．Conclusions The magnetic resonance imaging CUBE sequence has a high consistency with pathological diagnosis results in the differential diagnosis of orbital tumors and tumor like lesions．

       目的 验证尿沉渣评分（USS）对肾前性急性肾损伤（AKI）与急性肾小管坏死（ATN）的鉴别价值，评估USS与AKI严重程度及预后的相关性，为优化AKI分层管理提供依据。方法 回顾性分析2021年3月至2022年2月在郑州市中医院治疗的120 AKI患者，根据肾组织活检及改良FENa-UA诊断标准分为肾前性AKI组（n=68）与ATN组（n=52），于入院日检测USS、血清胱抑素C（Cys-C）及尿中性粒细胞明胶酶相关脂质运载蛋白（NGAL），分析USS诊断效能。结果 ATN组USS高于肾前性组（P＜0.001），且评分随AKI分期升高而增加（P＜0.001）。USS诊断肾前性AKI的ROC曲线下面积（AUC）为0.892，联合Cys-C与NGAL后AUC提升至0.941，灵敏度与特异度分别达90.12%和88.51%。结论 USS通过量化肾小管结构性损伤，可早期鉴别肾前性AKI与ATN，其与Cys-C、NGAL的联合应用提高诊断准确性，且对AKI预后具有重要价值，为临床分层管理提供客观依据。

       Objective To validate the discriminative value of urinary sediment score（USS）in differentiating prerenal acute kidney injury（AKI）from acute tubular necrosis（ATN），and to evaluate the correlation between USS and AKI severity/prognosis，providing evidence for optimizing stratified AKI management．Methods A retrospective analysis was conducted on 120 AKI patients treated at Zhengzhou Traditional Chinese Medicine Hospital from March 2021 to February 2022．According to renal tissue biopsy and modified FENa-UA diagnostic criteria，patients were divided into a prerenal AKI group（n=68）and an ATN group（n=52）．On the day of admission，USS，serum cystatin C（Cys-C），and urinary neutrophil gelatinase-associated lipocalin（NGAL）were measured to analyze the diagnostic performance of USS．Results USS was significantly higher in ATN group than prerenal group（P＜0.001），and increased with advancing AKI stages（P＜0.001）．The area under the ROC curve（AUC）of USS for diagnosing prerenal AKI was 0.892，which improved to 0.941 when combined with Cys-C and NGAL，yielding sensitivity and specificity of 90.12% and 88.51%，respectively．Conclusions USS quantifies structural damage to the renal tubules，allowing for early differentiation between prerenal AKI and ATN．Its combined use with Cys-C and NGAL improves diagnostic accuracy and is of significant value in predicting AKI prognosis，providing an objective basis for clinical stratified management．

       自闭症谱系障碍（ASD）是一类神经发育障碍性疾病，其核心临床表现为社交行为障碍、语言沟通困难以及重复刻板行为。早期诊断并进行早期行为干预，是目前能改善患者临床症状且减少终身残疾的主要措施。但早期诊断困难，因为目前所采用的行为量表，比如ABC（异常行为检查表）等，在儿童生命早期阶段，如2岁左右，很难准确地反应出被试者的社交行为或者语言交流能力；而且，其判断也非常依赖于医生的经验，具有一定的主观性。近年来，随着脑影像技术，比如核磁共振（MRI），特别是功能性核磁共振（fMRI），以及人工智能技术（AI）的飞速发展，为ASD的早期诊断，从无创、客观、以及神经活动异常-行为异常偶联的角度，展示了一种新的机遇。本文比较系统地介绍了ASD的临床基础与诊断挑战，并详细阐述了AI在ASD早期诊断中的数据来源、核心算法和典型研究案例。通过分析当前技术面临的挑战与局限性，提出未来研究方向与临床转化路径，以期进一步加强AI在ASD早期诊断中的临床使用研究，使之最终能高效的服务于临床。

   Autism spectrum disorder（ASD）is a group of neurodevelopmental disorders clinically characterized by deficits in social interaction and verbal communication，along with repetitive behaviors．Early diagnoses，followed by early behavioral interventions，are currently effective strategies to attenuate clinical symptoms and improve patient outcomes in ASD; however，early diagnosis remains challenging at present．Current diagnostic tools，such as the Aberrant Behavior Checklist（ABC），have difficulty in accurately evaluating social engagement and verbal communication in early childhood（e.g. ，at 2 years of age）．Furthermore，such evaluations may be somewhat subjective，as they rely，at least partially，on clinicians’ experience．Recently，with the rapid development of brain imaging techniques（e.g. ，MRI，especially fMRI）and artificial intelligence（AI），a significant opportunity has emerged to develop novel early-diagnostic tools for ASD．These tools exhibit clear advantages，including being non-invasive，more objective，and focusing on the coupling of abnormalities in both neuronal activity and behavioral responses．Here，we systematically introduce the clinical features of ASD，discuss the challenges in early diagnosis，and review the current status of AI-driven diagnostic tool development in detail，including data acquisition methods，computational architectures，and typical clinical applications．Through a detailed analysis of the technical challenges，advantages，and limitations of these tools，we propose future research directions，aiming to eventually establish highly valuable AI-based diagnostic approaches for clinical use in ASD care．

       目的 在体外诊断试剂（IVDR）临床试验中，准确快速地完成EP09c的统计分析工作。方法 利用MedCalc软件对差异图（Difference Plot）执行偏倚量化；利用SPSS或MedCalc软件的回归模型对散点图（Scatter Plot）执行偏倚量化；差异图和散点图被用于确认偏倚量化结果的正确性。结果 MedCalc的差异图确定工作样本的低浓度数据符合恒定标准差分布，偏倚为0.10（0.09，0.28）；高浓度数据符合恒定变异系数分布，偏倚为-5.0%（中位数：-7.2%，1.5%）或-3.2%（Hodges-Lehmann中位数：-5.5%，-0.8%）。散点图确认Passing&Bablok回归和加权线性回归（权重1/x_i ^1.4）适用于工作样本的数据，回归方程分别为y=0.122+0.952x（R²=0.983）和y=0.269+0.977^x（R²=0.981）。结论 偏倚量化结果必须得到差异图和散点图的确认，否则结果的正确性无法保证。

      Objective To perform accurate and efficient statistical analysis of EP09c in clinical studies of in vitro diagnostic reagents（IVDR）．Methods Bias quantification was performed on the difference plot using MedCalc．Bias quantification was conducted on the scatter plot using regression modeling in SPSS and MedCalc．The difference plot and scatter plot were employed to corroborate the accuracy of the bias quantification results．Results Difference plots demonstrated that the low-concentration data of the working sample exhibited a constant standard deviation distribution with a bias of 0.10（0.09，0.28），while the high-concentration data conformed to a constant coefficient of variation distribution with a bias of -5.0%（median：-7.2%，1.5%） or -3.2%（Hodges-Lehmann median：-5.5%，-0.8%）．Scatter plots confirmed that Passing & Bablok（P-B） regression and weighted least square（WLS） regression（weight 1/x_i ^1.4） were applicable to the data from the working sample，with the resulting regression equations being y=0.122+0.952x（R²=0.983） and y=0.269+0.977x（R²=0.981），respectively．Conclusions The results of bias quantification must be confirmed by difference plot and scatter plot，otherwise the correctness of the results cannot be assured．

       目的 探讨肌少症性肥胖（SO）诊断标准的演进及其在中国老年人群中的本土化综合干预路径。方法 评述ESPEN/EASO最新共识，结合我国老年人代谢特征，系统分析“筛查-诊断-分期”流程及运动营养协同干预的临床效能。结果 SO诊断核心在于识别“隐性肥胖”，建议在AWGS2019标准基础上，叠加中国特异性腰围切点（男≥90 cm，女≥85 cm）或体脂率指标，并应用ALM/BMI校正肌肉质量。研究证实，以渐进式抗阻训练联合高蛋白营养（1.2~1.5 g·kg-1·d-1）为核心的协同模式，通过激活mTOR通路可显著逆转肌肉流失并改善胰岛素抵抗。融入八段锦等传统功法及乳清蛋白补充，能有效重塑中国患者“高碳水、低蛋白”的膳食习惯，提升依从性。结论 构建护士主导、社区依托的多学科管理模式，并借助远程健康工具实现闭环监测，是提升我国SO精准诊疗水平的关键路径。

      Objective To explore the evolution of diagnostic criteria for sarcopenic obesity（SO）and its localized comprehensive intervention pathways tailored to the metabolic characteristics of the Chinese elderly population．Methods The latest ESPEN/EASO consensus was reviewed．Combined with the metabolic profile of Chinese older adults，the “screening-diagnosis-staging” workflow and the clinical efficacy of synergistic exercise and nutrition interventions were systematically analyzed．Results The core of SO diagnosis lies in identifying “hidden obesity．”It is recommended to incorporate Chinese-specific waist circumference cut-offs（male≥90 cm，female≥85 cm）or body fat percentage into the AWGS2019 framework，utilizing ALM/BMI for muscle mass calibration．Evidence suggests that a synergistic model，centered on progressive resistance training（PRT）and high-protein nutrition（1.2~1.5 g·kg-1·d-1），can significantly reverse muscle loss and improve insulin resistance by activating the mTOR pathway．Integrating traditional Chinese exercises（e. g. ，Baduanjin）and whey protein supplementation effectively reshapes the “high-carbohydrate，low-protein” dietary habits of Chinese patients，thereby enhancing intervention adherence．Conclusions Establishing a nurse-led，community-based multidisciplinary management model，integrated with digital health tools for closed-loop monitoring，is a pivotal strategy for enhancing the precision of SO diagnosis and treatment in China．

       目的   探讨孕中晚期口腔二维轴向切面超声在产前诊断胎儿唇腭裂中的应用价值，评估其对唇裂、唇腭裂及继发腭裂的检出率和准确性。方法   本研究为前瞻性研究，共纳入2020年3月—2023年12月在我院超声科行产前超声诊断的3 666例孕中晚期胎儿，其中经超声检查诊断出111例唇腭裂，这些病例归为唇腭裂组，其余3 555例归入正常对照组。所有受试者均通过口腔二维轴向切面超声进行评估，诊断结果经产后随访确认。结果   在正常对照组中，上唇及上牙槽突的评估成功率为100%，软硬腭分界线显示率为99%，软腭显示率为85%。在唇腭裂组中，超声对唇裂、唇腭裂及继发腭裂的检出率分别为45%、48%和7%，且超声诊断的灵敏度、特异度和预测值均超过98%。结论   孕中晚期口腔二维轴向切面超声在产前诊断胎儿唇腭裂中具有较高的准确性和可靠性，为早期干预和临床管理提供了重要的影像学依据。

       Objective  To explore the application value of two-dimensional axial section ultrasound in prenatal diagnosis of fetal cleft lip and palate in the second and third trimesters of pregnancy，and to evaluate its detection rate and accuracy for cleft lip，cleft lip and palate，and secondary cleft palate．Methods  This study is a prospective study that included 3 666 fetuses in the second and third trimesters of pregnancy．Among them，111 cases of cleft lip and palate were diagnosed by ultrasound examination．These cases were classified as the cleft lip and palate group，and the remaining 3 555 cases were classified as the normal control group．All subjects were evaluated by oral two-dimensional axial section ultrasound，and the diagnostic  results were confirmed by postpartum follow-up．Results  In the normal control group，the success rates of evaluating the upper lip and upper alveolar process were 100%．The present rate of the soft hard palate boundary was 99%，and the present rate of the soft palate was 85%．In the cleft lip and palate group，the detection rates of cleft lip，cleft lip and palate，and secondary cleft palate by ultrasound were 45%，48% and 7% respectively，and the sensitivity，specificity，and predictive value of ultrasound diagnosis exceeded 98%．Conclusions  Two dimensional axial section ultrasound of the oral cavity in second and third trimesters of pregnancy has high accuracy and reliability in prenatal diagnosis of fetal cleft lip and palate，providing strong imaging evidence for early intervention and clinical management．

        目的   探讨临床特征联合外周血血管内皮生长因子（VEGF）与α-羟基丁酸脱氢酶（α-HBDH）对卵巢癌的诊断价值。方法   选取2022年6月—2024年6月在天津市中心妇产科医院妇科接收的84例卵巢癌恶性肿瘤患者纳入观察组，同期选取84例卵巢良性病变患者纳入对照组。对比两组患者临床资料及VEGF、α-HBDH水平的差异，分析VEGF、α-HBDH水平与卵巢癌恶性肿瘤患者临床特征的相关性。采用二元Logistics回归分析卵巢癌恶性肿瘤的独立危险因素，并采用受试者工作特征（ROC）曲线分析VEGF、α-HBDH水平诊断卵巢癌恶性肿瘤的价值。结果   观察组年龄、身体质量指数（BMI）及血清CA125、HE4、VEGF、α-HBDH水平显著高于对照组（P＜0.05），VEGF与α-HBDH水平与国际妇产科联盟（FIGO）分期、分化等级及淋巴结转移均呈正相关关系（P＜0.05）。将年龄、BMI、VEGF、α-HBDH作为自变量纳入二元Logistic回归，结果显示BMI、VEGF、α-HBDH是卵巢癌恶性肿瘤的影响因素（P＜0.05），ROC曲线分析显示，联合检测VEGF和α-HBDH的AUC达0.921，灵敏度和特异度分别为81.0%和91.7%，优于单独检测（VEGF：AUC=0.702；α-HBDH：AUC=0.796）。结论  BMI联合VEGF与α-HBDH检测可为卵巢癌的诊断提供高效、无创的辅助手段，具有重要临床应用潜力。

      Objective  To explore the  diagnostic value of clinical features combined with  peripheral  blood vascular endothelial growth factor（VEGF）and α-hydroxybutyrate dehydrogenase（α-HBDH）levels in ovarian cancer．Methods  A total of 84 patients with malignant ovarian cancer admitted to the gynecology department of Tianjin Central Hospital of Gynecology and Obstetrics from June 2022 to June 2024 were included in the observation group，and 84 patients with benign ovarian lesions during the same period were included in the control group．The clinical data and VEGF，α-HBDH levels of the two groups were compared．Pearson analysis was used to explore the correlation between VEGF，α-HBDH levels，and clinical characteristics of patients with malignant ovarian cancer．Binary Logistic regression analysis was conducted to identify independent risk factors for malignant ovarian cancer，and receiver operating characteristic（ROC） curves were used to analyze the diagnostic value of VEGF and α-HBDH levels for malignant ovarian cancer．Results  The observation group had significantly higher age，BMI，and serum CA125，HE4，VEGF，α-HBDH levels compared to the control group（P＜0.05）．VEGF and α-HBDH levels were significantly positively correlated with FIGO stage，differentiation grade，and lymph node metastasis（P＜0.05）．Age，BMI，VEGF，and α-HBDH were included as independent variables in binary Logistic regression，and the results showed that BMI，VEGF，and α-HBDH levelswere independent risk factors for malignant ovarian cancer（P＜0.05）．ROC curve analysis  revealed that the AUC for combined detection of VEGF and α-HBDH reached 0.921，with sensitivity and specificity of 81.0% and 91.7%，respectively，significantly superior to individual detection（VEGF：AUC=0.702；α-HBDH：AUC=0.796）．Conclusions  The detection of BMI combined with VEGF and α-HBDH levels can provide an efficient and noninvasive auxiliary means for the diagnosis of ovarian cancer，which has important clinical application potential．

       目的   评估ChatGPT 4与Llama 3微调模型在乳腺癌诊断中的应用效果，特别是在超声、钼靶及超声联合钼靶的非结构化报告和影像诊断方面。方法   回顾性收集了689例同时接受乳腺超声和钼靶检查的患者数据，比较两种模型在文本和图像模态下的诊断性能，并探讨乳腺密度对模型表现的影响。结果   在文本模态下，微调Llama 3表现优异，联合诊断准确率达91.7%，优于ChatGPT 4的71.7%。图像模态中两模型准确率均低于70%，但ChatGPT 4灵敏度较高（78.3%），Llama 3特异度突出（98.3%）。分组分析表明，在非致密型乳腺中钼靶表现更佳，而致密型乳腺中超声诊断更具优势。结论   大语言模型在医学图像处理和多模态整合方面仍需进一步优化，医学领域微调的大语言模型在处理非结构化临床文本方面具有潜力。

       Objective  To evaluate the application effectiveness of ChatGPT 4 and the fine-tuned Llama 3 model in breast cancer diagnosis，particularly in processing unstructured reports and diagnostic imaging of ultrasound，mammography，and their combined modalities．Methods  Retrospective data from 689 patients who underwent both breast ultrasound and mammography examinations were collected．The diagnostic performance of the two models was compared across text and image modalities，and the impact of breast density on model performance was explored．Results  In the text modality，the fine-tuned Llama 3 model performed excellently，achieving a combined diagnostic accuracy of 91.7%，outperforming 71.7% of ChatGPT 4．In the image modality，both models had accuracies below 70%，but ChatGPT 4 exhibited higher sensitivity（78.3%），while Llama 3 demonstrated outstanding specificity（98.3%）．Subgroup analysis indicated that mammography performed better in non-dense breasts，whereas ultrasound was more advantageous in dense breasts．Conclusions  The large language models  still  require further optimization in medical image processing and multimodal integration，but fine-tuned large language models in the medical field show potential in handling unstructured clinical texts．

       目的   针对孤独症多模态证据融合与定量化辨识的关键问题，本研究提出基于图卷积神经网络（GCN）的孤独症谱系障碍（ASD）诊断模型研究思路。方法  通过对来源于ABIDE的ASD儿童脑部fMRI数据进行整理和筛选，提取脑区功能连接矩阵作为图结构的邻接矩阵，并融合临床表型数据，构建了ASD多模态关联网络。通过网络特征比较分析，识别出了ASD与典型发育组的脑功能连接网络组间差异。进一步地构建一个端到端的GCN模型，并尝试引入注意力机制，提高模型决策的可解释性。结果  该模型在诊断性能指标优于传统机器学习方法（准确率=0.710，精确率=0.709，召回率=0.780，F1=0.743，曲线下面积=0.746）。背侧注意网络与边缘系统-颞极枢纽的功能连接减弱是模型做出判断的最主要依据。结论  以异质图为多模态数据整合的基本架构，本模型为ASD的潜在病理机制探索提供了新的方法学范例。

      Objective   To develop a quantitative model for autism spectrum disorder（ASD）integration multimodal evidences．Methods The fMRI  dataset from ABIDE was  used for extracting connectivity function  network of ASD after  data preprocessing．Difference between ASD and typical development about their brain connectivity function was evaluated with t-test．Integrating phenotypic data and fMRI dataset，an graph convolutional neural network （GCN）with attention module was estimated and compared against benchmark models about their efficiency and interpretability．Results  The GCN model was evaluated outperformed other models with better accuracy indices．And regions from Dorsal Attention Network and Limbic-Temporal Pole were ranked as the highest weights for the differentiation in the model．Conclusions  This study provided a novel paradigm for quantitative diagnosis and exploring pathogenesis of ASD．

中医诊断学是一门中医学专业的主干课程, 也是连接基础理论与临床实践的桥梁课程,其知识点繁杂、实践性强导致学生感觉枯燥无味, 教师教学质量欠佳。随着“互联网+教育”的高速发展, 混合式教学作为一种创新型教学模式,有诸多优势, 但也存在一些不足。文章从多元化教学方法、思政教育、多元化评价三个方面出发, 研究创新混合教学模式措施, 以期提升教学效果,提高学生的中医思维能力和临床水平, 培养学生的医德医风,实现知识传授与价值引领, 为社会输送德才兼备的中医药人才。文章研究了中医诊断学课程混合教学模式的教学现状和实践探索, 以进一步提高教学质量, 可为各大中医院校混合教学模式的开展提供借鉴。

Traditional Chinese medicine（TCM）diagnostics is a main course of TCM specialty, and it is also a bridge course connecting basic theory and clinical practice．Its complex knowledge and strong practicability lead to students feeling bored and poor teaching quality．With the rapid development of “Internet + Education”, blended teaching, as an innovative teaching mode,has many advantages, but it also has some shortcomings．This paper starts from three aspects of diversified teaching methods, civic education and diversified evaluation to study the measures of innovative mixed teaching mode, with a view to enhancing the teaching effect, improving the students’ thinking ability and clinical level of Chinese medicine, cultivating the students’ medical ethics and medical style,realizing the knowledge pass on and value leadership, and delivering both moral and talented talents in traditional Chinese medicine for the society．This paper studies the teaching status and practical exploration of the mixed teaching mode of TCM diagnostics curriculum in order to further improve the teaching quality and provide reference for the development of the mixed teaching mode in major TCM colleges．