Both cathartic colon （CC） and cathartic-dependent constipation （CDC） are caused by the abuse of stimulant laxatives， while their concepts are not completely the same.Starting from the disease name of CC， this article traced the origin and evolution of the concept of CC， summarizes and compared the similarities and differences between CC， CDC， and slow transit constipation （STC）， and called for strict differentiation among the three.Furthermore， this article explored the specific contents of Western medicine clinical subtypes and traditional Chinese medicine （TCM） syndrome differentiation of CDC and delved into the TCM pathogenesis of CDC according to both literature and clinical practice.The relationship between clinical subtypes and TCM syndromes was established， and the syndrome characteristics of CDC of different clinical subtypes and TCM syndromes were summarized.The recommended prescriptions for corresponding syndromes were listed.A systematic CDC diagnosis and treatment approach of "clinical subtypes-syndrome differentiation-syndrome characteristics-recommended prescriptions" was thus formed.Additionally， the paper provides an overview of current research on CDC in both Western medicine and TCM contexts， identifies future research directions， and suggests research pathways for refining and advancing CDC studies.

ObjectiveTo observe the clinical efficacy of the Yiqi Yangyin Huoxue prescription （YYHP） in the treatment of cathartic colon （CC） and its effects on fecal short-chain fatty acids （SCFAs）， and to explore the correlations among CC severity indicators and between these indicators and patient history. MethodsAccording to the inclusion and exclusion criteria， 98 patients meeting the diagnostic criteria of both traditional Chinese and Western medicine for CC with the syndrome of Qi-Yin deficiency complicated by blood stasis were randomly assigned to an observation group and a control group. The observation group received YYHP granules， while the control group received lactulose. Both medications were administered twice daily， one sachet each time， half an hour after breakfast and dinner， with a treatment course of 8 weeks. The primary constipation symptom score， Patient Assessment of Constipation Quality of Life （PAC-QOL） score， and TCM syndrome score were assessed before and after treatment and at the 8^th week after the end of treatment. The overall clinical effective rate， as well as the efficacy attenuation index and degree， were evaluated. Fecal SCFA levels were measured using gas chromatography-mass spectrometry （GC-MS）. Spearman correlation analysis was performed to explore the correlations among CC severity indicators and between these indicators and patient history. ResultsThe overall clinical effective rate in the observation group （95.83%） was higher than that in the control group （78.72%） （P<0.05）. After treatment， the total scores for primary constipation symptoms， PAC-QOL， and TCM syndromes decreased in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. The severity of all primary constipation symptoms was alleviated in both groups （P<0.05）. In terms of "excessive straining and difficult defecation"， "anal heaviness， incomplete evacuation， and bloating sensation"， "abdominal distension"， and "defecation frequency"， the observation group showed better efficacy than the control group （P<0.05）. Scores of the four PAC-QOL dimensions and the scores and severity of primary and secondary TCM symptoms were reduced in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. After treatment， acetic acid， propionic acid， butyric acid， and total SCFAs in the observation group increased significantly （P<0.05）. The efficacy attenuation index and degree in the observation group were lower than those in the control group （P<0.05）. No severe adverse reactions occurred in either group， and there was no statistically significant difference in the incidence of adverse reactions between the two groups. Positive correlations of varying degrees were observed among the total scores of primary constipation symptoms， PAC-QOL， and TCM syndromes， as well as between these scores and the history of stimulant laxative use， disease duration， and age. ConclusionYYHP can effectively alleviate the primary constipation symptoms in CC patients， improve quality of life， and ameliorate TCM syndromes， with good safety. It also has the advantage of a lower rebound degree after drug withdrawal， and its mechanism may be related to increasing fecal SCFA levels. Long-term abuse of stimulant laxatives may aggravate the severity of CC and prolong the disease course.

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.

Flap transplantation is a critical surgical strategy for the reconstruction of tissue defects caused by trauma, tumor resection, and congenital malformations, and its survival rate directly determines surgical efficacy and patient prognosis. Following transplantation, flaps inevitably undergo ischemia-reperfusion (I/R) injury, during which oxidative stress, inflammatory responses, and metabolic disturbances are intricately intertwined, ultimately leading to cellular injury and tissue necrosis. Recent studies have demonstrated that multiple forms of programmed cell death—including apoptosis, pyroptosis, ferroptosis, necroptosis, and PANoptosis—play central roles in flap I/R injury. The extensive crosstalk and molecular interactions among these pathways form a highly complex cell death network. Specifically, apoptosis is mediated by the imbalance of Bcl-2 family proteins and the activation of cysteine-dependent aspartate-specific protease (caspase) cascades; pyroptosis is driven by the NLRP3-caspase-1-GSDMD axis, resulting in membrane pore formation and the release of pro-inflammatory cytokines; ferroptosis is characterized by iron-dependent lipid peroxidation and dysfunction of glutathione peroxidase 4 (GPX4); necroptosis is triggered by the receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-RIPK3-MLKL signaling complex, leading to membrane rupture; and PANoptosis represents an integrated form of inflammatory cell death that coordinates multiple death pathways. Importantly, these forms of programmed cell death are not independent but are interconnected through extensive signaling crosstalk. Key regulatory molecules, including caspase-8, reactive oxygen species (ROS), nuclear factor-κB (NF-κB), and nuclear factor erythroid 2-related factor 2 (Nrf2), collectively modulate the dynamic balance among these pathways. Therefore, the multidimensional interplay and spatiotemporal dynamics of programmed cell death constitute a fundamental pathological basis of flap I/R injury. This review systematically summarizes the latest advances in the mechanisms and interactions of various programmed cell death pathways in flap I/R injury, aiming to elucidate the underlying regulatory network. These insights may provide novel theoretical foundations for optimizing flap protection strategies, improving flap survival, and promoting tissue repair.

[摘 要] 目的：探讨麻疹-流行性腮腺炎-风疹联合减毒活疫苗（MMR）通过诱导免疫原性细胞死亡（ICD）对三阴性乳腺癌（TNBC）的免疫调节机制。方法：体外实验采用CCK-8法检测MMR对TNBC细胞4T1和MDA-MB-231存活率的影响，免疫荧光法检测MDA-MB-231细胞中钙网蛋白（CALR）表达，磷钼酸比色法检测MDA-MB-231细胞内ATP的含量，ELISA检测细胞上清液中高迁移率族蛋白B1（HMGB1）的表达水平，通过GEPIA网站分析CALR和HMGB1对乳腺癌患者生存期的影响。体内实验中经皮下注射4T1-Luc细胞于雌性BALB/c小鼠乳腺脂肪垫构建TNBC小鼠模型。设Control组、盐酸阿霉素（Dox）组、MMR组，按照分组每两天静脉给药1次，连续给药3次。动物活体成像系统观察肿瘤体积变化；记录小鼠体质量及各器官指数初步评估疫苗安全性；H-E染色观察肿瘤病理变化；免疫组化和Western blotting检测肿瘤中CALR和HMGB1蛋白的表达。流式细胞术分析小鼠脾T淋巴细胞亚群及肿瘤树突状细胞和巨噬细胞比例；免疫组化检测肿瘤CD8+ T淋巴细胞浸润；ELISA检测血清中促炎细胞因子IL-6和TNF-α含量。结果：MMR对4T1细胞的活性抑制作用较弱；MMR对MDA-MB-231细胞抑制率达90.39%（P < 0.001）。与Control组相比，MMR组MDA-MB-231细胞中ICD相关蛋白（CALR、ATP、HMGB1）表达上调（P < 0.001）。GEPIA网站分析表明，CALR和HMGB1高表达的患者总生存期有所延长。MMR延缓了荷瘤小鼠肿瘤体积增长（P < 0.001），延长小鼠的生存期，且28 d内MMR组荷瘤小鼠体重与Control组无显著性差异（P > 0.05）；H-E染色显示，与Control组相比，MMR组小鼠肿瘤组织坏死区域扩大且有免疫细胞浸润；MMR上调肿瘤ICD相关蛋白CALR、HMGB1的表达水平；MMR组脾CD4+、CD8+ T淋巴细胞及肿瘤树突状细胞和M1型巨噬细胞的比例增加（P < 0.05），CD8+ T淋巴细胞在肿瘤组织中的浸润增加（P < 0.001），且促炎细胞因子IL-6和TNF-α水平升高（P < 0.01）。结论：MMR减毒活疫苗对TNBC的抗肿瘤作用可能与诱导肿瘤发生ICD进而激活抗肿瘤免疫相关。

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To identify risk factors associated with lymphatic leakage after laparoscopic radical prostatectomy(LRP)and to develop a machine learning-based nomogram for predicting such outcomes to support clinical prevention strategies.Methods We retrospectively analyzed perioperative data from 248 patients who underwent radical prostatectomy for prostate cancer between January 2020 and January 2024.Independent risk factors were identified through univariate and multivariate logistic regression analyses.A predictive model was developed,and its diagnostic performance was assessed by the area under the receiver operating characteristic curve(AUC).Five-fold cross-validation was performed to evaluate the model's generalizability.A nomogram was subsequently constructed to facilitate individualized risk quantification.Results Among the 248 patients,89(35.9%)developed lymphatic leakage,while 159(64.1%)did not.Independent risk factors for lymphatic leakage included intraopera-tive lymph node dissection(OR=5.415,95%CI:2.167～13.532,P<0.001),intraoperative plasma transfusion(OR=2.952,95%CI:1.524～5.718,P=0.001),and postoperative fasting duration of≥2 days(OR=1.412,95%CI:1.089～1.829,P=0.009).The predictive model showed good discrimination and calibration(AUC=0.711,95%CI:0.647～0.776,P<0.001;sensitivity:0.764;specificity:0.597).Model robustness was confirmed through five-fold cross-validation(training set AUC=0.822;test set AUC=0.829).The nomogram provided a clinically useful tool for quantifying individual risk of lymphatic leakage.Conclusions Intraoperative lymph node dissection,plasma transfusion,and postoperative fasting lasting≥2 days are independent risk factors for lymphatic leakage following radical prostatectomy.The validated predictive model demonstrates favorable clinical utility.

Objective:To investigate the current status and influencing factors of decision anxiety in guardians of children with acute appendicitis under Endoscopic retrograde appendicitis therapy (ERAT) background, and to provide reference for the development of targeted intervention programs for decision anxiety.Methods:Convenient sampling method was used to select 254 guardians of children with acute appendicitis treated in the Department of Pediatrics, Second Affiliated Hospital of PLA Air Force Medical University from February 2023 to April 2024. A cross-sectional survey was conducted using the General Data Questionnaire, the State-Trait Anxiety Inventory Form Y-State anxiety subscale and the Preparation for Decision Making Scale. Multiple linear regression was used to analyze the influencing factors in guardians of children with acute appendicitis.Results:Among the guardians of 254 children with acute appendicitis, 156 were males and 98 were females, aged (37.44 ± 3.63) years old. The decision anxiety score of guardians of children with acute appendicitis was (52.49 ± 6.54). The results of multiple linear regression showed that age of children, gender of guardian, education level of guardian, per capita monthly income of family, decision making tendency and decision preparation were the main influencing factors of decision anxiety in guardians of children with acute appendicitis ( t values were -7.07-3.58, all P<0.05), which could explain 64.4% of the total variation. Conclusions:The decision anxiety in guardians of children with acute appendicitis is at a high level. Medical staff should provide targeted decision guidance, improve decision assistance programs and provide more effective decision support for guardians of children with acute appendicitis.

The symptom science model identifies complex symptoms and measures their phenotypic characteristics.It provides an in-depth analysis of symptom behaviors and biological mechanisms,aiding healthcare professionals in early symptom detection and initiating appropriate diagnostic and treatment measures.The model supports personalized interventions,aiming to achieve precision care and ultimately improve patient health.This study reviews the development and scope of the symptom science model,analyzes its current applications in chronic kidney disease,and explores its implications for symptom management in this condition.The aim is to offer insights and references for the scientific management of chronic kidney disease symptoms.