背景:治疗后交叉韧带胫骨附着点撕脱骨折的最佳手术技术仍值得商榷。随着关节镜手术的应用与成熟,它在后交叉韧带胫骨附着点撕脱骨折的诊疗中有很大前景。目的:综述关节镜技术在后交叉韧带胫骨附着点撕脱骨折治疗中的应用与进展,包括不同关节镜治疗方法、手术入路、胫骨隧道设计、缝合材料选择以及内固定植入物选择等。方法:通过计算机对中国知网、PubMed、Web of Science及ScienceDirect等数据库中的相关文献进行检索,检索时间为2003年1月至2023年11月,中文检索词为“后交叉韧带,后十字韧带,撕脱骨折,关节镜”;英文检索词为“posterior cruciate ligament,avulsion,fracture,tibia,arthroscopic,operation,fixation,treatment”。共纳入97篇文献进行综述。结果与结论:关节镜技术提供了一种可靠的治疗方式来治疗后交叉韧带胫骨附着点撕脱骨折。根据入路、缝合材料类型以及用于缝合的入路和胫骨隧道数量等不同,关节镜技术可以分为关节镜下缝线固定结合自体移植物增强重建、关节镜下多交叉带缝合桥固定、关节镜下高强度缝线固定以及关节镜下直接前后缝合悬吊固定等几类。在各种研究中,常用的临床结果评估指标包括关节活动度、Lysholm评分、国际膝关节文献委员会评分及KT-2000关节测量仪差等,研究显示关节镜手术后末次随访时上述指标检测结果较术前显著改善,影像学随访结果显示关节镜手术都取得了令人满意的结果。在随访过程中,接受关节镜技术治疗后的各类交叉韧带胫骨附着点撕脱骨折患者都未出现严重并发症,例如创伤性关节炎、神经血管损伤、围手术期伤口感染、血栓形成以及骨折不愈合等。
烧伤疼痛是影响烧伤患者康复及生活质量的关键因素,其机制复杂,涉及多种炎症与免疫信号通路。本研究整合生物信息学和实验验证,旨在筛选鉴定与烧伤疼痛密切相关的关键基因,探索其作为潜在治疗靶点的临床价值。通过GEO数据库获取烧伤患者与健康对照的表达谱数据(GSE19743作训练集,GSE37069作验证集),结合GeneCaRNA数据库筛选疼痛相关基因。运用差异分析、GO与KEGG富集分析、构建可视化PPI网络,以及LASSO回归、SVM和RF三种机器学习方法识别关键基因,构建诊断模型,利用ROC曲线与DCA评估诊断效能。最终经RT-qPCR对外周血样本中候选基因表达水平进行实验验证。本研究筛选出117个烧伤疼痛相关差异表达基因,富集于PI3K-Akt、MAPK等炎症信号通路,IFNG、IL10和TLR4被三种机器学习方法共同识别为关键特征基因。基于此三基因构建的诊断模型在GSE37069验证集中表现优异,AUC达0.959。RT-qPCR验证表明,烧伤患者中IL10显著上调,IFNG表达下降,TLR4表达无显著差异,部分结果与生物信息学分析一致。IFNG、IL10和TLR4或通过调控免疫与炎症反应参与烧伤疼痛的发生维持,有望成为诊断生物标志物及治疗靶点,未来研究需进一步探讨其信号通路机制及临床干预价值。Burn pain is a critical factor affecting the recovery and quality of life of burn patients. Its underlying mechanisms are complex, involving multiple inflammatory and immune signaling pathways. This study integrates bioinformatics and experimental validation to identify key genes closely associated with burn pain and to explore their potential clinical value as therapeutic targets. Gene expression profiles (GSE19743 as the training set and GSE37069 as the validation set) were retrieved from the GEO database, and pain-related genes were screened via the GeneCaRNA database. Subsequent analyses included differential analysis, GO and KEGG enrichment analyses, and PPI network construction and visualization. Three machine learning algorithms—LASSO regression, SVM, and RF—were employed to identify key genes, following which a diagnostic model was established and evaluated using ROC curves and DCA. RT-qPCR validated candidate gene expression in peripheral blood samples. A total of 117 differentially expressed burn pain-related genes were identified, primarily enriched in inflammatory signaling pathways such as PI3K-Akt and MAPK. IFNG, IL10, and TLR4 were consistently identified as key feature genes across all three machine-learning methods. The diagnostic model based on these genes demonstrated excellent performance in the GSE37069 validation set, achieving an AUC of 0.959. RT-qPCR validation indicated that IL10 was significant
背景:血管阻力(VR)指的是血液在流经血管过程中所遇到的阻力。这是一种在正常血液循环和心脏功能中发挥关键作用的生理现象。然而,异常的血管阻力是多种循环系统疾病和心血管病理状态的基础。尽管近年来对血管阻力展开了广泛研究,但迄今为止尚未有相关的文献计量分析。本研究旨在阐明血管阻力研究的发展趋势和新兴焦点,为未来的研究以及基于证据的决策提供指导。方法:所有相关文献均从Web of Science核心合集(WoSCC)数据库中获取。采用HistCite、CiteSpace和VOSviewer对文献进行计量分析和可视化处理。结果:本研究的主要学科领域为“生物学与医学”。共纳入6645篇与“血管阻力”相关的英文文献,年度发表数量呈现稳定趋势。美国在发表文献数量和引用量上均位居第一。产出最多的机构、期刊和作者分别为Mayo Clinic、Pulmonary Circulation和Marc Humbert;而引用量最高的期刊和作者则分别为International Journal of Cardiology和Simonneau,Gerald。伦敦帝国学院在机构间的合作最为广泛。在聚类分析中,“心力衰竭”(聚类0#)为最大的聚类。此外,“肺动脉高压”、“血压”和“血管阻力”为主要关键词,而“社会”和“性别差异”则是近年来出现的最新突现关键词。结论:肺动脉高压可能成为血管阻力领域的新兴热点,这在一定程度上与2019冠状病毒病(COVID-19)与肺动脉高压之间的关联有关。近期在慢性血栓栓塞性肺动脉高压(CTEPH)研究中的进展,有助于深入理解肺部疾病的发病机制和治疗策略。此外,血管阻力监测技术在心血管疾病的诊断和管理中具有重要的临床意义。Background: Vascular Resistance (VR) refers to the resistance encountered by blood flow as it moves through the blood vessels. It is a physiological phenomenon that plays a vital role in normal blood circulation and heart function. Nonetheless, aberrant vascular resistance underlies various circulatory disorders and cardiovascular pathologies. Despite extensive investigations of VR in recent years, no bibliometric analysis has been conducted thus far. The objective of this is to elucidate the evolutionary trends and emerging focal points within VR research while offering guidance for future investigations and evidence-based decision-making. Methods: All the relevant literature was obtained from the Web of Science Core Collection (WoSCC) database. HistCite, CiteSpace, and VOSviewer were employed to perform bibliometric analysis and visualization. Results: “Biology and Medicine” is the main research categories in this research. A total of 6645 English documents related to “Vascular Resistance” were included. The number of annual publications shows a stable trend. The United States is the country with the largest publications and the largest citations. The most productive institution, journal, and author are Mayo Clinic, Pulmonary Circulation, Marc Humbert, res
暂无评论