目的 探讨弥漫性轴索损伤（diffuse axonal injury，DAI）的发病机制、临床特点、诊断及治疗方法，以提高治愈率，降低致残、致死率。 方法 回顾性分析200６年6月-2010年3月间65例临床诊断为DAI患者的受伤机制、临床特征、影像学表现、治疗及预后。 结果 DAI最常见原因为车祸伤70.7%，其次为坠落、坠物伤（10.7%），其他（18.6%）。按格拉斯哥昏迷分级（GCS）评分结果3~5分18例，6~8分15例，9~12分32例；治愈43例，轻残15例，中残8例，重残或植物生存7例，死亡7例。 结论 DAI具有诊断、治疗困难，预后差等特点，交通事故是导致DAI的主要原因，格拉斯哥昏迷分级（GCS）评分、昏迷时间和瞳孔变化是判定预后的重要指标。目前尚无特效治疗方法，由于80％以上患者往往是多发伤，故早期气管切开、呼吸机辅助呼吸、促醒、亚低温治疗、防治并发症、钙离子拮抗剂应用等综合治疗可显著改善预后。
ObjectiveTo explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). MethodsThe Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. GO, KEGG, and GSEA enrichment analyses were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients' 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Finally, single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. ResultsDifferentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. Through scRNA-seq analysis, RORA and KLF10 were mainly expressed in natural killer cells. ConclusionThe prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.