Object ive To summa r i z e the advanc ement of cytoske l e ton and axon outgrowth of neuron. Methods The recent l iterature concerning cytoskeleton and axon outgrowth of neuron was reviewed and summarized. Results The actin filaments and microtubules in neuron were highly polarized and dynamic structures confined to the ti ps of axons and the reci procal interactions between these two major cytoskeletal polymers was also dynamic. Attractive or a repulsive cue whose final common path of action was the growth cone cytoskeleton mediated the growth of axons of neuron by intracellular signaling cascades. Regulating the actin filament and microtubule dynamics as well as their interactions in growth cones played a key role in neurite outgrowth and axon guidance. Rho-GTPases and glycogen synthase kinase 3β (GSK-3β), the two major intracellular signal ing pathways had emerged in recent years as candidates for regulating the dynamics of actin filaments and microtubules. Conclusion The axon outgrowth and guidance depend on well-coordinated cytoskeletal and reciprocal interaction dynamics which also mediate axon regeneration after spinal cord injury. Regulating activity of Rho-GTPases and GSK- 3β simultaneously may acts as key role to regulate the dynamics of cytoskeletal and to determine axon outgrowth.
目的 探讨躯体感觉诱发电位（SEP）在颈脊髓损伤术前、术中监测的意义。 方法 纳入2010年1月－2012年4月治疗的241例颈脊髓损伤患者，术前按美国脊柱脊髓损伤协会（ASIA）评分并分级，确定损伤平面。术前与术中SEP监测，分析不同损伤分级以及不同损伤平面术前的波幅及潜伏期的差异，术中SEP监测以波幅下降＞50%和或潜伏期延长＞10%为预警标准。 结果 各损伤分级组术前SEP监测：A级组SEP波消失，呈一直线，而B、C、D、E级组均测出SEP波形，根据是否可测出SEP波形，可将A级与B、C、D、E及组区别。B、C、D级组之间波幅和潜伏期均无统计学意义（P＞0.05）。E级组较B、C、D级组波幅增高、潜伏期缩短，差异有统计学意义（P＜0.05）；不完全性颈脊髓损伤组内不同损伤平面组之间波幅和潜伏期差异均无统计学意义（P＞0.05）。术中SEP对脊髓功能损伤监测的灵敏度83.3%、特异度98.7%。其中术中：SEP阳性8例，真阳性5例，4例术者处理后波幅及潜伏期回复至正常范围，术后无新的神经功能损伤，另1例术者采取各种处理后波幅及潜伏期无恢复，术后神经功能损伤较术前加重；假阳性3例，1例麻醉师给予升高血压后波形恢复至正常，另2例经麻醉师调整麻醉深度后波形恢复正常，此3例术后无新的神经功能损伤。SEP阴性233例，真阴性232例，术后无新的神经功能损伤；假阴性1例，患者术中、术后波形未见异常，术后运动功能损伤程度较术前加重。 结论 ① SEP能准确评估完全性和不完性颈脊髓损伤，但对不完全性颈脊髓损伤的损伤程度不能作出准确评估、也不能区分颈脊髓损伤的损伤平面；② 术中SEP监测能较好地反映颈脊髓功能完整性，对减少颈脊髓损伤术中发生医源性颈脊髓损伤风险具有重要意义。
Objective To explore the clinical effect of failure mode and effect analysis (FMEA) combined with PDCA cycle management model in the prevention and control of multidrug-resistant organisms (MDROs) in intensive care unit (ICU), and provide evidences for drawing up improvement measures in healthcare-associated MDRO infections in ICU. Methods In January 2020, a risk assessment team was established in the Department of Critical Care Medicine, the First People’s Hospital of Longquanyi District of Chengdu, to analyze the possible risk points of MDRO infections in ICU from then on. FMEA was used to assess risks, and the failure modes with high risk priority numbers were selected to evaluate the high-risk points of MDRO infections. The causes of the high-risk points were analyzed, and improvement measures were formulated to control the risks through PDCA cycle management model. The incidence of healthcare-associated MDRO infections in ICU, improvement of high-risk events, and satisfaction of doctors and nurses after the implementation of intervention measures (from January 2020 to June 2021) were retrospectively collected and compared with those before the implementation of intervention measures (from January 2018 to December 2019). Results Six high-risk factors were screened out, namely single measures of isolation, unqualified cleaning and disinfection of bed units, irrational use of antimicrobial agents, weak consciousness of isolation among newcomers of ICU, weak awareness of pathogen inspection, and untimely disinfection. The incidence of healthcare-associated MDRO infections was 2.71% (49/1800) before intervention and 1.71% (31/1808) after intervention, and the difference between the two periods was statistically significant (χ2=4.224, P=0.040). The pathogen submission rate was 56.67% (1020/1800) before intervention and 61.23% (1107/1808) after intervention, and the difference between the two periods was statistically significant (χ2=7.755, P=0.005). The satisfaction rate of doctors and nurses was 75.0% (30/40) before intervention and 95.0% (38/40) after intervention, and the difference between the two periods was statistically significant (χ2=6.275, P=0.012). Conclusions FMEA can effectively find out the weak points in the prevention and treatment of MDRO infections in ICU, while PDCA model can effectively formulate improvement measures for the weak points and control the risks. The combined application of the two modes provides a scientific and effective guarantee for the rational prevention and treatment of MDRO infections in ICU patients.