EBUS-TBNA超声内镜对纵隔肿大淋巴结良恶性的鉴别诊断价值

目的:分析超声内镜引导下经支气管针吸活检(endobronchial ultrasound-guided transbronchial needle aspiration，EBUS-TBNA)术中肿大纵隔淋巴结的超声图像特点，探讨EBUS-TBNA超声内镜对纵隔淋巴结良恶性的鉴别诊断价值，以期提高EBUS-TBNA对纵隔淋巴结恶性病变的活检率。方法:回顾性分析2014年10月至2018年11月行EBUS-TBNA患者的超声内镜图像。我们使用以下EBUS超声内镜特征来预测淋巴结的良恶:回声，长轴长度，短轴长度，纵横比，形态，边界，淋巴门有无，淋巴结内血流信号分级。将超声检查结果与最终病理结果或临床随访结果进行比较。采用SPSS 20.0软件进行统计学分析，采用logistic回归分析评价肿大淋巴结EBUS-TBNA超声内镜下的特征与良恶性的相关性，以 P<0.05 为标准判定差异有统计学意义。结果:对130例纵隔淋巴结肿大患者的227个淋巴结进行回顾性分析，67.4%的肿大淋巴结被证实为恶性转移。Logistic回归分析显示回声、长轴及短轴的长度、正常淋巴门结构的消失是诊断恶性淋巴结的独立预测因素。结论:纵隔恶性淋巴结具有一定的超声特征，可以通过这些超声特征提高EBUS-TBNA对纵隔恶性淋巴结的检出率。     

Clinical analysis of high-intensity focussed ultrasound ablation for abdominal wall endometriosis: a 4-year experience at a specialty gynecological institution

Objective: To evaluate the long-term clinical effect of high-intensity focussed ultrasound (HIFU) as a non-invasive modality for ablation of abdominal wall endometriosis (AWE) foci.

Methods: All women who were diagnosed with cutaneous endometriosis and underwent HIFU ablation and 4-year follow-up were included. Patient symptoms, imaging performed, HIFU ablation, recurrence, lesion location, size and number were collected and analyzed.

Results: A total of 51 women with 57 painful abdominal wall masses with a median volume of 4.00?cm³ and a mean age of 30.5±2.12 years were treated with HIFU. The main symptoms were a palpable painful abdominal mass (93%), protrusion of the skin (28.1%, 16) or lack of protrusion of the skin (71.9%, 41). Ultrasound was initially performed in 100% (51) of women, whereas 6% (3) required MRI examinations to distinguish the features and range of the masses. Ablation was performed with a median 300?s of sonication time, 40?min treatment time, 150?W of power and 41800?J of total energy to treat lesions that were a median volume of 3.83?cm³. No severe complications occurred, except in one patient with a first-degree skin burn, during the 48-month follow-up period. The pooled recurrence of cutaneous endometriosis occurred in 3.9% (2) of women.

Conclusion: The diagnosis of AWE should be confirmed with imaging of the lesion number, location, size and features before HIFU ablation. HIFU should be the first choice for the treatment of AWE as it is a non-invasive method, with high efficiency and safety and rapid postoperative recovery.     

PERK信号通路介导结肠癌细胞对5-氟尿嘧啶耐药机制的研究

目的:观察PERK蛋白对结肠癌细胞药物敏感性的影响，并进一步探讨其相关作用机制。方法:结肠癌细胞系HCT116分为三组:空白对照（Control）组、下调PERK表达（si-PERK）组、阴性对照（si-NC）组；采用免疫荧光及RT-PCR验证转染效率；利用CCK-8实验检测下调PERK表达后结肠癌细胞对化疗药物5-FU的敏感性变化；Annexin V-FITC凋亡实验检测下调PERK表达对结肠癌细胞凋亡的影响；利用RT-PCR及Western Blot实验检测PERK信号通路中关键分子eIF2α、ATF4、CHOP、XIAP的mRNA及蛋白表达变化。结果:RT-PCR实验表明:与正常对照组相比，si-PERK 组mRNA的表达显著下降（P＜0.05）,免疫荧光提示转染效率达80%以上；CCK-8实验发现与si-NC组相比，5-FU对 si-PERK组细胞的半数抑制浓度（IC50）明显降低（P＜0.01）；Annexin V-FITC凋亡实验发现与si-NC组相比，si-PERK组细胞的凋亡发生率显著升高（P＜0.05）；RT-PCR及Western Blot实验发现与si-NC组相比，si-PERK组细胞中PERK信号通路下游关键分子eIF2α、ATF4、CHOP的mRNA及蛋白表达均明显降低（P＜0.05）。结论:在结肠癌细胞中，抑制PERK表达后，其可能通过下调eIF2α、ATF4、CHOP的表达促进细胞发生凋亡，从而促进细胞对化疗药物5-FU的敏感性。     

医院信息化系统在武汉新冠肺炎防疫救治过程中暴露出的问题及其引发的思考

目的针对武汉地区医院信息化系统在新型冠状病毒肺炎(简称新冠肺炎)防疫救治过程中暴露出的问题,提出应对突发公共卫生事件时医院信息化的完善方法。方法充分分析医院信息化系统在新冠肺炎防疫救治中所暴露出的各个医院信息化系统结构不同、各个医院之间无法实施信息共享、门诊病房之间系统相互独立、数据信息更新不及时等九大问题,并提出医院信息化基础布局的建立、区域链及大数据临床中的应用等多项措施。结果医院信息化能力的提高有助于降低医护人员工作强度,提高患者的安全。结论新冠肺炎疫情的发生给我国医院信息化系统带来了严峻的挑战,但同时也给我们带来了更大的机遇。我国在未来针对突发公共卫生事件时,医院信息化将为医护人员、患者提供更有利的支持。     

Four new diarylheptanoids from Rhizoma Zingiberis

Four new diarylheptanoids, (1S, 3R, 5R, 6R)-1, 5-epoxy-3, 6 dihydroxy-1-(4-hydroxy-3, 5-dimethoxyphenyl)-7-(4-hydroxy-3-methoxyphenyl) heptane (1), (1R, 3R, 5S)-1, 5-epoxy-3-acetoxy-1-(4, 5-dihydroxy-3-methoxyphenyl)-7-(3, 4- hydroxyphenyl) heptane (2), (3R, 5S, 6R, 7S)-3, 6-epoxy-7-hydroxyl-1-(4-hydroxyphenyl)-7-(3-methoxy-4-hydroxyphenyl) heptane (3), (E)-3-keto-1-(3-methoxy-4-hydroxyphenyl)-7-(4, 5-dihydroxy-3-methoxyphenyl)-4- heptene (4), were isolated from Rhizoma Zingiberis, and their structures were determined based on HR-ESI-MS and extensive spectroscopic techniques (UV, IR, 1D-NMR and 2D-NMR). Compounds 1–4 exhibited no cytotoxicity against HepG2 cell lines.