鸡尾酒抗体D2-40/CD34-CK对淋巴结检出数量不足结直肠癌标本的临床病理评价

目的探讨鸡尾酒抗体D2-40/CD34-CK双重免疫组化染色在淋巴结检出数量不足的结直肠癌(colorectal cancer,CRC)标本脉管侵犯评估中的应用及意义。方法收集133例淋巴结检出数量<12枚的CRC标本,分别行HE染色及鸡尾酒抗体双重免疫组化染色,比较两种方法在脉管侵犯筛查效果中的差异,并分析应用鸡尾酒抗体免疫组化染色证实的脉管侵犯与临床病理特征及患者总生存期(overall survival,OS)的关系。结果 (1)鸡尾酒抗体D2-40/CD34-CK双重免疫组化染色及HE染色对脉管侵犯的检出率分别为42. 9%(57/133)和21. 8%(29/133),差异有显著性(P <0. 001)。(2)鸡尾酒抗体D2-40/CD34-CK双重免疫组化法证实的脉管侵犯与Dukes分期、浸润深度、临床分期、淋巴结转移、肿瘤出芽相关(P <0. 05)。(3)脉管侵犯、侵犯位置深度、程度及脉管侵犯灶数≤2个灶且癌栓细胞数量≥5. 5个与患者OS密切相关(P <0. 05)。结论鸡尾酒抗体D2-40/CD34-CK双重免疫组化染色对脉管侵犯评估优于常规HE染色切片观察,与肿瘤分期、淋巴结转移及出芽情况密切相关,是患者预后的独立影响因素,可作为淋巴结检出数量不足CRC病例的补充检测指标。国家自然科学基金青年科学基金(81301787

基于概率分布差异的医学命名实体识别方法

医学命名实体识别是从医学文本中抽取出指代特定概念的医学实体，是医学信息抽取的基础性任务。当前主流的医学命名实体识别算法普遍基于深度学习技术，需要大量高质量的标注样本进行模型训练。然而医学领域的样本标注成本很高，严重限制了模型性能的提升。为了降低模型对标注样本的需求，一种重要的方法是基于主动学习思想，设计合理的样本采样策略，自动选取高价值样本优先标注，从而使模型提前收敛。现有算法普遍基于样本长度、样本识别的概率等特征来设计采样策略，忽视了样本类别分布这一深层次特征，导致命名实体识别召回率较低。提出了一种基于概率分布差异的主动学习算法，通过计算样本间的概率分布差异来评估样本的标注价值，并在标注样本更新时动态优化模型。在真实的医学检查文本上的实验表明，相比已有算法，达到同等的模型性能，该算法所需要的标注数据可缩减10%以上；在相同标注样本量的情况下，本算法F1值提高5%以上

薄壁真空管道及由薄壁真空管道制造真空室的制造方法

<span style="color: rgb(69, 69, 69); font-family: Arial, Helvetica, sans-serif; line-height: 21px; text-indent: 24px;">&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;本发明主要涉及电真空设备的制造方法，尤其涉及一种可以在高频交流电场或交变磁场下使用的真空管道的制造方法。一种薄壁真空管道的制造方法，包括制管、卷边、设置加强筋等多个步骤，还提供一种由制成的真空管道制造真空室的制造方法，包括焊管、制造液压波纹管装置等工艺，用此工艺程序、参数和方法匹配制造出的薄壁真空管道，整个真空管道尺寸大、通体薄壁，能够满足在高频交流电场或交变磁场下使用要求。</span

绿洲农业高效用水技术集成与示范

简要技术说明： 该成果围绕棉花、葡萄、小麦3大作物,从干旱绿洲区作物高效用水和提高作物水分生产效率的目标出发,研究形成了棉花高效用水技术模式3套、葡萄高效用水技术模式1套、小麦优化灌溉节水及配套栽培技术模式1套、干旱绿洲区农业高效用水管理技术模式1套,开发了15项农业节水关键技术和1套“农业灌溉决策支持系统”,筛选出节水配套抗旱小麦品种2个、抗旱棉花品种1个,制定了农业高效用水技术规程7项,研发了专利产品1项、软件著作权登记1项,人才培养12名、发表论文45篇。通过对高效灌溉技术、农艺高效用水技术、高效用水管理技术等3方面的关键技术的集成与创新,研究形成了干旱绿洲区特色作物(棉花、葡萄、..

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies