双重实时荧光PCR快速鉴别人参和西洋参＊

目的 建立一种能够快速鉴定人参和西洋参的双重实时荧光PCR方法。方法 通过对人参属及其近似种基因序列的分析比对，设计特异性的引物探针，建立双重实时荧光PCR检测方法。PCR反应体系为Premix Ex Taq （Probe qPCR） 10 μL，人参上下游引物各0.5 μL，西洋参上下游引物各0.3 μL，人参与西洋参特异性探针各0.4 μL，DNA模板2 μL，灭菌去离子水补至20 μL。反应条件为95℃预变性30 s；然后以95℃变性5 s，60℃退火延伸30 s进行40个循环。应用该方法测试了27份DNA样品，包括7份人参、6份西洋参、4份人参与西洋参混合样、10份其他人参属样品及其他常见中药材样品的DNA，以确定该方法的特异性。将人参与西洋参样品DNA混合后10倍稀释成不同浓度后进行检测，用以确定该方法的灵敏度。结果 人参及西洋参样品均在特定的荧光通道下出现典型的阳性扩增曲线，人参与西洋参混合样品均同时出现两条阳性扩增曲线，其它对照样品及空白对照均没有出现阳性扩增曲线。灵敏度检测结果显示该方法检测人参及西洋参的最低检测限均为2 pg DNA/反应。结论 本实验建立的双重实时荧光PCR方法能够同时快速、准确、灵敏地鉴别出人参和西洋参。     

中医健康状态辨识模式的研究现状与展望

健康状态的辨识是把握健康的前提。当前学界已存在专家辨识模式、标准辨识模式、数字辨识模式、智能辨识模式以及微观辨识模式等。联合多种辨识方法,构建健康状态辨识体系,形成常态与动态结合、主观与客观结合、人机互参的中医健康状态个体化辨识方法是研究的趋势所在。文章对未来的研究方向进行展望,探讨了多元辨识模式、远程辨识模式、终身辨识模式、自动辨识模式的思路方法,以期促进全民健康事业,助力"健康中国"战略。     

Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma

PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.ResultsThirty-seven patients (21 men, 16 women; mean age, 56 ± 13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60 ± 46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70 ± 51 [SD] mm [range: 18 - 196 mm] vs. 42 ± 24 [SD] mm [range: 8 - 94 mm], respectively; P = 0.039), with more tumor necrosis (75% vs. 33%, respectively; P = 0.030) and lower attenuation on precontrast (30 ± 4 [SD] HU [range: 25-39 HU] vs. 37 ± 6 [SD] [range: 25-45 HU], respectively; P = 0.002) and on portal venous phase CT images (75 ± 18 [SD] HU [range: 43 - 108 HU] vs. 92 ± 19 [SD] HU [range: 46 - 117 HU], respectively; P = 0.014). Hemorrhagic content on MRI was only observed in NEC (P = 0.007). The mean ADC value was lower in NEC ([1.1 ± 0.1 (SD)] × 10⁻³ mm²/s [range: (0.91 - 1.3) × 10⁻³ mm²/s] vs. [1.4 ± 0.2 (SD)] × 10⁻³ mm²/s [range: (1.1 - 1.6) × 10⁻³ mm²/s]; P = 0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7 ± 0.2 [SD] [range: 4.2-5.1] vs. 4.5 ± 0.4 [SD] [range: 3.7-4.9]; P = 0.023).ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.     

液质联用技术鉴定清血八味片化学成分研究

目的:采用高效液相色谱-三重四级杆质谱(HPLC-MS/MS)测定清血八味片中的化学成分。方法:在负离子条件下采用Halo C_(18)色谱柱(2.1 mm×100 mm,2.7μm),以0.1%甲酸-10 mmol/L甲酸铵水和乙腈为流动相进行梯度洗脱,质谱采用Scan模式和MRM模式,检测清血八味片中的化学成分。结果:共鉴定出紫草中成分7种、土木香中成分3种、人工牛黄中成分4种、栀子中成分7种、瞿麦中成分7种、甘草中成分12种。结论:该方法快速可靠,操作简便,可用于清血八味片的质量控制研究,为临床药物使用提供一定的依据。     

薄层色谱法在当前中药质量标准中的应用探讨

薄层色谱鉴别在历版《中国药典》中的应用经历了从无到有、从少到多的过程；而薄层扫描含量测定在最近几版《中国药典》中的应用比例逐渐降低。随着对中药质量标准体系要求的进一步提高，薄层色谱法的不足之处陆续显现，如仪器普及率低、设备并不简单、结果重复性和稳定性较差、鉴别速度及准确性不及高效液相色谱法、展开剂毒性大等，逐渐不合时宜。在制定中药质量标准时，研究者不应该墨守成规，薄层色谱鉴别也不应该是雷打不动的定性鉴别必备选项。高效液相色谱法具备完全取代薄层色谱法的可行性，薄层色谱法可作为高效液相色谱法的补充。为充分降低检测成本、缩短检测周期、提高鉴别效率，笔者建议中药质量标准体系应该大幅减少薄层色谱鉴别方法的应用，增加高效液相特征图谱鉴定，尽量做到“一个条件，一张图谱”；除非确有必要，《中国药典》等国家质量标准体系应将薄层色谱鉴别作为推荐方法，而非强制标准。     

Developmental validation of the ANDE™ rapid DNA system with FlexPlex™ assay for arrestee and reference buccal swab processing and database searching

A developmental validation was performed to demonstrate reliability, reproducibility and robustness of the ANDE System with the FlexPlex assay, including an integrated Expert System, across a number of laboratories and buccal sample variations. Previously, the related DNAscan™/ANDE 4C Rapid DNA System using the PowerPlex^®16 assay and integrated Expert System Software received NDIS approval in March 2016. The enhanced ANDE instrument, referred to as ANDE 6C, and the accompanying 6-dye, 27-locus STR assay, referred to as FlexPlex, have been developed to be compatible with all widely used global loci, including the expanded set of the CODIS core 20 loci.Six forensic and research laboratories participated in the FlexPlex Rapid DNA developmental validation experiments, testing a total of 2045 swabs, including those obtained from 1387 unique individuals. The goal of this extensive and comprehensive validation was to thoroughly evaluate and document the ANDE System and its internal Expert System to reliably genotype reference buccal swab samples in a manner compliant with the FBI’s Quality Assurance Standards and the NDIS Operational Procedures.The ANDE System, including automated Expert System analysis, generated reproducible and concordant results for buccal swabs when testing various instruments at different laboratories by a number of different operators. When testing a number of non-human DNAs, including oral bacteria, the ANDE System and FlexPlex assay demonstrated limited cross-reactivity. Potential PCR inhibitors were evaluated as part of the validation and no inhibition was detected. Reproducible and concordant profiles were generated from buccal swab samples collected with a limit of detection appropriate for buccal swab collections from arrestees. The precision and resolution of the System met industry standards for detection of microvariants and single base resolution.The integrated Expert System appropriately demonstrated the ability to correctly pass or fail profiles for CODIS upload without human review. During this comprehensive developmental validation, the ANDE System successfully interpreted over 2000 samples tested with over 99.99% concordant alleles. The data package described herein led to the ANDE System with the FlexPlex assay receiving NDIS approval in June 2018.     

浙江省2007－2017年罕见病住院病例特征分析

目的 分析2007-2017年浙江省24 388例罕见病住院病例特征，为制定罕见病防控策略提供依据。方法 收集2007-2017年浙江省10家三级甲等（三甲）医院罕见病住院病例资料和各年度住院数，进行描述性统计分析。结果 罕见病病例共24 388例，占住院总例数的2.69‰（24 388/9 054 201），病例数居前3位的疾病类型依次为"血液和造血器官疾病以及某些涉及免疫机能的异常"（占32.81%，8 001/24 388）、"先天性畸形、变形和染色体异常"（占24.87%，6 065/24 388）和"神经系统疾病"（占19.01%，4 635/24 388）；2007-2017年罕见病病例数呈逐年增长趋势，年均增幅19.69%，而罕见病例数占同期住院总例数比例仅在2016-2017年明显上升，各类型罕见病时间分布呈不同特征；罕见病的病例数男女性别比为1.35：1（13 990/10 398），男女性别比最高的3类疾病依次为"消化系统疾病"（4.45：1，1 180/265）、"损伤、中毒和外因的某些其他后果"（3.51：1，281/80）和"神经系统疾病"（2.26：1，3 213/1 422）；各年龄段罕见病类型、各类型罕见病年龄分布均呈不同特征；病例数居前10位的疾病占全部罕见病例数的53.55%（13 060/24 388），其中前3位疾病分别为成人粒细胞缺乏症（14.41%，3 515/24 388）、皮质基底核退化症（7.60%，1 854/24 388）和亨诺克-舍恩莱因紫癜（6.01%，1 466/24 388）。结论 本研究分析的浙江省2007-2017年24 388例罕见病住院病例的特征资料，是推动我国罕见病的研究、监测或登记数据库构建、制定防控策略的参考依据。