基于文献的老年人群常见证候分布特征研究＊

目的 了解我国老年人中医证候分布特征，为中医药辨治老年人提供参考依据。方法 系统检索中国知识基础设施（CNKI）、中文科技期刊数据库（CCD）、万方数据资源系统数据库（CSPD），纳入研究对象为老年人的临床流行病学调查研究文献，对其调查目的、调查疾病及调查结果等进行描述统计。结果 ①最终纳入168篇文献，其中2010至2020年之间发表138篇（82.14%）；调查地区涵盖全国28个省市自治区，共纳入43948例老年人，累计覆盖340个研究中心；②主要研究结果显示，老年人中医证候阴虚阳亢证（10.05%）>血瘀证（9.5%）>痰浊（湿）证（8.91%）>阴阳两虚证（4.98%）>痰瘀互结证（4.96%）；单元证分布阴虚证（14.70%）>痰证（11.22%）>气虚证（7.15%）>肾虚证（4.72%）>血瘀证（4.18%）；涉及病变脏腑肾>肝>脾>肺>心。结论 根据统计结果，可以看出老年人证候分布虚证多于实证，虚证中又以阴虚证、气虚证最为多见，实证常见血瘀证、痰浊（湿）证等，且多见痰瘀互结证；老年人五脏皆损，其中又以肾、肝、脾功能失调最为突出。     

朝鲜淫羊藿酸性多糖的理化特性及对HepG2细胞脂质堆积的改善作用＊

目的 对比研究朝鲜淫羊藿酸性多糖酯化还原前后的理化特性，并探讨其改善油酸诱导的肝癌HepG2细胞脂质堆积活性的差异。方法 采用高效凝胶渗透色谱法测定朝鲜淫羊藿酸性多糖（EFPA）的均一性和分子量，高效液相色谱法测定EFPA和酯化还原后朝鲜淫羊藿酸性多糖（EFPA-R）的单糖组成；采用油酸（OA）处理HepG2细胞诱导建立脂质蓄积模型，不同浓度EFPA与EFPA-R（10、30、100、300 μg·mL^-1）分别和OA共同作用于细胞24 h，采用CCK-8试剂盒测定细胞存活率，油红O染色观察细胞内脂滴蓄积情况，并采用试剂盒测定细胞内总胆固醇（TC）、甘油三酯（TG）含量。结果 EFPA为成分均一的多糖组分，分子量为125.8 kDa，由甘露糖、葡萄糖、半乳糖、葡萄糖醛酸和阿拉伯糖组成，摩尔比为1.7∶7.4∶1.4∶1.8∶1.0，葡萄糖占比最大，EFPA-R由甘露糖、葡萄糖、半乳糖和阿拉伯糖组成，摩尔比为0.8∶10.6∶2.1∶1.0；在10-300 μg·mL^-1范围内，EFPA和EFPA-R对HepG2细胞的抑制作用较弱，作为给药浓度；与空白组相比，模型组细胞中TC、TG含量显著升高（P < 0.01），细胞内红色脂滴显著增多，与模型组相比，EFPA可显著降低细胞中TC、TG含量（P < 0.01），明显减少细胞内红色脂滴（P < 0.05或P < 0.01），EFPA-R干预后细胞则无明显变化。结论 EFPA可明显改善HepG2细胞脂质堆积情况，且呈现剂量依赖性，而半乳糖醛酸（GalA）的存在可能是其抑制HepG2细胞脂质蓄积的关键因素。     

特发性肺纤维化急性加重期证候与血清生物标志物的相关性研究＊

目的 通过分析特发性肺纤维化急性加重期（AE-IPF）患者证候与血清生物标志物的关系，为中医辨证治疗提供参考。方法 采用观察性研究设计，收集2019年3月至2019年11月三个中心的AE-IPF患者76例，其中痰热壅肺证26例、痰浊阻肺证50例，并纳入健康志愿者10例作为对照。采用ELISA测定患者血清CCL18、HMGB1、KL-6、MMP-7、SP-A和SP-D水平，分析与中医证候的相关性。结果 AE-IPF患者血清CCL18、HMGB1、KL-6、MMP-7、SP-A和SP-D水平均显著高于健康对照组。血清CCL18、HMGB1、KL-6、MMP-7和SP-D水平在痰热壅肺证和痰浊阻肺证患者间无显著性差异（P＞0.05），而血清SP-A水平存在显著性差异（P＜0.05）。结论 血清SP-A与AE-IPF证候存在一定的相关性，血清SP-A的浓度升高，与痰热壅肺证关系越密切，反之，血清SP-A浓度降低，则与痰浊阻肺证关系越密切。AE-IPF痰热壅肺证患者的预后可能较痰浊阻肺证患者更差。     

2011—2020年呼和浩特市流行性腮腺炎流行特征分析

目的 分析呼和浩特市2011—2020年流行性腮腺炎(流腮)流行病学特征,为制定有针对性防控措施提供参考依据。方法 对呼和浩特市2011—2020年流行性腮腺炎的发病数据进行监测分析,描述其分布及趋势。 呼和浩特市2011—2020年共报告流腮病例6 176例,年均发病率20.60/10万,其中2012年发病率最高为40.17/10万,2020年发病率最低为7.08/10万,2012年和2020年发病率差异有统计学意义(χ2=717.641,P<0.001),10年间流腮发病呈波动下降趋势。流腮发病具有明显季节性,11月至次年1月和4—7月出现2个发病高峰。年龄分布以儿童和青少年为主,占总病例数60.83%。流腮病例最多人群是学生,占总病例数的61.08%。 流腮暴发疫情主要发生在中小学校,应加强儿童入托、入学预防接种证查验和流腮疫苗查漏补种工作,必要时开展6～15岁学生为目标人群的应急接种。     

Organic and Inorganic Mercury in Biological Samples of Flouresecent Lamp Industries Workers and Health Risks

Objective The present study aims to investigate the concentrations of Hg and its aspects methyl mercury(Me-Hg) and inorganic mercury(I-Hg) in the biological samples(BSs) of fluorescent lamp industries workers(FLIWs).Methodology Different BSs including red blood cells(RBCs),plasma,urine,hair and nails were collected from the workers exposed to Hg and unexposed persons were selected as control group to measure both the T-Hg concentration as well as its species in different biological samples through quantitative analysis.Health data was collected through questionnaire survey.Results The mean concentrations of T-Hg(31.9 μg/L),Me-Hg(27.7 μg/L),and I-Hg(5.36 μg/L) in RBCs were found significantly(P 0.001) higher among the workers(n = 40) as compared to the control group(n = 40).Similarly the mean Hg concentrations in plasma,urine,hair and nails were also significantly higher among the workers than the control group.The statistical relation between Hg concentration and demographic characteristics observed that workers experience and fish consumption has increased the Hg concentration while age,weight and smoking found no significant effect on Hg concentration in the BSs.Conclusion The study observed that the workers were highly exposed to high concentration of Hg and they are at a high health risk.     

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%.