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。     

人参内生菌的研究进展

内生菌由细菌、真菌、古菌和原生生物组成，它们生活在植物的活体组织中，具有丰富的次级代谢产物多样性。人参内生菌在人参的生长发育、次级代谢产物的生成和环境适应等方面均有重要的促进作用，对人参的产量和品质有较大影响。随着人们在微生物领域研究的深入，高通量测序技术已经成为研究植物内生菌的重要方法。文章主要从人参内生菌分离与鉴定研究方法、人参内生菌的多样性、人参内生菌及其次级代谢产物的活性、人参内生菌对宿主的影响等4个方面对人参内生菌近年来的研究进展进行讨论，并对其发展方向提出展望，以期为药用植物内生菌研究和品质改良提供新思路、新方法。     

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。     

Unconditional Positivity-Preserving and Energy Stable Schemes for a Reduced Poisson-Nernst-Planck System

The Poisson-Nernst-Planck (PNP) system is a widely accepted model for simulation of ionic channels. In this paper, we design, analyze, and numerically validate a second order unconditional positivity-preserving scheme for solving a reduced PNP system, which can well approximate the three dimensional ion channel problem. Positivity of numerical solutions is proven to hold true independent of the size of time steps and the choice of the Poisson solver. The scheme is easy to implement without resorting to any iteration method. Several numerical examples further confirm the positivity-preserving property, and demonstrate the accuracy, efficiency, and robustness of the proposed scheme, as well as the fast approach to steady states.     

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%.     

Chemical applicability domain of the Local Lymph Node Assay (LLNA) for skin sensitisation potency. Part 2. The biological variability of the murine Local Lymph Node Assay (LLNA) for skin sensitisation

The Local Lymph Node Assay (LLNA) is the most common in vivo regulatory toxicology test for skin sensitisation, quantifying potency as the EC3, the concentration of chemical giving a threefold increase in thymidine uptake in the local lymph node. Existing LLNA data can, along with clinical data, provide useful comparator information on the potency of sensitisers. Understanding of the biological variability of data from LLNA studies is important for those developing non-animal based risk assessment approaches for skin allergy. Here an existing set of 94 EC3 values for 12 chemicals, all tested at least three times in the same vehicle have been analysed by calculating standard deviations (SD) for logEC3 values. The SDs range from 0.08 to 0.22. The overall SD for the 94 logEC3 values is 0.147. Thus the 95% confidence limits (2xSD) for LLNA EC3 values are within a factor of 2, comparable to those for physico-chemical measurements such as partition coefficients and solubility. The residual SDs of Quantitative Mechanistic Models (QMMs) based on physical organic chemistry parameters are similar to the overall SD of the LLNA, indicating that QMMs of this type are unlikely to be bettered for predictive accuracy.