3组常见马源性成分鉴定引物特异性和灵敏度比较

比较筛选基于聚合酶链式反应(polymerase chain reaction, PCR)技术的马源性成分鉴定方法中高灵敏度和特异性引物。方法 选取来自国标法、专利和文献报道的3组马源性成分鉴定引物, 比较其灵敏度和特异性, 筛选高灵敏度和特异性引物。结果 3组引物的灵敏度和特异性存在差异, 以线粒体DNA为靶标的Ⅱ组马源性成分鉴定引物的特异性和灵敏度优于分别以线粒体和核基因组DNA为靶标的马驴通用鉴定引物, 检出最低限度均满足检测需求。结论 通过比较马源性成分鉴定的3组PCR引物, 以线粒体DNA为靶标的Ⅱ组马源性成分特异性鉴定引物可作为马成分鉴定的首选, 线粒体和核基因组靶标联合可提高马成分鉴定的准确性并可用于杂交种鉴定, 为马源性成分及产制品鉴定提供了一定基础。     

Hydrophilic Modification of PVDF Microfiltration Membrane with Poly (Ethylene Glycol) Dimethacrylate through Surface Polymerization

The hydrophilic modification of poly (vinylidene fluoride) (PVDF) membrane with poly (ethylene glycol) dimethacrylate (PEGDMA) through grafting reaction for antifouling was reported. The influence of PEGDMA content, reaction temperature and time, on the structure, morphology, antifouling, and hydrophilicity of PVDF-g-PEGDMA membrane has been investigated. The PEGDMA monomers that were grafted on the surface of PVDF microfiltration membrane were confirmed by Attenuation total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and X-ray photoelectron spectroscopy (XPS), and morphology study conducted by SEM revealed the changes before and after modification. The protein adsorption, filtration performance, water content, and dynamic contact angle were used to characterize the antifouling and hydrophilicity of the modified PVDF membranes. Compared with the pristine PVDF membrane, the bovine serum albumin (BSA) adsorption on the PVDF-g-PEGDMA membrane decreased about 80%, and the water contact angle of the membrane dropped to 0°. Besides, the experimental results revealed no significant differences between the membrane samples with respect to pore size.     

益生菌/草本提取物复方清咽作用的实验研究

目的探讨益生菌/草本提取物复方的清咽作用。方法大鼠灌胃给予益生菌和/或草本提取物45 d,依据2012修订的保健食品"清咽功能检验方法"进行大鼠棉球植入实验、大鼠足趾肿胀实验及小鼠耳肿胀实验。结果棉球植入实验中,益生菌高剂量、草本中剂量和高剂量、益生菌低剂量+草本中剂量、益生菌低剂量+草本高剂量、益生菌高剂量+低/中/高剂量草本剂量组,大鼠肉芽肿净量显著低于对照组(P0.05),具有干预肉芽肿(慢性炎症)形成的作用;足趾肿胀实验中,致炎1 h后,草本高剂量组大鼠足趾肿胀率显著降低(P0.05),致炎1、2、6h后,益生菌高剂量+草本高剂量组足趾肿胀率均显著低于对照组(P0.05)且低于益生菌高剂量组和草本高剂量组,提示益生菌草本高剂量复方干预致炎剂诱发的足趾肿胀作用效果优于单独给予高剂量益生菌或高剂量草本;小鼠耳廓肿胀实验中,各组耳廓肿胀值及肿胀率均无显著变化。结论高剂量草本和益生菌草本高剂量复方样品具有清咽作用,且益生菌草本高剂量复方干预致炎剂诱导的急性炎症效果优于高剂量草本。     

偏重亚硫酸钠对微生物法测定维生素B12含量的影响

摘 要: 目的 探究偏重亚硫酸钠对微生物法测定婴幼儿食品和乳品中维生素B12(VB12)含量的影响。方法 通过在标准工作液和样品待测液中添加质量浓度梯度为0、0.0025、0.005、0.02、0.08和0.16 mg/mL偏重亚硫酸钠, 测定不同处理组实验样品中VB12含量值并对质控样品进行质控结果分析, 研究偏重亚硫酸钠对莱士曼氏乳杆菌生长的促进作用及其对原生VB12提取的影响。结果 在标准溶液中添加质量浓度为0~0.16 mg/mL的偏重亚硫酸钠都可以促进莱士曼氏乳杆菌的生长。偏重亚硫酸钠能促进样品中原生VB12的提取。偏重亚硫酸钠终浓度在0~0.16 mg/mL的范围内都不会抑制莱士曼氏乳杆菌的生长, 同时在0~0.05 mg/mL的范围内, 随偏重亚硫酸钠质量浓度增加, 原生VB12的提取会成比例增加。结论 偏重亚硫酸钠在0~0.16 mg/mL浓度范围内可以促进莱士曼氏乳杆菌的生长, 提高食品原生VB12的提取率, 进而增加检测结果的稳定性和准确度。     

Direct electrochemistry of catalase at amine-functionalized graphene/gold nanoparticles composite film for hydrogen peroxide sensor

Direct electrochemistry and electrocatalysis of catalase (Cat) was studied based on a nano-composite film consisting of amine functionalized graphene and gold nanoparticles (AuNPs) modified glassy carbon electrode. Graphene was synthesized chemically by Hummers and Offeman method and then was functionalized with amino groups via chemical modification of carboxyl groups introduced on the graphene surface. The nano-composite film showed an obvious promotion of the direct electron transfer between Cat and the underlying electrode, which attributed to the synergistic effect of graphene-NH₂ and AuNPs. The resultant bioelectrode retained its biocatalytic activity and offered fast and sensitive H₂O₂ quantification. Under the optimized experimental conditions, hydrogen peroxide was detected in the concentration range from 0.3 to 600 μM with a detection limit of 50 nM at S/N = 3. The biosensor exhibited some advantages, such as short time respond (2 s), high sensitivity (13.4 μA/mM) and good reproducibility (RSD = 5.8%).     

The Role of Peritoneal Alternatively Activated Macrophages in the Process of Peritoneal Fibrosis Related to Peritoneal Dialysis

It has been confirmed that alternatively activated macrophages (M2) participate in tissue remodeling and fibrosis occurrence, but the effect of M2 on peritoneal fibrosis related to peritoneal dialysis (PD) hasn’t been elucidated. This study was therefore conducted to assess the association between M2 and peritoneal fibrosis related to PD. In this study, peritoneal fibrosis was induced by intraperitoneal (i.p.) injection of Lactate-4.25% dialysate (100 mL/kg) to C57BL/6J mice for 28 days, and liposome-encapsulated clodronate (LC, the specific scavenger of macrophages) was used to treat the peritoneal fibrosis mice model by i.p. injection at day 18 and day 21. All animals were sacrificed at day 29. Parietal peritonea were stained with Masson’s trichrome, and the expression of type I collagen (Col-I), fibronectin, mannose receptor (CD206), transforming growth factor beta (TGF-β), chemokine receptor 7 (CCR7), chitinase 3-like 3 (Ym-1) and arginase-1 (Arg-1) was determined by Western blotting, immunofluorescence and quantitative real-time PCR. Our results revealed that peritoneal thickness, Col-I, fibronectin, CD206, TGF-β, Ym-1 and Arg-1 were upregulated in the peritoneal fibrosis mice model, and all of these indexes were downregulated in those treated with LC. Additionally, there was no difference in the level of CCR7 between the model and treatment group. Our study indicated that peritoneal M2 played an important role in the process of peritoneal fibrosis related to PD and might be a potential target for intervention therapy of peritoneal fibrosis.     

Imputing manufacturing material in data mining

Data plays a vital role as a source of information to organizations, especially in times of information and technology. One encounters a not-so-perfect database from which data is missing, and the results obtained from such a database may provide biased or misleading solutions. Therefore, imputing missing data to a database has been regarded as one of the major steps in data mining. The present research used different methods of data mining to construct imputative models in accordance with different types of missing data. When the missing data is continuous, regression models and Neural Networks are used to build imputative models. For the categorical missing data, the logistic regression model, neural network, C5.0 and CART are employed to construct imputative models. The results showed that the regression model was found to provide the best estimate of continuous missing data; but for categorical missing data, the C5.0 model proved the best method.     

Preparation of Fe-doped TiO2 nanotube arrays and their photocatalytic activities under visible light

Fe-doped TiO₂ nanotube arrays have been prepared by the template-based liquid phase deposition method. Their morphologies, structures and optical properties were investigated by scanning electron microscopy, transmission electron microscopy, X-ray diffraction and UV-vis absorption spectroscopy. Their photocatalytic activities were evaluated by the degradation of methylene blue under visible light. The UV-vis absorption spectra of the Fe-doped TiO₂ nanotube arrays showed a red shift and an enhancement of the absorption in the visible region compared to the undoped sample. The Fe-doped TiO₂ nanotube arrays exhibited good photocatalytic activities under visible light irradiation, and the optimum dopant amount was found to be 5.9 at% in our experiments.     

Application of UNIQUAC and SVM to ultrafiltration for modeling ternary mixtures of oil, FAME and methanol

To describe a membrane separator for ternary mixtures of oil-FAME-MeOH, two models of UNIQUAC and support vector machine (SVM) are developed for the permeate composition and permeate flux, respectively. The UNIQUAC model is used to represent the liquid-liquid phase equilibrium of oil-FAME-MeOH. Its prediction results are consistent with the experimental data measured at the temperatures of 293, 313 and 333 K, respectively. For this two-phase system, experimental results show that the oil-rich phase can be rejected by the ceramic membrane while the methanol-rich phase permeates through the membrane. The permeate composition is mainly determined by the feed bulk concentration, and therefore is consistent with the concentration of the methanol-rich phase predicted by the UNIQUAC model. On the other hand, the permeate flux under various operating conditions, such as feed concentrations, temperatures, inlet flow rates and transmembrane pressures, is modeled by the SVM algorithm. Unlike the general data-based neural network model, SVM is especially valuable in the present crossflow filtration problem of small sample sizes. By combining UNIQUAC and SVM with the experimental ultrafiltration of biodiesel mixtures, the predicted membrane separator performance shows no significant lack of fit, and continuous production of biodiesel with both high purity and maximal productivity is also discussed.     

A multi-level ant-colony mining algorithm for membership functions

Fuzzy data mining is used to extract fuzzy knowledge from linguistic or quantitative data. It is an extension of traditional data mining and the derived knowledge is relatively meaningful to human beings. In the past, we proposed a mining algorithm to find suitable membership functions for fuzzy association rules based on ant colony systems. In that approach, precision was limited by the use of binary bits to encode the membership functions. This paper elaborates on the original approach to increase the accuracy of results by adding multi-level processing. A multi-level ant colony framework is thus designed and an algorithm based on the structure is proposed to achieve the purpose. The proposed approach first transforms the fuzzy mining problem into a multi-stage graph, with each route representing a possible set of membership functions. The new approach then extends the previous one, using multi-level processing to solve the problem in which the maximum quantities of item values in the transactions may be large. The membership functions derived in a given level will be refined in the subsequent level. The final membership functions in the last level are then outputted to the rule-mining phase to find fuzzy association rules. Experiments are also performed to show the performance of the proposed approach. The experimental results show that the proposed multi-level ant colony systems mining approach can obtain improved results.