pH值对乳清蛋白糖基化产物体外抗氧化特性的影响

选择6种不同的糖基配体,通过湿热糖基化反应,研究乳清蛋白不同糖基化复合物在不同pH值下的反应特性及抗氧化特性。结果表明:在pH值3～9的条件下,6种乳清蛋白糖基化复合物与乳清蛋白420nm和294nm处的吸光值差异显著(P<0.05);且6种乳清蛋白糖基化复合物的游离氧基酸含量均显著降低(P<0.05)。除了乳清蛋白-蔗糖复合物外,其他5种乳清蛋白糖基化复合物的还原能力、DPPH自由基清除能、·OH自由基清除能力和抗脂质过氧化能力随pH值的升高都有所提高。乳清蛋白-木糖复合物的抗氧化能力提高最大,而且在pH值7～9的反应条件下,具有比V_c更高的还原能力。     

碳纳米管和镍共修饰BDD电极及其在非酶葡萄糖电化学传感器中的应用

目的 制备碳纳米管-镍/掺硼金刚石复合电极（CNTs-Ni/BDD）,并用于非酶葡萄糖电化学检测。方法 采用热丝化学气相沉积（HFCVD）在硅基体上沉积BDD,然后采用物理气相沉积（PVD）技术在BDD上沉积Ni薄膜,最后在管式炉中对Ni/BDD样品进行900 ℃热催化处理,调控热处理时间分别为30、90 min,得到不同微观结构的CNTs-Ni/BDD复合电极。采用扫描电子显微镜（SEM）、Raman光谱和电化学工作站分别表征电极的表面形貌、成分和电化学性能。结果 在Ni的高温催化作用下,BDD作为基体和唯一碳源,在其表面直接生长出CNTs,实现Ni纳米颗粒和CNTs共修饰BDD。热处理时间由30 min增加到90 min,CNTs长度明显增加,对BDD的覆盖程度增加,且顶端的Ni颗粒消失。CNTs和Ni的共修饰作用极大地提升了葡萄糖的电化学检测性能,且30 min-CNTs-Ni/BDD复合电极性能更优异,其灵敏度在葡萄糖浓度0.005~0.02 mmol/L、0.02~1 mmol/L、1.0~5.5 mmol/L线性范围内分别为475、42、19 μA/((mmol/L)?cm2),检测限为0.42 μmol/L（S/N=3）。结论 热催化处理可以简单高效地实现CNTs、Ni共修饰BDD,该复合电极能够有效地提升葡萄糖电化学检测性能。     

超声预处理制备大豆分离蛋白/糖复合物及其结构与溶解性

将大豆分离蛋白（soybean protein isolate,SPI）分别与葡萄糖和麦芽糖进行糖基化反应,对SPI/糖复合物进行超声预处理,探讨超声预处理对SPI/糖复合物结构和溶解性的影响。葡萄糖比麦芽糖更易与SPI发生糖基化反应,超声预处理能制备高接枝度且低褐变的SPI/糖复合物,且超声预处理20 min时,SPI/糖复合物的接枝度最大。傅里叶变换红外光谱分析证明了SPI/糖复合物的形成。糖基化反应会减少热处理过程中SPI二级结构由有序向无序的转变程度,使其三级结构变得松散;超声预处理对SPI/糖复合物二级结构的影响并不显著（P＞0.05）,但会加强糖基化复合物三级结构的松散程度,这可能是导致超声预处理制备的SPI/糖复合物具有较高溶解性的主要原因。此外,溶解性的改善可能与超声预处理提高SPI/糖复合物的接枝度有关。     

Solvent Participation in a One‐Pot Glycosylation Strategy (SPOG)

Solvent participation in a one‐pot glycosylation strategy (SPOG) was developed on the basis of the low concentration β‐selective glycosylation method. This strategy enables the production of a β‐glycosidic bond in a one‐pot oligosaccharide synthesis without or with minimal use of any C‐2 participating function.     

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Characterization of a Galactosynthase Derived from Bacillus circulans β‐Galactosidase: Facile Synthesis of D‐Lacto‐ and D‐Galacto‐N‐bioside

Glycosynthases—retaining glycosidases mutated at their catalytic nucleophile—catalyze the formation of glycosidic bonds from glycosyl fluorides as donor sugars and various glycosides as acceptor sugars. Here the first glycosynthase derived from a family 35 β‐galactosidase is described. The Glu→Gly mutant of BgaC from Bacillus circulans (BgaC‐E233G) catalyzed regioselective galactosylation at the 3‐position of the sugar acceptors with α‐galactosyl fluoride as the donor. Transfer to 4‐nitophenyl α‐D ‐N‐acetyl‐glucosaminide and α‐D ‐N‐acetylgalactosaminide yielded 4‐nitophenyl α‐lacto‐N‐biose and α‐galacto‐N‐biose, respectively, in high yields (up to 98 %). Kinetic analysis revealed that the high affinity of the acceptors contributed mostly to the BgaC‐E233G‐catalyzed transglycosylation. BgaC‐E233G showed no activity with β‐(1,3)‐linked disaccharides as acceptors, thus suggesting that this enzyme can be used in “one‐pot synthesis” of LNB‐ or GNB‐containing glycans.     

Glycosyltransferase B4GALNT2 as a Predictor of Good Prognosis in Colon Cancer: Lessons from Databases

Background: glycosyltransferase B4GALNT2 and its cognate carbohydrate antigen Sd^a are highly expressed in normal colon but strongly downregulated in colorectal carcinoma (CRC). We previously showed that CRC patients expressing higher B4GALNT2 mRNA levels displayed longer survival. Forced B4GALNT2 expression reduced the malignancy and stemness of colon cancer cells. Methods: Kaplan–Meier survival curves were determined in “The Cancer Genome Atlas” (TCGA) COAD cohort for several glycosyltransferases, oncogenes, and tumor suppressor genes. Whole expression data of coding genes as well as miRNA and methylation data for B4GALNT2 were downloaded from TCGA. Results: the prognostic potential of B4GALNT2 was the best among the glycosyltransferases tested and better than that of many oncogenes and tumor suppressor genes; high B4GALNT2 expression was associated with a lower malignancy gene expression profile; differential methylation of an intronic B4GALNT2 gene position and miR-204-5p expression play major roles in B4GALNT2 regulation. Conclusions: high B4GALNT2 expression is a strong predictor of good prognosis in CRC as a part of a wider molecular signature that includes ZG16, ITLN1, BEST2, and GUCA2B. Differential DNA methylation and miRNA expression contribute to regulating B4GALNT2 expression during colorectal carcinogenesis.