转基因技术对实现作物增产增质, 降低农药使用量, 降低生产成本等具有重要作用, 但对生态环境也存在一定的潜在威胁。 为了防止转基因大豆在食品化中的滥用, 对转基因产品快速鉴别技术的研究尤为迫切。 紫外拉曼光谱检测技术具备外场远距离无损遥测检测, 简单高效, 快速准确等优点, 可有效用于物质遥测鉴别领域。 基于紫外拉曼光谱的转基因/非转基因大豆油以及与其他类别食用油鉴别方法, 采集了五种不同食用油(两种品牌转基因/非转基因大豆油各500组样本和一种稻米油100组样本, 共2 100组样本)在3 500~400 cm-1(268~293 nm)范围内的日盲紫外拉曼光谱信息, 为提高光谱数据的信噪比并保证分类识别的准确性, 对上述光谱数据采用Savitzky-Golay滤波降噪、 基于自适应迭代加权惩罚最小二乘法(airPLS)的基线校正以及多元散射校正(MSC)的光谱数据修正等预处理。 根据大豆油的紫外拉曼指纹图谱, 分析出主要化学成分包含脂肪类、 蛋白质类、 酰胺类。 将每种大豆油样本按1∶1划分为训练集和测试集, 输入训练集数据至支持向量机(SVM)进行训练, 采用10折交叉验证建立最佳模型, 识别准确率达99.81%, 对转基因大豆油的判别效果显著; 采用主成分分析法(PCA)进行数据降维处理, 提取出8个主成分, 累计贡献率为74.84%, 可代表大部分原始数据特征。 在此基础上, 将预处理后的光谱数据按4∶1划分为训练集和测试集, 采用偏最小二乘回归判别分析方法(PLS-DA), 结合10折交叉验证法建立全谱的最佳PLS-DA模型(判别阈值设置为0.5), 判别准确率达到70.95%。 研究表明, 紫外拉曼光谱分析方法可较为准确地鉴别非转基因/转基因大豆油, 同时可鉴别大豆油与稻米油, 实现对转基因大豆食品的快速无损鉴别, 可望成为转基因大豆油及其食品的现场检测新的技术途径, 对推动转基因产品遥测鉴别技术的发展具有进步意义。

NAC转录因子, 对植物的生长发育及抵御逆境胁迫起着重要的作用。实验室前期克隆了辽宁碱蓬(Suaeda liaotungensis)Slnac2基因, 转Slnac2拟南芥(Arabidopsis thaliana)提高了抵御盐胁迫的能力。本研究利用基因芯片技术筛选转SlNAC2拟南芥差异表达基因, 共筛选出差异表达2倍以上的基因1 258个。GO富集度分析结果显示, 分子功能相关基因占34.06%, 细胞组分相关基因占33.13%, 生物学过程相关基因占32.81%。KEGG分析表明, 差异表达基因涉及63个信号通路, 主要有植物激素信号转导、核糖体、植物病原物相互作用和抗坏血酸代谢等。通过实时荧光定量PCR对部分差异基因进行验证, 所得结果与基因芯片结果一致。本研究揭示, SlNAC2可调控多个下游基因的表达, 提高植物在逆境胁迫下的生存能力。

The moving-window bis-correlation coe±cients (MW-BiCC) was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and --thalassemia with visible and nearinfrared (Vis–NIR) spectroscopy. The well-performed moving-window principal component analysis linear discriminant analysis (MW-PCA–LDA) was also conducted for comparison. A total of 306 transgenic (positive) and 150 nontransgenic (negative) leave samples of sugarcane were collected and divided to calibration, prediction, and validation. The diffuse reflection spectra were corrected using Savitzky–Golay (SG) smoothing with first-order derivative (d=1), third-degree polynomial (p=3) and 25 smoothing points (m=25). The selected waveband was 736–1054 nm with MW-BiCC, and the positive and negative validation recognition rates (V REC+, V REC-T were 100%, 98.0%, which achieved the same effect as MW-PCA–LDA. Another example, the 93 --thalassemia (positive) and 148 nonthalassemia (negative) of human hemolytic samples were collected. The transmission spectra were corrected using SG smoothing with d=1, p=3 and m=53. Using MW-BiCC, many best wavebands were selected (e.g., 1116–1146, 1794–1848 and 2284–2342nm). The V REC+ and V REC- were both 100%, which achieved the same effect as MW-PCA–LDA. Importantly, the BiCC only required calculating correlation coe±cients between the spectrum of prediction sample and the average spectra of two types of calibration samples. Thus, BiCC was very simple in algorithm, and expected to obtain more applications. The results first confirmed the feasibility of distinguishing --thalassemia and normal control samples by NIR spectroscopy, and provided a promising simple tool for large population thalassemia screening.

Alzheimer's disease (AD) is a chronic neurodegenerative disease. The symptoms include memory and spatial learning di±culties, language disorders, and loss of motivation, which get worse over time, eventually ending in death. No effective treatments are available for AD, currently. Current treatments only attenuate symptoms temporarily and are associated with severe side effects. Near infra-red (NIR) light has been studied for a long time. We investigated the effect of NIR on AD using a transgenic mouse model, which was obtained by co-injecting two vectors carrying AD mutations in amyloid precursor protein (APP) and presenilin-1 (PSEN1) into C57BL/6J mice. The irradiation equipment consisted of an accommodating box and an LED array. The wavelength of NIR light emitted from LED was between 1040 nm and 1090 nm. The power density delivered at the level of the mice was approximately 15mW/cm2. Firstly, we treated the mice with NIR for 40 days. Then, the irradiation was suspended for 28 days. Finally, another 15 days treatment was brought to mice. We conducted Morris water maze and immunofluorescence analysis to evaluate the effects of treatment. Immunofluorescence analysis was based on measuring the quantity of plaques in mouse brain slices. Our results show that NIR light improves memory and spatial learning ability and reduces plaques moderately. NIR light represents a potential treatment for AD.

转基因技术在过去的几十年里快速发展, 然而此项技术对生态环境、 伦理道德等可能带来的影响尚存争议, 因此针对农作物的转基因成分检测和鉴别的相关技术研究十分重要。 本研究以转双价基因(cry1Ab/cry2Aj-G10evo)玉米籽粒和玉米面粉为研究对象, 采用近红外光谱仪采集900～1 700 nm波段范围的光谱, 结合 Savitzky-Golay(SG)平滑算法对提取出的光谱数据进行去除噪声处理。 基于全波段光谱和PCA主成分分别建立了偏最小二乘判别分析(PLS)和支持向量机判别模型(SVM)。 试验结果表明, 在转基因玉米籽粒全谱的判别分析模型中, SVM判别模型效果要优于PLS判别模型, SVM模型识别正确率达到90%以上, PLS的模型识别率只有85%左右。 以PCA降维后建立的模型中, SVM模型也取得了最优的效果, 建模集和预测集识别正确率达到100%。 虽然转基因玉米在研磨加工后外源蛋白和DNA有所下降, 但是转基因玉米粉末基于全波段光谱建立的SVM模型的建模集正确率仍有90.625%。 结果表明应用近红外光谱技术集合化学计量学方法对转基因玉米的鉴别是可行的, 为转基因玉米乃至其他转基因农产品的鉴别提供了技术支持, 具有重要的理论意义和应用价值。

大豆Lea5基因是LEA基因家族成员之一。为分析大豆Lea5基因的功能, 构建了大豆Lea5基因植物过表达载体pBI121-Lea5。通过农杆菌介导法转化烟草,获得TL-06、TL-09、TL-17和TL-32等4个转大豆Lea5基因烟草株系。RT-PCR分析表明大豆Lea5基因在4个转基因烟草株系的T2代植株均有不同程度的表达。以转基因TL-09和TL-32株系T2代植株为材料, 进行了干旱和盐渍处理, 结果表明, 2个转大豆Lea5基因烟草株系T2代植株对干旱和盐渍的抗性显著强于野生型烟草, 说明大豆Lea5基因可以提高植物抗干旱和盐碱的能力。

通过木质素基因工程能够有效降低杨木细胞壁木质素含量, 从而改善人工林杨树作为木质纤维材料的利用现状。 选取C3H基因活性抑制表达的转基因杨树和其对照组杨树为实验材料, 利用傅里叶红外光谱（FTIR）技术快速表征C3H基因表达活性降低后幼龄杨木细胞壁木质素的含量, 并结合激光共聚焦显微镜（CLSM）和组织化学染色技术原位表征木质素含量微区分布变化规律。 结果表明转基因杨树与对照组杨树红外谱图的形状和特征峰数目、 位置基本一致, 表明C3H基因活性降低并未改变杨木细胞壁主要化学成分及结构, 但I1 508/I1 379, I1 508/I1 425和I1 508/I1 740木质素特征峰高度比值结果表明转基因杨木木质素含量下降了8.2%～9.5%, 峰强度的区别说明C3H基因活性抑制表达能够改变杨木细胞壁上木质素等化学组分含量; CLSM观察发现转基因杨木木质素微区分布含量均为纤维细胞角隅>复合胞间层>次生壁, 与对照组木质素呈现相同的沉积规律, 且转基因杨木细胞壁木质素浓度低于对照组杨木; 组织化学染色的结果同样表明杨木S单体木质素均匀分布于纤维细胞壁上, 而G单体木质素微区沉积规律为纤维细胞角隅>复合胞间层>次生壁, 进一步揭示了C3H基因活性的降低并没有改变转基因杨木G和S木质素单体的沉积规律, 但对其纤维和导管壁上木质素单体含量分布有一定影响。

太赫兹时域光谱(THz-TDS)技术是基于飞秒超快激光技术的 THz 波段光谱测量新技术, 具有较强的光谱分辨本领以及良好的透视性和安全性, 在物质检测方面具有广泛的应用价值。文中在采用太赫兹时域光谱技术对转基因大豆油光谱检测的基础上结合主成分分析方法(PCA)及支持向量机(SVM), 构建PCA-SVM模型对转基因大豆油进行鉴别。首先, 从样品在太赫兹波段测得的时域光谱中得到其吸光度光谱; 然后, 将其作为输入源导入PCA-SVM模型中, 剔除冗余数据、降低数据维数并鉴别。实验结果表明, 所建立的PCA-SVM模型能准确识别校验集, 可以准确地对转基因大豆油进行鉴别。研究结果表明: 太赫兹时域光谱技术可以实现转基因大豆油的快速、无损检测, 在食品安全领域有广泛的应用前景。