走马胎的组织培养与快速繁殖

以走马胎(Ardisia gigantifolia)幼嫩茎段为外植体, 通过腋芽增殖的方式进行组织培养和快速繁殖研究。结果表明, 培养基MS+1.0 mg·L ^-1 6-BA+0.2 mg·L ^-1NAA和MS+0.5 mg·L ^-1 ZT均可用于腋芽的诱导和前期继代培养, 诱导率分别为89.3%和85.7%; 芽增殖最佳培养基为MS+0.5 mg·L ^-16-BA+0.1 mg·L ^-1ZT+0.1 mg·L ^-1NAA, 增殖系数为4.3倍; 根诱导最佳培养基为1/2MS+1.5 mg·L ^-1 IAA+1.0 mg·L ^-1 NAA, 生根率达92.3%, 且根系发达, 植株健壮; 生根苗在混合基质园土:泥炭:珍珠岩=3:1:1 (v/v/v )中移栽成活率为82%。该研究建立了走马胎种苗的组织培养快速繁殖技术体系, 且可应用于规模化生产。     

黑胸大蠊（Periplaneta fuliginosa）病毒的分离及某些特性

从黑胸大蠊(Periplaneta fuliginosa)自然罹病的虫尸中分离得到一株非包涵体病毒。将病毒悬液均匀拌入无菌饲料并供食154～169日龄黑胸大蠊健康若虫时,能使其感染、发病,死亡率可达98％以上。在电子显微镜下观察时,病毒为球形二十面体颗粒,直径约23nm。病毒悬液具有典型核蛋白紫外吸收光谱。病毒用DNase和RNase处理并经吖啶橙染色、二苯胺和苔黑酚试验及甲醛反应证明:该病毒含有单链DNA。以上特性与细小病毒科的特征有点类似。     

为害黄芪种子的广肩种子小蜂属四新种(膜翅目:广肩小蜂科)

据我们在北京和内蒙古等地多年研究表明,黄芪的植食性种子小蜂包括广肩小蜂科Bruchophagus属5种和金小蜂科Habrocytus属1种,为多种混合群体。我们通过大量标本的形态比较以及交配行为的观察,结合其生物学特性研究以及应用扫描电镜对其并胸腹节花纹的超微结构观察,鉴定出黄芪种子里有5种广肩种子小蜂,即黄芪种子小蜂Bruchophagus huonchi Liao et Fan及本文的4新种。     

HL-60细胞诱导分化期间细胞表面ConA受体结合量变化的研究

 <正> 在用二甲亚砜(DMSO)诱导人急性早幼粒细胞性白血病细胞系(HL-60 Cell)沿粒系统分化成熟的实验基础上,我们用受体荧光标记技术和荧光分光光度法,进一步观察了HL-60细胞诱导分化期间,细胞膜流动性动态降低对膜上伴刀豆球蛋白(ConA)受体结合量的影响。     

Quantitation of Rat Dopamine Transporter mRNA: Effects of Cocaine Treatment and Withdrawal

Dopamine transporter mRNA levels in the rat substantia nigra were quantified using a sensitive nuclease protection assay with a highly homologous human dopamine transporter cDNA clone. The same probe was also used to visualize dopamine transporter mRNA in the substantia nigra by in situ hybridization. Repeated cocaine administration (15 mg/kg, twice a day for 6.5 days) resulted in a greater than 40% decrease in nigral dopamine transporter mRNA levels. In contrast, dopamine transporter mRNA levels were unchanged after either acute treatment (4 h before death) or repeated cocaine treatment followed by a 72-h withdrawal period. Thus, blockade of the dopamine transporter by repeated cocaine administration may result in the down-regulation of dopamine transporter gene expression in dopamine neurons.     

Predicting protein secondary structure using neural net and statistical methods.

A comparison of neural network methods and Bayesian statistical methods is presented for prediction of the secondary structure of proteins given their primary sequence. The Bayesian method makes the unphysical assumption that the probability of an amino acid occurring in each position in the protein is independent of the amino acids occurring elsewhere. However, we find the predictive accuracy of the Bayesian method to be only minimally less than the accuracy of the most sophisticated methods used to date. We present the relationship of neural network methods to Bayesian statistical methods and show that, in principle, neural methods offer considerable power, although apparently they are not particularly useful for this problem. In the process, we derive a neural formalism in which the output neurons directly represent the conditional probabilities of structure class. The probabilistic formalism allows introduction of a new objective function, the mutual information, which translates the notion of correlation as a measure of predictive accuracy into a useful training measure. Although a similar accuracy to other approaches (utilizing a mean-square error) is achieved using this new measure, the accuracy on the training set is significantly and tantalizingly higher, even though the number of adjustable parameters remains the same. The mutual information measure predicts a greater fraction of helix and sheet structures correctly than the mean-square error measure, at the expense of coil accuracy, precisely as it was designed to do. By combining the two objective functions, we obtain a marginally improved accuracy of 64.4%, with Matthews coefficients C alpha, C beta and Ccoil of 0.40, 0.32 and 0.42, respectively. However, since all methods to date perform only slightly better than the Bayes algorithm, which entails the drastic assumption of independence of amino acids, one is forced to conclude that little progress has been made on this problem, despite the application of a variety of sophisticated algorithms such as neural networks, and that further advances will require a better understanding of the relevant biophysics.     

南滚河流域土地利用变化对亚洲象生境的影响

土地利用变化对亚洲象生境影响显著,明晰其影响机制是有效保护亚洲象的前提。为探明土地利用变化对亚洲象生境影响的时空过程及机制,以亚洲象残存的中-缅跨境流域-南滚河流域为例,在1988和2018年两期Landsat土地利用/土地覆被遥感分类图的基础上,采用LandTrendr算法检测30年间流域土地利用变化引起的天然林扰动,结合生态位因子分析（ENFA）模型评定的亚洲象生境适宜性分布,探究以天然林扰动为主的土地利用变化对亚洲象生境的影响。结果表明：（1）1988-2018年间,南滚河流域土地利用变化主要为天然林转化为其他地类,且天然林扰动强度在中、缅境内差异明显;（2）以橡胶种植扩张导致毁林为主的土地利用变化造成南滚河流域亚洲象生境萎缩,生境斑块间连通性降低,破碎化程度较高;（3）该流域亚洲象生境丧失过程表现为由边缘向内部逐渐被蚕食,适宜生境最终被分割为上、下游两个相互孤立的子区域。因此,抑制以橡胶林为主的热作种植扩张,恢复上、下游生境连通性,建立流域尺度的跨境保护区,是实现南滚河流域亚洲象种群保护和缓解人象冲突的重要途径。     

大溪水库和沙河水库主要鱼类营养结构的时空变化

为了解大溪水库和沙河水库主要鱼类食物网营养结构的时空变化特征,依据2017年夏、秋季和2018年春季在大溪水库和沙河水库的调查结果,利用稳定同位素方法对这两个水域内鱼类的营养关系进行研究,得到以下主要结论：大溪水库共出现鱼类28种,沙河水库29种,鱼类群落结构组成结构相似,呈现出以湖泊定居性鱼类和鲤科鱼类为主的特征。配对双样本时空差异分析显示,相同季度内两个水库鱼类的δ¹³C值差异显著,说明两个水库的初级食物源存在明显不同;相同区域内,大溪水库季度差异不明显,而沙河水库差异显著,说明大溪水库的初级食物源组成变动较沙河水库的更小。δ¹⁵N值时空变化规律不明显,这可能与水库周围农业活动和人类活动的不确定性有关。鱼类群落指标值分析结果显示,沙河水库的CR、NR、TA、SEAc、CD、MNND和SDNND指标值均高于大溪水库,且春季高于其他季度,这表明沙河水库春季食物网较其他季节、较大溪水库更为复杂,食物源更加丰富,食物链更长,营养层次更多,核心生态位宽幅更低,营养级多样性的总程度更高,营养生态位均匀度较低,大溪水库食物网的冗余程度较高,说明相较于沙河水库,大溪水库生态系统稳定性更高,抗干扰能力更强,这可能与沙河水库周边广泛的茶园、旅游区和和居民区密集分布有关。基于各种量化群落指标对大溪水库和沙河水库的食物网结构进行时空差异分析,能够为大溪水库和沙河水库水生生态系统的管理与修复提供理论支撑。