Tetanic stimulation and cyclic adenosine monophosphate regulate segregation of presynaptic inputs on a common postsynaptic target neuron in vitro

Previous studies indicated that Aplysia sensory neurons (SNs) compete when reestablishing synapses with a motor cell target (1.7) in vitro. The competition is characterized by a cell number-dependent decrease in the efficacy of each connection, an increase in the elimination of SN varicosities, a reduction in the formation of new SN varicosities, and the segregation of varicosities of each SN to restricted portions of the target axons. The changes do not require spike activity, since both the SNs and L7 do not fire spontaneously. Here, we examined whether adding activity to SNs during the early stages of synapse formation with stimuli known to evoke facilitatory responses in stable SN-L7 connections—tetanic stimulation or increase in intracellular cyclic adenosine monophosphate (cAMP)—would modulate the intrinsic segregatory process. Tetanic stimulation to one SN increased synapse efficacy and the number of varicosities of the stimulated SNs while reducing the functional changes by the nonstimulated SNs in the same cultures. An increase in the stability of preexisting varicosities contributed to the overall increase in varicosities evoked by tetanus. The functional changes evoked by tetanus were not expressed when the same tetanic stimulation was also given to the other SN, or when L7 was hyperpolarized during the tetanus to the SN. Raising cAMP levels in one SN increased synapse efficacy and the rate of new varicosity formation by the injected SNs without affecting the development of the connections formed by the noninjected SNs. These results suggest that different forms of presynaptic and postsynaptic activities in neurons can regulate specific aspects of the competitive process associated with the fine-tuning of connections formed by converging presynaptic inputs. © 1996 John Wiley & Sons, Inc.     

Morphological effects of ciliary neurotrophic factor treatment during neuromuscular synapse elimination

In adult skeletal muscles, exogenous ciliary neurotrophic factor (CNTF) induces axons and their nerve terminals to sprout. CNTF also regulates the amount of multiple innervation in developing skeletal muscles during synapse elimination, maintaining multiple innervation of muscle fibers. While CNTF may maintain multiple innervation by regulating developmental synapse elimination, it is also possible that CNTF induces the formation of new multiple innervation through a sprouting response. In this study I examined morphologically the effects of CNTF during synapse elimination in the extensor digitorum longus (EDL) muscle. Rat pups received injections of CNTF in one leg and vehicle in the other either early [postnatal day 7 (P7)-P13] or late (P14–P20) in development. The early treatment period corresponds to that time when the pattern of innervation in the EDL is converted from predominantly multiple to single innervation. The late treatment period is at the end of synapse elimination for the EDL but corresponds to the major period of synapse elimination in the levator ani (LA), allowing a comparison of effects on these two muscles from the same animals. On the day after the final injection, EDL muscles were dissected and stained with tetranitroblue tetrazolium and the resulting pattern of innervation was assessed. The present findings indicate that only the early CNTF treatment regulates the level of multiple innervation in the EDL. Moreover, the effect of early CNTF treatment was local, affecting multiple innervation only in the EDL from the CNTF-treated leg. CNTF injected during the late treatment period had no apparent effects on the EDL but had a potent effect on the pattern of innervation in the LA, significantly increasing the level of multiple innervation in this muscle. Thus, CNTF affected multiple innervation in these two muscles only if provided during the period when single innervation normally develops. There was no evidence to indicate that CNTF induced axons or their terminals to sprout during either treatment period. In conclusion, CNTF increases the level of multiple innervation, probably by regulating synapse elimination, and skeletal muscles themselves may be an important target site for CNTF action. Presumably, the sprouting response to CNTF found in adult muscle develops sometime after P21. © 1996 John Wiley & Sons, Inc.     

Disproportionate numbers of rDNA loci in diploid and polyploid testis nuclei of gerris najas detected by fluorescence in situ hybridization

The replication state of rDNA in testes nuclei undergoing polyploidization by classical-type endomitosis was investigated in Gerris najas (Heteroptera) by means of fluorescence in situ hybridization. The number of just one rDNA locus per haploid genome was determined by in situ hybridization on meiotic nuclei. Additionally, DNA measurements of spermatids and testes nuclei were performed. Although regular duplication levels of nuclear DNA were found within the limits of the accuracy of the method, these did evidently not apply to the ribosomal genes. The comparison of the number of rDNA signals with the DNA content of 106 testis nuclei revealed drastic variations of the number of rDNA loci between individual nuclei with similar DNA content. Polyploid nuclei of the testis epithelium showed too low numbers of rDNA loci in relation to those expected from the levels of ploidy, while cyst cell nuclei displayed increased numbers of rDNA loci. The results indicate that the ribosomal genes are either underreplicated, or in part eliminated, during the endomitotic cycles of epithelium cell nuclei, but amplified in the cyst cell nuclei, probably already at their diploid stage.     

基于SIFT特征和近似最近邻算法的医学CT图像检索

针对医学X线计算机断层（Computed Tomography,CT）图像,提出了一种基于尺度不变特征变换（Scale InvariantFeature Transform,SIFT）特征和近似最近邻算法的检索方法。首先通过SIFT算法得到图像的特征点和相应的特征向量,再采用近似最近邻算法进行SIFT特征向量的匹配搜索,得到数据库中与参考图像最相似的图像序列。实验结果表明,该法能检索到与目标图像细节相符的结果,大大提高了检索速度。与传统的基于纹理的检索方法相比,查准率和检索结果与目标图像的相似程度方面更佳,符合医学CT图像检索的要求。     

基于鼠脑海马位置细胞与Q学习面向目标导航

生理学实验表明在鼠脑海马结构中存在的一种具有特异性放电特征的细胞,它在大鼠空间导航和环境认知中起着关键性作用,该特异性神经元被称之为位置细胞。本文将基于位置细胞、运动神经元来构建一种前馈神经网络模型,采用Q学习算法实现大鼠面向目标导航任务。实验结果表明该前馈神经网络模型能快速实现大鼠面向目标导航任务。     

基于HP模型的蛋白质折叠问题的研究

基于蛋白质二维HP模型提出改进的遗传算法对真实蛋白质进行计算机折叠模拟。结果显示疏水能量函数最小值的蛋白质构象对应含疏水核心的稳定结构,疏水作用在蛋白质折叠中起主要作用。研究表明二维HP模型在蛋白质折叠研究中是可行的和有效的并为进一步揭示蛋白质折叠机理提供重要参考信息。     

基于遗传算法特征选择的HBV再激活分类预测模型

探讨原发性肝癌患者精确放疗后乙型肝炎病毒(hepatitis b virus,HBV)再激活的危险特征和分类预测模型。提出基于遗传算法的特征选择方法,从原发性肝癌数据的初始特征集中选择HBV再激活的最优特征子集。建立贝叶斯和支持向量机的HBV再激活分类预测模型,并预测最优特征子集和初始特征集的分类性能。实验结果表明,基于遗传算法的特征选择提高了HBV再激活分类性能,最优特征子集的分类性能明显优于初始特征子集的分类性能。影响HBV再激活的最优特征子集包括:HBV DNA水平,肿瘤分期TNM,Child-Pugh,外放边界和全肝最大剂量。贝叶斯的分类准确性最高可达82.89%,支持向量机的分类准确性最高可达83.34%。     

基于序列特征的环状RNA识别

环状RNA是新发现的一类具有重要生物学功能的RNA。现有的环状RNA识别工具依赖高通量测序数据,因数据本身和识别方式的弊端而普遍存在准确性不足、不同方法间重复性低以及假阳性率/假阴性率高等缺点。为了解决该问题,我们搭建模型来实现不依赖于测序数据而根据序列的内在特征的环状RNA从头预测。本文选取了包括剪接位点上下游内含子的长度、A-to-I密度和Alu重复序列等100个与RNA成环相关的序列特征,建立了机器学习模型,并识别了人类基因组中的环状RNA,比较了两种机器学习方法随机森林法(RF)和支持向量机(SVM)的分类效果。结果表明,所选序列特征能有效地鉴别RNA能否成环,同时,不同序列特征对模型的分类预测能力的贡献也不同。相比于SVM方法,RF分类的效果更好。     

DNA存储中的编码技术

脱氧核糖核酸(Deoxyribonucleic Acid, DNA)是一种天然的信息存储介质,具有存储密度高、存储时间长、损耗率低等特点。在传统存储方式不能满足信息增长的需求时,DNA数据存储技术逐渐成为研究热点。DNA编码是用尽可能少的碱基序列无错的存储数据信息,包括压缩(尽可能少的占用空间)、纠错(无错存储)和转换(数字信息转为碱基序列)3部分。DNA编码是DNA存储中的关键技术,它的结果直接影响存储性能的优劣和数据读写的完整。本文首先介绍DNA存储的发展历史,然后介绍DNA存储的框架,其中重点介绍DNA编码技术,最后对DNA存储中的编解码技术的未来发展方向进行讨论。     

Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic

Many chemical and environmental data sets are complicated by the existence of fully missing values or censored values known to lie below detection thresholds. For example, week-long samples of airborne particulate matter were obtained at Alert, NWT, Canada, between 1980 and 1991, where some of the concentrations of 24 particulate constituents were coarsened in the sense of being either fully missing or below detection limits. To facilitate scientific analysis, it is appealing to create complete data by filling in missing values so that standard complete-data methods can be applied. We briefly review commonly used strategies for handling missing values and focus on the multiple-imputation approach, which generally leads to valid inferences when faced with missing data. Three statistical models are developed for multiply imputing the missing values of airborne particulate matter. We expect that these models are useful for creating multiple imputations in a variety of incomplete multivariate time series data sets.