生物光子场的光谱分布特性研究

改装设计了分光谱段测试生物光子场辐射强度的装置;用此装置实验证明生物系统的超微弱光子辐射（ＵＰＥ）存在于从紫外－可见到红外的宽光谱范围内,而且其ｆ（λ）≌常数。此结果对于证实生物光子场的相干特性具有一定意义。     

Distribution and Features of the Six Classes of Peroxiredoxins

Peroxiredoxins are cysteine-dependent peroxide reductases that group into 6 different, structurally discernable classes. In 2011, our research team reported the application of a bioinformatic approach called active site profiling to extract active site-proximal sequence segments from the 29 distinct, structurally-characterized peroxiredoxins available at the time. These extracted sequences were then used to create unique profiles for the six groups which were subsequently used to search GenBank(nr), allowing identification of ∼3500 peroxiredoxin sequences and their respective subgroups. Summarized in this minireview are the features and phylogenetic distributions of each of these peroxiredoxin subgroups; an example is also provided illustrating the use of the web accessible, searchable database known as PREX to identify subfamily-specific peroxiredoxin sequences for the organism Vitis vinifera (grape).     

Fluorescence and Absorption Spectra of Biological Dyes

Data include charts and tables of absorbance and fluorescence of 4 coupling agents for immunity reactions, 34 typical fluorescent dyes and reagents, and 12 dyes or reagents having no fluorescence in solution but which may be fluorescent in the dry state. Since this report consists largely of reference data, the original must be consulted for details. Reprint source: The Perkin-Elmer Corporation, Norwalk, Connecticut, U. S. A.     

串联重复序列的物种差异及其生物功能

串联重复序列是指1-200个碱基左右的核心重复单位,以头尾相串联的方式重复多次所组成的重 复序列。它广泛存在于真核生物和一些原核生物的基因组中,并表现出种属、碱基组成等的特异性。在基因组 整体水平上,各种优势的重复序列类型不同。即使在同一重复序列类型内部,不同重复拷贝类别(如AT、AC 等)在基因组中的存在也表现出很大的差异。同时,这些重复序列类型和各重复拷贝类别在同一物种的不同染 色体间,以及基因的编码区和非编码区间也表现种属和碱基组成差异。这些差异显示了重复序列起源和进化的 复杂性,可能涉及到多种机制和因素,并与生物功能密切相关。另外,由于重复序列分析软件和统计标准还存 在算法、重复长度、完美性等问题,需要进一步探讨。此外,串联重复序列的自身进化关系、全基因组水平上 的进化地位、在基因组中的生物功能、重复序列数据库建立和应用研究等,将是今后研究的主要课题。     

Distribution of a Population of Rhizobium leguminosarum bv. trifolii among Different Size Classes of Soil Aggregates

A combination of the plant infection-soil dilution technique (most-probable-number [MPN] technique) and immunofluorescence direct count (IFDC) microscopy was used to examine the effects of three winter cover crop treatments on the distribution of a soil population of Rhizobium leguminosarum bv. trifolii across different size classes of soil aggregates (<0.25, 0.25 to 0.5, 0.5 to 1.0, 1.0 to 2.0, and 2.0 to 5.0 mm). The aggregates were prepared from a Willamette silt loam soil immediately after harvest of broccoli (September 1995) and before planting and after harvest of sweet corn (June and September 1996, respectively). The summer crops were grown in soil that had been either fallowed or planted with a cover crop of red clover (legume) or triticale (cereal) from September to April. The Rhizobium soil population was heterogeneously distributed across the different size classes of soil aggregates, and the distribution was influenced by cover crop treatment and sampling time. On both September samplings, the smallest size class of aggregates (<0.25 mm) recovered from the red clover plots carried between 30 and 70% of the total nodulating R. leguminosarum population, as estimated by the MPN procedure, while the same aggregate size class from the June sampling carried only approximately 6% of the population. In June, IDFC microscopy revealed that the 1.0- to 2.0-mm size class of aggregates from the red clover treatment carried a significantly greater population density of the successful nodule-occupying serotype, AR18, than did the aggregate size classes of <0.5 mm, and 2 to 5 mm. In September, however, the population profile of AR18 had shifted such that the density was significantly greater in the 0.25- to 0.5-mm size class than in aggregates of <0.25 mm and >1.0 mm. The populations of two other Rhizobium serotypes (AR6 and AS36) followed the same trends of distribution in the June and September samplings. These data indicate the existence of structural microsites that vary in their suitabilities to support growth and protection of bacteria and that are influenced by the presence and type of plant grown in the soil.     

Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks

Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules). We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression.     

CoGA: An R Package to Identify Differentially Co-Expressed Gene Sets by Analyzing the Graph Spectra

Gene set analysis aims to identify predefined sets of functionally related genes that are differentially expressed between two conditions. Although gene set analysis has been very successful, by incorporating biological knowledge about the gene sets and enhancing statistical power over gene-by-gene analyses, it does not take into account the correlation (association) structure among the genes. In this work, we present CoGA (Co-expression Graph Analyzer), an R package for the identification of groups of differentially associated genes between two phenotypes. The analysis is based on concepts of Information Theory applied to the spectral distributions of the gene co-expression graphs, such as the spectral entropy to measure the randomness of a graph structure and the Jensen-Shannon divergence to discriminate classes of graphs. The package also includes common measures to compare gene co-expression networks in terms of their structural properties, such as centrality, degree distribution, shortest path length, and clustering coefficient. Besides the structural analyses, CoGA also includes graphical interfaces for visual inspection of the networks, ranking of genes according to their “importance” in the network, and the standard differential expression analysis. We show by both simulation experiments and analyses of real data that the statistical tests performed by CoGA indeed control the rate of false positives and is able to identify differentially co-expressed genes that other methods failed.     

Gene Duplication and the Properties of Biological Networks

Patterns of network connection of members of multigene families were examined for two biological networks: a genetic network from the yeast Saccharomyces cerevisiae and a protein–protein interaction network from Caenorhabditis elegans. In both networks, genes belonging to gene families represented by a single member in the genome (“singletons”) were disproportionately represented among the nodes having large numbers of connections. Of 68 single-member yeast families with 25 or more network connections, 28 (44.4%) were located in duplicated genomic segments believed to have originated from an ancient polyploidization event; thus, each of these 28 loci was thus presumably duplicated along with the genomic segment to which it belongs, but one of the two duplicates has subsequently been deleted. Nodes connected to major “hubs” with a large number of connections, tended to be relatively sparsely interconnected among themselves. Furthermore, duplicated genes, even those arising from recent duplication, rarely shared many network connections, suggesting that network connections are remarkably labile over evolutionary time. These factors serve to explain well-known general properties of biological networks, including their scale-free and modular nature. [Reviewing Editor : Dr. Manyuan Long]     

Distribution of Orientation Selectivity in Recurrent Networks of Spiking Neurons with Different Random Topologies

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.     

Distinctly Phosphorylated Neurofilaments in Different Classes of Neurons

Abstract: Recent immunohistochemical experiments revealed that specific anti-neurofilament monoclonal antibodies yield distinct patterns in different types of neurons. This led to the suggestion that neurofilaments are a family of heterogeneous molecules whose occurrence and distribution are a function of cell type. In the present study we examined the hypothesis that this heterogeneity is due to differences in the extent of phosphorylation of neurofilament proteins in distinct types of neurons. In view of the large number of potential phosphorylation sites on the heavy neurofilament protein (NF-H), we focused on this protein and examined its extent of phosphorylation in different types of neurons. This was performed using neurofilaments isolated from axons of the cholinergic bovine ventral root motor neurons and of the chemically heterogeneous bovine dorsal root neurons. Two-dimensional gel electrophoresis revealed that the isoelectric point of ventral root NF-H (pl 5.10) was ∼0.2 pl units more acidic than that of dorsal root NH-F. This difference was abolished by treating the neurofilaments with alkaline phosphatase, suggesting that the excess negative charge of ventral root NF-H is due to increased levels of phosphorylation. Amino acid analysis confirmed that the phosphoserine content of ventral root NF-H (27.2 ± 2.5% of the serines) is markedly higher than that of dorsal root NF-H (15.5 ± 6.2% of the serines). These findings provide a novel system for studying the biochemistry and function of distinctly phosphorylated neurofilaments in different types of neurons.     

不同激发波长的人体血清自体荧光光谱分析

利用分子荧光光度计测定了激发波长分别为457.9 nm,476.5 nm,488.0 nm,501.7 nm和514.5 nm光的血清自体荧光光谱,并对这些光谱的特征和产生机制进行了分析。实验和分析结果表明:在500 nm~750 nm的波长范围内,518 nm和640 nm附近有两个比较明显的荧光峰;590 nm处有一个非常弱的峰。它们可能主要来自于血清中胆红素,核黄素及其衍生物,β-胡萝卜素,锌卟啉及原卟啉IX等的贡献。这些研究结果将为利用氩离子激光器作为光源进行光谱诊断研究选择最佳激发波长提供一些参考。     

Genetic Differentiation in Populations with Different Classes of Individuals

I formulate and analyse a model of population structure with different classes of individuals. These different classes may be age classes, other demographic classes, or different types of habitats homogeneously distributed over a geographical area. The value of population differentiation under an island model of dispersal and the increase of differentiation with geographical distance in one- and two-dimensional "isolation by distance" models are then obtained for a generalization of the FST measure of population structure, as a function of "effective" mutation, migration, and population size parameters. The relevant effective subpopulation size is related to the "mutation effective population size" of a single isolated subpopulation and, in models of age-structured populations, to the inbreeding effective population size.     

Fluorescence and Absorption Spectra of Biological Dyes (Ii)

This paper supplements a previous report: Stain Techn. 38, 37-48, 1963. Spectra and tables of data are given for 11 fluorescent dyes in solution, 6 to clarify nomenclature, 3 for which fluorescence had not been observed, and 2 as controls. Improved instrumentation was used. Since this report consists largely of reference data, the original must be consulted for details. Reprint source: The Perkin-Elmer Corporation, Norwalk, Connecticut 06852, U. S. A.     

Another Step Forward to the understanding of Biological Signaling Networks

In this editorial I briefly review the new JCCS scientific directions that have emerged from the complicated situations created by the pandemics of COVID- 19, and by the internal audit of both Journal of Cell Communication and Signaling and International CCN Society, that were initiated since my proposal at the 2019 International Workshop on the CCN family of genes.I also welcome the distinguished members of our renewed JCCS Editorial and congratulate all those who have in many different ways participated to the consolidation of the 2021 JCCS Impact Factor attaining 5.908.     

Encoding of Naturalistic Stimuli by Local Field Potential Spectra in Networks of Excitatory and Inhibitory Neurons

Recordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely unknown. To understand the rules of translation between the structure of sensory stimuli and the fluctuations of cortical responses, we simulated a sparsely connected network of excitatory and inhibitory neurons modeling a local cortical population, and we determined how the LFPs generated by the network encode information about input stimuli. We first considered simple static and periodic stimuli and then naturalistic input stimuli based on electrophysiological recordings from the thalamus of anesthetized monkeys watching natural movie scenes. We found that the simulated network produced stimulus-related LFP changes that were in striking agreement with the LFPs obtained from the primary visual cortex. Moreover, our results demonstrate that the network encoded static input spike rates into gamma-range oscillations generated by inhibitory–excitatory neural interactions and encoded slow dynamic features of the input into slow LFP fluctuations mediated by stimulus–neural interactions. The model cortical network processed dynamic stimuli with naturalistic temporal structure by using low and high response frequencies as independent communication channels, again in agreement with recent reports from visual cortex responses to naturalistic movies. One potential function of this frequency decomposition into independent information channels operated by the cortical network may be that of enhancing the capacity of the cortical column to encode our complex sensory environment.     

Intra-Species Extrapolation in Risk Assessment of Different Classes of Antimicrobials

The risk assessment process for non-carcinogens incorporates all available scientific information, including toxicokinetic and toxicodynamic data. A 10-fold uncertainty factor (UF) is most commonly used to account for underlying variability within the human species. The purposes of this investigation are to evaluate whether the magnitude of the 10X-UF can be reduced when pharmacokinetic and pharma-codynamic data are incorporated to characterize interindividual variability and whether another UF is needed for the children group. An extensive literature search was conducted on seven antimicrobials in order to incorporate information on kinetics and dynamics to allow extrapolation among susceptible humans. The drugs are cefaclor, cefuroxime, erythromycin, clarithromycin, ampicillin, gentamicin and amikacin. The composite factor was calculated using the highest ratio for appropriate parameters and default subfactor. According to the data, we concluded that when relevant kinetic and dynamic data are available, replacing the default factors with actual data-derived values was possible for the antimicrobials evaluated and that there is no need to add another UF to the children group.     

垂体腺苷酸环化酶激活肽的分布及其生物学功能

垂体腺苷酸环化酶激活肽 (PituitaryAdenylateCyclaseActivitingPoly peptide ,PACAP) ,是一种新发现的神经肽 ,具有多种生物活性。主要综述PACAP的分子结构和基因组成、组织器官分布及其生物学功能。     

Different Classes of Ribonucleic Acid Isolated from Lymphocytic Choriomeningitis Virus

Purified preparations of lymphocytic choriomeningitis virus (LCM virus) contain three classes of RNA. The previously described 18s, 23s, 28s, and 31s RNAs, where the 23s and 31s RNAs are viral-specific, and the 18s and 28s RNAs probably are host RNAs incorporated in the virion. Now, 4s, 5s, and 5.5s RNAs can be isolated as well. Thus five RNAs which migrate by acrylamide gel electrophoresis as ribosome-derived RNA can be isolated from purified LCM virus. This observation further supports the reports that arenaviruses may contain ribosomes. The ribosome-derived RNA can be synthesized both before and after the virus infection. The viral 23s could be a hydrogen-bonded complex forming the 31s RNA, or it could be contained in defective interfering LCM virus particles; these possibilities are examined.     

从生物大分子结构特征解析植物凝集素的多样性

利用计算机模拟分析了植物凝集素结构与功能的特征。结果显示：(1)植物凝集素在结合糖之前其结构变化是一致的;(2)植物凝集素存在结构上的多样性,且可能与其生物功能的多样性有关;(3)在结合糖的过程中,植物凝集素表面局部结构的构象会有所变化,这种变化有利于其识别不同的糖而结合不同的外来糖缀合物,发挥其防御功能。对于同一家族的植物凝集素,虽然序列同源性较高,但在功能上却表现出强烈的多样性。分析表明：对于生物大分子而言,欲完成同一功能,不一定结构相同;结构相同,不一定功能一样。