Aspects of randomness in neural graph structures

In the past two decades, significant advances have been made in understanding the structural and functional properties of biological networks, via graph-theoretic analysis. In general, most graph-theoretic studies are conducted in the presence of serious uncertainties, such as major undersampling of the experimental data. In the specific case of neural systems, however, a few moderately robust experimental reconstructions have been reported, and these have long served as fundamental prototypes for studying connectivity patterns in the nervous system. In this paper, we provide a comparative analysis of these “historical” graphs, both in their directed (original) and symmetrized (a common preprocessing step) forms, and provide a set of measures that can be consistently applied across graphs (directed or undirected, with or without self-loops). We focus on simple structural characterizations of network connectivity and find that in many measures, the networks studied are captured by simple random graph models. In a few key measures, however, we observe a marked departure from the random graph prediction. Our results suggest that the mechanism of graph formation in the networks studied is not well captured by existing abstract graph models in their first- and second-order connectivity.     

Probabilistic discovery of overlapping cellular processes and their regulation.

In this paper, we explore modeling overlapping biological processes. We discuss a probabilistic model of overlapping biological processes, gene membership in those processes, and an addition to that model that identifies regulatory mechanisms controlling process activation. A key feature of our approach is that we allow genes to participate in multiple processes, thus providing a more biologically plausible model for the process of gene regulation. We present algorithms to learn each model automatically from data, using only genomewide measurements of gene expression as input. We compare our results to those obtained by other approaches and show that significant benefits can be gained by modeling both the organization of genes into overlapping cellular processes and the regulatory programs of these processes. Moreover, our method successfully grouped genes known to function together, recovered many regulatory relationships that are known in the literature, and suggested novel hypotheses regarding the regulatory role of previously uncharacterized proteins.     

Estimation of the stage-specific survival rate in the insect population with overlapping stages

An application ofHokyo andKiritani 's method (1967) was attempted to estimate the stage specific survival rates of the population with overlapping stages. This method can be written as follows assuming a constant daily survival rate (K) throughout the life: where, and F refer respectively to the total incidence of ith instar nymphs and that of individuals after ith instar inclusive, and α_i refers to the developmental period of ith instar. Application of this model to caged and natural populations of the southern green stink bug, Nezara viridula, was made to test its validity. The estimates of the initial number of successive stages obtained from the present method were compared with those fromRichards andWaloff 's method (1954) for the caged populations of 1st, 2nd and 3rd generations. The superiority of the present method to theRichards andWaloff 's in estimating adult numbers was shown in all the generations examined. When different daily survival rates are involved in the course of population decrease, application of the revised method proposed byHokyo andKiritani (1967), gives much reliable estimate as compared with one before correction. The present method is useful in constructing life table of such species as scale insects which complete their life cycle within a defined space, but their successive stages overlap considerably.     

Optical imaging of nanoscale cellular structures

Visualization of subcellular structures and their temporal evolution is of utmost importance to understand a vast range of biological processes. Optical microscopy is the method of choice for imaging live cells and tissues; it is minimally invasive, so processes can be observed over extended periods of time without generating artifacts due to intense light irradiation. The use of fluorescence microscopy is advantageous because biomolecules or supramolecular structures of interest can be labeled specifically with fluorophores, so the images reveal information on processes involving only the labeled molecules. The key restriction of optical microscopy is its moderate resolution, which is limited to about half the wavelength of light (～200 nm) due to fundamental physical laws governing wave optics. Consequently, molecular processes taking place at spatial scales between 1 and 100 nm cannot be studied by regular optical microscopy. In recent years, however, a variety of super-resolution fluorescence microscopy techniques have been developed that circumvent the resolution limitation. Here, we present a brief overview of these techniques and their application to cellular biophysics.     

Quantifying the randomness of extinctions

Extinctions occur either randomly or in a more deterministic and predictable manner, with certain characteristics making some species more vulnerable to (local) extinction than others. Although the quantification of extinction randomness would better our understanding of the extinction causes and increase the predictability of future species losses, few quantification methods are currently available. To this purpose, we propose two indices based on a comparison of an a priori (expected) extinction series with an observed one. Whereas the first index requires data on the order of extinctions, the second index is only concerned with which species went extinct and which did not. Using a model for generating extinction data, we tested both indices successfully for accordance with the robustness prerequisites. Index outputs were furthermore unaffected by species richness, apart from decreased variation with rising species numbers. Because of its independence of non-extinct species and its focus on extinction sequences, the first randomness index seems especially useful for use in paleontological and paleo-ecological research. The second index is likely a good tool to study shorter term extinctions, for which the extinction order is often not known and for which the comparison with species that did persist is of greater interest. We use a real dataset to illustrate this. Finally, we discuss how it is possible to expand the use of this index toward identifying previously unknown extinction-promoting species characteristics, and toward a credible assessment of the extinction risk posed by global change.     

Interactive visual exploration of overlapping similar structures for three-dimensional microscope images

Background

Recent advances in microscopy enable the acquisition of large numbers of tomographic images from living tissues. Three-dimensional microscope images are often displayed with volume rendering by adjusting the transfer functions. However, because the emissions from fluorescent materials and the optical properties based on point spread functions affect the imaging results, the intensity value can differ locally, even in the same structure. Further, images obtained from brain tissues contain a variety of neural structures such as dendrites and axons with complex crossings and overlapping linear structures. In these cases, the transfer functions previously used fail to optimize image generation, making it difficult to explore the connectivity of these tissues.

Results

This paper proposes an interactive visual exploration method by which the transfer functions are modified locally and interactively based on multidimensional features in the images. A direct editing interface is also provided to specify both the target region and structures with characteristic features, where all manual operations can be performed on the rendered image. This method is demonstrated using two-photon microscope images acquired from living mice, and is shown to be an effective method for interactive visual exploration of overlapping similar structures.

Conclusions

An interactive visualization method was introduced for local improvement of visualization by volume rendering in two-photon microscope images containing regions in which linear nerve structures crisscross in a complex manner. The proposed method is characterized by the localized multidimensional transfer function and interface where the parameters can be determined by the user to suit their particular visualization requirements.     

Estimation of descriptive parameters of overlapping chromatographic peaks: a simulation study

The characteristics of a non-linear optimization technique for resolution of overlapping chromatographic peaks are examined. A modified Meiron-Marquardt method was used. The estimates of the parameters of overlapping peaks in simulated chromatograms were investigated to indicate the limitations of present mathematical methods and, hopefully, to improve their ultimate utility. Gaussian shapes as well as exponential-Gaussian convolutes were used to simulate the chromatographic peaks. Effects on the overall performance of varying heights, widths, and separation of two peaks were determined. Random additive noise and base line drift were also simulated. For illustrative purposes, the performance of the parameter estimation techniques was expressed in terms of relative errors in estimating the second (or smaller) peak's area, height and location. The results presented indicate the relative importance of noise, skewness, height and width ratios and peak separation on the maximum resolution achievable by numerical methods in an automated chromatographic system.     

Estimation of cellular fabric in embryonic epithelia

Recent computational and analytical studies have shown that cellular fabric-as embodied by average cell size, aspect ratio and orientation-is a key indicator of the stresses acting in an embryonic epithelium. Cellular fabric in real embryonic tissues could not previously be measured automatically because the cell boundaries tend to be poorly defined, significant lighting and cell pigmentation differences occur and tissues contain a variety of cell geometries. To overcome these difficulties, four algorithms were developed: least squares ellipse fitting (LSEF), area moments (AM), correlation and axes search (CAS) and Gabor filters (GF). The AM method was found to be the most reliable of these methods, giving typical cell size, aspect ratio and orientation errors of 18%, 0.10 and 7.4 degrees, respectively, when evaluated against manually segmented images. The power of the AM algorithm to provide new insights into the mechanics of morphogenesis is demonstrated through a brief investigation of gastrulation, where fabric data suggest that key gastrulation movements are driven by epidermal tensions circumferential to the blastopore.     

Heterogeneity in cellular antigen retention structures

The mechanism of presentation of foreign antigens to helper T lymphocytes and the nature of the structures involved in this process are not totally understood. It is well documented that this event is carried out by antigen-presenting cells (APC) (e.g., macrophages, dendritic cells, and B lymphocytes) that internalize the antigen, process it, reexpress it on their membrane surface, and present it to the T cell in the context of major histocompatibility complex class II (Ia) molecules. Recent evidence supports the hypothesis that peptide antigens associate directly with Ia molecules on the APC surface membrane. However, the characteristics of other APC membrane structures potentially involved in antigen presentation are not entirely clear. Previous studies in our laboratories identified a guinea pig macrophage membrane-bound, non-Ia-containing antigenic complex (peak A) formed upon incubation of APC with the octapeptide antigen angiotensin (AII). This complex was capable of stimulating AII-immune guinea pig T cells and thus appeared to contain the immunologically relevant form of the antigen. For this reason it was important to establish whether such complex formation with peptides occurs with other cell types and with other peptide antigens. In the present study we found that other types of cells are also capable of forming such a membrane complex with antigen (peak A) and that this event is not unique to AII. Two other peptides, alpha-melanocyte-stimulating hormone and human fibrinopeptide B, both of which are antigenic in mice, were found to form peak A with a number of murine cell lines. As in our earlier studies with guinea pig macrophages, there was no evidence from these experiments for a role for major histocompatibility complex Ia antigens in the peptide binding observed. Differences in both the amount of peak A formation and the pattern of peptide antigen degradation were found from cell line to cell line for a given peptide, and from peptide to peptide for a given cell line, suggesting cellular heterogeneity in peptide processing and retention. In addition, cross-inhibition studies indicated that there was peptide specificity in the formation of peak A perhaps suggestive of molecular heterogeneity in the structure of peak A. These results indicate that there may be several types of cell surface molecules that specifically bind and retain peptide antigens.(ABSTRACT TRUNCATED AT 400 WORDS)     

Proteomics of organelles and large cellular structures

The mass-spectrometry-based identification of proteins has created opportunities for the study of organelles, transport intermediates and large subcellular structures. Traditional cell-biology techniques are used to enrich these structures for proteomics analyses, and such analyses provide insights into the biology and functions of these structures. Here, we review the state-of-the-art proteomics techniques for the analysis of subcellular structures and discuss the biological insights that have been derived from such studies.     

Observations on cellular structures of Porphyridium cruentum

The cellular structure of Porphyridium cruentum was studied with both light and electron microscope. The photosynthetic plastid in this red alga was found to be structurally similar to that in the Chlorophyceae and higher green plants. The phycobilins, as well as the chlorophyll, seem to be associated with the lamellae of the plastid. The pyrenoid, a region of low lamellar density, contains no tubules, and does not appear to function in synthesis or storage of reserve material. Grains of floridean starch are located in the cytoplasm, outside the plastid. Typical mitochondrial organelles were not observed. The nucleus is eccentric, and contains a nucleolus located on the inner face of the nucleus, nearest the plastid. The schedule for staining the nucleus is given in detail. Other cell structures (sheath, dictyosomes, etc.) are described. Growing cells in light of intensity leads to disruption of the parallel arrangement of the lamellar characteristic of cells grown in moderate light.     

Environmental randomness and the tenacity of equilibria

A concept of “stability” for equilibria of population models in randomly fluctuating environments, which takes into account the possibility of random jumps from one domain of attraction to another, is proposed. It is applied to a simple model of harvested populations, and related to May's well-known “stability” criterion.     

4Pi microscopy of quantum dot-labeled cellular structures

The most prominent restrictions of fluorescence microscopy are the limited resolution and the finite signal. Established conventional, confocal, and multiphoton microscopes resolve at best approximately 200nm in the focal plane and only 500nm in depth. Additionally, organic fluorophores and fluorescent proteins are bleached after 10(4)-10(5) excitation cycles. To overcome these restrictions, we synergistically combine the 3- to 7-fold improved axial resolution of 4Pi microscopy with the greatly enhanced photostability of semiconductor quantum dots. Co-localization studies of immunolabeled microtubules and mitochondria demonstrate the feasibility of this approach for routine biological measurements. In particular, we visualize the three-dimensional entanglement of the two networks with unprecedented detail.     

Integrating overlapping structures and background information of words significantly improves biological sequence comparison

Word-based models have achieved promising results in sequence comparison. However, as the important statistical properties of words in biological sequence, how to use the overlapping structures and background information of the words to improve sequence comparison is still a problem. This paper proposed a new statistical method that integrates the overlapping structures and the background information of the words in biological sequences. To assess the effectiveness of this integration for sequence comparison, two sets of evaluation experiments were taken to test the proposed model. The first one, performed via receiver operating curve analysis, is the application of proposed method in discrimination between functionally related regulatory sequences and unrelated sequences, intron and exon. The second experiment is to evaluate the performance of the proposed method with f-measure for clustering Hepatitis E virus genotypes. It was demonstrated that the proposed method integrating the overlapping structures and the background information of words significantly improves biological sequence comparison and outperforms the existing models.     

Quantitative motion analysis and visualization of cellular structures

The availability of cellular markers tagged with the green fluorescent protein (GFP) has recently allowed a large number of cell biological studies to be carried out in live cells, thereby addressing the dynamic organization of cellular structures. Typically, microscopes capable of video recording are used to generate time-resolved data sets. Dynamic imaging data are complex and often difficult to interpret by pure visual inspection. Therefore, specialized image processing methods for object detection, motion estimation, visualization, and quantitation are required. In this review, we discuss concepts for automated analysis of multidimensional image data from live cell microscopy and their application to the dynamics of cell nuclear subcompartments.     

Estimation of evolutionary distances from protein spatial structures

New equations are derived to estimate the number of amino acid substitutions per site between two homologous proteins from the root mean square (RMS) deviation between two spatial structures and from the fraction of identical residues between two sequences. The equations are based on evolutionary models, analyzing predominantly structural changes and not sequence changes. Evolution of spatial structure is treated as a diffusion in an elastic force field. Diffusion accounts for structural changes caused by amino acid substitutions, and elastic force reflects selection, which preserves protein fold. Obtained equations are supported by analysis of protein spatial structures. Received: 21 September 1995 / Accepted: 19 May 1997     

Isolation and characteristics of the cellular structures of Candida tropicalis]

Using the method of radioactive indicators, the specific content of proteins, lipids, total phosphorus, and lipid phosphorus was estimated in the morphological cell fractions of Candida tropicalis after growth in a liquid mineral medium containing n-octadecane as a source of carbon. The morphological cell fractions were produced by means of differential centrifuging. The following comparatively pure fractions were obtained simultaneously: soluble fraction, microsomes, mitochondria, large membranes, and cell walls.