PhysioSpace: Relating Gene Expression Experiments from Heterogeneous Sources Using Shared Physiological Processes

Relating expression signatures from different sources such as cell lines, in vitro cultures from primary cells and biopsy material is an important task in drug development and translational medicine as well as for tracking of cell fate and disease progression. Especially the comparison of large scale gene expression changes to tissue or cell type specific signatures is of high interest for the tracking of cell fate in (trans-) differentiation experiments and for cancer research, which increasingly focuses on shared processes and the involvement of the microenvironment. These signature relation approaches require robust statistical methods to account for the high biological heterogeneity in clinical data and must cope with small sample sizes in lab experiments and common patterns of co-expression in ubiquitous cellular processes. We describe a novel method, called PhysioSpace, to position dynamics of time series data derived from cellular differentiation and disease progression in a genome-wide expression space. The PhysioSpace is defined by a compendium of publicly available gene expression signatures representing a large set of biological phenotypes. The mapping of gene expression changes onto the PhysioSpace leads to a robust ranking of physiologically relevant signatures, as rigorously evaluated via sample-label permutations. A spherical transformation of the data improves the performance, leading to stable results even in case of small sample sizes. Using PhysioSpace with clinical cancer datasets reveals that such data exhibits large heterogeneity in the number of significant signature associations. This behavior was closely associated with the classification endpoint and cancer type under consideration, indicating shared biological functionalities in disease associated processes. Even though the time series data of cell line differentiation exhibited responses in larger clusters covering several biologically related patterns, top scoring patterns were highly consistent with a priory known biological information and separated from the rest of response patterns.     

微生物连续发酵酶催化动力系统的鲁棒性与并行计算

依据甘油连续发酵生产1,3-丙二醇的非线性酶催化动力系统.针对1,3-丙二醇可能存在的跨膜运输方式建立相应的动力学模型,提出了酶催化动力系统的定量鲁棒性定义,并建立了以鲁棒性为性能指标、非线性动力系统为主要约束的参数辨识模型.由于求解该辨识问题的数值计算量大,在普通的PC机上难以完成,因此本文构建了相应的并行算法.根据数值结果推断出1,3-丙二醇最有可能的跨膜运输方式,这对于进一步研究甘油连续发酵的机理具有重要的参考价值.     

Inheritance as Evolved and Evolving Physiological Processes

Acta Biotheoretica - In this paper, we adopt a physiological perspective in order to produce an intelligible overview of biological transmission in all its diversity. This allows us to put forward...     

Application of Image Analysis Techniques in Activated Sludge Wastewater Treatment Processes

Image analytical techniques have been extensively developed to evaluate complex microbial aggregates such as sludge flocs and biofilms. This review covers the latest contributions concerning the application of image analysis to the activated sludge systems with respect to the most frequently used morphological parameters and relations between them and traditional wastewater treatment parameters. Recent developments have indicated that image analysis can be successfully used for the quantification of flocs and filamentous bacteria in the operating wastewater treatment plants, which enables prediction of bulking events and pinpoint flocs formation.     

Reactive Oxygen Species: Participation in Cellular Processes and Progression of Pathology

Russian Journal of Bioorganic Chemistry - Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are not only side products of chemical reactions, but participants in various cellular...     

Effect of Ecdysterone on Morphological and Physiological Processes in Plants

In order to elucidate the physiological role of phytoecdysteroids in plants, we investigated the effects of exogenous ecdysterone (ECD) and phytohormones (IAA, GA₃, and 24-epibrassinolide (EBL)) on the growth of wheat coleoptiles and Arabidopsis thaliana seedlings (wild-type ecotype Columbia (Col) and its det2 mutant), on -amylase activity in the barley aleurone layer, and on the pigment content in the kidney bean senescent leaves. The range of effective ECD concentrations depended on the type of a reaction to be regulated. The regulation of growth processes was affected by a wide range of ECD concentrations (10^–13–10^–5 M), whereas some metabolic processes, such as the activation of -amylase and the retardation of leaf yellowing, by a narrow range, that is, 10^–9–10^–7 M and 10^–9–10^–8 M, respectively. We noted the synergetic effect of ECD and IAA on coleoptile elongation, the antagonistic effect of ECD and EBL on coleoptile elongation, as well as the antagonistic action of ECD and GA₃ on coleoptile elongation and -amylase activity. The data obtained demonstrate that ECD is a physiologically active compound. ECD might be supposed to act as a source of sterols or a regulator of IAA and protein synthesis. The effects of this regulator seems to be brought about by its interaction with the EBL and GA₃ receptors.     

An Image Analysis Algorithm for Malaria Parasite Stage Classification and Viability Quantification

With more than 40% of the world’s population at risk, 200–300 million infections each year, and an estimated 1.2 million deaths annually, malaria remains one of the most important public health problems of mankind today. With the propensity of malaria parasites to rapidly develop resistance to newly developed therapies, and the recent failures of artemisinin-based drugs in Southeast Asia, there is an urgent need for new antimalarial compounds with novel mechanisms of action to be developed against multidrug resistant malaria. We present here a novel image analysis algorithm for the quantitative detection and classification of Plasmodium lifecycle stages in culture as well as discriminating between viable and dead parasites in drug-treated samples. This new algorithm reliably estimates the number of red blood cells (isolated or clustered) per fluorescence image field, and accurately identifies parasitized erythrocytes on the basis of high intensity DAPI-stained parasite nuclei spots and Mitotracker-stained mitochondrial in viable parasites. We validated the performance of the algorithm by manual counting of the infected and non-infected red blood cells in multiple image fields, and the quantitative analyses of the different parasite stages (early rings, rings, trophozoites, schizonts) at various time-point post-merozoite invasion, in tightly synchronized cultures. Additionally, the developed algorithm provided parasitological effective concentration 50 (EC50) values for both chloroquine and artemisinin, that were similar to known growth inhibitory EC50 values for these compounds as determined using conventional SYBR Green I and lactate dehydrogenase-based assays.     

Some Physiological Mechanisms Functioning in Models of Pain-Related Processes

Neurophysiology - Psychophysiological sensing of pain is formed due to the activity of a number of neuronal mechanisms. Among the pain-related processes, nociception per se, peripheral...     

Traces of Unconscious Mental Processes in Introspective Reports and Physiological Responses

Unconscious mental processes have recently started gaining attention in a number of scientific disciplines. One of the theoretical frameworks for describing unconscious processes was introduced by Jung as a part of his model of the psyche. This framework uses the concept of archetypes that represent prototypical experiences associated with objects, people, and situations. Although the validity of Jungian model remains an open question, this framework is convenient from the practical point of view. Moreover, archetypes found numerous applications in the areas of psychology and marketing. Therefore, observation of both conscious and unconscious traces related to archetypal experiences seems to be an interesting research endeavor. In a study with 36 subjects, we examined the effects of experiencing conglomerations of unconscious emotions associated with various archetypes on the participants’ introspective reports and patterns of physiological activations. Our hypothesis for this experiment was that physiological data may predict archetypes more precisely than introspective reports due to the implicit nature of archetypal experiences. Introspective reports were collected using the Self-Assessment Manikin (SAM) technique. Physiological measures included cardiovascular, electrodermal, respiratory responses and skin temperature of the subjects. The subjects were stimulated to feel four archetypal experiences and four explicit emotions by means of film clips. The data related to the explicit emotions served as a reference in analysis of archetypal experiences. Our findings indicated that while prediction models trained on the collected physiological data could recognize the archetypal experiences with accuracy of 55 percent, similar models built based on the SAM data demonstrated performance of only 33 percent. Statistical tests enabled us to confirm that physiological observations are better suited for observation of implicit psychological constructs like archetypes than introspective reports.     

Quantitation of Satellite Cell Proliferation in Vivo Using Image Analysis

A nonisotopic, double fluorescence technique was developed to study myogenic satellite cell proliferation in posthatch turkey skeletal muscle. Labeled satellite cell nuclei were identified on enzymatically isolated myofiber segments using a mouse monoclonal antibody (anti-BrdU) followed by fluorescein-5-isothiocyanate (FITC) conjugated goat anti-mouse IgG secondary antibody. Myofiber nuclei (myonuclei + satellite cell nuclei) were counterstained with propidium iodide (PI). The myofiber segment length, myofiber segment diameter, and the number of PI and FITC labeled nuclei contained in each segment was determined using a Nikon fluorescence microscope, a SIT video camera and Image-1 software. Data collected by three different operators of the image analysis system revealed 5.0 ± 1.4 satellite cell nuclei per 1000 myofiber nuclei and 5284 ± 462 μm³ of cytoplasm surrounding each myofiber nucleus in the pectoralis thoracicus of 9-week-old tom turkeys. BrdU immunohistochemistry coupled with the new approach of PI staining of whole myofiber mounts is an effective combination to allow the use of an efficient semi-automated image analysis protocol.     

Discovery and Analysis of MicroRNAs in Leymus chinensis under Saline-Alkali and Drought Stress Using High-Throughput Sequencing

Leymus chinensis (Trin.) Tzvel. is a perennial rhizome grass of the Poaceae (also called Gramineae) family, which adapts well to drought, saline and alkaline conditions. However, little is known about the stress tolerance of L. chinensis at the molecular level. microRNAs (miRNAs) are known to play critical roles in nutrient homeostasis, developmental processes, pathogen responses, and abiotic stress in plants. In this study, we used Solexa sequencing technology to generate high-quality small RNA data from three L. chinensis groups: a control group, a saline-alkaline stress group (100 mM NaCl and 200 mM NaHCO₃), and a drought stress group (20% polyethylene glycol 2000). From these data we identified 132 known miRNAs and 16 novel miRNAs candidates. For these miRNAs we also identified target genes that encode a broad range of proteins that may be correlated with abiotic stress regulation. This is the first study to demonstrate differentially expressed miRNAs in L. chinensis under saline-alkali and drought stress. These findings may help explain the saline-alkaline and drought stress responses in L. chinensis.     

Quantitative Ultrastructural Immunocytochemistry Using a Computerized Image Analysis System

Secretory granules in human pituitary adenoma cells have been examined indirectly for hormone epitopes by immunogold labelling of resin-embedded ultra thin sections. The specific binding of different immunoglobulin-gold complexes to the antigrowth hormone antibodies over the secretory granules was measured using a computerized image analysis system. This facilitated the assessment of the preferential binding to the target granules of gold particles with three different average particle diameters (Au₇, Au₁₁, Au₁₇). The time of pretreatment of sections with H₂0₂ or a buffer was found to influence the staining considerably. The scanning electron microscopic findings of protruded secretory granules with a mountain-like surface might be relevant to the uneven distribution of immunolabels seen over the secretory granules in the adenohypophysis.     

Data-Driven Analysis in Drug Discovery

In the process of drug discovery for new chemical entities, application of appropriate pharmacological models often is not possible because the molecular mechanism of the compound is not yet elucidated. Therefore, a data-driven approach using generic tools designed to quantify characteristic patterns of concentration-response curves is required. This article outlines the options available for quantifying agonist and antagonist activity. Specifically, for agonists, the use of the Operational model for the determination of functional effects (equimolar potency ratios for full agonists, calculation of relative efficacy) is described. For antagonists, the measurement of pK_B (-log of the equilibrium dissociation constant of the antagonist-receptor complex) for orthosteric antagonists that do not alter basal response (simple competitive antagonists), increase basal response (partial agonists), and decrease basal response (in constitutively active systems; inverse agonists) is discussed. In addition, this article considers methods to discern orthosteric receptor antagonism from allosteric antagonism whereby the agonist and antagonist bind to separate sites and interact through a conformational change in the receptor. Methods for the measurement of the pK_B for allosteric modulators as well as co-operativity constants for these modulators is described.     

A Spatially Continuous Model of Carbohydrate Digestion and Transport Processes in the Colon

A spatially continuous mathematical model of transport processes, anaerobic digestion and microbial complexity as would be expected in the human colon is presented. The model is a system of first-order partial differential equations with context determined number of dependent variables, and stiff, non-linear source terms. Numerical simulation of the model is used to elucidate information about the colon-microbiota complex. It is found that the composition of materials on outflow of the model does not well-describe the composition of material in other model locations, and inferences using outflow data varies according to model reactor representation. Additionally, increased microbial complexity allows the total microbial community to withstand major system perturbations in diet and community structure. However, distribution of strains and functional groups within the microbial community can be modified depending on perturbation length and microbial kinetic parameters. Preliminary model extensions and potential investigative opportunities using the computational model are discussed.