Combination of quantification and observation methods for study of "Side Population" cells in their "in vitro" microenvironment.

BACKGROUND: Qualitative and quantitative analyses of the rare phenotypic variants in in vitro culture systems is necessary for the understanding of cell differentiation in cell culture of primary cells or cell lines. Slide-based cytometry combines image acquisition and data treatment, and associates the power of flow cytometry (FCM) and the resolution of the microscopic studies making it suitable for the analysis of cells with rare phenotype. In this paper we develop a method that applies these principles to a particularly hot problem in cell biology, the study of stem cell like cells in cultures of primary cells, cancer cells, and various cell lines. METHODS: The adherent cells were labeled by the fluorescent dye Hoechst 33342. The images of cell populations were collected by a two-photon microscope and processed by a software developed by us. The software allows the automated segmentation of the nuclei in a very dense cell environment, the measurement of the fluorescence intensity of each nucleus and the recording of their position in the plate. The cells with a given fluorescence intensity can then be located easily on the recorded image of the culture plate for further analysis. RESULTS: The potential of our method is illustrated by the identification and localization of SP cells in the cultures of the C2C12 cell line. Although these cells represent only about 1% of the total population as calculated by flow cytometry, they can be identified in the culture plate with high precision by microscopy. CONCLUSION: Cells with the rare stem-cell like phenotype can be efficiently identified in the undisturbed cultures. Since the fluorescence intensity of rare events and the position of thousands of surrounding cells are recorded at the same time, the method associates the advantage of the FCM analysis and the microscopic observation.     

Circadian chronobiology of epilepsy: murine models of seizure susceptibility and theoretical perspectives for neurology

As an integrative discipline in physiology and medical research, chronobiology renders possible the discovery of new regulation processes regarding the central mechanisms of epilepsy. In this context, the temporal fluctuations of seizure susceptibility rhythmometrically detected tend to demonstrate 1. that tonic-clonic events are circadian stage-dependent processes whose temporal characteristics (i.e. MESOR, amplitude, acrophase) and clinical parameters (e.g. neurological components, severity of motor discharges) are predictable on the basis of mathematical models, and 2. that the generalized epileptic onsets may respond to telencephalic integrations modulated by centrencephalic circadian processes of vigilance. Considering the data model assumed for our rhythmometric analyses, the circadian psychophysiological patterns of epilepsy also express dynamic biologic systems which reveal some intermodulating endogenous processes between vigilance and seizure susceptibility. The new chronophysiology investigations considered at a rhythmometric level of resolution suggest several heuristic perspectives regarding 1. the central pathophysiology of epilepsy and 2. the behavioral classification of convulsive events. Such circadian studies also show that chronobiology raises some working hypotheses in psychophysiology and permits the development of new theoretical concepts in the field of neurological science.     

How to engage medical students in chronobiology: an example on autorhythmometry

This contribution describes a new laboratory experience that improves medical students' learning of chronobiology by introducing them to basic chronobiology concepts as well as to methods and statistical analysis tools specific for circadian rhythms. We designed an autorhythmometry laboratory session where students simultaneously played the role of researchers and experimental subjects. During this session, which lasted 24 h, students recorded their own arterial pressure, heart rate, oral temperature, forced expiratory flow, glucose tolerance, muscular strength, reaction time, and sensorimotor coordination at regular intervals and also took the Horne and Ostberg test, after which they analyzed their own data. Furthermore, to gather information from subjects under normal sleep and eating schedules, some students acquired data at home. To guide and help students with their work, a dedicated web page was implemented with scientific references, cosinor analysis software, and other valuable information. All these "raw" data were combined into a single database that students could use to evaluate whatever aspect of the data they seemed fit. A number of suggestions were offered to them as guidance. Students were then instructed to write a scientific article on the subject they had chosen. The experience was highly rewarding for both instructors and students alike. In view of the high level of absenteeism in Spanish universities and the fact that 93% of the students attended the exam and 95% of these passed, the experience was considered a great success.     

Use of methods of spectral-correlation analysis for studying the temporal and spatial organization of tissues]

Tissues within the organism represent multidimensional systems organized in time and space and having statistical dispersion in each parameter. Changes in its state may have a character of a monotonous trend and be periodical (the matter of chronobiology). The methods for detection of latent periodicities, developed in chronobiology, are applied for estimation of not only temporary but also spacial characteristics of the object. One of such methods is the calculation of the power spectrum of the autocorrelative function. Examples of its application are given.     

Using GaBi 3 to perform life cycle assessment and life cycle engineering

The growing availability of software tools has increased the speed of generating LCA studies. Databases and visual tools for constructing material balance modules greatly facilitate the process of analyzing the environmental aspects of product systems over their life cycle. A robust software tool, containing a large LCI dataset and functions for performing LCIA and sensitivity analysis will allow companies and LCA practitioners to conduct systems analyses efficiently and reliably. This paper discusses how the GaBi 3 software tool can be used to perform LCA and Life Cycle Engineering (LCE), a methodology that combines life cycle economic, environmental, and technology assessment. The paper highlights important attributes of LCA software tools, including high quality, well-documented data, transparency in modeling, and data analysis functionality. An example of a regional power grid mix model is used to illustrate the versatility of GaBi 3.     

Chronobiology of blood pressure in childhood: implications for tracking

Chronobiology, in its methodological evolution, developed data series analyses paying particular attention to blood pressure (BP), because of the importance of this biorhythmic variable for assessing the risk of developing hypertension. An example of the potentiality of the chronobiologic procedures is given in the present report which deals with the inferential analysis of the BP 24-h patterns in 3-12 year-old children. By using the chronobiologic methodology, time-qualified standards for BP are calculated. Rhythmometric parameters for circadian rhythm of systolic and diastolic components of BP are also computed. Data presented are a tangible outcome for emphasizing the introduction of chronobiology in epidemiology and pediatrics in order to optimize the primary prevention and care of hypertension taking as reference the chronobiologic standards of BP.     

中西医观解读时间生物学

时间生物学是一门研究生命活动节律的科学。在西方医学中,研究时间生物学是利用分子生物学实验来阐释其机制,以西医的思维方法解释时间生物学的生理及病理过程;中医对时间生物学的记载有两千多年的历史,阴阳理论、子午流注学说以及五运六气学说一直以来都在指导中医的诊断和治疗。中西医观的不同对时间生物学的研究提供了新的研究思路,同时时间生物学也为研究中西医结合提供了广阔的前景。     

A QconCAT informatics pipeline for the analysis, visualization and sharing of absolute quantitative proteomics data

Absolute protein concentration determination is becoming increasingly important in a number of fields including diagnostics, biomarker discovery and systems biology modeling. The recently introduced quantification concatamer methodology provides a novel approach to performing such determinations, and it has been applied to both microbial and mammalian systems. While a number of software tools exist for performing analyses of quantitative data generated by related methodologies such as SILAC, there is currently no analysis package dedicated to the quantification concatamer approach. Furthermore, most tools that are currently available in the field of quantitative proteomics do not manage storage and dissemination of such data sets.     

THEA: ontology-driven analysis of microarray data

MOTIVATION: Microarray technology makes it possible to measure thousands of variables and to compare their values under hundreds of conditions. Once microarray data are quantified, normalized and classified, the analysis phase is essentially a manual and subjective task based on visual inspection of classes in the light of the vast amount of information available. Currently, data interpretation clearly constitutes the bottleneck of such analyses and there is an obvious need for tools able to fill the gap between data processed with mathematical methods and existing biological knowledge. RESULTS: THEA (Tools for High-throughput Experiments Analysis) is an integrated information processing system allowing convenient handling of data. It allows to automatically annotate data issued from classification systems with selected biological information coming from a knowledge base and to either manually search and browse through these annotations or automatically generate meaningful generalizations according to statistical criteria (data mining). AVAILABILITY: The software is available on the website http://thea.unice.fr/     

Chronobiology in mental retardation research: progress and prospects.

The premise of this review is that chronobiology, the science of biologic time structure and rhythms, is important in investigations concerning the etiology, mechanisms and effects of deficient mental adaptive development. Chronobiology is also shown to have potential importance in therapeutics and rehabilitation. Most of the information available now and supporting this wide-spread relevance of chronobiology relates to circadian rhythms, but physiological and behavioral rhythms having other cycle lengths also contribute. Recent findings in seven topic areas of chronobiology are reviewed with emphasis on facts and relationships actually or potentially important for consideration in mental retardation research. These are: 1) development of sleep and EEG patterns; 2) rhythmic susceptibility to seizures; 3) adrenocortical and dependent rhythms; 4) circadian rhythms in amino acids and biogenic amines; 5) rhythmic behaviors; 6) circadian rhythms in susceptibility and responses to drugs; and 7) circadian rhythms in human perception and performance.     

Nucleic acid sequence analysis software for microcomputers

It is clear that a computer-aided data control system is required for even small laboratories generating nucleic acid data. While the molecular biologist at many universities and large research institutions has access to mainframe computers and nucleic acid sequence analysis software, many find it more convenient to perform sequence analysis on microcomputers that are typically located within the investigator's laboratory and totally dedicated to sequence storage and analysis, in essence giving the investigator more personal control of analysis activities than is sometimes possible with shared mini- or mainframe computers. New programs are being written and released at an increasing rate to perform increasingly more complex and specialized analyses using small computer-based systems. This trend will undoubtedly continue, fueled by the need to manage the ever increasing quantity of sequence data.     

Clustering-based approaches to discovering and visualising microarray data patterns

This article focuses on clustering techniques for the analysis of microarray data and discusses contributions and applications for the implementation of intelligent diagnostic systems and therapy design studies. Approaches to validating and visualising expression clustering results and software and other relevant resources to support clustering-based analyses are reviewed. Finally, this paper addresses current limitations and problems that need to be investigated for the development of an advanced generation of pattern discovery tools.     

Validation and discovery from computational biology models

Simulation software is often a fundamental component in systems biology projects and provides a key aspect of the integration of experimental and analytical techniques in the search for greater understanding and prediction of biology at the systems level. It is important that the modelling and analysis software is reliable and that techniques exist for automating the analysis of the vast amounts of data which such simulation environments generate. A rigorous approach to the development of complex modelling software is needed. Such a framework is presented here together with techniques for the automated analysis of such models and a process for the automatic discovery of biological phenomena from large simulation data sets. Illustrations are taken from a major systems biology research project involving the in vitro investigation, modelling and simulation of epithelial tissue.     

Q-omics: Smart Software for Assisting Oncology and Cancer Research

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.     

Two 19th-century Chronobiologists: Thomas Laycock and Edward Smith by P. Lavie

Lavie has written an admirably clear account of some of the work of Laycock and Smith, two researchers whom he considers to be pioneers of chronobiology. In making an assessment of this claim, we will consider two areas in particular: collecting data and interpreting results.     

Data standards for flow cytometry

Flow cytometry (FCM) is an analytical tool widely used for cancer and HIV/AIDS research, and treatment, stem cell manipulation and detecting microorganisms in environmental samples. Current data standards do not capture the full scope of FCM experiments and there is a demand for software tools that can assist in the exploration and analysis of large FCM datasets. We are implementing a standardized approach to capturing, analyzing, and disseminating FCM data that will facilitate both more complex analyses and analysis of datasets that could not previously be efficiently studied. Initial work has focused on developing a community-based guideline for recording and reporting the details of FCM experiments. Open source software tools that implement this standard are being created, with an emphasis on facilitating reproducible and extensible data analyses. As well, tools for electronic collaboration will assist the integrated access and comprehension of experiments to empower users to collaborate on FCM analyses. This coordinated, joint development of bioinformatics standards and software tools for FCM data analysis has the potential to greatly facilitate both basic and clinical research--impacting a notably diverse range of medical and environmental research areas.