Alumorphs--human DNA polymorphisms detected by polymerase chain reaction using Alu-specific primers

The simultaneous analysis of multiple loci could substantially increase the efficiency of mapping studies. Toward this goal, we used the polymerase chain reaction to amplify multiple DNA fragments originating from dispersed genomic segments that are flanked by Alu repeats. Analysis of different human DNA samples revealed numerous amplification products distinguishable by size, some of which vary between individuals. A family study demonstrated that these polymorphic fragments are inherited in a Mendelian fashion. Because of the ubiquitous distribution of Alu repeats, these markers, called "alumorphs," could be useful for linkage mapping of the human genome. A major advantage of alumorphs is that no prior knowledge of DNA sequence of marker loci is required. This approach may find general application for any genome where interspersed repetitive sequences are found.     

Myriapod metamerism and arthropod segmentation

Outstanding progress in understanding segmentation of tracheate arthropods (Atelocerata), i.e. Chilopoda, Diplopoda, Pauropoda, Symphyla and Insecta, has been gained through experimental studies carried out on a single, very derivative organism, i.e. Drosophila. We stress the need for a broader comparative approach. We have studied the segmental structure of the trunk in geophilomorph centipedes, where we can identify morphogenetic units of two, four, eight or 16 segments. Accordingly, we sketch an improved model for arthropod segmentation, with the following initial steps: (a) biochemical marking of a very few repetitive units (eosegments); (b) iterative duplications of this first periodicity, until the embryo acquires an array of biochemical markings matching the whole number of segments of the future larva or juvenile specimen; (c) transpatterning, stabilization and interpretation of this 'segmental' arrangement; (d) possible repatterning, to give a final repetitive pattern we define as metasegmental. Finally, we express some doubt about the homology between annelid and arthropod segmentation.     

A model for dual channel segmentation of the EEG signal

Dual channel segmentation of the EEG signal has been developed. The purpose was to divide the signals into segments, according to information common for the two channels. The criterion for segmentation was based on the changes in the cross-spectrum of the two signals. It has been shown theoretically, as well as by simulation studies and by analysis of real EEG data that this method is sensitive to changes common for both channels, whereas segmentation does not occur as a result of changes in each channel separately.     

Edged watershed segmentation: A semi-interactive algorithm for segmentation of low-resolution maps from electron cryomicroscopy

Electron cryomicroscopy (cryo-EM) allows for the structural analysis of large protein complexes that may be difficult to study by other means. Frequently, maps of complexes from cryo-EM are obtained at resolutions between 10 and 25 Å. To aid in the interpretation of these medium- to low-resolution maps, they may be subdivided into three-dimensional segments representing subunits or subcomplexes. This division is often accomplished using a manual segmentation approach. While extremely useful, manual segmentation is subjective. We have developed a novel semi-interactive segmentation algorithm that can incorporate prior knowledge of subunit composition or structure without biasing the boundaries between subunits or subcomplexes. This algorithm has been characterized with experimental and simulated cryo-EM density maps at resolutions between 10 and 25 Å.     

Segmentation of moving images by the human visual system

 New segments appearing in an image sequence or spontaneously accelerated segments are band limited by the visual system due to a nonperfect tracking of these segments by eye movements. In spite of this band limitation and acceleration of segments, a coarse segmentation (initial segmentation phase) can be performed by the visual system. This is interesting for the development of purely automatic segmentation algorithms for multimedia applications. In this paper the segmentation of the visual system is modelled and used in an automatic coarse initial segmentation. A suitable model for motion processing based on a spectral representation is presented and applied to the segmentation of synthetic and real image sequences with band limited and accelerated moving foreground and background segments. Received: 1 August 1995/Accepted in revised form: 25 February 1997     

Work-related musculoskeletal disorders: the epidemiologic evidence and the debate.

The debate about work-relatedness of musculoskeletal disorders (MSDs) reflects both confusion about epidemiologic principles and gaps in the scientific literature. The physical ergonomic features of work frequently cited as risk factors for MSDs include rapid work pace and repetitive motion, forceful exertions, non-neutral body postures, and vibration. However, some still dispute the importance of these factors, especially relative to non-occupational causes. This paper addresses the controversy with reference to a major report recently commissioned by the US Congress from the National Research Council (NRC) and Institute of Medicine (IOM) (2001). The available epidemiologic evidence is substantial, but will benefit from more longitudinal data to better evaluate gaps in knowledge concerning latency of effect, natural history, prognosis, and potential for selection bias in the form of the healthy worker effect. While objective measures may be especially useful in establishing a more secure diagnosis, subjective measures better capture patient impact. Examination techniques still do not exist that can serve as a "gold standard" for many of the symptoms that are commonly reported in workplace studies. Finally, exposure assessment has too often been limited to crude indicators, such as job title. Worker self-report, investigator observation, and direct measurement each add to understanding but the lack of standardized exposure metrics limits ability to compare findings among studies. Despite these challenges, the epidemiologic literature on work-related MSDs-in combination with extensive laboratory evidence of pathomechanisms related to work stressors-is convincing to most. The NRC/IOM report concluded, and other reviewers internationally have concurred, that the etiologic importance of occupational ergonomic stressors for the occurrence of MSDs of the low back and upper extremities has been demonstrated.     

Heuristic Bayesian Segmentation for Discovery of Coexpressed Genes within Genomic Regions

Segmentation aims to separate homogeneous areas from the sequential data, and plays a central role in data mining. It has applications ranging from finance to molecular biology, where bioinformatics tasks such as genome data analysis are active application fields. In this paper, we present a novel application of segmentation in locating genomic regions with coexpressed genes. We aim at automated discovery of such regions without requirement for user-given parameters. In order to perform the segmentation within a reasonable time, we use heuristics. Most of the heuristic segmentation algorithms require some decision on the number of segments. This is usually accomplished by using asymptotic model selection methods like the Bayesian information criterion. Such methods are based on some simplification, which can limit their usage. In this paper, we propose a Bayesian model selection to choose the most proper result from heuristic segmentation. Our Bayesian model presents a simple prior for the segmentation solutions with various segment numbers and a modified Dirichlet prior for modeling multinomial data. We show with various artificial data sets in our benchmark system that our model selection criterion has the best overall performance. The application of our method in yeast cell-cycle gene expression data reveals potential active and passive regions of the genome.     

Segmental patterning of the vertebrate embryonic axis

The body axis of vertebrates is composed of a serial repetition of similar anatomical modules that are called segments or metameres. This particular mode of organization is especially conspicuous at the level of the periodic arrangement of vertebrae in the spine. The segmental pattern is established during embryogenesis when the somites--the embryonic segments of vertebrates--are rhythmically produced from the paraxial mesoderm. This process involves the segmentation clock, which is a travelling oscillator that interacts with a maturation wave called the wavefront to produce the periodic series of somites. Here, we review our current understanding of the segmentation process in vertebrates.     

TomoFlow: Analysis of Continuous Conformational Variability of Macromolecules in Cryogenic Subtomograms based on 3D Dense Optical Flow

Cryogenic Electron Tomography (cryo-ET) allows structural and dynamics studies of macromolecules in situ. Averaging different copies of imaged macromolecules is commonly used to obtain their structure at higher resolution and discrete classification to analyze their dynamics. Instrumental and data processing developments are progressively equipping cryo-ET studies with the ability to escape the trap of classification into a complete continuous conformational variability analysis. In this work, we propose TomoFlow, a method for analyzing macromolecular continuous conformational variability in cryo-ET subtomograms based on a three-dimensional dense optical flow (OF) approach. The resultant lower-dimensional conformational space allows generating movies of macromolecular motion and obtaining subtomogram averages by grouping conformationally similar subtomograms. The animations and the subtomogram group averages reveal accurate trajectories of macromolecular motion based on a novel mathematical model that makes use of OF properties. This paper describes TomoFlow with tests on simulated datasets generated using different techniques, namely Normal Mode Analysis and Molecular Dynamics Simulation. It also shows an application of TomoFlow on a dataset of nucleosomes in situ, which provided promising results coherent with previous findings using the same dataset but without imposing any prior knowledge on the analysis of the conformational variability. The method is discussed with its potential uses and limitations.     

Motion edges and regions guide image segmentation by colour.

Image segmentation is an important early stage in visual processing in which the visual system groups together parts of the image that belong together, prior to or in conjunction with object recognition. Two principal processes may be involved in image segmentation: an edge-based process that uses feature contrasts to mark boundaries of coherent regions, and a region-based process that groups similar features over a larger scale. Earlier, we have shown that motion and colour interact strongly in image segmentation by the human visual system. Here we explore the nature of this interaction in terms of edge- and region-based processes. We measure performance on a region-based colour segmentation task in the presence of distinct types of motion information, in the form of edges and regions which in themselves do not reveal the location of the colour target. The results show that both motion edges and regions may guide the integrative process required for this colour segmentation task. Motion edges appear to act by delimiting areas over which to integrate colour information, whereas motion similarities define primitive surfaces within which colour grouping and segmentation processes are deployed.     

CIRDO: Smart companion for helping elderly to live at home for longer

Cirdo project is intended to establish new healthcare systems to ensure the safety at home of seniors and people with decreasing independence. In particular, extending “e-lio footnote http://www.technosens.fr/” devise, Cirdo aims to develop an audio/video-based system which makes it possible for elderly to live with a sufficient degree of autonomy. To achieve this goal, generic purposes on video analysis and audio processing are discussed and implemented in the same process. Audio and video analysis algorithms are launched simultaneously and thinks to GPU implementation, the tasks are done in real time. To comply with the requirements set out in the Cirdo project namely: respect privacy and preserve personal data, the processing tasks is performed through background tasks, without any human intrusion. In order to have different types of fall for our experiences, multiple scenarios were designed and performed by several persons. Besides the technical aspect, the project also focuses on generic technology validation by potential users and their human environment (family, caregivers/care takers…). Psychological and ergonomic assessment on the use of services developed was conducted. It focused on the usefulness, usability and accessibility and acceptance of the tool. This evaluation was completed by critical investigation of knowledge acquired by professionals (geriatricians, caregivers school and associations).     

The evolution of teratological testing

The beginnings of mammalian experimental teratology in this century are briefly reviewed and it is noted that prior to 1960 a degree of sophistication in concept and technology had already been achieved. Thus, contrary to claims that teratology had its beginning with the thalidomide catastrophe, a modest but expanding activity and body of knowledge already existed before this unfortunate event. This activity and this knowledge, however, were largely confined to academic and research institute laboratories and made little impact on the agencies in medicine, government and industry which oversaw public health and safety and set policies intended to preserve them. No individual, group, or agency can rightly be blamed for not having sooner brought together the concepts and methodology needed for meaningful animal testing and the regulatory insignt and experience needed intelligently to apply test data to human safety evaluation and experience needed intelligently to apply test data to human safety evaluation. To accomplish this liaison seems to have required the largest toxicological catastrophe yet recorded in human history. The major events leading to formulation of the first standardized guidelines are reviewed, but it is emphasized that even today the best animal testing can only provide a limited statement of probability regarding human risk vis-à-vis safety.     

Cellular oscillators in animal segmentation

Kinetic modeling of developmental dynamics requires detailed knowledge about genetic and metabolic networks that underlie developmental processes. However, such knowledge is not available for a vast majority of developmental processes. Here, we present an coarse-grained, phenomenological model of periodic pattern formation in multicellular organisms based on cellular oscillators (CO) that can be applied to systems for which little or no molecular data is available. An oscillatory process within cells serves as a developmental clock whose period is tightly regulated by cell-autonomous and non-autonomous mechanisms. A spatial pattern is generated as a result of an initial temporal ordering of the cell oscillators freezing into spatial order as the clocks slow down and stop at different times or phases in their cycles. When applied to vertebrate somitogenesis, the CO model can reproduce the dynamics of periodic gene expression patterns observed in the presomitic mesoderm. Different somite lengths can be generated by altering the period of the oscillation. There is evidence that a CO-type mechanism might also underlie segment formation in certain invertebrates, such as annelids and short germ insects. This suggests that the dynamical principles of sequential segmentation might be equivalent throughout the animal kingdom although most of the genes involved in segment determination differ between distant phyla.     

Combining protein-protein interactions information with support vector machine to identify chronic obstructive pulmonary disease related genes

Chronic obstructive pulmonary disease (COPD) is a complex human disease with a high mortality rate. So far, the studies of COPD have not been well organized despite the well-documented role of cigarette smoking in the genesis of COPD. In the recent years, microarray analyses have helped to identify some potential disease related genes. However, the low reproducibility of many published gene signatures has been criticized. It therefore suggested that incorporation of network or pathway information into prognostic biomarker discovery might improve the prediction performance. In this analysis, we combined protein-protein interactions (PPI) information with the support vector machine (SVM) method to identify potential COPD-related genes that would allow one to distinguish accurately severe emphysema from non-/mildly emphysematous lung tissue. We identified 8 COPD-related feature genes. When compared with another SVM method which did not use the prior PPI information, the prediction accuracy was significantly enhanced (AUC was increased from 0.513 to 0.909). On the base of results obtained one can suppose that incorporating network of prior knowledge into gene selection methods significantly improves classification accuracy. Consequently, the gene expression profiles from human emphysematous lung tissue may provide insight into the pathogenesis, and a good classification prediction algorithm based on prior biological knowledge can further strengthen this performance.     

Vertebrate segmentation: from cyclic gene networks to scoliosis

One of the most striking features of the human vertebral column is its periodic organization along the anterior-posterior axis. This pattern is established when segments of vertebrates, called somites, bud off at a defined pace from the anterior tip of the embryo's presomitic mesoderm (PSM). To trigger this rhythmic production of somites, three major signaling pathways--Notch, Wnt/β-catenin, and fibroblast growth factor (FGF)--integrate into a molecular network that generates a traveling wave of gene expression along the embryonic axis, called the "segmentation clock." Recent systems approaches have begun identifying specific signaling circuits within the network that set the pace of the oscillations, synchronize gene expression cycles in neighboring cells, and contribute to the robustness and bilateral symmetry of somite formation. These findings establish a new model for vertebrate segmentation and provide a conceptual framework to explain human diseases of the spine, such as congenital scoliosis.     

A Web-based semantic tagging and activity recognition system for species' accelerometry data

Increasingly, animal biologists are taking advantage of low cost micro-sensor technology, by deploying accelerometers to monitor the behavior and movement of a broad range of species. The result is an avalanche of complex tri-axial accelerometer data streams that capture observations and measurements of a wide range of animal body motion and posture parameters. Analysis of these parameters enables the identification of specific animal behaviors—however the analysis process is immature with much of the activity identification steps undertaken manually and subjectively. Consequently, there is an urgent need for the development of new tools to streamline the management, analysis, indexing, querying and visualization of such data. In this paper, we present a Semantic Annotation and Activity Recognition (SAAR) system which supports storing, visualizing, annotating and automatic recognition of tri-axial accelerometer data streams by integrating semantic annotation and visualization services with Support Vector Machine (SVM) techniques. The interactive Web interface enables biologists to visualize and correlate 3D accelerometer data streams with associated video streams. It also enables domain experts to accurately annotate or tag segments of tri-axial accelerometer data streams, with standardized terms from an activity ontology. These annotated data streams can then be used to dynamically train a hierarchical SVM activity classification model, which can be applied to new accelerometer data streams to automatically recognize specific activities. This paper describes the design, implementation and functional details of the SAAR system and the results of the evaluation experiments that assess the performance, usability and efficiency of the system. The evaluation results indicate that the SAAR system enables ecologists with little knowledge of machine learning techniques to collaboratively build classification models with high levels of accuracy, sensitivity, precision and specificity.     

Segmentation of stained blood cell images measured at high scanning density with high magnification and high numerical aperture optics

In hematological morphology, it is necessary to resolve and analyze the smallest possible cellular details appearing in the light microscope. A prerequisite for computer-aided analysis of subtle morphological features is measuring the cells at a high scanning density with high magnification and high numerical aperture optics. Contrary to visual observations, the information content in a measured picture can be increased by setting the condensor's numerical aperture (NA) greater than the objective's NA. The complexity and heterogeneity of such cell images necessitate a new segmentation method that conserves the morphological information required in the subsequent image analysis, feature extraction, and cell classification. In our segmentation strategy, characteristic color difference thresholds for each nucleus and cytoplasm are combined with geometric operations, probability functions, and a cell model. All thresholds are repeatedly recalculated during the successive improvements of the image masks. None of the thresholds are fixed. This strategy segments blood cell images containing touching cells and large variations in staining, texture, size, and shape. Biological inconsistencies in the calculated cell masks are eliminated by comparing each mask with the cell model criteria integrated into the entire segmentation process. All 20,000 leukocyte images from 120 smears in our leukemia project were segmented with this method.     

Segmentation of the central nervous system in ligated embryos ofDrosophila melanogaster

Summary We have visualized segmentation in theDrosophila embryoniccentral nervous system (CNS) by staining for acetylcholinesterase activity. This technique was used to evaluate the effect of ligation on segments in the ventral CNS. When embryos were ligated prior to cellularization (60 min) fewer segmental ganglia developed in posterior fragments than when embryos were ligated at the blatoderm stage (3 h). This result is consistent with previous ligation experiments in which hypodermal segments were counted (Schubiger and Wood 1977). The number of ganglia scored exceeded the number of hypodermal segments scored especially after ligations at 60 min. Possible explanations for this difference are discussed.