IMAGE ANALYSIS AS A RAPID PATHOGEN DETECTION METHOD FOR USE IN POULTRY INDUSTRY

An image analysis system was developed and evaluated as a method for rapid detection of Salmonella typhimurium in pure culture and in chicken washes. A direct immunomagnetic separation and immunofluorescent staining technique was developed to capture and identify target cells. Digital images were acquired and segmented into background and bacteria. Bacteria were enumerated using a custom designed image analysis software. The image analyses results were compared with manual enumeration. A correlation coefficient of 0.78 was established between manual and image analysis counts. In addition, the difference between the manual and the image analysis bacterial counts in individual images was low. Image analysis took an average of 15 s to analyze an image. The results indicate that the proposed system has the potential to be used as a rapid screening procedure for bacterial detection in the food industry.     

A computer system for handling data from bacterial sensitivity testing.

A computer system for handling data collected from antibiotic sensitivity testing of clinical bacterial isolates is described. The system allows a rapid handling of the information collected, supplying the ward and laboratory with cummulative data on each patient. The bacteriologist and the clinician are thus suitably armed when creating a rational antibiotic therapy.     

Simple method for quantification of fast plasma membrane movements.

We present a method for the quantification of the fast plasma membrane movements that are involved in ruffling, blebbing, fast shape change, and fast translocation. The method is based on the Kontron Vidas image analysis computer program. Video images from cells viewed through an inverted microscope were transmitted to the computer. The procedure was as follows: 4 consecutive video images were averaged (image 1); 28 s later a second set of 4 video images was averaged (image 2); image 2 was subtracted from image 1 and the grey level of each pixel of the resulting image was increased with 128 grey level units, resulting in the subtraction image, showing a uniform grey background speckled with brighter and darker spots corresponding to areas of movement. These spots were discriminated and turned into white objects against a black background. Interactive editing was used to delete artefacts that resulted from floating debris. The total area of the discriminated objects was measured, and the parameter motile area in micron2 per cell was calculated. We have applied our method to the study of motility induced in epithelial cell lines by the tumor promoter 12-O-tetradecanoyl-phorbol-13-acetate and by epidermal growth factor.     

Classification of immature and mature cells of the neutrophil series using morphometrical parameters

Quantitative morphological data of six classes of immature and mature cells of the neutrophil series of the bone marrow of normal persons were used for statistical classification experiments (myeloblasts, promyelocytes, myelocytes, metamyelocytes, bands and segments). On each cell, parameters were measured directly from the image or calculated from the shape of the density histogram or the counting densitogram using a Texture Analysis System (E. Leitz, Wetzlar, Germany). The parameters were analyzed with the interactive statistical pattern recognition system ISPAHAN. One half of the data were used as a learning set and the other half as the test set. The parameters were compared according to their performance in discrimination between the classes, alone and in combinations. Parameters not contributing to an improvement of the discrimination were disregarded. Eleven parameters were selected and used for classification by two different methods: a stepwise and a "one-shot" method. Stepwise classification resulted in a 79% correct classification rate. Most errors occurred between cell classes in neighboring stages of maturation. In 96% of all cases the computer classification was either in accordance with that of the technician or with a cell class of a neighboring maturation stage. One step classification by the computer was in agreement with the technicians in 82% of the cases. For 98% of the cells the computer classification was either in accordance with that of the technician or with a cell class of a neighboring maturation stage. The data set was collected by two technicians, operating independently. Differences in their interpretation of the maturation stage were found by comparing the performance of classifiers based on both cell samples. Since the images of the cells were not available for reexamination, the causes of disagreement in classification between the technicians and between computer and technicians could not be evaluated.     

Detecting infection-related changes in peripheral blood smears with image analysis techniques

High-resolution image analysis has the potential to flag subtle changes in white blood cell morphology that may indicate the presence of certain diseases. A study was made of the feasibility of identifying patients with hematologic bacterial infections (sepsis) using measurements on Wright-Giemsa-stained peripheral blood smears. Neutrophils and lymphocytes from a group of patients with sepsis and from a control group were digitized, and parameters quantifying geometry, color, texture and shape were extracted. While color parameters differed the most between the infected and control samples, substantial differences in geometric, texture and shape parameters also were observed. Analysis of the data showed that individual neutrophils and lymphocytes from patients with sepsis were distinguishable from those of the control group with better than 84% accuracy. When average parameters were calculated from all cells of one type for each specimen, 100% accurate classification was obtained. These studies demonstrate that the image-analysis techniques used are sensitive enough to detect disease-related changes in cell morphology that are generally too subtle for reliable detection by the human eye. Future experiments will determine the specificity of this test for bacterial infections and will explore the possibility of using image analysis techniques on peripheral blood to detect and monitor a wide variety of diseases.     

Automated computer evaluation of time-varying cryomicroscopical images

A system has been developed to perform automatic computerized recognition, tracking, and quantitative morphological analysis of viable cells in freezing solutions. Cryomicroscopical image sequences of freezing cells are digitized and analyzed by computer. Image-processing techniques are used which are insensitive to contrast fluctuations from image to image, and which perform well even in noisy, cluttered images. The generalized Hough transform is used for shape detection, and a heuristic graph-search boundary completion algorithm is applied for shape extraction. The extracted cell shape may be analyzed for changes in cross-sectional area, perimeter length, shape deformation, and other metrics of interest. Knowledge from the shapeextraction phase is used to form a prediction of what shape the cell will be in the next image frame, and thus what to look for in the next shape-detection phase. This combination of knowledge-feedback with a powerful shape-detection technique produces an automatic, dynamic shape-recognition scheme capable of accurate recognition and analysis of the cells regardless of how deformed they may become during the freezing sequence. Example performance of the system is illustrated for a series of micrographs of freezing granulocytes.     

Modeling and simulation of biological systems from image data

This essay provides an introduction to the terminology, concepts, methods, and challenges of image‐based modeling in biology. Image‐based modeling and simulation aims at using systematic, quantitative image data to build predictive models of biological systems that can be simulated with a computer. This allows one to disentangle molecular mechanisms from effects of shape and geometry. Questions like “what is the functional role of shape” or “how are biological shapes generated and regulated” can be addressed in the framework of image‐based systems biology. The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum.     

Effect of adaptive biocontrol sessions on persons with strong professional skills

We studied the effect of adaptive biocontrol on the quality of the professional activity of an operator possessing stable skills in modeling manual control of station-keeping and berthing to the International Space Station (ISS) of the Soyuz transport ship. The operational quality was evaluated in terms of time, energy, and precision parameters. A computer model of the dynamic ISS image and machinery identical to the real machinery were used in the study.     

A new registration method for three-dimensional knee nearthrosis model using two X-ray images

The purpose of this study is to develop a method to analyse the pose of the knee nearthrosis mounted and to automate the registration procedure for easy use in clinical applications. The proposed registration method is essentially a model-based method, in which the CAD model is acquired by reverse engineering. The CAD model is converted into a two-dimensional (2D) image by a rendering technique, and the compatibility of the X-ray image and the image of the CAD model is investigated. To avoid the optimisation of six unknown parameters with respect to the relative pose between the condyle and tibial models, a 2D coordinate system is set on each component of the X-ray images. A 3D coordinate system is also set on each of the two nearthrosis components. With such a setup, there is only one unknown rotational angle on each component, which is determined by an optimum algorithm in accordance with the contour error between the X-ray image and the image of the CAD model. Extensive computer simulation and in vitro experiments using real X-ray images have been implemented to investigate the feasibility of the proposed registration method.     

Evaluation of different DNA extraction procedures for the detection of Salmonella from chicken products by polymerase chain reaction

Polymerase chain reaction (PCR) was used after a short pre-enrichment culture to detect Salmonella subspecies in chicken fillets. A direct PCR assay performed with chicken meat inoculated with Salmonella Typhimurium produced no PCR products. Six different DNA extraction protocols were tested to recover efficiently Salmonella DNA after a short incubation period. Three of them gave results that were reliable, rapid and sensitive. Successful protocols used Proteinase K and/or a centrifugation step to concentrate the samples. For reliable detection of Salmonella subspecies, a few thousand bacterial cells per ml must be present. To obtain this number of bacterial cells with an inoculation of about one cell in 25 g of ionized food products, it was necessary to incubate samples for at least 10 h before PCR. A larger inoculum of approximately 10 cells in 25 g of ionized food products, required 8 h in culture broth to give positive results by PCR-based assay.     

SseA is required for translocation of Salmonella pathogenicity island-2 effectors into host cells

The Salmonella pathogenicity island-2 (SPI2) is a virulence locus on the bacterial chromosome required for intracellular proliferation and systemic infection in mice. Cell culture models and a murine model of systemic infection were used to address the role of an uncharacterized SPI2 open reading frame, designated as sseA, in Salmonella virulence. A Salmonella strain with an unmarked internal deletion of sseA displayed a phenotype that was similar to an SPI2-encoded type III secretion system apparatus mutant. Moreover, SseA was required for survival and replication within epithelial cells and macrophages. Murine infection studies confirmed that the DeltasseA strain was severely attenuated for virulence. Using immunofluorescence microscopy, the virulence defect in the DeltasseA strain was attributed to an inability to translocate SPI2 effector proteins into host cells. These data demonstrate that SseA is essential for SPI2-mediated translocation of effector proteins.     

A rapid and direct real time PCR-based method for identification of Salmonella spp

The aim of this work was the validation of a rapid, real-time PCR assay based on TaqMan technology for the unequivocal identification of Salmonella spp. to be used directly on an agar-grown colony. A real-time PCR system targeting at the Salmonella spp. invA gene was optimized and validated through a four times repeated blind experiment performed in two different laboratories including 50 Salmonella spp. with representative strains from each of the 5 different Salmonella subgenera and 30 non-Salmonella strains. Both parameters DeltaR(n) (fluorescence intensity of template through a normalized reporter value) and C(T) (cycle at which the fluorescence intensity achieved a pre-established threshold) were analyzed. Overall mean DeltaR(n) and C(T) values for Salmonella strains (2.14+/-0.87 and 15.30+/-0.90, respectively) were statistically different from values for non-Salmonella strains, allowing the establishment of cut-off DeltaR(n) and C(T) values based on 95% confidence intervals that allowed the correct identification of all strains tested in each independent experiment. The accuracy of this assay in terms of inclusivity and exclusivity was 100%. Moreover, the PCR system proved to be especially convenient because the pre-mix containing all PCR reagents except for the bacterial cells could be kept at -20 degrees C for at least 1 month before its use. The optimized TaqMan real-time PCR assay is a useful, simple and rapid method for routine identification of Salmonella spp., irrespective of the particular subgenus.     

Analysis of interactions of Salmonella type three secretion mutants with 3-D intestinal epithelial cells

The prevailing paradigm of Salmonella enteropathogenesis based on monolayers asserts that Salmonella pathogenicity island-1 Type Three Secretion System (SPI-1 T3SS) is required for bacterial invasion into intestinal epithelium. However, little is known about the role of SPI-1 in mediating gastrointestinal disease in humans. Recently, SPI-1 deficient nontyphoidal Salmonella strains were isolated from infected humans and animals, indicating that SPI-1 is not required to cause enteropathogenesis and demonstrating the need for more in vivo-like models. Here, we utilized a previously characterized 3-D organotypic model of human intestinal epithelium to elucidate the role of all characterized Salmonella enterica T3SSs. Similar to in vivo reports, the Salmonella SPI-1 T3SS was not required to invade 3-D intestinal cells. Additionally, Salmonella strains carrying single (SPI-1 or SPI-2), double (SPI-1/2) and complete T3SS knockout (SPI-1/SPI-2: flhDC) also invaded 3-D intestinal cells to wildtype levels. Invasion of wildtype and TTSS mutants was a Salmonella active process, whereas non-invasive bacterial strains, bacterial size beads, and heat-killed Salmonella did not invade 3-D cells. Wildtype and T3SS mutants did not preferentially target different cell types identified within the 3-D intestinal aggregates, including M-cells/M-like cells, enterocytes, or Paneth cells. Moreover, each T3SS was necessary for substantial intracellular bacterial replication within 3-D cells. Collectively, these results indicate that T3SSs are dispensable for Salmonella invasion into highly differentiated 3-D models of human intestinal epithelial cells, but are required for intracellular bacterial growth, paralleling in vivo infection observations and demonstrating the utility of these models in predicting in vivo-like pathogenic mechanisms.     

An iterative region-growing process for cell image segmentation based on local color similarity and global shape criteria

An image segmentation process was derived from an image model that assumed that cell images represent objects having characteristic relationships, limited shape properties and definite local color features. These assumptions allowed the design of a region-growing process in which the color features were used to iteratively aggregate image points in alternation with a test of the convexity of the aggregate obtained. The combination of both local and global criteria allowed the self-adaptation of the algorithm to segmentation difficulties and led to a self-assessment of the adequacy of the final segmentation result. The quality of the segmentation was evaluated by visual control of the match between cell images and the corresponding segmentation masks proposed by the algorithm. A comparison between this region-growing process and the conventional gray-level thresholding is illustrated. A field test involving 700 bone marrow cells, randomly selected from May-Grünwald-Giemsa-stained smears, allowed the evaluation of the efficiency, effectiveness and confidence of the algorithm: 96% of the cells were evaluated as correctly segmented by the algorithm's self-assessment of adequacy, with a 98% confidence. The principles of the other major segmentation algorithms are also reviewed.     

A program system for interactive measurements on digitized cell images.

Using a high precision image scanner and a PDP-8/F minicomputer, we have developed a program system for interactive measurements on microscopic images. By giving simple keyboard commands, the operator can run the image scanner and manipulate the digitized images. The interface between the operator and the microscope-computer system is a Tektronix 4010 graphic terminal. The system allows objects to be isolated and parameters to be calculated from each object, e.g., parameters characterizing shape of the object, irregularity in light transmission over the object, area, integrated light transmission, etc. Objects are isolated and parameters are calculated under complete operator control using interactive computer graphics technique. Calculated parameters may be stored in dedicated data records, which are stored in files for later statistical analysis. The system also includes a statistical evaluation part. Technically, the system consists of a command scanner, which translates commands into internal representation, a parser, which checks the syntax of the commands, and an interpreter, which executes the commands. The system is designed so that new commands can be added easily.     

基于对象特征的山东省丘陵地区多时相遥感土地覆被自动分类

对于基于像元的土地覆被分类来说,植被的分类是难点。使用多时相面向对象分类方法可以较好的解决这个问题。以山东省烟台市丘陵地区为研究区,采用Landsat TM(Landsat Thematic Mapper remotely sensed imagery)、DEM(Digital Elevation Model)、坡度、坡位、坡向等多种数据,利用基于对象特征的多时相分类方法对研究区进行土地覆盖自动分类。首先对影像进行多尺度分割并检验分割结果选取合适的分割尺度,然后分析对象的光谱、纹理、形状特征。根据各类地物的光谱特征、地理相关性、形状、空间分布等特征,明确类别之间的差异。建立决策树使用隶属度函数进行模糊分类,借助支持向量机提高分类精度。研究结果表明,通过使用多时相影像采用面向对象分类方法,相对于传统的基于像素的分类可以明显提高分类精度,尤其是解决了乔灌草的区分问题。     

Multiple large filament bundles observed in Caulobacter crescentus by electron cryotomography

While the absence of any cytoskeleton was once recognized as a distinguishing feature of prokaryotes, it is now clear that a number of different bacterial proteins do form filaments in vivo. Despite the critical roles these proteins play in cell shape, genome segregation and cell division, molecular mechanisms have remained obscure in part for lack of electron microscopy-resolution images where these filaments can be seen acting within their cellular context. Here, electron cryotomography was used to image the widely studied model prokaryote Caulobacter crescentus in an intact, near-native state, producing three-dimensional reconstructions of these cells with unprecedented clarity and fidelity. We observed many instances of large filament bundles in various locations throughout the cell and at different stages of the cell cycle. The bundles appear to fall into four major classes based on shape and location, referred to here as 'inner curvature', 'cytoplasmic', 'polar' and 'ring-like'. In an attempt to identify at least some of the filaments, we imaged cells where crescentin and MreB filaments would not be present. The inner curvature and cytoplasmic bundles persisted, which together with their localization patterns, suggest that they are composed of as-yet unidentified cytoskeletal proteins. Thus bacterial filaments are frequently found as bundles, and their variety and abundance is greater than previously suspected.     

Image analysis in fluorescence microscopy: bacterial dynamics as a case study

Fluorescence microscopy is the primary tool for studying complex processes inside individual living cells. Technical advances in both molecular biology and microscopy have made it possible to image cells from many genetic and environmental backgrounds. These images contain a vast amount of information, which is often hidden behind various sources of noise, convoluted with other information and stochastic in nature. Accessing the desired biological information therefore requires new tools of computational image analysis and modeling. Here, we review some of the recent advances in computational analysis of images obtained from fluorescence microscopy, focusing on bacterial systems. We emphasize techniques that are readily available to molecular and cell biologists but also point out examples where problem-specific image analyses are necessary. Thus, image analysis is not only a toolkit to be applied to new images but also an integral part of the design and implementation of a microscopy experiment.     

Population modeling for a captive squirrel monkey colony

Population modeling for a squirrel monkey colony breeding in a captive laboratory environment was approached with the use of two different mathematical modeling techniques. Deterministic modeling was used initially on a spreadsheet to estimate future census figures for animals in various age/sex classes. Historical data were taken as input parameters for the model, combined with harvesting policies to calculate future population figures in the colony. This was followed by a more sophisticated stochastic model that is capable of accommodating random variations in biological phenomena, as well as smoothing out measurement errors. Point estimates (means) for input parameters used in the deterministic model are replaced by probability distributions fitted into historical data from colony records. With the use of Crystal Ball (Decisioneering, Inc., Denver, CO) software, user-selected distributions are embedded in appropriate cells in the spreadsheet model. A Monte Carlo simulation scheme running within the spreadsheet draws (on each cycle) random values for input parameters from the distribution embedded in each relevant cell, and thus generates output values for forecast variables. After several thousand runs, a distribution is formed at the output end representing estimates for population figures (forecast variables) in the form of probability distributions. Such distributions provide the decision-maker with a mathematical habitat for statistical analysis in a stochastic setting. In addition to providing standard statistical measures (e.g., mean, variance, and range) that describe the location and shape of the distribution, this approach offers the potential for investigating crucial issues such as conditions surrounding the plausibility of extinction.     

General model, based on two mixed weibull distributions of bacterial resistance, for describing various shapes of inactivation curves

Cells of Listeria monocytogenes or Salmonella enterica serovar Typhimurium taken from six characteristic stages of growth were subjected to an acidic stress (pH 3.3). As expected, the bacterial resistance increased from the end of the exponential phase to the late stationary phase. Moreover, the shapes of the survival curves gradually evolved as the physiological states of the cells changed. A new primary model, based on two mixed Weibull distributions of cell resistance, is proposed to describe the survival curves and the change in the pattern with the modifications of resistance of two assumed subpopulations. This model resulted from simplification of the first model proposed. These models were compared to the Whiting's model. The parameters of the proposed model were stable and showed consistent evolution according to the initial physiological state of the bacterial population. Compared to the Whiting's model, the proposed model allowed a better fit and more accurate estimation of the parameters. Finally, the parameters of the simplified model had biological significance, which facilitated their interpretation.