A flow system for the on-line quantitative measurement of the retention of dosage forms on biological surfaces using spectroscopy and image analysis

Measuring the retention, or residence time, of dosage forms to biological tissue is commonly a qualitative measurement, where no real values to describe the retention can be recorded. The result of this is an assessment that is dependent upon a user's interpretation of visual observation. This research paper outlines the development of a methodology to quantitatively measure, both by image analysis and by spectrophotometric techniques, the retention of material to biological tissues, using the retention of polymer solutions to ocular tissue as an example. Both methods have been shown to be repeatable, with the spectrophotometric measurement generating data reliably and quickly for further analysis.

The use of image analysis to estimate population growth rate in Daphnia magna

1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

Influence of environmental stress on distributions of times to first division in Escherichia coli populations, as determined by digital-image analysis of individual cells

The distributions of times to first cell division were determined for populations of Escherichia coli stationary-phase cells inoculated onto agar media. This was accomplished by using automated analysis of digital images of individual cells growing on agar and calculation of the "box area ratio." Using approximately 300 cells per experiment, the mean time to first division and standard deviation for cells grown in liquid medium at 37 degrees C and inoculated on agar and incubated at 20 degrees C were determined as 3.0 h and 0.7 h, respectively. Distributions were observed to tail toward the higher values, but no definitive model distribution was identified. Both preinoculation stress by heating cultures at 50 degrees C and postinoculation stress by growth in the presence of higher concentrations of NaCl increased mean times to first division. Both stresses also resulted in an increase in the spread of the distributions that was proportional to the mean division time, the coefficient of variation being constant at approximately 0.2 in all cases. The "relative division time," which is the time to first division for individual cells expressed in terms of the cell size doubling time, was used as measure of the "work to be done" to prepare for cell division. Relative division times were greater for heat-stressed cells than for those growing under osmotic stress.

A novel method for measuring lag times in division of individual bacterial cells using image analysis

A method is presented for determining the time to first division of individual bacterial cells growing on agar media. Bacteria were inoculated onto agar-coated slides and viewed by phase-contrast microscopy. Digital images of the growing bacteria were captured at intervals and the time to first division estimated by calculating the "box area ratio". This is the area of the smallest rectangle that can be drawn around an object, divided by the area of the object itself. The box area ratios of cells were found to increase suddenly during growth at a time that correlated with cell division as estimated by visual inspection of the digital images. This was caused by a change in the orientation of the two daughter cells that occurred when sufficient flexibility arose at their point of attachment. This method was used successfully to generate lag time distributions for populations of Escherichia coli, Listeria monocytogenes and Pseudomonas aeruginosa, but did not work with the coccoid organism Staphylococcus aureus. This method provides an objective measure of the time to first cell division, whilst automation of the data processing allows a large number of cells to be examined per experiment. (c) 2005 Elsevier B.V. All rights reserved.

Computer generation and quantitative morphometric analysis of virtual neurons

An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.

Techniques for image analysis of movement of juveniles of root-knot nematodes encumbered with Pasteuria penetrans spores

Root-knot nematodes (Meloidogyne spp.) are the most significant plant-parasitic nematodes that damage many crops all over the world. The free-living second stage juvenile (J2) is the infective stage that enters plants. The J2s move in the soil water films to reach the root zone. The bacterium Pasteuria penetrans is an obligate parasite of root-knot nematodes, is cosmopolitan, frequently encountered in many climates and environmental conditions and is considered promising for the control of Meloidogyne spp. The infection potential of P. penetrans to nematodes is well studied but not the attachment effects on the movement of root-knot nematode juveniles, image analysis techniques were used to characterize movement of individual juveniles with or without P. penetrans spores attached to their cuticles. Methods include the study of nematode locomotion based on (a) the centroid body point, (b) shape analysis and (c) image stack analysis. All methods proved that individual J2s without P. penetrans spores attached have a sinusoidal forward movement compared with those encumbered with spores. From these separate analytical studies of encumbered and unencumbered nematodes, it was possible to demonstrate how the presence of P. penetrans spores on a nematode body disrupted the normal movement of the nematode.

Performance evaluation of crowd image analysis using the PETS2009 dataset

This paper presents the PETS2009 outdoor crowd image analysis surveillance dataset and the performance evaluation of people counting, detection and tracking results using the dataset submitted to five IEEE Performance Evaluation of Tracking and Surveillance (PETS) workshops. The evaluation was carried out using well established metrics developed in the Video Analysis and Content Extraction (VACE) programme and the CLassification of Events, Activities, and Relationships (CLEAR) consortium. The comparative evaluation highlights the detection and tracking performance of the authors’ systems in areas such as precision, accuracy and robustness and provides a brief analysis of the metrics themselves to provide further insights into the performance of the authors’ systems.

Recent advances in capillary electrophoresis methods for food analysis

This review article addresses recent advances in the analysis of foods and food components by capillary electrophoresis (CE). CE has found application to a number of important areas of food analysis, including quantitative chemical analysis of food additives, biochemical analysis of protein composition, and others. The speed, resolution and simplicity of CE, combined with low operating costs, make the technique an attractive option for the development of improved methods of food analysis for the new millennium.

Optimal protection of stabilised dry live bacteria from bile toxicity in oral dosage forms by bile acid adsorbent resins

We previously found that dried live bacteria of a vaccine strain can be temporarily sensitive to bile acids and suggested that Bile Adsorbing Resins (BAR) can be used in oral vaccine tablets to protect dried bacteria from intestinal bile. Here, we report a quantitative analysis of the ability of BAR to exclude the dye bromophenol blue from penetrating into matrix tablets and also sections of hard capsule shells. Based on this quantitative analysis, we made a fully optimised formulation, comprising 25% w/w of cholestyramine in Vcaps™ HPMC capsules. This gave effectively 100% protection of viability from 4% bile, with 4200-fold more live bacteria recovered from this formulation compared to unprotected dry bacteria. From the image analysis, we found that the filler material or compaction force used had no measurable effect on dye exclusion but did affect the rate of tablet hydration. Increasing the mass fraction of BAR gave more exclusion of dye up to 25% w/w, after which a plateau was reached and no further dye exclusion was seen. More effective dye exclusion was seen with smaller particle sizes (i.e. cholestyramine) and when the BAR was thoroughly dried and disaggregated. Similar results were found when imaging dye penetration into capsule sections or tablets. The predictions of the dye penetration study were tested using capsules filled with dried attenuated Salmonella vaccine plus different BAR types, and the expected protection from bile was found, validating the imaging study. Surprisingly, depending on the capsule shell material, some protection was given by the capsule alone without adding BAR, with Vcaps™ HPMC capsules providing up to 174-fold protection against 1% bile; faster releasing Vcaps Plus™ HPMC capsules and Coni Snap™ gelatin capsules gave less protection.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Hydroponic isotope labeling of entire plants (HILEP) for quantitative plant proteomics

Quantitative analysis by mass spectrometry (MS) is a major challenge in proteomics as the correlation between analyte concentration and signal intensity is often poor due to varying ionisation efficiencies in the presence of molecular competitors. However, relative quantitation methods that utilise differential stable isotope labelling and mass spectrometric detection are available. Many drawbacks inherent to chemical labelling methods (ICAT, iTRAQ) can be overcome by metabolic labelling with amino acids containing stable isotopes (e.g. 13C and/or 15N) in methods such as Stable Isotope Labelling with Amino acids in Cell culture (SILAC). SILAC has also been used for labelling of proteins in plant cell cultures (1) but is not suitable for whole plant labelling. Plants are usually autotrophic (fixing carbon from atmospheric CO2) and, thus, labelling with carbon isotopes becomes impractical. In addition, SILAC is expensive. Recently, Arabidopsis cell cultures were labelled with 15N in a medium containing nitrate as sole nitrogen source. This was shown to be suitable for quantifying proteins and nitrogen-containing metabolites from this cell culture (2,3). Labelling whole plants, however, offers the advantage of studying quantitatively the response to stimulation or disease of a whole multicellular organism or multi-organism systems at the molecular level. Furthermore, plant metabolism enables the use of inexpensive labelling media without introducing additional stress to the organism. And finally, hydroponics is ideal to undertake metabolic labelling under extremely well-controlled conditions. We demonstrate the suitability of metabolic 15N hydroponic isotope labelling of entire plants (HILEP) for relative quantitative proteomic analysis by mass spectrometry. To evaluate this methodology, Arabidopsis plants were grown hydroponically in 14N and 15N media and subjected to oxidative stress.

Rapid, automated detection of stem canker symptoms in woody perennials using artificial neural network analysis

Background Pseudomonas syringae can cause stem necrosis and canker in a wide range of woody species including cherry, plum, peach, horse chestnut and ash. The detection and quantification of lesion progression over time in woody tissues is a key trait for breeders to select upon for resistance. Results In this study a general, rapid and reliable approach to lesion quantification using image recognition and an artificial neural network model was developed. This was applied to screen both the virulence of a range of P. syringae pathovars and the resistance of a set of cherry and plum accessions to bacterial canker. The method developed was more objective than scoring by eye and allowed the detection of putatively resistant plant material for further study. Conclusions Automated image analysis will facilitate rapid screening of material for resistance to bacterial and other phytopathogens, allowing more efficient selection and quantification of resistance responses.

A geomatics-based approach for the derivation of the spatial distribution of sediment transport processes in periglacial mountain environments

Within this paper modern techniques such as satellite image analysis and tools provided by geographic information systems (GIS.) are exploited in order to extend and improve existing techniques for mapping the spatial distribution of sediment transport processes. The processes of interest comprise mass movements such as solifluction, slope wash, dirty avalanches and rock- and boulder falls. They differ considerably in nature and therefore different approaches for the derivation of their spatial extent are required. A major challenge is addressing the differences between the comparably coarse resolution of the available satellite data (Landsat TM/ETM+, 30 in x 30 m) and the actual scale of sediment transport in this environment. A three-stepped approach has been developed which is based on the concept of Geomorphic Process Units (GPUs): parameterization, process area delineation and combination. Parameters include land cover from satellite data and digital elevation model derivatives. Process areas are identified using a hierarchical classification scheme utilizing thresholds and definition of topology. The approach has been developed for the Karkevagge in Sweden and could be successfully transferred to the Rabotsbekken catchment at Okstindan, Norway using similar input data. Copyright (C) 2008 John Wiley & Sons, Ltd.

Quantifying sediment transport processes in periglacial mountain environments at a catchment scale using geomorphic process units

The research record on the quantification of sediment transport processes in periglacial mountain environments in Scandimvia dates back to the 1950s. A wide range of measurements is. available, especially from the Karkevagge region of northern Sweden. Within this paper satellite image analysis and tools provided by geographic information systems (GIS) are exploited in order to extend and improve this research and to complement geophysical methods. The processes of interest include mass movements such as solifluction, slope wash, dirty avalanches and rock-and boulder falls. Geomorphic process units have been derived in order to allow quantification via GIS techniques at a catchment scale. Mass movement rates based on existing Field measurements are employed in the budget calculation. In the Karkevagge catch ment. 80% of the area can be identified either as a source area for sediments or as a zone where sediments are deposited. The overall budget for the slopes beneath the rockwalls in the Karkevagge is approximately 680 t a(-1) whilst about 150 : a-1 are transported into the fluvial System.