Objective threshold selection procedure (OTS) for segmentation of scanning laser confocal microscope images

Green synthesis of silver and iron oxide nanoparticles mediated photothermal effects on Blastocystis hominis

The evolution of parasite resistance to antiparasitic agents has become a serious health issue indicating a critical and pressing need to develop new therapeutics that can conquer drug resistance. Nanoparticles are novel, promising emerging drug carriers that have demonstrated efficiency in treating many parasitic diseases. Lately, attention has been drawn to a broad-spectrum nanoparticle capable of converting absorbed light into heat via the photothermal effect phenomenon. The present study is the first to assess the effect of silver nanoparticles (Ag NPs) and iron oxide nanoparticles (Fe3O4 NPs) as sole agents and with the combined action of the light-emitting diode (LED) on Blastocystis hominins (B. hominis) in vitro. Initially, the aqueous synthesized nanoparticles were characterized by UV-Vis spectroscopy, zeta potential, and transmission electron microscopy (TEM). The anti-blastocyst efficiency of these NPs was tested separately in dark conditions. As these NPs have a wide absorption spectrum in the visible regions, they were also excited by a continuous wave LED of wavelength band (400-700 nm) to test the photothermal effect. The sensitivity of B. hominis cysts was evaluated using scanning laser confocal microscopy whereas the live and dead cells were accurately segmented based on superpixels and the k-mean clustering algorithm. Our findings showed that this excitation led to hyperthermia that induced a significant reduction in the number of cysts treated with photothermally active NPs. The results of this study elucidate the potential role of photothermally active NPs as an effective anti-blastocystis agent. By using this approach, new therapeutic antiparasitic agents can be developed.

Tools of the Trade: Image Analysis Programs for Confocal Laser-Scanning Microscopy Studies of Biofilms and Considerations for Their Use by Experimental Researchers

Confocal laser-scanning microscopy (CLSM) is the bedrock of the microscopic visualization of biofilms. Previous applications of CLSM in biofilm studies have largely focused on observations of bacterial or fungal elements of biofilms, often seen as aggregates or mats of cells. However, the field of biofilm research is moving beyond qualitative observations alone, toward the quantitative analysis of the structural and functional features of biofilms, across clinical, environmental, and laboratory conditions. In recent times, several image analysis programs have been developed to extract and quantify biofilm properties from confocal micrographs. These tools not only vary in their scope and relevance to the specific biofilm features under study but also with respect to the user interface, compatibility with operating systems, and raw image requirements. Understanding these considerations is important when selecting tools for quantitative biofilm analysis, including at the initial experimental stages of image acquisition. In this review, we provide an overview of image analysis programs for confocal micrographs of biofilms, with a focus on tool selection and image acquisition parameters that are relevant for experimental researchers to ensure reliability and compatibility with downstream image processing.

Characterization of biofilm structure and properties via processing of 2D optical coherence tomography images in BISCAP

MOTIVATION

Processing of Optical Coherence Tomography (OCT) biofilm images is currently restricted to a set of custom-made MATLAB scripts. None of the tools currently available for biofilm image processing (including those developed for Confocal Laser Scanning Microscopy-CLSM) enable a fully automatic processing of 2D OCT images.

RESULTS

A novel software tool entitled Biofilm Imaging and Structure Classification Automatic Processor (BISCAP) is presented. It was developed specifically for the automatic processing of 2D OCT biofilm images. The proposed approach makes use of some of the key principles used in CLSM image processing, and introduces a novel thresholding algorithm and substratum detection strategy. Two complementary pixel continuity checks are executed, enabling very detailed pixel characterizations. BISCAP delivers common structural biofilm parameters and a set of processed images for biofilm analysis. A novel biofilm 'compaction parameter' is suggested. The proposed strategy was tested on a set of 300 images with highly satisfactory results obtained. BISCAP is a Python-based standalone application, not requiring any programming knowledge or property licenses, and where all operations are managed via an intuitive Graphical User Interface. The automatic nature of this image processing strategy decreases biasing problems associated to human-perception and allows a reliable comparison of outputs.

AVAILABILITY AND IMPLEMENTATION

BISCAP and a collection of biofilm images obtained from OCT scans can be found at: https://github.com/diogonarciso/BISCAP.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Optimal surface estimation and thresholding of confocal microscope images of biofilms using Beer's Law

Beer's Law explains how light attenuates into thick specimens, including thick biofilms. We use a Bayesian optimality criterion, the maximum of the posterior probability distribution, and computationally efficiently fit Beer's Law to the 3D intensity data collected from thick living biofilms by a confocal scanning laser microscope. Using this approach the top surface of the biofilm and an optimal image threshold can be estimated. Biofilm characteristics, such as bio-volumes, can be calculated from this surface. Results from the Bayesian approach are compared to other approaches including the method of maximum likelihood or simply counting bright pixels. Uncertainty quantification (i.e., error bars) can be provided for the parameters of interest. This approach is applied to confocal images of stained biofilms of a common lab strain of Pseudomonas aeruginosa, stained biofilms of Janthinobacterium isolated from the Antarctic, and biofilms of Staphylococcusaureus that have been genetically modified to fluoresce green.

Understanding the fundamental mechanisms of biofilms development and dispersal: BIAM (Biofilm Intensity and Architecture Measurement), a new tool for studying biofilms as a function of their architecture and fluorescence intensity

Confocal laser scanning microscopy (CLSM) is one of the most relevant technologies for studying biofilms in situ. Several tools have been developed to investigate and quantify the architecture of biofilms. However, an approach to quantify correctly the evolution of intensity of a fluorescent signal as a function of the structural parameters of a biofilm is still lacking. Here we present a tool developed in the ImageJ open source software that can be used to extract both structural and fluorescence intensity from CLSM data: BIAM (Biofilm Intensity and Architecture Measurement). This is of utmost significance when studying the fundamental mechanisms of biofilm growth, differentiation and development or when aiming to understand the effect of external molecules on biofilm phenotypes. In order to provide an example of the potential of such a tool in this study we focused on biofilm dispersion. cis-2-Decenoic acid (CDA) is a molecule known to induce biofilm dispersion of multiple bacterial species. The mechanisms by which CDA induces dispersion are still poorly understood. To investigate the effects of CDA on biofilms, we used a reporter strain of Escherichia coli (E. coli) that expresses the GFPmut2 protein under control of the rrnBP1 promoter. Experiments were done in flow cells and image acquisition was made with CLSM. Analysis carried out using the new tool, BIAM, indicates that CDA affects the fluorescence intensity of the biofilm structures as well as biofilm architectures. Indeed, our results demonstrate that CDA removes more than 35% of biofilm biovolume and suggest that it results in an increase of the biofilm's mean fluorescence intensity (MFI) by more than 26% compared to the control biofilm in the absence of CDA.

Investigation of microbial biofilm structure by laser scanning microscopy

Microbial bioaggregates and biofilms are hydrated three-dimensional structures of cells and extracellular polymeric substances (EPS). Microbial communities associated with interfaces and the samples thereof may come from natural, technical, and medical habitats. For imaging such complex microbial communities confocal laser scanning microscopy (CLSM) is the method of choice. CLSM allows flexible mounting and noninvasive three-dimensional sectioning of hydrated, living, as well as fixed samples. For this purpose a broad range of objective lenses is available having different working distance and resolution. By means of CLSM the signals detected may originate from reflection, autofluorescence, reporter genes/fluorescence proteins, fluorochromes binding to specific targets, or other probes conjugated with fluorochromes. Recorded datasets can be used not only for visualization but also for semiquantitative analysis. As a result CLSM represents a very useful tool for imaging of microbiological samples in combination with other analytical techniques.

Spatial quantitation of FISH signals in diploid versus aneuploid nuclei

Fluorescence in situ hybridization (FISH) is the most widely used molecular technique to visualize chromosomal abnormalities. Here, we describe a novel 3D modeling approach to allow precise shape estimation and localization of FISH signals in the nucleus of human embryonic stem cells (hES) undergoing progressive but defined aneuploidy. The hES cell line WA09 acquires an extra copy of chromosome 12 in culture with increasing passages. Both diploid and aneuploid nuclei were analyzed to quantitate the differences in the localization of centromeric FISH signals for chromosome 12 as it transitions from euploidy to aneuploidy. We employed superquadric modeling primitives coupled with principal component analysis to determine the 3D position of FISH signals within the nucleus. A novel aspect of our modeling approach is that it allows comparison of FISH signals across multiple cells by normalizing the position of the centromeric signals relative to a reference landmark in oriented nuclei. Using this model we present evidence of changes in the relative positioning of centromeres in trisomy-12 cells when compared with diploid cells from the same population. Our analysis also suggests a significant change in the spatial distribution of at least one of the FISH signals in the aneuploid chromosome complements implicating that an overall change in centromere position may occur in trisomy-12 due to the addition of an extra chromosome. These studies underscore the unique utility of our modeling algorithms in quantifying FISH signals in three dimensions.

A computational approach to understand phenotypic structure and constitutive mechanics relationships of single cells

The goal of this study is to construct a representative 3D finite element model (FEM) of individual cells based on their sub-cellular structures that predicts cell mechanical behavior. The FEM simulations replicate atomic force microscopy (AFM) nanoindentation experiments on live vascular smooth muscle cells. Individual cells are characterized mechanically with AFM and then imaged in 3D using a spinning disc confocal microscope. Using these images, geometries for the FEM are automatically generated via image segmentation and linear programming algorithms. The geometries consist of independent structures representing the nucleus, actin stress fiber network, and cytoplasm. These are imported into commercial software for mesh refinement and analysis. The FEM presented here is capable of predicting AFM results well for 500 nm indentations. The FEM results are relatively insensitive to both the exact number and diameter of fibers used. Despite the localized nature of AFM nanoindentation, the model predicts that stresses are distributed in an anisotropic manner throughout the cell body via the actin stress fibers. This pattern of stress distribution is likely a result of the geometric arrangement of the actin network.

Development of 3D architecture of uropathogenic Proteus mirabilis batch culture biofilms-A quantitative confocal microscopy approach

This work studies the development of the 3D architecture of batch culture P. mirabilis biofilms on the basis of morpho-topological descriptors calculated from confocal laser scanning microscopy (CLSM) stacks with image processing routines. A precise architectonical understanding of biofilm organization on a morpho-topological level is necessary to understand emergent interactions with the environment and the appearance of functionally different progeny swarmer cells. P. mirabilis biofilms were grown on glass coverslips for seven days on LB broth and subjected to in situ immunofluorescence. Confocal image stacks were deconvolved prior to segmentation of regions of interest (ROI) that identify individual bacteria and extracellular material, followed by 3D reconstruction and calculation of different morpho-topological key descriptors. Results showed that P. mirabilis biofilm formation followed a five stage process: (i) reversible adhesion to the surface characterized by slow growth, presence of elongated bacteria, and absence of extracellular material, (ii) irreversible bacterial adhesion concomitant to decreasing elongation, and the beginning of extracellular polymer production, (iii) accelerated bacterial growth concomitant to continuously decreasing elongation and halting of extracellular polymer production, (iv) maturation of biofilm defined by maximum bacterial density, volume, minimum elongation, maximum extracellular material, and highest compaction, and (v) decreased bacterial density and extracellular material through detachment and dispersion. Swarmer cells do not play a role in P. mirabilis biofilm formation under the applied conditions. Our approach sets the basis for future studies of 3D biofilm architecture using dynamic in vivo models and different environmental conditions that assess clinical impacts of P. mirabilis biofilm.

Visualization of adherent micro-organisms using different techniques

The visualization and quantification of adherent bacteria is still one of the most relevant topics in microbiology. Besides electron microscopic techniques such as transmission electron microscopy, scanning electron microscopy and environmental scanning electron microscopy, modern fluorescence microscopic approaches based on fluorogenic dyes offer detailed insight into bacterial biofilms. The aim of the present review was to provide an overview of the advantages and disadvantages of different methods for visualization of adherent bacteria with a special focus on the experiences gained in dental research.

Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.

Imaging and quantifying virus fluorescence signals on aquatic aggregates: a new method and its implication for aquatic microbial ecology

The development of accurate methods to detect and enumerate viruses is an important issue in aquatic microbial ecology. In particular, viruses attached to floating aggregates are a largely ignored field both in marine and inland water ecology. Data on the total abundance and the colonization of aggregates by viruses are rare, mainly due to methodological difficulties. In the present study, we used confocal laser scanning microscopy (CLSM) to resolve fluorescence signals of single viruses and bacterial cells in a complex three-dimensional matrix of riverine aggregates. CLSM in combination with different fluorochromes is a very promising approach for obtaining information both on the aggregate architecture and on the spatial distribution of viruses attached to fully hydrated aggregates. Aggregates from the Danube River harbored up to 5.39 x 10(9) viruses cm(-3). We discuss the problems associated with different methods such as sonication or directly counting viruses on aggregates, both combined with epifluorescence microscopy and CLSM, to quantify viruses on suspended particles.

Image analysis software based on color segmentation for characterization of viability and physiological activity of biofilms

The novel image analysis software package bioImage_L was tested to calculate biofilm structural parameters in oral biofilms stained with dual-channel fluorescent markers. By identifying color tonalities in situ, the software independently processed the color subpopulations and characterized the viability and metabolic activity of biofilms.

Model system studies of the influence of bacterial biofilm formation on mineral surface reactivity

Biofilm development on mineral surfaces and related changes in surface reactivity were studied using batch and flow through experiments. An artificial groundwater was used as the primary nutrient medium, Pseudomonas aeruginosa (PAO1) was the model microbial organism and 'mineral' surfaces were kept as simple as possible by using glass or a polished quartz tile. Experiments were also completed with very low concentrations (100 mg l(-1)) of iron, Fe(2+ ), in the solution. In situ confocal laser scanning microscopy of developing colonies during the live growth phase, and of thick, mature biofilms, revealed only sporadic coverage of biofilm cells and associated polymers at the 'mineral-microbe interface'. Imaging and analysis of biofilm-conditioned surfaces doped with Fe(2+ )-rich solutions allowed the locus and form of Fe-rich mineral precipitation to be determined and show that biological surface components can cause mineral precipitation from dilute dissolved species which might otherwise remain in solution.

A two-step procedure for automatic and accurate segmentation of volumetric CLSM biofilm images

This paper presents a robust two-step segmentation procedure for the study of biofilm structure. Without user intervention, the procedure segments volumetric biofilm images generated by a confocal laser scanning microscopy (CLSM). This automated procedure implements an anisotropic diffusion filter as a preprocessing step and a 3D extension of the Otsu method for thresholding. Applying the anisotropic diffusion filter to even low-contrast CLSM images significantly improves the segmentation obtained with the 3D Otsu method. A comparison of the results for several CLSM data sets demonstrated that the accuracy of this procedure, unlike that of the objective threshold selection algorithm (OTS), is not affected by biofilm coverage levels and thus fills an important gap in developing a robust and objective segmenting procedure. The effectiveness of the present segmentation procedure is shown for CLSM images containing different bacterial strains. The image saturation handling capability of this procedure relaxes the constraints on user-selected gain and intensity settings of a CLSM. Therefore, this two-step procedure provides an automatic and accurate segmentation of biofilms that is independent of biofilm coverage levels and, in turn, lays a solid foundation for achieving objective analysis of biofilm structural parameters.

Automatic thresholding of three-dimensional microvascular structures from confocal microscopy images

We have combined confocal microscopy, image processing, and optimization techniques to obtain automated, accurate volumetric measurements of microvasculature. Initially, we made tissue phantoms containing 15-microm FocalCheck microspheres suspended in type I collagen. Using these phantoms we obtained a stack of confocal images and examined the accuracy of various thresholding schemes. Thresholding algorithms from the literature that utilize a unimodal histogram, a bimodal histogram, or an intensity and edge-based algorithm all significantly overestimated the volume of foreground structures in the image stack. Instead, we developed a heuristic technique to automatically determine good-quality threshold values based on the depth, intensity, and (optionally) gradient of each voxel. This method analyzed intensity and gradient threshold methods for each individual image stack, taking into account the intensity attenuation that is seen in deeper images of the stack. Finally, we generated a microvascular construct comprised of rat fat microvessel fragments embedded in collagen I gels and obtained stacks of confocal images. Using our new thresholding scheme we were able to obtain automatic volume measurements of growing microvessel fragments.

Toward automated analysis of biofilm architecture: bias caused by extraneous confocal laser scanning microscopy images

An increasing number of studies utilize confocal laser scanning microscopy (CLSM) for in situ visualization of biofilms and rely on the use of image analysis programs to extract quantitative descriptors of architecture. Recently, designed programs have begun incorporating procedures to automatically determine threshold values for three-dimensional CLSM image stacks. We have found that the automated threshold calculation is biased when a stack contains images lacking pixels of biological significance. Consequently, we have created the novel program Auto PHLIP-ML to resolve this bias by iteratively excluding extraneous images based on their area coverage of biomass. A procedure was developed to identify the optimal percent area coverage value used for extraneous image removal (PACVEIR). The optimal PACVEIR was defined to occur when the standard deviation of mean thickness, determined from replicate image stacks, was at a maximum, because it more accurately reflected inherent structural variation. Ten monoculture biofilms of either Ralstonia eutropha JMP228n::gfp or Acinetobacter sp. strain BD413 were tested to verify the routine. All biofilms exhibited an optimal PACVEIR between 0 and 1%. Prior to the exclusion of extraneous images, JMP228n::gfp appeared to develop more homogeneous biofilms than BD413. However, after the removal of extraneous images, JMP228n::gfp biofilms were found to form more heterogeneous biofilms. Similarly, JMP228n::gfp biofilms grown on glass surfaces vis-à-vis polyethylene membranes produced significantly different architectures after extraneous images had been removed but not when such images were included in threshold calculations. This study shows that the failure to remove extraneous images skewed a seemingly objective analysis of biofilm architecture and significantly altered statistically derived conclusions.

Analysis of a marine phototrophic biofilm by confocal laser scanning microscopy using the new image quantification software PHLIP

Background

Confocal laser scanning microscopy (CLSM) is the method of choice to study interfacial biofilms and acquires time-resolved three-dimensional data of the biofilm structure. CLSM can be used in a multi-channel modus where the different channels map individual biofilm components. This communication presents a novel image quantification tool, PHLIP, for the quantitative analysis of large amounts of multichannel CLSM data in an automated way. PHLIP can be freely downloaded from

Results

PHLIP is an open source public license Matlab toolbox that includes functions for CLSM imaging data handling and ten image analysis operations describing various aspects of biofilm morphology. The use of PHLIP is here demonstrated by a study of the development of a natural marine phototrophic biofilm. It is shown how the examination of the individual biofilm components using the multi-channel capability of PHLIP allowed the description of the dynamic spatial and temporal separation of diatoms, bacteria and organic and inorganic matter during the shift from a bacteria-dominated to a diatom-dominated phototrophic biofilm. Reflection images and weight measurements complementing the PHLIP analyses suggest that a large part of the biofilm mass consisted of inorganic mineral material.

Conclusion

The presented case study reveals new insight into the temporal development of a phototrophic biofilm where multi-channel imaging allowed to parallel monitor the dynamics of the individual biofilm components over time. This application of PHLIP presents the power of biofilm image analysis by multi-channel CLSM software and demonstrates the importance of PHLIP for the scientific community as a flexible and extendable image analysis platform for automated image processing.

Three-dimensional biofilm structure quantification

Quantitative parameters describing biofilm physical structure have been extracted from three-dimensional confocal laser scanning microscopy images and used to compare biofilm structures, monitor biofilm development, and quantify environmental factors affecting biofilm structure. Researchers have previously used biovolume, volume to surface ratio, roughness coefficient, and mean and maximum thicknesses to compare biofilm structures. The selection of these parameters is dependent on the availability of software to perform calculations. We believe it is necessary to develop more comprehensive parameters to describe heterogeneous biofilm morphology in three dimensions. This research presents parameters describing three-dimensional biofilm heterogeneity, size, and morphology of biomass calculated from confocal laser scanning microscopy images. This study extends previous work which extracted quantitative parameters regarding morphological features from two-dimensional biofilm images to three-dimensional biofilm images. We describe two types of parameters: (1) textural parameters showing microscale heterogeneity of biofilms and (2) volumetric parameters describing size and morphology of biomass. The three-dimensional features presented are average (ADD) and maximum diffusion distances (MDD), fractal dimension, average run lengths (in X, Y and Z directions), aspect ratio, textural entropy, energy and homogeneity. We discuss the meaning of each parameter and present the calculations in detail. The developed algorithms, including automatic thresholding, are implemented in software as MATLAB programs which will be available at site prior to publication of the paper.

Quantifying biofilm structure: facts and fiction

There is no doubt among biofilm researchers that biofilm structure is important to many biofilm processes, such as the transport of nutrients to deeper layers of the biofilm. However, biofilm structure is an elusive term understood only qualitatively, and as such it cannot be directly correlated with any measurable parameters characterizing biofilm performance. To correlate biofilm structure with the parameters characterizing biofilm performance, such as the rate of nutrient transport within the space occupied by the biofilms, biofilm structure must first be quantified and expressed numerically on an appropriate scale. The task of extracting numerical parameters quantifying biofilm structure relies on using biofilm imaging and image analysis. Although defining parameters characterizing biofilm structure is relatively straightforward, and multiple parameters have been described in the computer science literature, interpreting the results of such analyses is not trivial. Existing computer software developed by several research groups, including ours, for the sole purpose of analyzing biofilm images helps quantify parameters from biofilm images but does nothing to help interpret the results of such analyses. Although computing structural parameters from biofilm images permits correlating biofilm structure with other biofilm processes, the meaning of the results is not obvious. The first step to understanding the quantification of biofilm structure, developing image analysis, methods to quantify information from biofilm images, has been made by several research groups. The next step is to explain the meaning of these analyses. This presentation explains the meaning of several parameters commonly used to characterize biofilm structure. It also reviews the authors' research and experience in quantifying biofilm structure and their attempts to quantitatively relate biofilm structure to fundamental biofilm processes.

Autoinducer 2 production by Streptococcus gordonii DL1 and the biofilm phenotype of a luxS mutant are influenced by nutritional conditions

The luxS gene, present in many bacterial genera, encodes the autoinducer 2 (AI-2) synthase. AI-2 has been implicated in bacterial signaling, and this study investigated its role in biofilm formation by Streptococcus gordonii, an organism that colonizes human tooth enamel within the first few hours after professional cleaning. Northern blotting and primer extension analyses revealed that S. gordonii luxS is monocistronic. AI-2 production was dependent on nutritional conditions, and maximum AI-2 induction was detected when S. gordonii was grown in the presence of serum and carbonate. In planktonic cultures, AI-2 production rose sharply during the transition from exponential to stationary phase, and the AI-2 concentration peaked approximately 4 h into stationary phase. An S. gordonii luxS mutant that did not produce AI-2 was constructed by homologous recombination. Complementation of the mutant by insertion of an intact luxS gene into the chromosome in tandem with the disrupted gene restored AI-2 production to a level similar to that of the wild-type strain. In planktonic culture, no growth differences were observed between the mutant and wild-type strains when five different media were used. However, when grown for 4 h as biofilms in 25% human saliva under flow, the luxS mutant formed tall microcolonies that differed from those formed by the wild-type and complemented mutant strains. Biofilms of the luxS mutant exhibited finger-like projections of cells that extended into the flow cell lumen. Thus, the inability to produce AI-2 is associated with altered microcolony architecture within S. gordonii biofilms formed in saliva during a time frame consistent with initial colonization of freshly cleaned enamel surfaces.

Assessing technician effects when extracting quantities from microscope images

Consider an experiment where the response is based on an image; e.g., an image captured to a computer file by a digital camera mounted on a microscope. Suppose relevant quantitative measures are extracted from the images so that results can be analyzed by conventional statistical methods. The steps involved in extracting the measures may require that the technicians, who are processing the images, perform some subjective manipulations. In this case, it is important to determine the bias and variability, if any, attributable to the technicians' decisions. This paper describes the experimental design and statistical analyses that are useful for those determinations. The design and analysis are illustrated by application to two biofilm research projects that involved quantitative image analysis. In one investigation, the technician was required to choose a threshold level, then the image analysis program automatically extracted relevant measures from the resulting black and white image. In the other investigation, the technician was required to choose fiducial points in each of two images collected on different microscopes; then the image analysis program registered the images by stretching, rotating, and overlaying them, so that their quantitative features could be correlated. These investigations elucidated the effects of the technicians' decisions, thereby helping us to assess properly the statistical uncertainties in the conclusions for the primary experiments.

Modern scientific methods and their potential in wastewater science and technology

Application of novel analytical and investigative methods such as fluorescence in situ hybridization, confocal laser scanning microscopy (CLSM), microelectrodes and advanced numerical simulation has led to new insights into micro- and macroscopic processes in bioreactors. However, the question is still open whether or not these new findings and the subsequent gain of knowledge are of significant practical relevance and if so, where and how. To find suitable answers it is necessary for engineers to know what can be expected by applying these modern analytical tools. Similarly, scientists could benefit significantly from an intensive dialogue with engineers in order to find out about practical problems and conditions existing in wastewater treatment systems. In this paper, an attempt is made to help bridge the gap between science and engineering in biological wastewater treatment. We provide an overview of recently developed methods in microbiology and in mathematical modeling and numerical simulation. A questionnaire is presented which may help generate a platform from which further technical and scientific developments can be accomplished. Both the paper and the questionnaire are aimed at encouraging scientists and engineers to enter into an intensive, mutually beneficial dialogue.