On the nucleation and growth of amyloid beta-protein fibrils: detection of nuclei and quantitation of rate constants.

We have studied the fibrillogenesis of synthetic amyloid beta-protein-(1-40) fragment (A beta) in 0.1 M HCl. At low pH, A beta formed fibrils at a rate amenable to detailed monitoring by quasi-elastic light-scattering spectroscopy. Examination of the fibrils with circular dichroism spectroscopy and electron microscopy showed them to be highly similar to those found in amyloid plaques. We determined the hydrodynamic radii of A beta aggregates during the entire process of fibril nucleation and growth. Above an A beta concentration of approximately 0.1 mM, the initial rate of elongation and the final size of fibrils were independent of A beta concentration. Below an A beta concentration of 0.1 mM, the initial elongation rate was proportional to the peptide concentration, and the resulting fibrils were significantly longer than those formed at higher concentration. We also found that the surfactant n-dodecylhexaoxyethylene glycol monoether (C12E6) slowed nucleation and elongation of fibrils in a concentration-dependent manner. Our observations are consistent with a model of A beta fibrillogenesis that includes the following key steps: (i) peptide micelles form above a certain critical A beta concentration, (ii) fibrils nucleate within these micelles or on heterogeneous nuclei (seeds), and (iii) fibrils grow by irreversible binding of monomers to fibril ends. Interpretation of our data enabled us to determine the sizes of fibril nuclei and A beta micelles and the rates of fibril nucleation (from micelles) and fibril elongation. Our approach provides a powerful means for the quantitative assay of A beta fibrillogenesis.

Early p53 alterations in mouse skin carcinogenesis by UVB radiation: immunohistochemical detection of mutant p53 protein in clusters of preneoplastic epidermal cells.

High levels of the p53 protein are immunohistochemically detectable in a majority of human nonmelanoma skin cancers and UVB-induced murine skin tumors. These increased protein levels are often associated with mutations in the conserved domains of the p53 gene. To investigate the timing of the p53 alterations in the process of UVB carcinogenesis, we used a well defined murine model (SKH:HR1 hairless mice) in which the time that tumors appear is predictable from the UVB exposures. The mice were subjected to a series of daily UVB exposures, either for 17 days or for 30 days, which would cause skin tumors to appear around 80 or 30 weeks, respectively. In the epidermis of these mice, we detected clusters of cells showing a strong immunostaining of the p53 protein, as measured with the CM-5 polyclonal antiserum. This cannot be explained by transient accumulation of the normal p53 protein as a physiological response to UVB-induced DNA damage. In single exposure experiments the observed transient CM-5 immunoreactivity lasted for only 3 days and was not clustered, whereas these clusters were still detectable as long as 56 days after 17 days of UVB exposure. In addition, approximately 70% of these patches reacted with the mutant-specific monoclonal antibody PAb240, whereas transiently induced p53-positive cells did not. In line with indicative human data, these experimental results in the hairless mouse model unambiguously demonstrate that constitutive p53 alterations are causally related to chronic UVB exposure and that they are a very early event in the induction of skin cancer by UVB radiation.

Infrared microspectroscopy of inflammatory process and colon tumors.

According to the last global burden of disease published by the World Health Organization, tumors were the third leading cause of death worldwide in 2004. Among the different types of tumors, colorectal cancer ranks as the fourth most lethal. To date, tumor diagnosis is based mainly on the identification of morphological changes in tissues. Considering that these changes appears after many biochemical reactions, the development of vibrational techniques may contribute to the early detection of tumors, since they are able to detect such reactions. The present study aimed to develop a methodology based on infrared microspectroscopy to characterize colon samples, providing complementary information to the pathologist and facilitating the early diagnosis of tumors. The study groups were composed by human colon samples obtained from paraffin-embedded biopsies. The groups are divided in normal (n=20), inflammation (n=17) and tumor (n=18). Two adjacent slices were acquired from each block. The first one was subjected to chemical dewaxing and H&E staining. The infrared imaging was performed on the second slice, which was not dewaxed or stained. A computational preprocessing methodology was employed to identify the paraffin in the images and to perform spectral baseline correction. Such methodology was adapted to include two types of spectral quality control. Afterwards the preprocessing step, spectra belonging to the same image were analyzed and grouped according to their biochemical similarities. One pathologist associated each obtained group with some histological structure based on the H&E stained slice. Such analysis highlighted the biochemical differences between the three studied groups. Results showed that severe inflammation presents biochemical features similar to the tumors ones, indicating that tumors can develop from inflammatory process. A spectral database was constructed containing the biochemical information identified in the previous step. Spectra obtained from new samples were confronted with the database information, leading to their classification into one of the three groups: normal, inflammation or tumor. Internal and external validation were performed based on the classification sensitivity, specificity and accuracy. Comparison between the classification results and H&E stained sections revealed some discrepancies. Some regions histologically normal were identified as inflammation by the classification algorithm. Similarly, some regions presenting inflammatory lesions in the stained section were classified into the tumor group. Such differences were considered as misclassification, but they may actually evidence that biochemical changes are in course in the analyzed sample. In the latter case, the method developed throughout this thesis would have proved able to identify early stages of inflammatory and tumor lesions. It is necessary to perform additional experiments to elucidate this discrepancy between the classification results and the morphological features. One solution would be the use of immunohistochemistry techniques with specific markers for tumor and inflammation. Another option includes the recovering of the medical records of patients who participated in this study in order to check, in later times to the biopsy collection, whether they actually developed the lesions supposedly detected in this research.

Detection and mapping of burnt areas from time series of MODIS-derived NDVI data in a Mediterranean region

Moderate resolution remote sensing data, as provided by MODIS, can be used to detect and map active or past wildfires from daily records of suitable combinations of reflectance bands. The objective of the present work was to develop and test simple algorithms and variations for automatic or semiautomatic detection of burnt areas from time series data of MODIS biweekly vegetation indices for a Mediterranean region. MODIS-derived NDVI 250m time series data for the Valencia region, East Spain, were subjected to a two-step process for the detection of candidate burnt areas, and the results compared with available fire event records from the Valencia Regional Government. For each pixel and date in the data series, a model was fitted to both the previous and posterior time series data. Combining drops between two consecutive points and 1-year average drops, we used discrepancies or jumps between the pre and post models to identify seed pixels, and then delimitated fire scars for each potential wildfire using an extension algorithm from the seed pixels. The resulting maps of the detected burnt areas showed a very good agreement with the perimeters registered in the database of fire records used as reference. Overall accuracies and indices of agreement were very high, and omission and commission errors were similar or lower than in previous studies that used automatic or semiautomatic fire scar detection based on remote sensing. This supports the effectiveness of the method for detecting and mapping burnt areas in the Mediterranean region.

Algorithm for the detection of outliers based on the theory of rough sets

Outliers are objects that show abnormal behavior with respect to their context or that have unexpected values in some of their parameters. In decision-making processes, information quality is of the utmost importance. In specific applications, an outlying data element may represent an important deviation in a production process or a damaged sensor. Therefore, the ability to detect these elements could make the difference between making a correct and an incorrect decision. This task is complicated by the large sizes of typical databases. Due to their importance in search processes in large volumes of data, researchers pay special attention to the development of efficient outlier detection techniques. This article presents a computationally efficient algorithm for the detection of outliers in large volumes of information. This proposal is based on an extension of the mathematical framework upon which the basic theory of detection of outliers, founded on Rough Set Theory, has been constructed. From this starting point, current problems are analyzed; a detection method is proposed, along with a computational algorithm that allows the performance of outlier detection tasks with an almost-linear complexity. To illustrate its viability, the results of the application of the outlier-detection algorithm to the concrete example of a large database are presented.

Detection of differentially expressed genes in synovial fibroblasts by restriction fragment differential display

Objective. To identify differentially expressed genes in synovial fibroblasts and examine the effect on gene expression of exposure to TNF-alpha and IL-1beta. Methods. Restriction fragment differential display was used to isolate genes using degenerate primers complementary to the lysophosphatidic acid acyl transferase gene family. Differential gene expression was confirmed by reverse transcription-polymerase chain reaction and immunohistochemistry using a variety of synovial fibroblasts, including cells from patients with osteoarthritis and self-limiting parvovirus arthritis. Results. Irrespective of disease process, synovial fibroblasts constitutively produced higher levels of IL-6 and monocyte chemoattractant protein 1 (MCP-1) (CCL2) than skin fibroblasts. Seven genes were differentially expressed in synovial fibroblasts compared with skin fibroblasts. Of these genes, four [tissue factor pathway inhibitor 2 (TFPI2), growth regulatory oncogene beta (GRObeta), manganese superoxide dismutase (MnSOD) and granulocyte chemotactic protein 2 (GCP-2)] were all found to be constitutively overexpressed in synoviocytes derived from patients with osteoarthritis. These four genes were only weakly expressed in other synovial fibroblasts (rheumatoid and self-limiting parvovirus infection). However, expression in all types of fibroblasts was increased after stimulation with TNF-alpha and IL-1beta. Three other genes (aggrecan, biglycan and caldesmon) were expressed at higher levels in all types of synovial fibroblasts compared with skin fibroblasts even after stimulation with TNF-alpha and IL-1. Conclusions. Seven genes have been identified with differential expression patterns in terms of disease process (osteoarthritis vs rheumatoid arthritis), state of activation (resting vs cytokine activation) and anatomical location (synovium vs skin). Four of these genes, TFPI2, GRObeta (CXCL2), MnSOD and GCP-2 (CXCL6), were selectively overexpressed in osteoarthritis fibroblasts rather than rheumatoid fibroblasts. While these differences may represent differential behaviour of synovial fibroblasts in in vitro culture, these observations suggest that TFPI2, GRObeta (CXCL2), MnSOD and GCP-2 (CXCL6) may represent new targets for treatments specifically tailored to osteoarthritis.

A simplified PCR test for early detection of dwarf off-types in micropropagated Cavendish bananas (Musa spp. AAA)

The dwarf somaclonal variant is a major problem affecting micropropagation of the banana cultivar Williams (Musa spp. AAA; subgroup Cavendish). This problem arises from genetic changes that occur during the tissue culture process. Early identification of this problem is difficult and propagators must wait until plants are ex vitro in order to visualise the dwarfism phenotype. In this study, we have improved a SCAR-based molecular diagnostic technique, developed by Damasco et al. [Acta Hortic. 461 (1997) 157], for the early identification of dwarf off-types. We have included a positive internal control in a multiplex PCR and adapted the technique for use with small amounts of fresh in vitro leaf material as PCR template. The control product is a 500 bp fragment from 18S rRNA and is amplified in all tissues irrespective of phenotype. The use of small in vitro leaf material removing the need for genomic DNA extraction. (C) 2004 Elsevier B.V. All rights reserved.

The influence of memory for prior instances on performance in a conflict detection task

In 3 experiments, the authors examined the role of memory for prior instances for making relative judgments in conflict detection. Participants saw pairs of aircraft either repeatedly conflict with each other or pass safely before being tested on new aircraft pairs, which varied in similarity to the training pairs. Performance was influenced by the similarity between aircraft pairs. Detection time was faster when a conflict pair resembled a pair that had repeatedly conflicted. Detection time was slower, and participants missed conflicts, when a conflict pair resembled a pair that had repeatedly passed safely. The findings identify aircraft features that are used as inputs into the memory decision process and provide an indication of the processes involved in the use of memory for prior instances to make relative judgments.

Collagen in the scarless fetal skin wound: Detection with Picrosirius-polarization

Our group has developed an ovine model of deep dermal, partial-thickness burn where the fetus heals scarlessly and the lamb heals with scar. The comparison of collagen structure between these two different mechanisms of healing may elucidate the process of scarless wound healing. Picrosirius staining followed by polarized light microscopy was used to visualize collagen fibers, with digital capture and analysis. Collagen deposition increased with fetal age and the fibers became thicker, changing from green (type III collagen) to yellow/red (type I collagen). The ratio of type III collagen to type I was high in the fetus (166), whereas the lamb had a much lower ratio (0.2). After burn, the ratios of type III to type I collagen did not differ from those in control skin for either fetus or lamb. The fetal tissue maintained normal tissue architecture after burn while the lamb tissue showed irregular collagen organization. In conclusion, the type or amount of collagen does not alter significantly after injury. Tissue architecture differed between fetal and lamb tissue, suggesting that scar development is related to collagen cross-linking or arrangement. This study indicates that healing in the scarless fetal wound is representative of the normal fetal growth pattern, rather than a response to burn injury.

Frequency band selection of radars for buried object detection

Choice of the operational frequency is one of the most responsible parts of any radar design process. Parameters of radars for buried object detection (BOD) are very sensitive to both carrier frequency and ranging signal bandwidth. Such radars have a specific propagation environment with a strong frequency-dependent attenuation and, as a result, short operational range. This fact dictates some features of the radar's parameters: wideband signal-to provide a high range resolution (fractions of a meter) and a low carrier frequency (tens or hundreds megahertz) for deeper penetration. The requirement to have a wideband ranging signal and low carrier frequency are partly in contradiction. As a result, low-frequency (LF) ultrawide-band (UWB) signals are used. The major goal of this paper is to examine the influence of the frequency band choice on the radar performance and develop relevant methodologies for BOD radar design and optimization. In this article, high-efficient continuous wave (CW) signals with most advanced stepped frequency (SF) modulation are considered; however, the main conclusions can be applied to any kind of ranging signals.

Evaluation of a method for fusing LIDAR data and multispectral images for building detection

In this paper, we describe the evaluation of a method for building detection by the Dempster-Shafer fusion of LIDAR data and multispectral images. For that purpose, ground truth was digitised for two test sites with quite different characteristics. Using these data sets, the heuristic model for the probability mass assignments of the method is validated, and rules for the tuning of the parameters of this model are discussed. Further we evaluate the contributions of the individual cues used in the classification process to the quality of the classification results. Our results show the degree to which the overall correctness of the results can be improved by fusing LIDAR data with multispectral images.

Hazard detection in older adult drivers

Older adults make up an increasing propordon of automobile drivers in Australia. Despite the fact that older drivers generally drive much less than younger drivers, there is a disdnct increase in accidents, fatalides and injuries in drivers over age 65 (per actual kilometres driven). Accurate means of screening older adults to idendfy those at increased risk of motor vehicle accidents have proved elusive. Neuropsychological assessment and clinical examinadon are not well-correlated with accident risk. On-road tesdng, which is more highly correlated with accident risk, is expensive and dme-consuming, as well as being less suitable as a screening process. Hazard percepdon methods have been used as an effecdve screening method for idendfying younger adults at increased risk of accidents. A brief video-based hazard percepdon screening test involving footage of genuine traffic hazards for use on older individuals will be presented.

Semi-global techniques in image matching and change detection with applications to civil and environmental engineering.

This work of thesis wants to present a dissertation of the wide range of modern dense matching algorithms, which are spreading in different application and research fields, with a particular attention to the innovative “Semi-Global” matching techniques. The choice of develop a semi-global numerical code was justified by the need of getting insight on the variables and strategies that affect the algorithm performances with the primary objective of maximizing the method accuracy and efficiency, and the results level of completeness. The dissertation will consist in the metrological characterization of the proprietary implementation of the semi-global matching algorithm, evaluating the influence of several matching variables and functions implemented in the process and comparing the accuracy and completeness of different results (digital surface models, disparity maps and 2D displacement fields) obtained using our code and other commercial and open-source matching programs in a wide variety of application fields.

Outlier detection with partial information:Application to emergency mapping

This paper, addresses the problem of novelty detection in the case that the observed data is a mixture of a known 'background' process contaminated with an unknown other process, which generates the outliers, or novel observations. The framework we describe here is quite general, employing univariate classification with incomplete information, based on knowledge of the distribution (the 'probability density function', 'pdf') of the data generated by the 'background' process. The relative proportion of this 'background' component (the 'prior' 'background' 'probability), the 'pdf' and the 'prior' probabilities of all other components are all assumed unknown. The main contribution is a new classification scheme that identifies the maximum proportion of observed data following the known 'background' distribution. The method exploits the Kolmogorov-Smirnov test to estimate the proportions, and afterwards data are Bayes optimally separated. Results, demonstrated with synthetic data, show that this approach can produce more reliable results than a standard novelty detection scheme. The classification algorithm is then applied to the problem of identifying outliers in the SIC2004 data set, in order to detect the radioactive release simulated in the 'oker' data set. We propose this method as a reliable means of novelty detection in the emergency situation which can also be used to identify outliers prior to the application of a more general automatic mapping algorithm. © Springer-Verlag 2007.