Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

Monitoring growth in rapidly urbanizing areas using remotely sensed data

Urbanization and the ability to manage for a sustainable future present numerous challenges for geographers and planners in metropolitan regions. Remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their change over time, at various spatial and temporal scales. Data models for establishing the range of urban land cover types and their biophysical composition (vegetation, soil, and impervious surfaces) are integrated to provide a hierarchical approach to classifying land cover within urban environments. These data also provide an essential component for current simulation models of urban growth patterns, as both calibration and validation data. The first stages of the approach have been applied to examine urban growth between 1988 and 1995 for a rapidly developing area in southeast Queensland, Australia. Landsat Thematic Mapper image data provided accurate (83% adjusted overall accuracy) classification of broad land cover types and their change over time. The combination of commonly available remotely sensed data, image processing methods, and emerging urban growth models highlights an important application for current and next generation moderate spatial resolution image data in studies of urban environments.

Global changes in gene expression observed at the transition from growth to stationary phase in Listeria monocytogenes ScottA batch culture

Listeria monocytogenes is a food-borne Gram-positive bacterium that is responsible for a variety of infections (worldwide) annually. The organism is able to survive a variety of environmental conditions and stresses, however, the mechanisms by which L. monocytogenes adapts to environmental change are yet to be fully elucidated. An understanding of the mechanism(s) by which L. monocytogenes survives unfavourable environmental conditions will aid in developing new food processing methods to control the organism in foodstuffs. We have utilized a proteomic approach to investigate the response of L. monocytogenes batch cultures to the transition from exponential to stationary growth phase. Proteomic analysis showed that batch cultures of L. monocytogenes perceived stress and began preparations for stationary phase much earlier (approximately A(600) = 0.75, mid-exponential) than predicted by growth characteristics alone. Global analysis of the proteome revealed that the expression levels of more than 50% of all proteins observed changed significantly over a 7-9 h period during this transition phase. We have highlighted ten proteins in particular whose expression levels appear to be important in the early onset of the stationary phase. The significance of these findings in terms of functionality and the mechanistic picture are discussed.

The mismatch negativity (MMN) response to complex tones and spoken words in individuals with aphasia

Background: The mismatch negativity (MMN) is a fronto-centrally distributed event-related potential (ERP) that is elicited by any discriminable auditory change. It is an ideal neurophysiological tool for measuring the auditory processing skills of individuals with aphasia because it can be elicited even in the absence of attention. Previous MMN studies have shown that acoustic processing of tone or pitch deviance is relatively preserved in aphasia, whereas the basic acoustic processing of speech stimuli can be impaired (e.g., auditory discrimination). However, no MMN study has yet investigated the higher levels of auditory processing, such as language-specific phonological and/or lexical processing, in individuals with aphasia. Aims: The aim of the current study was to investigate the MMN response of normal and language-disordered subjects to tone stimuli and speech stimuli that incorporate the basic auditory processing (acoustic, acoustic-phonetic) levels of non-speech and speech sound processing, and also the language-specific phonological and lexical levels of spoken word processing. Furthermore, this study aimed to correlate the aphasic MMN data with language performance on a variety of tasks specifically targeted at the different levels of spoken word processing. Methods M Procedures: Six adults with aphasia (71.7 years +/- 3.0) and six healthy age-, gender-, and education-matched controls (72.2 years +/- 5.4) participated in the study. All subjects were right-handed and native speakers of English. Each subject was presented with complex harmonic tone stimuli, differing in pitch or duration, and consonant-vowel (CV) speech stimuli (non-word /de:/versus real world/deI/). The probability of the deviant for each tone or speech contrast was 10%. The subjects were also presented with the same stimuli in behavioural discrimination tasks, and were administered a language assessment battery to measure their auditory comprehension skills. Outcomes O Results: The aphasic subjects demonstrated attenuated MMN responses to complex tone duration deviance and to speech stimuli (words and non-words), and their responses to the frequency, duration, and real word deviant stimuli were found to strongly correlate with performance on the auditory comprehension section of the Western Aphasia Battery (WAB). Furthermore, deficits in attentional lexical decision skills demonstrated by the aphasic subjects correlated with a word-related enhancement demonstrated during the automatic MMN paradigm, providing evidence to support the word advantage effect, thought to reflect the activation of language-specific memory traces in the brain for words. Conclusions: These results indicate that the MMN may be used as a technique for investigating general and more specific auditory comprehension skills of individuals with aphasia, using speech and/or non-speech stimuli, independent of the individual's attention. The combined use of the objective MMN technique and current clinical language assessments may result in improved rehabilitative management of aphasic individuals.

Seeing red: the use of Congo Red dye to identify cooked and damaged starch grains in archaeological residues

Starchy plant foods are significant in the diet of almost all peoples. Archaeologically, however, preservation of such plants is limited, and direct evidence of plant use by past people is also rare. Although starch grains can be preserved on artefacts used to process starchy plants, it is very difficult to identify grains damaged by processing methods such as milling or cooking. We present a method for identifying such damaged starch grains using Congo Red staining to identify cooking or milling activities in the past subsistence behaviour of Aboriginal people of southeast Queensland, Australia. (c) 2005 Elsevier Ltd. All rights reserved.

Monitoring changes in nisin susceptibility of Listeria monocytogenes Scott A as an indicator of growth phase using FACS

Listeria monocytogenes has previously been shown to adapt to a wide variety of environmental niches, principally those associated with low pH, and this compromises its control in food environments. An understanding of the mechanism(s) by which L. monocytogenes survives unfavourable environmental conditions will aid in developing new food processing methods to control the organism in foodstuffs. The present Study aimed to gain a further understanding of the physiological basis for the differential effects of one control strategy, namely the use of the lantibiotic nisin. Using propidium iodide (PI) to probe membrane integrity it was shown that L. monocytogenes Scott A was sensitive to nisin (8 ng mL(-1)) but this was growth phase dependent with stationary phase cells (OD600=1.2) being much more resistant than exponential phase cells (OD600=0.38). We demonstrate that, using a combination of techniques including fluorescence activated cell sorting (FACS), the membrane adaptations underpinning nisin resistance are triggered much earlier (OD600 < 0.5) than the onset of stationary phase. The significance of these findings in terms of mechanism and application are discussed. (c) 2005 Elsevier B.V.All rights reserved.

Mathematical Morphology: Star/Galaxy Differentiation & Galaxy Morphology Classication

We present an application of Mathematical Morphology (MM) for the classification of astronomical objects, both for star/galaxy differentiation and galaxy morphology classification. We demonstrate that, for CCD images, 99.3 +/- 3.8% of galaxies can be separated from stars using MM, with 19.4 +/- 7.9% of the stars being misclassified. We demonstrate that, for photographic plate images, the number of galaxies correctly separated from the stars can be increased using our MM diffraction spike tool, which allows 51.0 +/- 6.0% of the high-brightness galaxies that are inseparable in current techniques to be correctly classified, with only 1.4 +/- 0.5% of the high-brightness stars contaminating the population. We demonstrate that elliptical (E) and late-type spiral (Sc-Sd) galaxies can be classified using MM with an accuracy of 91.4 +/- 7.8%. It is a method involving fewer 'free parameters' than current techniques, especially automated machine learning algorithms. The limitation of MM galaxy morphology classification based on seeing and distance is also presented. We examine various star/galaxy differentiation and galaxy morphology classification techniques commonly used today, and show that our MM techniques compare very favourably.

Improvements in the data partitioning approach for frequent itemsets mining

Frequent Itemsets mining is well explored for various data types, and its computational complexity is well understood. There are methods to deal effectively with computational problems. This paper shows another approach to further performance enhancements of frequent items sets computation. We have made a series of observations that led us to inventing data pre-processing methods such that the final step of the Partition algorithm, where a combination of all local candidate sets must be processed, is executed on substantially smaller input data. The paper shows results from several experiments that confirmed our general and formally presented observations.

Data partitioning for parallel spatial join processing

The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. We show in this paper that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.

Combined in-fermenter extraction and cross-flow microfiltration for improved inclusion body processing

In this study we demonstrate a new in-fermenter chemical extraction procedure that degrades the cell wall of Escherichia coli and releases inclusion bodies (IBs) into the fermentation medium. We then prove that cross-flow microfiltration can be used to remove 91% of soluble contaminants from the released IBs. The extraction protocol, based on a combination of Triton X-100, EDTA, and intracellular T7 lysozyme, effectively released most of the intracellular soluble content without solubilising the IBs. Cross-flow microfiltration using a 0.2 mum ceramic membrane successfully recovered the granulocyte macrophagecolony stimulating factor (GM-CSF) IBs with removal of 91% of the soluble contaminants and virtually no loss of IBs to the permeate. The filtration efficiency, in terms of both flux and transmission, was significantly enhanced by infermenter Benzonase(R) digestion of nucleic acids following chemical extraction. Both the extraction and filtration methods exerted their efficacy directly on a crude fermentation broth, eliminating the need for cell recovery and re-suspension in buffer. The processes demonstrated here can all be performed using just a fermenter and a single cross-flow filtration unit, demonstrating a high level of process intensification. Furthermore, there is considerable scope to also use the microfiltration system to subsequently solubilise the IBs, to separate the denatured protein from cell debris, and to refold the protein using diafiltration. In this way refolded protein can potentially be obtained, in a relatively pure state, using only two unit operations. (C) 2004 Wiley Periodicals Inc.

Virtual models of the HLA class I antigen processing pathway

Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.

Special issue on methods and learning in functional MRI: Introductory remarks

This special issue represents a further exploration of some issues raised at a symposium entitled “Functional magnetic resonance imaging: From methods to madness” presented during the 15th annual Theoretical and Experimental Neuropsychology (TENNET XV) meeting in Montreal, Canada in June, 2004. The special issue’s theme is methods and learning in functional magnetic resonance imaging (fMRI), and it comprises 6 articles (3 reviews and 3 empirical studies). The first (Amaro and Barker) provides a beginners guide to fMRI and the BOLD effect (perhaps an alternative title might have been “fMRI for dummies”). While fMRI is now commonplace, there are still researchers who have yet to employ it as an experimental method and need some basic questions answered before they venture into new territory. This article should serve them well. A key issue of interest at the symposium was how fMRI could be used to elucidate cerebral mechanisms responsible for new learning. The next 4 articles address this directly, with the first (Little and Thulborn) an overview of data from fMRI studies of category-learning, and the second from the same laboratory (Little, Shin, Siscol, and Thulborn) an empirical investigation of changes in brain activity occurring across different stages of learning. While a role for medial temporal lobe (MTL) structures in episodic memory encoding has been acknowledged for some time, the different experimental tasks and stimuli employed across neuroimaging studies have not surprisingly produced conflicting data in terms of the precise subregion(s) involved. The next paper (Parsons, Haut, Lemieux, Moran, and Leach) addresses this by examining effects of stimulus modality during verbal memory encoding. Typically, BOLD fMRI studies of learning are conducted over short time scales, however, the fourth paper in this series (Olson, Rao, Moore, Wang, Detre, and Aguirre) describes an empirical investigation of learning occurring over a longer than usual period, achieving this by employing a relatively novel technique called perfusion fMRI. This technique shows considerable promise for future studies. The final article in this special issue (de Zubicaray) represents a departure from the more familiar cognitive neuroscience applications of fMRI, instead describing how neuroimaging studies might be conducted to both inform and constrain information processing models of cognition.

A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography

Little consensus exists in the literature regarding methods for determination of the onset of electromyographic (EMG) activity. The aim of this study was to compare the relative accuracy of a range of computer-based techniques with respect to EMG onset determined visually by an experienced examiner. Twenty-seven methods were compared which varied in terms of EMG processing (low pass filtering at 10, 50 and 500 Hz), threshold value (1, 2 and 3 SD beyond mean of baseline activity) and the number of samples for which the mean must exceed the defined threshold (20, 50 and 100 ms). Three hundred randomly selected trials of a postural task were evaluated using each technique. The visual determination of EMG onset was found to be highly repeatable between days. Linear regression equations were calculated for the values selected by each computer method which indicated that the onset values selected by the majority of the parameter combinations deviated significantly from the visually derived onset values. Several methods accurately selected the time of onset of EMG activity and are recommended for future use. Copyright (C) 1996 Elsevier Science Ireland Ltd.