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PubMed1997

Evidence-Based Pattern Classification: A Structural Approach to Human Perceptual Learning and Generalization

Models of human pattern classification have been traditionally based on implicit pattern descriptions which involve lists of continuous attribute values or discrete features. Here we propose an alternative approach which makes explicit use of pattern structure in terms of components and their unary (part-specific) and binary (part-relational) properties. Such attributes "evidence" different classes of patterns and allow one to model processes of both perceptual learning and generalization to novel instances. An object in an evidence-based system is represented by a set of rules, where each rule provides a certain amount of class-specific evidence. The accumulated class evidence over all activated rules determines the classification probability. We have examined how well this concept reflects human performance by training observers to classify compound Gabor patterns and then testing them with segmented (grey-level-transformed) versions of the patterns in the original training set. If the observers were to construct rules to define each pattern class in terms of perceived parts and their relations, then it should be expected that classification performance would generalize to these new patterns. Results confirm this hypothesis and the specific feature extraction, learning, and rule generation model used to predict performance. Copyright 1997 Academic Press

Journal Article↗

PubMed2005

Toxicogenomic analysis methods for predictive toxicology.

Toxicogenomics, the application of genomic data to elucidate or predict an organism's response to a toxicant, can inform the drug development process in important ways. It is apparent that standardized approaches to many types of toxicogenomic questions are still being formulated. Specifically, a significant body of proof of principle studies has emerged that demonstrates a range of statistical methodologies applied to predictive toxicology. These studies rely on class prediction methods--mathematical models generated using the gene expression profiles of known toxins from representative toxicological classes--to predict the toxicological effect of a compound based on the similarities between its gene expression profile and the profiles of a given toxicological class. Class prediction methods hold promise for increasing the rate at which compounds can be evaluated for toxicity early in the drug discovery process, while at the same time reducing the length of toxicological studies and their associated costs. Class prediction methods are informed by class comparison and class discovery steps, which inform, respectively, the selection of genes whose response can be used to distinguish among the toxicological classes and the number of classes distinguishable using the response of these genes. Together these steps use a variety of complementary statistical techniques to achieve a successful class prediction model. This report attempts to review some of the themes that appear to be emerging in the application of these techniques to predictive toxicology methods over toxicogenomics' short history.

Animals↗

PubMedDate not supplied

Structural emphysema does not correlate with lung compliance: lessons from the mouse smoking model.

The murine smoke-induced model produces histologic emphysema. The authors sought to assess whether the structural emphysema that occurred correlated with the development of compliance changes. The study exposed 2 strains of mice (CBA/J/J x C57BL/6J and A/J) to chronic cigarette smoke. Lung compliance and morphometry were measured. The smoking model generated significant emphysema in A/J mice in the absence of changes in compliance, lung matrix, or apoptosis. Importantly, there was no correlation between the emphysema measured by lung morphometry and pulmonary compliance. This lack of correlation suggests that the mechanisms involved in anatomic emphysema may be distinct from those that cause the loss of elastic recoil.

Animals↗

PubMed2004

G protein-coupled receptors: in silico drug discovery in 3D.

The application of structure-based in silico methods to drug discovery is still considered a major challenge, especially when the x-ray structure of the target protein is unknown. Such is the case with human G protein-coupled receptors (GPCRs), one of the most important families of drug targets, where in the absence of x-ray structures, one has to rely on in silico 3D models. We report repeated success in using ab initio in silico GPCR models, generated by the predict method, for blind in silico screening when applied to a set of five different GPCR drug targets. More than 100,000 compounds were typically screened in silico for each target, leading to a selection of <100 "virtual hit" compounds to be tested in the lab. In vitro binding assays of the selected compounds confirm high hit rates, of 12-21% (full dose-response curves, Ki < 5 microM). In most cases, the best hit was a novel compound (New Chemical Entity) in the 1- to 100-nM range, with very promising pharmacological properties, as measured by a variety of in vitro and in vivo assays. These assays validated the quality of the hits as lead compounds for drug discovery. The results demonstrate the usefulness and robustness of ab initio in silico 3D models and of in silico screening for GPCR drug discovery.

Algorithms↗

PubMed1994

In-phase and antiphase self-oscillations in a model of two electrically coupled pacemakers.

The dynamic behavior of a model of two electrically coupled oscillatory neurons was studied while the external polarizing current was varied. It was found that the system with weak coupling can demonstrate one of five stable oscillatory modes: (1) in-phase oscillations with zero phase shift; (2) antiphase oscillations with half-period phase shift; (3) oscillations with any fixed phase shift depending on the value of the external polarizing current; (4) both in-phase and antiphase oscillations for the same current value, where the oscillation type depends on the initial conditions; (5) both in-phase and quasiperiodic oscillations for the same current value. All of these modes were robust, and they persisted despite small variations of the oscillator parameters. We assume that similar regimes, for example antiphase oscillations, can be detected in neurophysiological experiments. Possible applications to central pattern generator models are discussed.

Animals↗

PubMed2005

Interaction between the CD8 coreceptor and major histocompatibility complex class I stabilizes T cell receptor-antigen complexes at the cell surface.

The off-rate (k(off)) of the T cell receptor (TCR)/peptide-major histocompatibility complex class I (pMHCI) interaction, and hence its half-life, is the principal kinetic feature that determines the biological outcome of TCR ligation. However, it is unclear whether the CD8 coreceptor, which binds pMHCI at a distinct site, influences this parameter. Although biophysical studies with soluble proteins show that TCR and CD8 do not bind cooperatively to pMHCI, accumulating evidence suggests that TCR associates with CD8 on the T cell surface. Here, we titrated and quantified the contribution of CD8 to TCR/pMHCI dissociation in membrane-constrained interactions using a panel of engineered pMHCI mutants that retain faithful TCR interactions but exhibit a spectrum of affinities for CD8 of >1,000-fold. Data modeling generates a "stabilization factor" that preferentially increases the predicted TCR triggering rate for low affinity pMHCI ligands, thereby suggesting an important role for CD8 in the phenomenon of T cell cross-reactivity.

Antigens↗

PubMed2004

PROSPECT-PSPP: an automatic computational pipeline for protein structure prediction.

Knowledge of the detailed structure of a protein is crucial to our understanding of the biological functions of that protein. The gap between the number of solved protein structures and the number of protein sequences continues to widen rapidly in the post-genomics era due to long and expensive processes for solving structures experimentally. Computational prediction of structures from amino acid sequence has come to play a key role in narrowing the gap and has been successful in providing useful information for the biological research community. We have developed a prediction pipeline, PROSPECT-PSPP, an integration of multiple computational tools, for fully automated protein structure prediction. The pipeline consists of tools for (i) preprocessing of protein sequences, which includes signal peptide prediction, protein type prediction (membrane or soluble) and protein domain partition, (ii) secondary structure prediction, (iii) fold recognition and (iv) atomic structural model generation. The centerpiece of the pipeline is our threading-based program PROSPECT. The pipeline is implemented using SOAP (Simple Object Access Protocol), which makes it easier to share our tools and resources. The pipeline has an easy-to-use user interface and is implemented on a 64-node dual processor Linux cluster. It can be used for genome-scale protein structure prediction. The pipeline is accessible at http://csbl.bmb.uga.edu/protein_pipeline.

Computational Biology↗

PubMed1976

Studies of bacterial chemotaxis in defined concentration gradients. A model for chemotaxis toward L-serine.

The details of the chemotactic response of Salmonella typhimurium to gradients of L-serine have been examined in some detail. Two relatively macroscopic techniques have been employed to measure the bacterial response. These include measurements of the average velocity as the bacterial population moves toward attractants, and measurement of the upward-to-downward flux ratio, R, in the stable preformed attractant gradients. The dependence of the average velocity on gradient appears to be hyperbolic in nature, while the flux ratio depends linearly on the gradient. These data suggest a microscopic model for the dependence of bacterial behavior on the serine gradient. The model involves a linear dependence of the mean lifetime of a bacterial trajectory on the gradient for those bacteria moving toward higher attractant concentration. Those moving toward low concentrations of attractant do not change the mean duration of their trajectories, or the speed at which a given bacterium swims through the solution. This model generates the observed dependences of the average velocity and flux ratio on gradient. Interpretation of the experimental data suggests that a gradient which increases serine concentration by a factor of 2 in 10 mm is sufficient to double the average duration of a trajectory for a bacterium moving directly up the gradient. The concentration dependence of the chemotactic response to serine is more complicated. It suggests that more than one receptor of serine may be involved in determining chemotactic behavior to this attractant.

Chemotaxis↗

PubMed1989

Problems of the third dimension.

The problems facing a pathologist or anatomist who wishes to embark on computer-assisted reconstruction of structures seen in serial light microscope sections are reviewed. They are illustrated by comparing a reconstruction of a bronchial gland made by cutting out polystyrene sheets with models generated by four computer-assisted systems, i.e. the IBAS 2000 system, the SSRCON (MRC) system, the AT-Videoplan system and the CHD (Cookson, Holman, Dykes) system. It is obvious that computer-assistance cannot solve the preparation problems of three-dimensional reconstruction (3DR) and that choosing a computer-assisted system is fraught with difficulties. It is recommended that intending purchasers of computer-assisted 3DR systems prepare material in advance to try out on the systems they are considering.

Bronchi↗

PubMed2006

Formulation and optimization of controlled release mucoadhesive tablets of atenolol using response surface methodology.

The aim of the current study was to design oral controlled release mucoadhesive compressed hydrophilic matrices of atenolol and to optimize the drug release profile and bioadhesion using response surface methodology. Tablets were prepared by direct compression and evaluated for bioadhesive strength and in vitro dissolution parameters. A central composite design for 2 factors at 3 levels each was employed to systematically optimize drug release profile and bioadhesive strength. Carbopol 934P and sodium carboxymethylcellulose were taken as the independent variables. Response surface plots and contour plots were drawn, and optimum formulations were selected by feasibility and grid searches. Compressed matrices exhibited non-Fickian drug release kinetics approaching zero-order, as the value of release rate exponent (n) varied between 0.6672 and 0.8646, resulting in regulated and complete release until 24 hours. Both the polymers had significant effect on the bioadhesive strength of the tablets, measured as force of detachment against porcine gastric mucosa (P < .001). Polynomial mathematical models, generated for various response variables using multiple linear regression analysis, were found to be statistically significant (P < .01). Validation of optimization study, performed using 8 confirmatory runs, indicated very high degree of prognostic ability of response surface methodology, with mean percentage error (+/- SD) as -0.0072 +/- 1.087. Besides unraveling the effect of the 2 factors on the various response variables, the study helped in finding the optimum formulation with excellent bioadhesive strength and controlled release.

Adrenergic beta-Antagonists↗

PubMed1997

Effect of image orientation contents on detection efficiency.

Contrast detection performance is known to be better for single component sinusoidal gratings than for sums of gratings at different orientations. A recent study Rovamo et al. (1994) (Investigative Ophthalmology and Visual Science, 35, 2611-2619) showed that spatial integration is less effective for multiple orientation component than for single component gratings. This suggests an explanation that the size of a spatial integration window depends on the orientation contents of the stimulus. To test this hypothesis we designed a computational detection model and tested it against new experimental data. The model generates a cross-correlation template, the extent of which is limited both in the spatial and spatial frequency domain. The template is a copy of the band-pass filtered signal weighted by a spatial window function. The spatial window function, which limits spatial integration, decreases with increasing orientation range of the stimulus. The experimental stimuli were composed of side-by-side located square shaped, one cycle, grating patches. The range of either grating orientations or phases within the patches as well as the number of patches in a stimulus were varied. We also measured detection efficiency for Bessel Jo images as a function of area. Human spatial integration became considerably weaker with increasing orientation range. The increasing phase range also reduced detection efficiency to some extent. Supporting the idea of the varying size of the spatial integration window, the computational model explained the orientation, phase, and Bessel Jo data well.

Contrast Sensitivity↗

PubMed1995

The value of ten common exercise tolerance test measures in predicting coronary disease in symptomatic females.

The diagnostic contribution of ten common exercise tolerance test (ETT) measures compared with coronary angiography was studied in 62 symptomatic females (mean age = 53 +/- 9 years). Logistic regression revealed that maximal ST-segment depression, the percent of predicted maximal heart rate achieved, and test chest pain all contributed unique predictive information and formed a model generating probabilities for coronary disease (CAD). Using a predicted probability for the presence of CAD of 0.50 as a cutpoint, test accuracy was markedly improved (sensitivity = 73%, specificity = 94%, and overall correct classification rate = 90%) over the standard ST response. We conclude that multivariate analysis using these three easily assessed ETT measures provides superior discrimination between symptomatic women with and without CAD when compared to changes in the ST-segment alone.

Coronary Angiography↗

PubMed2001

Constrained emergence of universals and variation in syllable systems.

A computational model of emergent syllable systems is developed based on a set of functional constraints on syllable systems and the assumption that language structure emerges through cumulative change over time. The constraints were derived from general communicative factors as well as from the phonetic principles of perceptual distinctiveness and articulatory ease. Through evolutionary optimization, the model generated mock vocabularies optimized for the given constraints. Several simulations were run to understand how these constraints might define the emergence of universals and variation in complex sound systems. The predictions were that (1) CV syllables would be highly frequent in all vocabularies evolved under the constraints; (2) syllables with consonant clusters, consonant codas, and vowel onsets would occur much less frequently; (3) a relationship would exist between the number of syllable types in a vocabulary and the average word length in the vocabulary; (4) different syllable types would emerge according to, what we termed, an iterative principle of syllable structure and their frequency would be directly related to their complexity; and (5) categorical differences would emerge between vocabularies evolved under the same constraints. Simulation results confirmed these predictions and provided novel insights into why regularities and differences may occur across languages. Specifically, the model suggested that both language universals and variation are consistent with a set of functional constraints that are fixed relative to one another. Language universals reflect underlying constraints on the system and language variation represents the many different and equally-good solutions to the unique problem defined by these constraints.

Computer Simulation↗

PubMed1987

Effects of brackets and ties on stiffness of an arch wire.

Beam theory was used to evaluate the stiffness of a simulated orthodontic model as affected by the type of bracket, interbracket distance, type of ligature tie, and size of segment. For a given deflection, the model generated greater force (increased stiffness) as the beam constant (N) increased. N increased as interbracket distance increased. Metal ties were as rigid or more rigid than o-rings. Four bracket segments were more rigid than two-bracket segments when tied with o-rings but not metal ligatures. Values of N of Lewis and narrow twin brackets with metal ties were similar and greater than the N of wide twin and medium single brackets. Wide twin brackets were more rigid than others with o-rings.

Elasticity↗

PubMed1995

The dominant role of psychosocial risk factors in the development of chronic low back pain disability.

STUDY DESIGN: An inception cohort design was used in which 421 patients were evaluated systematically with a standard battery of psychosocial assessment tests (Structured Interview for DSM-III-R Diagnosis, Minnesota Multiphasic Personality Inventory, and Million Visual Pain Analog Scale) within 6 weeks of acute back pain onset. OBJECTIVES: The present study evaluated the predictive power of a comprehensive assessment of psychosocial and personality factors in identifying acute low back pain patients who subsequently develop chronic pain disability problems (as measured by job-work status at 1-year follow-up evaluation). SUMMARY OF BACKGROUND DATA: There has been a relative paucity of prospective research in the United States comprehensively evaluating potential psychosocial risk factors that are associated with those injured workers who subsequently fail to return to work and productivity after 1 year because of low back pain disability. Such research has been quite limited because of the time and cost involved in conducting prospective studies. METHODS: All study patients were symptomatic with lumbar pain syndrome for no more than 6 weeks. These acute patients were tracked every 3 months, culminating in a structured telephone interview being conducted 1 year after the initial evaluation to document return-to-work status. RESULTS: Logistic regression analyses, conducted to differentiate between patients who were back at work after 1 year versus patients who were not because of the original back injury, revealed the importance of three psychosocial measures: self-reported pain and disability, scores on Scale 3 of the Minnesota Multiphasic Personality Inventory, and workers' compensation and personal injury insurance status. The model generated correctly classified 90.7% of the cases. Results revealed that major psychopathology, such as depression and substance abuse, did not precede or cause the development chronic pain disability. CONCLUSIONS: These results show the presence of a robust "psychosocial disability factor" that is associated with those injured workers who are likely to develop chronic low back pain disability problems. Based on these data, a statistical algorithm has been generated that can identify those acute patients who will require early intervention to prevent the development of chronic disability. The second major result is that preinjury or concomitant psychopathology does not appear to predispose patients to chronic pain disability, although high rates of psychopathology have been shown in chronic low back pain. Future research should be directed at emotional vulnerability and psychosocial events in the period after the injury that may lead to chronicity.

Adult↗

PubMed2001

Incorporation of covariates in multipoint model-free linkage analysis of binary traits: how important are unaffecteds?

When the mode of inheritance is unknown, genetic linkage analysis of binary trait is commonly performed using affected-sib-pair approaches. When there is evidence that some covariates influence the phenotype, incorporation of this information is expected to increase the power of the analysis since it allows (1) a better specification of the phenotype and (2) to take into account unaffected subjects. Here, we show how to account for covariates in the sibship-oriented Maximum-Likelihood-Binomial (MLB) linkage method by means of Pearson's logistic regression residuals which are computed using phenotypic and covariate information on both affected and unaffected subjects. These residuals are subsequently analysed as a quantitative phenotype with the corresponding extension of the MLB approach which can be used without any assumption on the distribution of these residuals. Then, a large simulation study is performed to study the relative power of incorporating or not unaffected sibs. To this aim, two different strategies in the multipoint analysis of family data are compared: (1) using residuals of the whole sibships (ie both covariate and genotypic information on unaffecteds is needed), and (2) using affecteds only (no information on unaffecteds is needed), under different generating models according to genetic and covariate effects. The results show that there is a clear increment in the power to detect the susceptibility locus when making use of the information carried by unaffecteds, in particular for dominant mode of inheritance and when values of the covariates influencing the disease are shared by all the members of the family.

Analysis of Variance↗

PubMed1991

Relationship of apparent systemic clearance to individual organ clearances: effect of pulmonary clearance and site of drug administration and measurement.

The relationships between apparent total-body clearance (CL) and individual organ clearances were mathematically defined with respect to the site of drug administration and measurement. The derived equations can be applied to drugs undergoing different pathways of elimination, including pulmonary clearance. A physiological pharmacokinetic model was used to test the validity of the equations. The apparent systemic clearance values obtained through the equations, using the individual organ clearance values, were identical to those calculated utilizing the model-generated data, indicating the validity of the equations. Furthermore, it was shown that the conventional estimation of CL of drugs subject to pulmonary clearance is highly dependent upon the site of drug administration and measurement. The relationships were further utilized to explain the reported CL values which are higher than the cardiac output. The equations developed here may be used to predict the contribution of different organs, such as the lungs, to the apparent systemic clearance of drugs.

Animals↗

PubMed1994

CO2 control of breathing: parameter estimation and stability evaluation.

A method is developed to evaluate system stability for the CO2 control of breathing in individuals by using data from the dynamics of CO2 rebreathing and elimination. The theoretical basis of the method is a physiological model of the CO2 respiratory control system and an explicit stability index (SI). The SI is algebraically related to the model parameters: system volume (Vs), cardiac output (Q), circulatory transit time (ts), and controller gain (G). A sequential optimization scheme is shown to yield estimates of the model parameters by comparing the alveolar ventilation and PCO2 of the model output with corresponding experimental data. Model simulation of CO2 rebreathing and elimination with different parameter values demonstrate that all parameters except ts have significant effect on the outputs. Least-squares estimation of the parameters using model-generated data with added noise showed good precision for all parameters (except ts). This analysis is performed with parameter values chosen to produce overdamped and underdamped responses that would occur in normal and abnormal respiratory control systems, respectively. It is anticipated that SI values of the (overdamped) normal and (underdamped) abnormal systems differ by much more than the variation produced by imprecision of the parameter estimates. For this circumstance, the method is expected to be sensitive enough to distinguish normal from abnormal CO2 respiratory control of individual subjects.

Carbon Dioxide↗