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PubMed1986

The exponential model for a regulatory enzyme. An interpretation of the linear free-energy relationship.

A physical mechanism is suggested to explain the linear free-energy relationship employed in the exponential model for a regulatory enzyme [Ainsworth (1977) J. Theor. Biol. 68, 391-413]. The interpretation depends on the assumption that the structure of the enzyme changes in proportion to its saturation by substrate but at a rate that is low compared with the rates of the association-dissociation reactions of the enzyme-substrate system.

Enzymes↗
PubMed1980

[Interpretative method as a synthesis of explicative, teleologic and analogic models].

To establish the basis of the interpretative method is congruous with finding a solid basis--epistemologically speaking--to the analytic theory. This basis would be the means to transform this theory into a real science with its necessary adecuation among method, act and object of knowledge. It is only from a scientific stand that the psychoanalytic theory will be able to face successfully the reductionisms that menace it, be it the biologist-naturalism with its explanations of the psychic phenomena by means of mechanisms and biologic models or be it the speculative ideologies with their nucleus of technical praxis which make it impossible for the social-factic sciences to become real sciences. We propose as interpretative method the union of two models: the teleologic one which makes possible the appearance of intelligible, contingent and variable explanations between an antecedent and a consequent on one side, and on the other, the analogic model with its two moments: the comparative and the symbolic one. These moments makes possible the comparison and the union between antecedent and consequent baring in mind the "natural" ambiguity of the subject-object in question. The principal objective of the method--as a regulative idea in the Kantian sense--would be the search of univocity as regards the choice of one and only one sense from all the possible senses that "explain" the motive relationship or motive-end relationship in order to make the interpretation scientific. This status of scientificity should obey the rules of explanation: that the interpretations be derived effectively from the presupposed theory, that they really explain what they claim to explain, that they are not contradictory or contrary in the same ontologic level. We postulate that the synthesis of the two mentioned models, the teleologic-explanative and the analogic one allows us to find a possibility to make clear the "dark" sense of the noun interpretation and in this way the factibility of speaking of an interpretative method that develops the real concrete object by producing the formal and abstract one--which for us is the behaviour of the subject--. In this way the interpretations come to be teleological explanations overdetermined by an analogical relationship. This means that they produce the formal and abstract object -the method--which is in itself an intelligible, continguent and variable relationship between an antecedent and a consequent permitting in this way the emergence of a symbolic comparison to explain the real concrete. The symbolic explanations and comparisons are strictly derived from the presupposed theory, the theoretical body of psychoanalysis.

Models, Psychological↗
PubMed2005

Unbiased descriptor and parameter selection confirms the potential of proteochemometric modelling.

BACKGROUND: Proteochemometrics is a new methodology that allows prediction of protein function directly from real interaction measurement data without the need of 3D structure information. Several reported proteochemometric models of ligand-receptor interactions have already yielded significant insights into various forms of bio-molecular interactions. The proteochemometric models are multivariate regression models that predict binding affinity for a particular combination of features of the ligand and protein. Although proteochemometric models have already offered interesting results in various studies, no detailed statistical evaluation of their average predictive power has been performed. In particular, variable subset selection performed to date has always relied on using all available examples, a situation also encountered in microarray gene expression data analysis. RESULTS: A methodology for an unbiased evaluation of the predictive power of proteochemometric models was implemented and results from applying it to two of the largest proteochemometric data sets yet reported are presented. A double cross-validation loop procedure is used to estimate the expected performance of a given design method. The unbiased performance estimates (P2) obtained for the data sets that we consider confirm that properly designed single proteochemometric models have useful predictive power, but that a standard design based on cross validation may yield models with quite limited performance. The results also show that different commercial software packages employed for the design of proteochemometric models may yield very different and therefore misleading performance estimates. In addition, the differences in the models obtained in the double CV loop indicate that detailed chemical interpretation of a single proteochemometric model is uncertain when data sets are small. CONCLUSION: The double CV loop employed offer unbiased performance estimates about a given proteochemometric modelling procedure, making it possible to identify cases where the proteochemometric design does not result in useful predictive models. Chemical interpretations of single proteochemometric models are uncertain and should instead be based on all the models selected in the double CV loop employed here.

Algorithms↗
PubMed2005

Species lifetime distribution for simple models of ecologies.

Interpretation of empirical results based on a taxa's lifetime distribution shows apparently conflicting results. Species' lifetime is reported to be exponentially distributed, whereas higher-order taxa, such as families or genera, follow a broader distribution, compatible with power-law decay. We show that both forms of evidence are consistent with a simple evolutionary model that does not require specific assumptions on species interaction. The model provides a zero-order description of the dynamics of ecological communities, and its species lifetime distribution can be computed exactly. Different behaviors are found as follows: an initial t(-3/2) power law, emerging from a random walk type of dynamics, which crosses over to a steeper t(-2) branching process-like regime and finally is cut off by an exponential decay that becomes weaker and weaker as the total population increases. Sampling effects also can be taken into account and shown to be relevant. If species in the fossil record were sampled according to the Fisher log-series distribution, lifetime should be distributed according to a t(-1) power law. Such variability of behaviors in a simple model, combined with the scarcity of data available, casts serious doubt on the possibility of validating theories of evolution on the basis of species lifetime data.

Animals↗
PubMed1996

Interpretive work in short-term individual psychotherapy: an analysis using hierarchical linear modeling.

"Work" and "resistance" responses to interpretation in short-term individual (STI) psychotherapy were examined using a hierarchical linear modeling (HLM) procedure. The relationships between interpretation characteristics and patient responses within therapy were considered. Process data were drawn from 60 STI therapy cases, 30 patients with low quality of object relations (QOR), and 30 patients with high QOR. In 4 instances, the relationships between technique and response were found to vary significantly across cases. One was identified for low QOR patients, and 3 were identified for high QOR patients. Individual differences in initial disturbance and outcome were used to account for the variation of technique-response relationships. Significant findings were limited to the high QOR sample. Initial disturbance was directly related to work in response to a transference-oriented approach. The transference focus-work relationship was found to be inversely related to outcome. The results extend previous findings regarding transference technique in STI therapy with high QOR patients. Through capitalizing on within-case variation, HLM can be used to illuminate process-outcome relationships in psychotherapy.

Adolescent↗
PubMed2005

Representing the Patient's Therapeutic History in Medical Records and in Guideline Recommendations for Chronic Diseases Using a Unique Model.

Computer-interpretable guidelines (CIGs) are more likely to affect the clinician's behavior when they deliver patient-specific and just-in-time clinical advice. CIGs must take into account the data stored in the patient's electronic medical records (EMR). For chronic diseases, the outcome of past and ongoing treatments (therapeutic history) is used in the clinical guidelines. We propose a model for the conceptualization of therapeutic history, facilitating data sharing between EMRs and CIGs and the representation of therapeutic history and recommended treatments in clinical guidelines.Based on medical literature review and an existing treatment model, a core structure is first defined taking into account drug and non-drug treatment components and treatment type (e.g. bitherapy). These elements together with additional concepts obtained by analyzing a sample guideline relating to diabetes, are then organized into an object-oriented model, using UML formalism.We show how this model can be used to store the patient's therapeutic history in the EMR, together with other attributes such as treatment efficacy and tolerance. We also explain how this model can efficiently code guidelines therapeutic rules.We evaluated this model, using additional guidelines hypercholesterolemia and asthma. We found it capable for representing guideline recommendations in several domains of chronic diseases.

Chronic Disease↗
PubMed1999

Basis function models of the CMAC network.

An interpretation of the Cerebellar Model Articulation Controller (CMAC) network as a member of the General Memory Neural Network (GMNN) architecture is presented. The usefulness of this approach stems from the fact that, within the GMNN formalism, CMAC can be treated as a particular form of a basis function network, where the basis function is inherently dependent on the type of input quantization present in the network mapping. Furthermore, considering the relative regularity of input-space quantization performed by CMAC, we are able to derive an expected (or average) form of the basis function characteristic of this network. Using this basis form, it is possible to create basis-functions models of CMAC mapping, as well as to gain more insight into its performance. The developments are supported by numerical simulations.

Journal Article↗
PubMed2006

The adrenocorticotropin stimulation test: contribution of a physiologically based model developed in horse for its interpretation in different pathophysiological situations encountered in man.

The present study aimed to characterize the adrenal response to ACTH. A model was developed that coupled the nonlinear disposition of cortisol with a physiologically based model for cortisol secretion by the adrenals. It was assumed that the response to ACTH resulted from two mechanisms: a stimulation of the cortisol secretion rate and control of the duration of the secretion. Seven dose levels of ACTH were tested in horses, a species similar to man as regards adrenal function. The main result was that the secretion rate of the adrenal gland can be modelized by a zero order process that is maximal for a relatively low dose of ACTH (0.1 microg/kg). Beyond this dose, the increasing adrenal gland response is only due to the prolongation of the time of its secretion. The consequences of these different features were explored by simulation to reproduce classical pathophysiological situations encountered in man. Our model was able to reproduce and simply explain many adrenal gland responses that are dimmed by the different nonlinearities of the system.

Adrenal Glands↗
PubMed2003

Excellent enantio-selective enclathration of (2R,3S)-3-methyl-2-pentanol in channel-like cavity of 3-epideoxycholic acid, interpreted by the four-location model for chiral recognition.

Pure (2R,3S)-3-methyl-2-pentanol is resolved from the racemates by a steroidal host; the interpretation of the recognition mechanism based on the crystal structure reveals that CH/O interaction between the host and guest plays a decisive role in enantio-selective enclathration of the small aliphatic secondary alcohol.

Journal Article↗
PubMed2000

Toward a mathematical description of dose-effect functions for self-administered drugs in laboratory animal models.

RATIONALE: The interpretation of dose-effect functions for self-administered drugs remains elusive. Since, for self-administered drugs, the amount of drug in an animal depends on its behavior, a mathematical theory of drug self-administration must include terms relevant to receptor theory, as well as a description of how an organism's behavior affects the amount of drug in the animal over time. OBJECTIVE: A theory was constructed in which the ability of a dose to maintain responding was described in terms of receptor theory and the function relating rate of responding to amount of drug self-administered. The main predictions of the theory were that: 1) there should be no ascending limb for drugs self-administered under ratio schedules, 2) running rate of response should not change as a function of dose and, 3) pause duration should be an exponential function of dose. RESULTS: Low doses of cocaine were either self-administered at high rates, or not at all. Run rates, though somewhat variable, did not change as an orderly function of dose. Pause duration could be well described by an exponential function. CONCLUSIONS: The theory provides an acceptable, though no doubt preliminary, description of drug self-administration.

Animals↗
PubMedDate not supplied

Introducing the consensus modeling concept in genetic algorithms: application to interpretable discriminant analysis.

An evolutionary statistical learning method was applied to classify drugs according to their biological target and also to discriminate between a compilation of oral and nonoral drugs. The emphasis was placed not only on how well the models predict but also on their interpretability. In an enhancement to previous studies, the consistency of the model weights over several runs of the genetic algorithm was considered with the goal of producing comprehensible models. Via this approach, the descriptors and their ranges that contribute most to class discrimination were identified. Selecting a bin step size that enables the average descriptor properties of the class being trained to be captured improves the interpretability and discriminatory power of a model. The performance, consistency, and robustness of such models were further enhanced by using two novel approaches that reduce the variability between individual solutions: consensus and splice modeling. Finally, the ability of the genetic algorithm to discriminate between activity classes was compared with a similarity searching method, while naïve Bayes classifiers and support vector machines were applied in discriminating the oral and nonoral drugs.

Algorithms↗
PubMed1996

Mechanistic considerations in the evaluation of chemopreventive data.

Possible chemopreventive mechanisms include carcinogen-blocking activities, antioxidant/anti-inflammatory activities and antiproliferation/antiprogression activities. Carcinogen-blocking activities encompass inhibition of carcinogen uptake, inhibition of carcinogen formation or activation, deactivation or detoxification of carcinogens, prevention of carcinogen binding to DNA, and enhancement of the level or fidelity of DNA repair. Antioxidant/anti-inflammatory activities include scavenging of reactive electrophiles and oxygen radicals, and inhibition of arachidonic acid metabolism. Antiproliferation/antiprogression activities comprise modulation of signal transduction, modulation of hormonal and growth factor activity, inhibition of aberrant oncogene activity, inhibition of polyamine metabolism, induction of terminal differentiation, restoration of immune responses, enhancement of intercellular communication, restoration of tumour suppressor function, induction of apoptosis, telomerase inhibition, correction of DNA methylation imbalances, inhibition of angiogenesis, inhibition of basement membrane degradation, and activation of antimetastasis genes. In evaluating the potential efficacy of chemopreventive agents several mechanistic parameters are weighed: (1) the number of chemoprevention-related pharmacological activities, (2) the impact of the agent on likely carcinogenesis pathways to the targeted cancer, (3) pharmacodynamics, and (4) specificity for chemopreventive activity compared with interference with normal cellular function. Mechanistic data are important throughout the development process for chemopreventive drugs, and they are particularly important in the earlier phases of identifying promising candidate agents and characterizing efficacy. In vitro mechanistic assays are a first step in evaluating chemopreventive potential. Mechanistic considerations are also useful in defining animal efficacy models and in interpreting the results of assays in these models. Mechanistic data are also applied in designing short-term Phase II clinical chemoprevention trials that use reductions in intermediate biomarkers of cancer rather than cancer incidence as end points. The basis for identifying and evaluating these biomarkers is in understanding carcinogenesis and chemopreventive mechanisms.

Anticarcinogenic Agents↗
PubMed2006

Equivalence of truncated count mixture distributions and mixtures of truncated count distributions.

This article is about modeling count data with zero truncation. A parametric count density family is considered. The truncated mixture of densities from this family is different from the mixture of truncated densities from the same family. Whereas the former model is more natural to formulate and to interpret, the latter model is theoretically easier to treat. It is shown that for any mixing distribution leading to a truncated mixture, a (usually different) mixing distribution can be found so that the associated mixture of truncated densities equals the truncated mixture, and vice versa. This implies that the likelihood surfaces for both situations agree, and in this sense both models are equivalent. Zero-truncated count data models are used frequently in the capture-recapture setting to estimate population size, and it can be shown that the two Horvitz-Thompson estimators, associated with the two models, agree. In particular, it is possible to achieve strong results for mixtures of truncated Poisson densities, including reliable, global construction of the unique NPMLE (nonparametric maximum likelihood estimator) of the mixing distribution, implying a unique estimator for the population size. The benefit of these results lies in the fact that it is valid to work with the mixture of truncated count densities, which is less appealing for the practitioner but theoretically easier. Mixtures of truncated count densities form a convex linear model, for which a developed theory exists, including global maximum likelihood theory as well as algorithmic approaches. Once the problem has been solved in this class, it might readily be transformed back to the original problem by means of an explicitly given mapping. Applications of these ideas are given, particularly in the case of the truncated Poisson family.

Algorithms↗
PubMed1995

Liquid chromatographic analysis of brain homogenates and microdialysates for the quantification of L-[beta-11C]DOPA and its metabolites for the validation of positron emission tomography studies.

The clinical use of positron emission tomography, PET, with selected radiolabelled tracer molecules visualizing and quantitating physiological processes in the tissue relies in many situations on compartmental models for the interpretation of the radiosignal. Validation of such models must, therefore, include chromatographic analysis of the radioactivity composition of the signal. Rapid and sensitive liquid chromatographic methods amenable for automation for the analysis of [11C] labelled L-DOPA and its metabolites were therefore developed and validated for the quantitation of radioactivity composition in rat brain microdialysates as well as homogenates. Analysis included a simple isolation step, separation using reversed phase liquid chromatography with radiometric detection and permitted assay following tracer doses with an analysis time of 15 min. The analysis of radioactivity composition in the rat striatum showed that peripherally formed O-methyl L-DOPA constituted less than 20% of the radioactivity 40 min after injection of L-[beta-11C]DOPA. In the extracellular space the main component was [11C]-homovanillic acid which increased with time indicating rapid formation but slow elimination. The cumulation of radioactivity in the striatum corresponded to the radioactivity signal of dopamine and derived metabolites. The formation rate of dopamine in the rat corresponded closely to the utilization rate in the striatum of monkey and man measured with PET. This indicated that the rate constants measured with PET correlates well to the dopamine synthesis rate.

Animals↗
PubMed2004

Quantification of human motion: gait analysis-benefits and limitations to its application to clinical problems.

The technology supporting the analysis of human motion has advanced dramatically. Past decades of locomotion research have provided us with significant knowledge about the accuracy of tests performed, the understanding of the process of human locomotion, and how clinical testing can be used to evaluate medical disorders and affect their treatment. Gait analysis is now recognized as clinically useful and financially reimbursable for some medical conditions. Yet, the routine clinical use of gait analysis has seen very limited growth. The issue of its clinical value is related to many factors, including the applicability of existing technology to addressing clinical problems; the limited use of such tests to address a wide variety of medical disorders; the manner in which gait laboratories are organized, tests are performed, and reports generated; and the clinical understanding and expectations of laboratory results. Clinical use is most hampered by the length of time and costs required for performing a study and interpreting it. A "gait" report is lengthy, its data are not well understood, and it includes a clinical interpretation, all of which do not occur with other clinical tests. Current biotechnology research is seeking to address these problems by creating techniques to capture data rapidly, accurately, and efficiently, and to interpret such data by an assortment of modeling, statistical, wave interpretation, and artificial intelligence methodologies. The success of such efforts rests on both our technical abilities and communication between engineers and clinicians.

Biomechanical Phenomena↗
PubMed2002

Drivers' response to the installation of road lighting. An economic interpretation.

An economic model of drivers' behaviour is introduced in order to explain recently published empirical findings telling us that road lighting increases speed, decreases concentration and reduces accidents. The model, combined with the empirical results, indicate that drivers perceive speed and concentration as complementary safety variables, while common sense suggests that speed and concentration influence real accident rate as substitutable safety means. If this holds, a positive but concave relationship between subjective and objective risks exists, which means that as the objective accident risk rises, it has less influence on perceived risk.

Attention↗