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PubMed2006

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models.

BACKGROUND: The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. RESULTS: We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. CONCLUSION: As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.

Algorithms↗
PubMed2006

Molecular models of tryptophan synthase from mycobacterium tuberculosis complexed with inhibitors.

The development of new therapies against infectious diseases is vital in developing countries. Among infectious diseases, tuberculosis is considered the leading cause of death. A target for development of new drugs is the tryptophan pathway. The last enzyme of this pathway, tryptophan synthase (TRPS), is responsible for conversion of the indole 3-glycerol phosphate into indol and the condensation of this molecule with serine-producing tryptophan. The present work describes the molecular models of TRPS from Mycobacterium tuberculosis (MtTRPS) complexed with six inhibitors, the indole 3-propanol phosphate and five arylthioalkyl-phosphonated analogs of substrate of the alpha-subunit. The molecular models of MtTRPS present good stereochemistry, and the binding of the inhibitors is favorable. Thus, the generated models can be used in the design of more specific drugs against tuberculosis and other infectious diseases.

Binding Sites↗
PubMed2003

Pharmacology of human experimental anxiety.

This review covers the effect of drugs affecting anxiety using four psychological procedures for inducing experimental anxiety applied to healthy volunteers and patients with anxiety disorders. The first is aversive conditioning of the skin conductance responses to tones. The second is simulated public speaking, which consists of speaking in front of a video camera, with anxiety being measured with psychometric scales. The third is the Stroop Color-Word test, in which words naming colors are painted in the same or in a different shade, the incongruence generating a cognitive conflict. The last test is a human version of a thoroughly studied animal model of anxiety, fear-potentiated startle, in which the eye-blink reflex to a loud noise is recorded. The evidence reviewed led to the conclusion that the aversive conditioning and potentiated startle tests are based on classical conditioning of anticipatory anxiety. Their sensitivity to benzodiazepine anxiolytics suggests that these models generate an emotional state related to generalized anxiety disorder. On the other hand, the increase in anxiety determined by simulated public speaking is resistant to benzodiazepines and sensitive to drugs affecting serotonergic neurotransmission. This pharmacological profile, together with epidemiological evidence indicating its widespread prevalence, suggests that the emotional state generated by public speaking represents a species-specific response that may be related to social phobia and panic disorder. Because of scant pharmacological data, the status of the Stroop Color-Word test remains uncertain. In spite of ethical and economic constraints, human experimental anxiety constitutes a valuable tool for the study of the pathophysiology of anxiety disorders.

Anti-Anxiety Agents↗
PubMed2000

A mechanistic, predictive model of dose-response curves for cell cycle phase-specific and -nonspecific drugs.

In vitro dose-response curves for anticancer agents are useful for predicting the clinical response to chemotherapy, and models to capture the time-dependency of dose-response curves are necessary for potential clinical extrapolation. Usually, the modified Hill model is used (see Levasseur et al., Cancer Res., 58: 5749-5761, 1998), although this model is neither mechanistic nor predictive for understanding how drug and tumor cell characteristics affect the shape of the dose-response curve. A new exponential kill (EK) model is proposed to predict the shape of dose-response curves based on the cell cycle phase specificity of a drug, the cell cycle time, the duration and concentration of drug exposure at the site of action, and a scaling factor for the level of drug resistance. Explicit analytical equations are presented for predicting the ICx (the concentration required to reduce cell growth by x%), the maximum cell kill achievable at high doses after a given duration of drug exposure, and the slope of the survival fraction versus log (concentration) plot at the ICx. Numerical solutions illustrate that there may be an optimal, finite duration of drug exposure that maximizes cell kill for a given area under the concentration versus time curve, and an analytical equation is given to calculate when such an optimal, finite duration exists. The EK model generates sigmoidal dose-response curves, like those seen empirically and previously described by the Hill model, which eventually plateau with increasing drug concentration at levels that depend on the cell cycle specificity of the drug, the cell cycle time, and the duration of exposure to the drug. This study includes no original data. Instead, empirical results in the literature are used to test the model. Because data by Levasseur et al. (1998) was fit to the Hill model assuming the plateau in the effect versus concentration curve to be independent of exposure duration, a full test of the model is not possible using their published data. Some tests of the EK model were possible, however, showing that EK model predictions yield good fits to in vitro data published in that and in another study. In addition, combining the EK model with a pharmacokinetic model resulted in predictions that were consistent with results of clinical studies comparing etoposide given in different schedules. Further tests of the model are necessary.

Antineoplastic Agents↗
PubMed1996

The new organization of the health care delivery system.

The U.S. health care system is restructuring at a dizzying pace. In many parts of the country, managed care has moved into third-generation models emphasizing capitated payment for enrolled lives and, in the process, turning most providers and institutions into cost centers to be managed rather than generators of revenue. While the full impact of the new managed care models remains to be seen, most evidence to date suggests that it tends to reduce inpatient use, may be associated with greater use of physician services and preventive care, and appears to result in no net differences either positive or negative with regard to quality or outcomes of care in comparison with fee-for-service plans. Some patients, however, tend to be somewhat less satisfied with scheduling of appointments and the amount of time spent with providers. There is no persuasive evidence that managed care lowers the rate of growth in overall health care costs within a given market. Further, managed care performance varies considerably across the country, and the factors influencing managed care performance are not well understood. Organized delivery systems are a somewhat more recent phenomenon representing various forms of ownership and strategic alliances among hospitals, physicians, and insurers designed to provide more cost-effective care to defined populations by achieving desired levels of functional, physician-system, and clinical integration. Early evidence suggests that organized delivery systems that are more integrated have the potential to provide more accessible coordinated care across the continuum, and appear to be associated with higher levels of inpatient productivity, greater total system revenue, greater total system cash flow, and greater total system operating margin than less integrated delivery forms. Some key success factors for developing organized delivery systems have been identified. Important roles are played by organizational culture, information systems, internal incentives, total quality management, physician leadership, and the growth of group practices. This chapter describes the growth and evolution of managed care and organized delivery systems, the research evidence regarding managed care and organized delivery systems, and the likely future organization of the health system in light of recent trends and evidence. It also highlights some of the more important public policy implications of the new health care infrastructure.

Cost Control↗
PubMed1978

Experience with a Fourier method for determining the extracellular potential fields of excitable cells with cylindrical geometry.

In this chapter, well-known solutions that utilize a Fourier transform method for determining the extracellular, volume-conductor potential distribution surrounding elongated excitable cells of cylindrical geometry are reformulated as a discrete Fourier transform (DFT) problem, which subsequently permits the volume-conductor problem to be viewed as an equivalent linear-filtering problem. This DFT formulation is fast and computationally efficient. In addition, it lends itself to the application of some rather well-known techniques in linear systems theory (e.g., the DFT for convolution and least mean-square (Wiener) filtering for optimal prediction of a signal in random noise). Two specific examples are employed to demonstrate the utility of this discrete Fourier method: (1) the single, isolated, active nerve fiber in an essentially infinite volume conductor and (2) the isolated, active nerve trunk in a similar type of extracellular medium. In each of these, our DFT method is employed to obtain both the classical "forward" and "inverse" potential solutions for each volume conductor problem. In the case where the single, active nerve fiber is the bioelectric source in the volume conductor, simulated action-potential data from an invertebrate giant axon is utilized, and potentials at various points in the extracellular medium are calculated. The calculated potential distributions in axial distance z, at various radial distances r, are consistent with well-known experimental fact. When the active nerve trunk acts as the bioelectric source, the DFT method provides calculated potential distributions that are fairly consistent with experimental data under a variety of experimental conditions. For example, in these experiments, a special, isolated frog spinal cord preparation is used that permits separate or combined stimulation of the motor and sensory nerve fiber components of the attached sciatic nerve trunk. By manipulating the stimulus intensity applied to the motor (ventral) or appropriate sensory (dorsal) roots of the spinal cord, a variety of multiphasic extracellular volume-conductor potentials can be recorded from the sciatic nerve. The excellent agreement of model-generated and experimental data, regardless of the complexity of surface potential waveform, tends to validate the modeling assumptions and offer encouragement that this computationally efficient DFT method may be usefully employed in volume-conductor problems where both the bioelectric source, and the surrounding volume conductor, are of a much more complicated nature.

Action Potentials↗
PubMed1980

Population and agricultural development models: the promise of the third generation.

The author briefly describes the work of Malthus and the development of first- and second-generation economic-demographic models. He then discusses a proposed third-generation model which "examines conjointly both consequences and determinants of population growth, and analyzes them at the level of the agricultural household." A project being conducted by the Food and Agricultural Organization to construct a third-generation model using data from the Philippines and two other countries is described

Agriculture↗
PubMed1990

Novel method for the rapid evaluation of packing in protein structures.

There has been considerable effort to predict the structure of proteins from their amino acid sequences. A major problem in all prediction efforts has been that, short of a direct comparison with crystallographic co-ordinates, it is often difficult to evaluate the merit of a model, or "proposed" protein structure. Here, we present a method for evaluating proposed protein structures that does not require a structural model of complete atomic detail. Our method evaluates residue-residue packing density using a simplified model of the polypeptide chain where amino acids are represented as one, two (histidine, tyrosine and phenylalanine), or three (tryptophan) spheres. This method also gives a measure of the appropriateness of residue-residue contacts, thus giving a measure of the amino acid distribution throughout the protein. Amino acid packing and amino acid distribution, as evaluated by this technique, are consistent with the accuracy of model-built structures. We have been able to select the best structures from a set of combinatorially generated models using this method, and we anticipate that it will be useful as a general tool for model-building.

Amino Acid Sequence↗
PubMed2006

Modeling the brain-pituitary-gonad axis in salmon.

To better understand the complexity of the brain-pituitary-gonad axis (BPG) in fish, we developed a biologically based pharmacodynamic model capable of accurately predicting the normal functioning of the BPG axis in salmon. This first-generation model consisted of a set of 13 equations whose formulation was guided by published values for plasma concentrations of pituitary- (FSH, LH) and ovary- (estradiol, 17alpha,20beta-dihydroxy-4-pregnene-3-one) derived hormones measured in Coho salmon over an annual spawning period. In addition, the model incorporated pertinent features of previously published mammalian models and indirect response pharmacodynamic models. Model-based equations include a description of gonadotropin releasing hormone (GnRH) synthesis and release from the hypothalamus, which is controlled by environmental variables such as photoperiod and water temperature. GnRH stimulated the biosynthesis of mRNA for FSH and LH, which were also influenced by estradiol concentration in plasma. The level of estradiol in the plasma was regulated by the oocytes, which moved along a maturation progression. Estradiol was synthesized at a basal rate and as oocytes matured, stimulation of its biosynthesis occurred. The BPG model can be integrated with toxico-genomic, -proteomic data, allowing linkage between molecular based biomarkers and reproduction in fish.

Animals↗
PubMed2000

The Mt. Hood challenge: cross-testing two diabetes simulation models.

Starting from identical patients with type 2 diabetes, we compared the 20-year predictions of two computer simulation models, a 1998 version of the IMIB model and version 2.17 of the Global Diabetes Model (GDM). Primary measures of outcome were 20-year cumulative rates of: survival, first (incident) acute myocardial infarction (AMI), first stroke, proliferative diabetic retinopathy (PDR), macro-albuminuria (gross proteinuria, or GPR), and amputation. Standardized test patients were newly diagnosed males aged 45 or 75, with high and low levels of glycated hemoglobin (HbA(1c)), systolic blood pressure (SBP), and serum lipids. Both models generated realistic results and appropriate responses to changes in risk factors. Compared with the GDM, the IMIB model predicted much higher rates of mortality and AMI, and fewer strokes. These differences can be explained by differences in model architecture (Markov vs. microsimulation), different evidence bases for cardiovascular prediction (Framingham Heart Study cohort vs. Kaiser Permanente patients), and isolated versus interdependent prediction of cardiovascular events. Compared with IMIB, GDM predicted much higher lifetime costs, because of lower mortality and the use of a different costing method. It is feasible to cross-validate and explicate dissimilar diabetes simulation models using standardized patients. The wide differences in the model results that we observed demonstrate the need for cross-validation. We propose to hold a second 'Mt Hood Challenge' in 2001 and invite all diabetes modelers to attend.

Albuminuria↗
PubMed2003

Patient specific finite element model of the face soft tissues for computer-assisted maxillofacial surgery.

This paper addresses the prediction of face soft tissue deformations resulting from bone repositioning in maxillofacial surgery. A generic 3D Finite Element model of the face soft tissues was developed. Face muscles are defined in the mesh as embedded structures, with different mechanical properties (transverse isotropy, stiffness depending on muscle contraction). Simulations of face deformations under muscle actions can thus be performed. In the context of maxillofacial surgery, this generic soft-tissue model is automatically conformed to patient morphology by elastic registration, using skin and skull surfaces segmented from a CT scan. Some elements of the patient mesh could be geometrically distorted during the registration, which disables Finite Element analysis. Irregular elements are thus detected and automatically regularized. This semi-automatic patient model generation is robust, fast and easy to use. Therefore it seems compatible with clinical use. Six patient models were successfully built, and simulations of soft tissue deformations resulting from bone displacements performed on two patient models. Both the adequation of the models to the patient morphologies and the simulations of post-operative aspects were qualitatively validated by five surgeons. Their conclusions are that the models fit the morphologies of the patients, and that the predicted soft tissue modifications are coherent with what they would expect.

Biomechanical Phenomena↗
PubMedDate not supplied

QSAR modeling using chirality descriptors derived from molecular topology.

Topological descriptors of chemical structures (such as molecular connectivity indices) are widely used in Quantitative Structure-Activity Relationships (QSAR) studies. Unfortunately, these descriptors lack the ability to discriminate between stereoisomers, which limits their application in QSAR. To circumvent this problem, we recently introduced chirality descriptors derived from molecular graphs and applied them in QSAR studies of ecdysteroids (Golbraikh A.; Bonchev, D.; Tropsha, A. J. Chem. Inf. Comput. Sci. 2001,41, 147-158). In this paper, we extend our earlier work by applying chirality descriptors to four data sets containing chiral compounds. All models were derived with the k-nearest neighbors (kNN) QSAR method developed in our laboratory (Zheng, W.; Tropsha, A. J. Chem. Inf. Comput. Sci. 2000, 40, 185-194). They were validated using the same training and test sets that were employed in various, mostly 3D-QSAR, investigations published by other authors. We show that for all data sets 2D-QSAR models that use a combination of chirality descriptors with conventional (chirality insensitive) topological descriptors afford better or similar predictive ability as compared to models generated with 3D-QSAR approaches. The results presented in this paper reassure that 2D-QSAR modeling provides a powerful alternative to 3D-QSAR.

Databases, Factual↗
PubMed1996

Ability of mathematical models to predict faecal output with a pulse dose of indigestible marker.

The aim of the work was to compare the faecal output and digestibility estimated by two mathematical approaches with the actual amount of faeces excreted or feed digested by Simmental cows. Experimental data (intakes and digestibility measured over 5 d) and faecal Cr concentrations (measured at 0, 4, 8, 12, 16, 24, 32, 48, 56, 72, 96, 120 and 144 h after a pulse dose of Cr-mordanted forage) were collected from published experiments and fitted to a multicompartmental (MC) model and a gamma age-dependent (AD) model. From a statistical point of view, the MC model was very satisfactory while the AD model produced lower r2 and higher SE values and reached satisfactory statistical values only for higher DM intakes (lactating animals). The MC model produced higher correlations with the digestibility values while the AD model generated better correlations with the intake data; DM intake and digestibilities were more highly correlated with the model's parameters than neutral-detergent fibre terms. The regression between the estimated faecal outputs obtained with the two models showed an intercept close to 0 (P > 0.05) and angular coefficients near 1; there was a good correspondence of the estimates especially for the lowest values of output. The r2 values of the regressions were 0.800 and 0.829 for the MC and AD models respectively and their SE were 2.93 and 2.63. The ability of the two models to predict faecal output and digestibility was very similar, independent of the statistical accuracy of fitting the Cr-concentration data. The results indicate that variation of Cr concentration is the result of the entire digestive process, i.e. dilution and passage, which interact in a competitive or associative way.

Animal Feed↗
PubMed2004

The evolution of mimicry under constraints.

The resemblance between mimetic organisms and their models varies from near perfect to very crude. One possible explanation, which has received surprisingly little attention, is that evolution can improve mimicry only at some cost to the mimetic organism. In this article, an evolutionary game theory model of mimicry is presented that incorporates such constraints. The model generates novel and testable predictions. First, Batesian mimics that are very common and/or mimic very weakly defended models should evolve either inaccurate mimicry (by stabilizing selection) or mimetic polymorphism. Second, Batesian mimics that are very common and/or mimic very weakly defended models are more likely to evolve mimetic polymorphism if they encounter predators at high rates and/or are bad at evading predator attacks. The model also examines how cognitive constraints acting on signal receivers may help determine evolutionarily stable levels of mimicry. Surprisingly, improved discrimination abilities among signal receivers may sometimes select for less accurate mimicry.

Animals↗
PubMed2005

Nonlinear statistical modeling and model discovery for cardiorespiratory data.

We present a Bayesian dynamical inference method for characterizing cardiorespiratory (CR) dynamics in humans by inverse modeling from blood pressure time-series data. The technique is applicable to a broad range of stochastic dynamical models and can be implemented without severe computational demands. A simple nonlinear dynamical model is found that describes a measured blood pressure time series in the primary frequency band of the CR dynamics. The accuracy of the method is investigated using model-generated data with parameters close to the parameters inferred in the experiment. The connection of the inferred model to a well-known beat-to-beat model of the baroreflex is discussed.

Algorithms↗
PubMed1988

Indirect vertical cultural transmission: a model for nongenetic parental influences on the liability to psychiatric illness.

A long tradition in psychiatry has focused on parental traits that directly influence the liability to psychiatric disorders in offspring. Because these traits rarely resemble the disorders they cause, traditional models of cultural transmission (which assume that "like perpetuates like") may not be appropriate. The author develops and illustrates several models for indirect vertical cultural transmission of psychiatric illness. These models generate falsifiable predictions about the pattern of risk in relatives of affected individuals. For example, all such models predict a substantially higher risk of illness in siblings than in offspring of affected individuals. It is now possible to develop and test rigorous models for the cultural transmission of psychiatric illness.

Culture↗
PubMed2002

Regulatory modules shared within gene classes as well as across gene classes can be detected by the same in silico approach.

Transcriptional regulation depends on the binding of transcription factors to their corresponding binding sites. The response to cellular signals is often mediated by the cooperative binding of transcription factors to well defined regulatory modules consisting of at least two transcription factor binding sites. Such regulatory modules can be responsible for the common regulation of genes within a gene class or confer a common function to promoters belonging to different gene classes. We developed in silico models representing a common framework of potential regulatory sites specific for one promoter class (actins). We also generated models for two different functional promoter modules both of which confer responsiveness to tumor necrosis factor (TNF) and interferon (IFN) to a variety of promoters. All models exhibited high selectivity, e.g. the mammalian muscle actin promoter model produced no false negatives in a database search.

Actins↗
PubMed1998

A neural model of the saccade generator in the reticular formation.

A neural model is developed of the neural circuitry in the reticular formation that is used to generate saccadic eye movements. The model simulates the behavior of identified cell types-such as long-lead burst neurons, short-lead excitatory and inhibitory burst neurons, omnipause neurons, and tonic neurons-under many experimental conditions. Simulated phenomena include: saccade staircases, duration and amplitude of cell discharges for saccades of variable amplitude, component stretching to achieve straight oblique saccades, saturation of saccade velocity after saturation of saccade amplitude in response to high stimulation frequencies, trade-offs between saccade velocity and duration to generate constant saccade amplitude, conservation of saccade amplitude in response to sufficiently brief stimulation of omnipause neurons, and high velocity smooth eye movements evoked by high levels of electrical stimulation of the superior colliculus. Previous saccade generator models have not explained this range of data. These models have also invoked mechanisms for which no neurophysiological evidence has been forthcoming, such as resetable integrators, perfect integrators, or target position movement commands. The present model utilizes only known reticular formation neurons. It suggests that a key part of the feedback loop within the saccade generator is realized by inhibitory feedback from short-lead to long-lead burst neurons, in response to excitatory feedforward signals from long-lead to short-lead burst neurons. When this property is combined with opponent interactions between agonist and antagonist muscle-controlling neurons, and motor error, or vector, inputs from the superior colliculus and other saccade-controlling brain regions, all of the above data can be explained. Taken together, these components generate a saccade reset cycle whereby activation of long-lead burst neurons inhibits omnipause neurons and thereby disinhibits short-lead excitatory burst neurons. The excitatory short-lead burst neurons can then respond to excitatory inputs from the long-lead burst neurons. Outputs from the excitatory short-lead burst neurons are integrated by the tonic cells while they also inhibit the long-lead burst neurons via inhibitory burst interneurons. When this inhibition is complete, the omnipause neurons are disinhibited. The omnipause neurons can then, once again, inhibit the short-lead burst neurons, whose inhibition of the long-lead burst neurons is thereby removed. The saccadic cycle can then begin again. In response to sustained electrical input, this cycle generates a staircase of identical saccades whose properties match the data much better than the staircases proposed by alternative models. A comparative analysis of the hypotheses and predictive capabilities of other saccade generator models is provided.

Journal Article↗