Albert Heyman, M.D. Boundless role model for generations of physicians.
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History, 20th Century↗
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Results for “Generative models”
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[Unfavorable results of testing model sound generators designed for repelling mosquitoes].
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Evaluation Studies as Topic↗
Animation of computer-generated molecular models.
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Chemical Phenomena↗
Re-examination of human speech generation acoustic model.
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Humans↗
Generating biological models through gene transfer to domestic animals.
Transgenic domestic animals remain infrequently used as models for biochemical, biomedical or pharmaceutical studies. The difficulty in obtaining these animals and the cost of their maintenance explains this situation. This review briefly summarizes the different techniques of gene transfer, targeted or not, and also the techniques for constructing vectors for transgene expression. A few examples of domestic animal models are also reported.
Animals↗
Meta-modelling: the appropriate solution for a family of applications.
The aim of this paper is to present an appropriate framework able to generate models and to implement them, in the objective of computerizing a family of medico-technical reports. The accelerated rate of technical development makes it necessary to design computerized applications independently of data-processing technology. This apparent paradox is a quite real challenge which needs research and development software environments to support frameworks. In this article, we present a meta-model (i.e. a generic structure - supported by the Méta-Gen software tool) ) which is able to generate various models of medico-technical reports. These models in turn are able to generate various types of instances. This meta-model is a "Meta-medical record", it is constituted of basic concepts : " User Semantic Group " to which are attached a set of " sentence-type ", a set of several corpus of variables with a set of graphs ("navigators"). Five models (echocardiography for hospital "A", echocardiography for hospital "B", gastroscopy, fibercoloscopy A.E.P.). were already generated from this "Meta-Medical Record". A beginning of implementation in echocardiography report is presented here. The advantages are a very thorough personalization of the document for the user, and a greater independence of the design diagram from the technological platform.
Echocardiography↗
Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning.
Mean firing rates (MFRs), with analogue values, have thus far been used as information carriers of neurons in most brain theories of learning. However, the neurons transmit the signal by spikes, which are discrete events. The climbing fibers (CFs), which are known to be essential for cerebellar motor learning, fire at the ultra-low firing rates (around 1 Hz), and it is not yet understood theoretically how high-frequency information can be conveyed and how learning of smooth and fast movements can be achieved. Here we address whether cerebellar learning can be achieved by CF spikes instead of conventional MFR in an eye movement task, such as the ocular following response (OFR), and an arm movement task. There are two major afferents into cerebellar Purkinje cells: parallel fiber (PF) and CF, and the synaptic weights between PFs and Purkinje cells have been shown to be modulated by the stimulation of both types of fiber. The modulation of the synaptic weights is regulated by the cerebellar synaptic plasticity. In this study we simulated cerebellar learning using CF signals as spikes instead of conventional MFR. To generate the spikes we used the following four spike generation models: (1) a Poisson model in which the spike interval probability follows a Poisson distribution, (2) a gamma model in which the spike interval probability follows the gamma distribution, (3) a max model in which a spike is generated when a synaptic input reaches maximum, and (4) a threshold model in which a spike is generated when the input crosses a certain small threshold. We found that, in an OFR task with a constant visual velocity, learning was successful with stochastic models, such as Poisson and gamma models, but not in the deterministic models, such as max and threshold models. In an OFR with a stepwise velocity change and an arm movement task, learning could be achieved only in the Poisson model. In addition, for efficient cerebellar learning, the distribution of CF spike-occurrence time after stimulus onset must capture at least the first, second and third moments of the temporal distribution of error signals.
Action Potentials↗
Three-dimensional quantitative structure activity relationships (3-D-QSAR) of antihyperglycemic agents.
A three-dimensional quantitative structure activity relationship study (3-D-QSAR) was performed on a set of thiazolidinedione antihyperglycemic agents using the comparative molecular field analysis (CoMFA) method. The CoMFA models were derived from a training set of 53 compounds. Fifteen compounds, which were not used in model generation were used to validate the CoMFA models. All the compounds were superimposed to the template structure by atom-based and shape-based strategies. The SYBYL QSAR rigid body field fit was also used for aligning the ligands. A total of twelve different alignments were generated. The resulting models exhibited a good cross-validated r2cv values (0.624-0.764) and the conventional r2 values (0.689-0.921). A more robust cross-validation test using cross-validation by 2 groups (leave half out method) was performed 100 times to ascertain the predictiveness of the CoMFA models. The mean of r2cv values from 100 runs ranged from 0.611-0.690. Few models exhibited good external predictivity. These models were then used to define a hypothetical receptor model for antihyperglycemic agents.
Animals↗
Generating correlation matrices with model error for simulation studies in factor analysis: a combination of the Tucker-Koopman-Linn model and Wijsman's algorithm.
Most simulation studies in factor analysis follow a process of constructing population correlation matrices from the common-factor model and generating sample correlation matrices from the population matrices. In the common-factor model, the population correlation matrix is perfectly fit by the model's containing common and unique factors. However, since no mathematical model accounts exactly for the real-world phenomena that it is intended to represent, the Tucker-Koopman-Linn model (1969) is more realistic for generating correlation matrices than the conventional common-factor model because the former incorporates model error. In this paper, a procedure for generating population and sample correlation matrices with model error by combining the Tucker-Koopman-Linn model and Wijsman's algorithm (1959) is presented. The SAS/IML program for generating correlation matrices is described, and an example is also provided.
Algorithms↗
Assessment of comparative modeling in CASP2.
An assessment is presented for all submissions to the comparative modeling challenge in the 1996 Critical Assessment of Structure Prediction (CASP2). Of the original 12 target structures, 9 were solved prior to the meeting: 8 by X-ray crystallography and 1 by NMR spectroscopy. These targets varied over a large range of difficulty, as assessed by the percentage sequence identity with the principal parent structure, which ranged from 20% up to 85%. The overall quality of the models reflected the similarity of the principal parent. As expected, when the sequence alignment was correct, the core was accurately modeled, with the largest deviations occurring in the loops. Models were built which gave C alpha root-mean-square deviations (RMSDs) compared with the observed structure of < 1 A for targets with high parental similarity; even at 26% sequence identity, the best model structures had C alpha deviations of only 2.2 A. Overall, these deviations are comparable with those observed between the parent structure and the target, but locally there are several examples where the model approaches closer to the target than does the parent. There were three targets below 25% sequence identity, and the models generated for these targets were, in general, significantly less accurate. This principally reflects errors in the alignment which, if systematically shifted, can generate C alpha RMSDs > 18 A. Compared with CASP1, the geometry of the models was significantly improved with no D-amino acids. By far the major contribution to RMSD error was the alignment accuracy, which varied from 100% down to 7% over the range of targets. In the structurally variable regions, global shifts, caused by hinge bending, were the major source of error, giving significantly lower local RMSDs than global RMSDs. In over 50% of these noncore regions, the difference between global and local RMSDs was more than 3 A, and was as high as 10 A for one structurally variable region. For the side chains, the chi 1 RMSDs are strongly correlated with the C alpha RMSDs. For models with C alpha deviations less than 1 A, on average 78.5% of side chains are placed in the correct rotamer, although the chi 1 RMSDs, though clearly better than random, were disappointing at around 46 degrees. As the backbone deviations increased, the side chain placement became less accurate, with an average chi 1 RMSD of 75 degrees on a 1.5-2.5 A C alpha backbone (average 51.4% correct rotamer). Refinement by energy minimization or molecular dynamics made only minor adjustments to improve local geometry and generally made small, but not significant, improvements to the RMSD. In total, 19 groups submitted 62 models (89 coordinate sets) that could be assessed. Most modelers used manual adjustments to sequence alignments and, in general, good alignments were obtained down to 25% sequence identity. The modeling methods ranged from "classical" modeling, involving core building followed by loop and side chain addition, to more sophisticated approaches based on probability distributions, Monte Carlo sampling or distance geometry. For each target, several groups produced equally good models, given the expected errors in the structures (about 0.5 A). No one method came out as clearly superior, although the approaches that inherit directly from the parents generally performed better than the more radical techniques. However, for each target there were some poor models, usually reflecting a poor sequence alignment, and the range of accuracy for each target is therefore large. Fully automated methods are able to perform very well for "easy" targets (85% sequence identity with parent), but when modeling using a distantly related parent, care and expertise, especially in performing the alignment, still appear to be important factors in generating accurate models.
Models, Molecular↗
Neural network implementation of a three-phase model of respiratory rhythm generation.
A mathematical model of the central neural mechanisms of respiratory rhythm generation is developed. This model assumes that the respiratory cycle consists of three phases: inspiration, post-inspiration, and expiration. Five respiratory neuronal groups are included: inspiratory, late-inspiratory, post-inspiratory, expiratory, and early-inspiratory neurons. Proposed interconnections among these groups are based substantially on previous physiological findings. The model produces a stable limit cycle and generally reproduces the features of the firing patterns of the 5 neuronal groups. When simulated feedback from pulmonary stretch receptors is made to excite late-inspiratory neurons and inhibit early-inspiratory neurons, the model quantitatively reproduces previous observations of the expiratory-prolonging effects of pulses and steps of vagal afferent activity presented in expiration. In addition the model reproduces expected respiratory cycle timing and amplitude responses to change of chemical drive both in the absence and in the presence of simulated stretch receptor feedback. These results demonstrate the feasibility of generating the respiratory rhythm with a simple neural network based on observed respiratory neuronal groups. Other neuronal groups not included in the model may be more important for shaping the waveforms than for generating the basic oscillation.
Animals↗
Power of segregation analysis for detection of major gene effects on quantitative traits.
The power to detect major gene effects by rejection of the "no major gene" null hypothesis against a mixed model alternative was determined in random samples of nuclear families over a variety of conditions. Benchmarks have been developed using a varying number of families whose structure includes both parents and three children. Phenotypes were simulated assuming a Mendelian major gene under either recessive or dominant inheritance, with 0-30% residual polygenic heritability. Three trait prevalences--5, 10, and 20%--were considered in combination with increasing displacement between homozygous means, spanning a range of 14 to 36% of the phenotypic variance attributable to the major gene effect. All other assumptions of the traditional mixed model were adopted in the generating models. Segregation analysis was carried out on the simulated data sets and the proportion of samples out of 200 replications in which the null hypothesis q = 0 was rejected is reported as the power. Thus, failure to detect a major gene effect in this context is solely due to sampling variation, since no other perturbations were introduced. In general, there appears to be greater power to detect dominant major gene effects as opposed to recessive ones using otherwise comparable parameter values, and the effect of varying sibship size under dominant models appears to be greater as well. The use of joint vs. conditional likelihood calculations also was evaluated: substantial drops in power were observed when using conditional likelihoods under recessive inheritance, while the differences in power appeared to be nominal under dominant inheritance. The results of this investigation are offered as a guide to assist in the design of family studies whose aim is to detect major gene effects.
Bias↗
A modified Trigg's Tracking Variable as an 'advisory' alarm during anaesthesia.
We wished to assess the accuracy of a modified form of Trigg's Tracking Variable (TTV) at detecting the onset of changes in systolic blood pressure. A computer model generated systolic blood pressures which changed to a new value after period of stability. A separate algorithm based on TTV indicated when a 'significant' change had been detected. This signal occurred when TTV had exceeded a set limit (0.8-0.99) a predetermined number of times (1-10). Five anaesthetists were shown 40 sets of data generated by same the computer model and asked to indicate the onset of changes. The greatest number of changes (94.1%) were correctly identified when TTV exceeded 0.92 on 4 consecutive determinations. The onset of the trend was detected after an average delay of 140 s. The anaesthetists correctly detected 85% of the changes after an average delay of 162 s. There was no statistically significant difference between the anaesthetists and the algorithm, although only one anaesthetist performed better than the modified TTV. The modified TTV detected changes in simulated invasive systolic blood pressures faster and more accurately than four of a group of five anaesthetists. Such simple trend detection systems may be useful as 'advisory' alarms.
Algorithms↗
Spinal motor patterns in the turtle.
Rhythmic alternation between ipsilateral hip flexors and extensors occurs during the normal pattern of fictive rostral scratching in response to unilateral midbody stimulation in D3-end turtles (complete spinal transection posterior to the forelimb enlargement). Unilateral midbody stimulation evokes rhythmic bursts of ipsilateral hip flexor activity with no hip extensor activity in D3-end turtles with D6-D7 contralateral hemisection (transverse hemisection anterior to the hindlimb enlargement). Bilateral midbody stimulation in these turtles evokes reconstruction of rhythmic alternation between intact side hip flexors and extensors. These normal motor patterns in response to two-site stimulation are reconstructed because one-site stimulation in this preparation activates only hip flexor rhythms (J. Neurosci. 18: 467). Hip flexor rhythms can therefore occur without hip extensor activation. This supports the concept that reciprocal inhibition between flexor and extensor interneurons is not required for flexor motor rhythm generation. Reciprocal inhibition, when present, also contributes to rhythmicity (J. Neurophysiol. 78: 3479; see also Currie and Gonsalves, this volume). Both mechanisms for rhythmicity are included in the Grillner unit burst generator model: hip flexor unit burst generators may be rhythmogenic in the absence of hip extensor activity and reciprocal inhibition contributes to rhythmogenesis. Contralateral midbody stimulation assisted in the activation of ipsilateral hip extensor rhythmicity during reconstructed rostral scratching. This result provides additional support for the hypothesis that a bilateral shared core of hip interneuronal circuitry plays a critical role in the generation of the normal pattern of fictive rostral scratching (J. Neurosci. 15: 4343).
Animals↗
The five generations of American medical revolutions.
Current medical authors frequently use the term "revolution," yet American medicine is resisting change rather than embracing it. The last completed American medical revolutionary movement was the specialist-technologist movement of the late 19th and early 20th centuries. This paper describes a five-generational model of revolution. First-generation persons foment revolution; second-generation persons shape it into workable form and precipitate conflict; third-generation persons join the fight only when it appears to be all but won; fourth-generation persons enjoy the fruits of revolution; and fifth-generation persons, having risen to domination in the mature system, resist all attempts at reform by the next round of revolutionaries. In political revolutions, severe reactionary activity by the ruling party is often an indicator of an imminent overthrow by revolution. In scientific revolutions, the opposition of an established (specialist-technologist) paradigm to an emerging alternative (generalist) paradigm increases in intensity as the old order declines in strength; the opposition becomes most fierce just before the collapse of the old order. American specialist-technologist medicine, declining into its senescent fifth generation, will resist all but incremental change whenever possible, and accept major change only by force.
Family Practice↗
Ultrastructure of chromatin. II. Three-dimensional reconstruction of isolated fibers.
Electron-microscope tomography has been used to reconstruct isolated, negatively stained chromatin fibers from Necturus maculosus erythrocytes. Tilt series micrographs from +70 degrees to -70 degrees at 5 degrees intervals were obtained, allowing a reconstruction resolution of 3.3 nm for fibers lying parallel to the tilt axis. The fibers were found to be flattened in the plane of the carbon support, and also stained differentially according to the distance from the carbon. A number of methods of presenting the three-dimensional information were explored. Especially useful was an automatic peak search method for locating putative nucleosome positions coupled with the production of a computer-generated model. Other valuable techniques included the generation of projection stereograms and construction of solid models. A peripheral location of nucleosomes in the chromatin fiber was indicated, and helical arrangements of nucleosomes were observed over short regions. However, no long-range ordering of nucleosomes was apparent. The extent to which this lack of order may be the result of events occurring during the preparation of chromatin for electron microscopy is discussed.
Animals↗
Topological structure of rat mesenteric microvessel networks.
Microvascular lengths, diameters, and flow directions were determined in all vessel segments (n = 1303) between bifurcations in three complete rat mesenteric microvessel networks (25 mm2 each) using intravital video- and photomicroscopy. The classification of vessel segments as arteriolar, venular, or av-segments (all segments connecting the arteriolar to the venular tree) was based on purely topological criteria. The topological structure of the networks was analyzed using the Horton-Strahler technique and a new generation scheme. Generation numbers were assigned to the vessel segments on the basis of the number of upstream (in the arteriolar tree) and downstream (in the venular tree) bifurcations. The mean generation number of the av-segments, a characteristic parameter of the generation scheme, reflects the topological structure of the network more accurately than Horton's branching ratio Rb. Both the arteriolar and venular tree of the mesenteric networks were found to be dichotomous branching structures which were neither strictly symmetric nor strictly asymmetric. The topological information obtained was compared to network models generated by different random branching algorithms. The result of this comparison suggests that the network structure changes at a certain generation level. Distal to this generation level, the mesenteric networks resemble a model network generated by random branching at any segment, while the proximal portion is similar to a model allowing random branching at terminal segments only.
Animals↗
Identification models of the nervous system.
It has been widely observed that when artificial neural networks are trained by supervised learning to do computations that also occur in the nervous system, the behavior of the model neurons often closely resembles that of the real neurons involved in the task. It is not immediately clear why this should be the case or what use can be made of models generated by supervised learning. Here, recent developments are reviewed and analysed in an attempt to clarify these issues. This analysis is facilitated by treating supervised learning models of the brain as a special case of system identification, a general and well-studied modeling paradigm. The neural systems identification paradigm provides a systematic way to generate realistic models starting with a high-level description of a hypothesized computation and some architectural and physiological constraints about the area being modeled. There is no inherent limitation to the realism that can be incorporated into identification models. This approach eliminates the need to find neural implementation algorithms by ad hoc means and provides neuroscientists with a convenient way to build models that account for observed data.
Algorithms↗