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At least 37 records · Page 2Linked to original sources

The role of global and feature based information in gender classification of faces: a comparison of human performance and computational models.

Most computational models for gender classification use global information (the full face image) giving equal weight to the whole face area irrespective of the importance of the internal features. Here, we use a global and feature based representation of face images that includes both global and featural information. We use dimensionality reduction techniques and a support vector machine classifier and show that this method performs better than either global or feature based representations alone. We also present results of human subjects performance on gender classification task and evaluate how the different dimensionality reduction techniques compare with human subjects performance. The results support the psychological plausibility of the global and feature based representation.

Algorithms↗

Assessment of lifetime gained as a result of mammographic breast cancer screening using a computer model.

A computer model for the simulation of breast cancer screening (MBS) is used to calculate the results of screening in terms of lifetime. To optimize breast cancer screening protocols, risk (lifetime lost due to radiation-induced tumours) versus benefit (lifetime gained due to early detection of breast cancer) analyses are performed for a simulated stable Swedish female population. The present study focuses on the results of different screening strategies employing single view mammography, including starting and finishing ages of screening, time interval between successive screening sessions as well as the influence of high detection screening and differences between different populations, based on lifetime lost or gained. To test the stability of the recommendations with respect to possible changes in the variables used in MBS, calculations are also performed for high risk factors for breast tumour induction using both the additive and multiplicative risk models, fast growing breast tumours, late incidence of breast tumours and age dependent survival. The results of the simulations expressed in terms of lifetime gained suggest that a theoretical benefit can be obtained employing starting and finishing ages of 35 and 75 years, respectively. In terms of number of fatal breast tumours, the favourable screening period is 40-80 years. It is concluded that the recommendations are stable for changes in the input variables of MBS. The benefits of higher detection screening are more marked for younger than for older women. A high screening frequency results in more lifetime gained, especially at relatively young ages, whereas for older ages the effect is only marginal.

Adult↗

Effects of early ethanol exposure on dendrite growth of cortical pyramidal neurons: inferences from a computational model.

A computational model has been used to infer rules governing dendritic growth of layer 2/3 associative pyramidal neurons in a rat model of foetal alcohol syndrome. Basal dendrites were studied in adult rats exposed to ethanol during the first postnatal week. Results suggest that ethanol exposure during early postnatal life affects mainly the branching of dendrites rather than their elongation.

Age Factors↗

Predicting gas chromatographic separation and stationary-phase selectivity using computer modeling.

A computer modeling technique has been developed which allows for the prediction of chromatographic separation and stationary-phase selectivity. This technique enables development of application-specific gas chromatographic columns by allowing for the simultaneous optimization of physical dimensions, flow and temperature programs, and stationary-phase composition. Stationary-phase selectivity is the most powerful tool available to achieve a separation; however most commercially available columns were not designed to have a selectivity specific to the separations for which they are used. The techniques described in this paper were developed to address this need.

Journal Article↗

Prehospital intravenous fluid therapy: physiologic computer modelling.

A computer model incorporating known behavior of the cardiovascular system and intravascular:interstitial fluid exchange was designed which allowed bleeding rate, IV infusion rate, and prehospital care times to be independently specified. All possible circumstances were examined. The model shows that IV's are potentially of benefit only when all of the following occur: 1) the bleeding rate is initially 25-100 ml/min, 2) the prehospital time exceeds 30 minutes, and 3) the IV infusion rate is approximately equal to the bleeding rate. IV infusions therefore appear of little benefit in the usual urban environment and have a sharply limited role overall. The possibility of pulmonary edema from fluid overload in nonhypovolemic patients, and reluctance of field personnel to infuse fluid at the rates necessary to produce benefit raise further questions about realistic benefit of IV's in all but the most rural systems.

Bleeding Time↗

Specificity and plasticity of retinotectal connections: a computational model.

A computational model is presented which simulates the development and regeneration of orderly connections between retinal fibers and tectal cells in frogs and goldfish. The model distinguishes two aspects of retinotectal connectivity: (1) the contact adhesion between retinal fibers and tectal cells as mediated by fixed chemospecific markers and (2) the formation of modifiable synapses between them. Chemospecificity is assumed to be an intrinsic property of both the retina and tectum and is modeled as a graded distribution of a binding determinant or marker. Synapse formation depends upon the timing of neural activity as well as on the intinsic chemospecificity of retinotectal contacts. In addition to the normal development and regeneration of the retinotectal map, the model simulates the compressed, expanded, translocated, and rotated maps that have been found in surgically manipulated contexts. There examples of plasticity in the retinotectal map can be simulated without assuming any changes in the marker distributions. Moreover, the model demonstrates that a very shallow gradient of a single marker suffices to organize retinotectal connections in a variety of contexts.

Afferent Pathways↗

Respiratory analogue computer model.

An analogue computer model has been constructed to simulate the dynamic behaviour of the human cardiorespiratory system for studying the effect of changes in different system-variables--as alveolar ventilation, functional residual capacity (FRC) of the human lung and the cardiac output--on the partial pressure of carbon dioxide in the arterial and mixed venous blood (pCO2a, pCO2v). The respiratory analogue computer model (RACM) simulates reliably well-known clinical physiological as well as pathological phenomena. Reducing FRC or breath rate an oscillation of pCO2a has been developed, but the mean value has not been changed. In alveolar hypoventilation the pCO2 of blood increases in good conformity with the clinical experience. Reducing cardiac output a characteristic dissociation appeared: pCO2v and pCO2a diverged from each other by increasing pCO2v and decreasing pCO2a. Since in general clinical practice of intensive care only arterial blood gas values are checked regularly, the conclusion that the patient's condition is improving by decreasing pCO2a is a serious misinterpretation in this case, because peripheral tissues are in balance with the increasing venous carbon dioxide tension, and consequently cannot get rid of this toxic agent. The computer-model-based conclusion has led to the practice of sampling both arterial and venous carbon dioxide tensions for better state assessment of seriously ill patients.

Carbon Dioxide↗

Linking animal models of psychosis to computational models of dopamine function.

Psychosis is linked to dysregulation of the neuromodulator dopamine and antipsychotic drugs (APDs) work by blocking dopamine receptors. Dopamine-modulated disruption of latent inhibition (LI) and conditioned avoidance response (CAR) have served as standard animal models of psychosis and antipsychotic action, respectively. Meanwhile, the 'temporal difference' algorithm (TD) has emerged as the leading computational model of dopamine neuron firing. In this report TD is extended to include action at the level of dopamine receptors in order to explain a number of behavioral phenomena including the dose-dependent disruption of CAR by APDs, the temporal dissociation of the effects of APDs on receptors vs behavior, the facilitation of LI by APDs, and the disruption of LI by amphetamine. The model also predicts an APD-induced change to the latency profile of CAR--a novel prediction that is verified experimentally. The model's primary contribution is to link dopamine neuron firing, receptor manipulation, and behavior within a common formal framework that may offer insights into clinical observations.

Action Potentials↗

Physically correlated muscle activation for a human head and neck computational model.

A computational 50th percentile male head and neck complex model was correlated to physical experimental data. The computational model utilizes 15 muscle pairs represented by the Hill Muscle Model with the complete head/neck system modeled using MADYMO. The model was used for analysis and optimization of activation and deactivation of muscle activity in flexion and extension. Sensitivity analysis performed using the model shows that, of the multiple parameters within the Hill Model, activation level and timing prove to have the greatest effect on the system kinematics. In addition, the rate by which an activation level is changed becomes an important factor in the simulation. With the use of numerical optimization techniques, a pattern was determined for the applied activation/deactivation rates and timing of flexors and extensors during flexion and extension of the head. The numerical optimization result correlated to within 9% of measured value during the initial flexion of the head. The optimized activation model reflected an activation onset 90 ms after the start of the impulse load, which agrees with published reaction times of muscles. Activation and deactivation rates for the extensors were found to be 1.7 and 0.29%, respectively. While the onset of activation of the flexor muscles occurred before rebound, it was found that muscles, at near the mid-plane, were triggered by the optimized model to abate the flexion. Rates of activation and deactivation of the flexors were found to be 0.9 and 0.3%, respectively. Both the extensors as well as the flexors were found to activate only up to 70% before deactivating. Therefore, it was evident from this study that using the Hill Muscle Model with the activation parameter modeled as binary, 0 or 100%, may lead to inaccurate simulation results.

Acceleration↗

The intraaortic balloon pump: a nonlinear digital computer model.

A computer based model for in-series cardiac assistance by intraaortic balloon pumping was developed in this study. The model, obtained from the Navier-Stokes and Continuity equations, was capable of computing pressures, volumetric flow rates and radii through the arterial system. The model was used to study the effects of a wide range of assist device timing adjustments on the benefits of ventricular assistance under conditions corresponding to those measured during animal experiments. The model was also used to study the relationship between device timing adjustments and the benefits of ventricular assistance under constant cardiovascular state conditions. Such studies are important in isolating the response of the system to assist device phasing from the response associated with system state. The results obtained in this study demonstrate that the hemodynamic response of the cardiovascular system to intraaortic balloon pumping is a sensitive function of both the state of the cardiovascular system and phasing of the assist device.

Animals↗

Blood conservation in coronary artery bypass surgery: prediction with assistance of a computer model.

A computer assisted model was created with the data from 514 consecutive coronary bypass patients in order to predict the potential need of a blood transfusion. During this time period strict management protocols were used. In this series 261 (55.9%) patients were never and 46 (9.9%) were only intraoperatively transfused. Intra- and postoperative transfusions were necessary for 160 (34.2%) patients. Preoperative hematocrit, age, sex, and weight were the statistically significant parameters in the development of the model.

Adult↗

[Truncation family selection and nonsystematic inbreeding leads to a rapid fixation of a pattern of mobile genetic elements in a computer model].

A computer simulation model of the population dynamics of a polygenic system and a pattern of mobile genetic elements (MGEs) under directional truncation selection for a quantitative trait was developed. Modifier MGEs were shown to be rapidly and adaptively fixed (or lost) together with the modified polygenes. Marker MGEs and independent MGE copies were fixed and lost just as rapidly but in a random manner. Using specific marking of initial haploid genomes and direct computing of the mean proportion of identical encounters at each locus in each generation, it was shown that the mean nonselective inbreeding coefficient F(n) dramatically increases in the course of selection, reaching values 0.7-0.9 in 15-20 generations. As a result, adaptive homozygotization of polygenes and modifier MGEs and random homozygotization of marker MGEs, independent MGE copies, and all other genes of the genome occurs. These results confirm the hypothesis on the "champion" polygene pattern advanced earlier to explain the data of selection experiments.

Animals↗

Effect of acyl chain unsaturation on the conformation of model diacylglycerols: a computer modeling study.

In a previous modeling study we identified an angle iron-shaped conformation of docosahexaenoic acid and showed that an sn-1-stearoyl diacylglycerol (DG) that contained an sn-2-docosahexaenoyl group in this conformation could adopt a highly regular shape. In the present study we compared the properties of this DG with those of sn-1-stearoyl DGs that contained other unsaturated fatty acyl groups in the sn-2 position. The major findings were that: 1) sn-1-stearoyl DGs that contain polyenoic fatty acids in the sn-2 position can assume regular shapes, and 2) these shapes differ depending on the location of the double bonds. sn-2-Polyenoic fatty acyl groups with a double bond sequence that begins close to the carboxyl ester bond are associated with one type of regular shape, while sn-2-polyenoic fatty acyl groups with a double bond sequence that begins toward the middle of the chain are associated with another. Such shapes would not have been predicted by current ideas relating membrane fluidity to unsaturation. In contrast, another finding of the present study, that sn-1-stearoyl-2-oleoyl DG can adopt, at best, only a highly irregular shape is in good agreement with the results of previous investigators.

Acylation↗

Computational models of neuromodulation.

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

Animals↗

A stylized computational model of the head for the reference Japanese male.

Computational models of human anatomy, along with Monte Carlo radiation transport simulations, have been used by Snyder et al. [MIRD Pamphlet No. 5, revised (The Society of Nuclear Medicine, New York, 1978)], Cristy and Eckerman [ORNL/TM-8381/VI, Oak Ridge National Laboratory, Oak Ridge, TN (1987)] and Zubal et al. [Med. Phys. 21, 299-302 (1994)] to estimate internal organ doses from internal and external radiation sources. These were created using physiological data from Caucasoid subjects but not from other races. There is a need for research to determine whether the obvious differences from the Caucasoid anatomy make these models unsuitable for estimating the absorbed dose in other races such as the Mongoloid. We used the cranial region of the adult Japanese male to represent the Mongoloid race. This region contains organs that are highly sensitive to radiation. The cranial region of a physical phantom produced by KYOTO KAGAKU Co., LTD. using numerical data from a Japanese Reference Man [Tanaka, Nippon Acta. Radiol. 48, 509-513 (1988)] was used to supply the data for the geometry of a stylized computational model. Our computational model was constructed with equations rather than voxel-based, in order to deal with as small a number of parameters as possible in the computer simulation experiment. The accuracy of our computational model was checked by comparing simulated experimental results obtained with MCNP4C with actual doses measured with thermoluminescence dosimeters (TLDs) inside the physical phantom from which our computational model was constructed. The TLDs, whose margin of error is less than +/-10%, were arranged at six positions. Co-60 was used as the radiation source. The irradiated dose was 2 Gy in terms of air kerma. In the computer simulation experiments, we used our computational model and Cristy's computational model, whose component data are those of the tissue substitute materials and of the human body as published in ICRU Report 46. The observed absorbed dose values (Gy) at all six points were calculated as the percentage difference between MCNP4C simulation and the TLDs. In our computational model, the average values of all the percentage differences were 6.0+/-4.0% (tissue substitute materials) and 7.6+/-6.6% (ICRU Report 46), respectively. In Cristy's model, the corresponding values were 20.4+/-3.8% (tissue substitute materials) and 21.0+/-4.1% (ICRU Report 46), respectively. Considering the margin of error in the radiation sensitivity of the TLDs, this study validates our computational model as a test object for radiation dosimetry studies.

Asian People↗

Hypothesis testing via integrated computer modeling and digital fluorescence microscopy.

Computational modeling has the potential to add an entirely new approach to hypothesis testing in yeast cell biology. Here, we present a method for seamless integration of computational modeling with quantitative digital fluorescence microscopy. This integration is accomplished by developing computational models based on hypotheses for underlying cellular processes that may give rise to experimentally observed fluorescent protein localization patterns. Simulated fluorescence images are generated from the computational models of underlying cellular processes via a "model-convolution" process. These simulated images can then be directly compared to experimental fluorescence images in order to test the model. This method provides a framework for rigorous hypothesis testing in yeast cell biology via integrated mathematical modeling and digital fluorescence microscopy.

Computational Biology↗

A computational model for quantitative analysis of cell cycle arrest and its contribution to overall growth inhibition by anticancer agents.

Most anticancer agents induce cell cycle arrest (cytostatic effect) and cell death (cytotoxic effect), resulting in the inhibition of population growth of cancer cells. When asynchronous cells are to be examined, the currently used flow cytometric method can not provide checkpoint-specific and quantitative information on the drug-induced cell cycle arrest. Hence, despite its significance, no good method to analyze in detail the mechanism of cell cycle arrest and its contribution to overall growth inhibition induced by an anticancer agent has yet been established. We describe in this study the development of a discrete time (Markov model)-based computational model for cell cycle progression / arrest with transition probability (TP(i)) as a model parameter. TP(i) was calculated using model equations that include easily measurable parameters such as the fraction of cells in each cell cycle phase and population doubling time. The TP(i) was then used to analyze checkpoint-specific and quantitative changes in cell cycle progression. We also used TP(i) in a Monte-Carlo simulation to predict growth inhibition caused by cell cycle arrest only. Human SCLC cells (SBC-3) exposed to UCN-01 were used to validate the model. The model-predicted growth curves agreed with the observed data for SBC-3 cells not treated or treated at a cytostatic concentration (0.2 mM) of UCN-01, indicating validity of the present model. The changes in TP(i) indicated that UCN-01 reduced the G(1)-to-S transition rate and increased the S-to-G(2) / M and G(2) / M-to-G(1) transition rates of SBC-3 cells in a concentration- and time-dependent manner. When the model-predicted growth curves were compared with the observed data for cells treated at a cytotoxic concentration (2 mM), they suggested that 22% out of 65% and 32% out of 73% of the growth inhibition could be attributed to the cell cycle arrest effect after 48 h and 72 h exposure, respectively. In conclusion, we report here the establishment of a novel method of analysis that can provide checkpoint-specific and quantitative information about cell cycle arrest induced by an anticancer agent and that can be used to assess the contribution of cell cycle arrest effect to the overall growth inhibition.

Alkaloids↗

Identifying constraints that govern cell behavior: a key to converting conceptual to computational models in biology?

Cells must abide by a number of constraints. The environmental constrains of cellular behavior and physicochemical limitations affect cellular processes. To regulate and adapt their functions, cells impose constraints on themselves. Enumerating, understanding, and applying these constraints leads to a constraints-based modeling formalism that has been helpful in converting conceptual models to computational models in biology. The continued success of the constraints-based approach depends upon identification and incorporation of new constraints to more accurately define cellular capabilities. This review considers constraints in terms of environmental, physicochemical, and self-imposed regulatory and evolutionary constraints with the purpose of refining current constraints-based models of cell phenotype.

Adaptation, Physiological↗