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At least 451 records · Page 25Linked to original sources
PubMed1987

A model for quantitative evaluation of embolic stroke therapy.

We developed a small animal embolic stroke model for pharmacological screening trials. Microspheres are injected into the carotid circulations and group embolus dose-response relationships are calculated. Emboli quantity is related to neurologic injury, and small changes in neurologic function are detectable. Rabbits tolerated twice as many microspheres when cyproheptadine-treated after embolization. This demonstrated both the sensitivity of the model and the value of serotonin antagonists in reducing neurological injury.

Animals↗
PubMed1983

A model for quantitative sampling of myocardial venous blood in the pig.

A lack of good models for studies of myocardial metabolism prompted us to develop a model which allows the continuous measurement of myocardial blood flow and sampling of adequate amounts of coronary sinus (c.s.) blood without admixture of blood from the right atrium, with the working heart in situ. In the pig the left azygos vein drains into the c.s. and can easily be cannulated after thoracotomy. Thus, a shunt to the right atrium can be established by closing the entrance of the c.s. into the right atrium by a stitch ligature. More than 90% of shunt flow originates from the left ventricular myocardium. It is presently shown that establishing the shunt does not compromise myocardial flow, and there are no observable changes in left ventricular pressure, flow or dimensions. Myocardial flow in the drained and adjacent regions, as determined by injections of microspheres, and flow determined by electromagnetic flowmetry on the shunt are all identical. The model is stable during aortic constriction and isoproterenol infusion which induce expected changes in myocardial flow- and oxygen consumption. Thus, the model described is suitable for hemodynamic and metabolic studies of the left ventricular myocardium with the working heart in situ.

Animals↗
PubMed1997

A new model for quantitative in vivo microscopic analysis of thrombus formation and vascular recanalisation: the ear of the hairless (hr/hr) mouse.

The alteration of rheological blood properties as well as deterioration of vascular perfusion conditions and cell-cell interactions are major determinants of thrombus formation. Herein, we present an experimental model which allows for quantitative in vivo microscopic analysis of these determinants during both thrombus formation and vascular recanalisation. The model does not require surgical preparation procedures, and enables for repeated analysis of identical microvessels over time periods of days or months, respectively. After i.v. administration of FITC-dextran thrombus formation was induced photochemically by light exposure to individual arterioles and venules of the ear of ten anaesthetised hairless mice. In venules, epi-illumination induced rapid thrombus formation with first platelet deposition after 0.59 +/- 0.04 min and complete vessel occlusion within 7.48 +/- 1.31 min. After a 24-h time period, 75% of the thrombosed venules were found recanalised. Marked leukocyte-endothelial cell interaction in those venules indicated persistent endothelial cell activation and/or injury, even after an observation period of 7 days. In arterioles, epi-illumination provoked vasomotion, while thrombus formation was significantly (p <0.05) delayed with first platelet deposition after 2.32 +/- 0.22 min and complete vessel occlusion within 20.07 +/- 3.84 min. Strikingly, only one of the investigated arterioles was found recanalised after 24 h, which, however, did not show leukocyte-endothelial cell interaction. Heparin (300 U/kg, i.v.) effectively counteracted the process of thrombus formation in this model, including both first platelet deposition and vessel occlusion. We conclude that the model of the ear of the hairless mouse allows for distinct in vivo analysis of arteriolar and venular thrombus formation/recanalisation, and, thus, represents an interesting tool for the study of novel antithrombotic and thrombolytic strategies, respectively.

Animals↗
PubMed1994

Analysis of bursting in a thalamic neuron model.

We extend a quantitative model for low-voltage, slow-wave excitability based on the T-type calcium current (Wang et al. 1991) by juxtaposing it with a Hodgkin-Huxley-like model for fast sodium spiking in the high voltage regime to account for the distinct firing modes of thalamic neurons. We employ bifurcation analysis to illustrate the stimulus-response behavior of the full model under both voltage regimes. The model neuron shows continuous sodium spiking when depolarized sufficiently from rest. Depending on the parameters of calcium current inactivation, there are two types of low-voltage responses to a hyperpolarizing current step: a single rebound low threshold spike (LTS) upon release of the step and periodic LTSs. Bursting is seen as sodium spikes ride the LTS crest. In both cases, we analyze the LTS burst response by projecting its trajectory into a fast/slow phase plane. We also use phase plane methods to show that a potassium A-current shifts the threshold for sodium spikes, reducing the number of fast sodium spikes in an LTS burst. It can also annihilate periodic bursting. We extend the previous work of Rose and Hindmarsh (1989a-c) for a thalamic neuron and propose a simpler model for thalamic activity. We consider burst modulation by using a neuromodulator-dependent potassium leakage conductance as a control parameter. These results correspond with experiments showing that the application of certain neurotransmitters can switch firing modes.

Action Potentials↗
PubMed2003

An evolutionary model of carcinogenesis.

A quantitative model of carcinogenesis based on methods from population biology and game theory demonstrates normal cells in vivo occupy a ridge-shaped maximum in a well-defined tissue fitness landscape, a novel configuration that allows cooperative coexistence of multiple cellular populations. This state, although necessary for development of functioning multicellular organisms, is subject to invasion by fitter, mutant phenotypes permitting somatic evolution of cancer. The model demonstrates carcinogenesis is an emergent phenomenon requiring a sequence of evolutionary steps as cellular proliferation follows successful adaptation to varying environmental constraints. In the initial development of preneoplastic lesions, cellular proliferation is controlled exclusively by interactions with other cells, the extracellular matrix, and soluble or insoluble growth factors so that gain of function mutations in oncogenes, loss of function mutations in tumor suppressor genes, and disruption of normal senescence pathways will permit clonal expansion. This provides explicit selection mechanisms for the mutations depicted in the classical Fearon-Vogelstein model of colorectal carcinogenesis. The model demonstrates neoplastic cellular proliferation can also be promoted by alterations in the somatic landscape that reduce inhibitory signals produced by the normal cells and extracellular matrix. This is consistent with experimental evidence for a strong microenvironmental influence in tumorigenesis independent of genomic changes in the neoplastic populations. However, we find that these changes alone produce only self-limited neoplastic growth because cellular crowding alters system dynamics so that proliferation is dependent on substrate availability. Consequent cellular competition for critical nutrients results in Darwinian selection pressures favoring phenotypes that increase substrate delivery (e.g., angiogenesis) or uptake (e.g., amplify membrane transporters). These previously unknown substrate dynamics in the later stages of carcinogenesis provide a mechanism for evolution of cellular properties typically found in invasive cancers including the angiogenic and glycolytic phenotypes.

Animals↗
PubMed1999

Model-based quantitation of 3-D magnetic resonance angiographic images.

Quantification of the degree of stenosis or vessel dimensions are important for diagnosis of vascular diseases and planning vascular interventions. Although diagnosis from three-dimensional (3-D) magnetic resonance angiograms (MRA's) is mainly performed on two-dimensional (2-D) maximum intensity projections, automated quantification of vascular segments directly from the 3-D dataset is desirable to provide accurate and objective measurements of the 3-D anatomy. A model-based method for quantitative 3-D MRA is proposed. Linear vessel segments are modeled with a central vessel axis curve coupled to a vessel wall surface. A novel image feature to guide the deformation of the central vessel axis is introduced. Subsequently, concepts of deformable models are combined with knowledge of the physics of the acquisition technique to accurately segment the vessel wall and compute the vessel diameter and other geometrical properties. The method is illustrated and validated on a carotid bifurcation phantom, with ground truth and medical experts as comparisons. Also, results on 3-D time-of-flight (TOF) MRA images of the carotids are shown. The approach is a promising technique to assess several geometrical vascular parameters directly on the source 3-D images, providing an objective mechanism for stenosis grading.

Algorithms↗
PubMed2003

Continuous analysis of dissolved gaseous mercury (DGM) and mercury flux in two freshwater lakes in Kejimkujik Park, Nova Scotia: evaluating mercury flux models with quantitative data.

Diurnal patterns for dissolved gaseous mercury (DGM) concentration, mercury flux, several water variables (pH, oxidation reduction potential (ORP), water temperature), and meteorological variables (wind speed, air temperature, % relative humidity, solar radiation) were measured in two lakes with contrasting dissolved organic carbon (DOC) concentrations in Kejimkujik Park, Nova Scotia. A continuous analysis system made it possible to measure quick changes in DGM over time. Consistently higher DGM concentrations were found in the high DOC lake as compared to the low DOC lake. An examination of current mercury flux models using this quantitative data indicated some good correlations between the date and predicted flux (r ranging from 0.27 to 0.83) but generally poor fit (standard deviation of residuals ranging from 0.97 to 3.39). Cross-correlation analysis indicated that DGM dynamics changed in response to solar radiation with lag-times of 65 and 90 min. This relationship with solar radiation was used to develop new predictive models of DGM and mercury flux dynamics for each lake. We suggest that a generalized approach using time-shifted solar radiation date to predict DGM can be incorporated into existing mercury flux models. It is clear from the work presented that DOC and wind speed may also play important roles in DGM and mercury flux dynamics, and these roles have not been adequately accounted for in current predictive models.

Air Pollutants↗
PubMed2005

A simple thermodynamic model for quantitatively addressing cooperativity in multicomponent self-assembly processes--part 1: Theoretical concepts and application to monometallic coordination complexes and bimetallic helicates possessing identical binding sites.

A thermodynamic model has been developed for quantitatively estimating cooperativity in supramolecular polymetallic [M(m)L(n)] assemblies, as the combination of two simple indexes measuring intermetallic (I(c)MM) and interligand (I(c)LL) interactions. The usual microscopic intermolecular metal-ligand affinities (f(i)(M,L)) and intermetallic interaction parameters (uMM), adapted to the description of successive intermolecular binding of metal ions to a preorganized receptor, are completed with interligand interactions (uLL) and effective concentrations (c(eff)), accounting for the explicit free energy associated with the aggregation of the ligands forming the receptor. Application to standard monometallic pseudo-octahedral complexes [M(L)(n)(H2O)(6 - n)] (M = Co, Ni, Hf, L = ammonia, fluoride, imidazole, n = 1-6) systematically shows negative cooperativity (uLL < 1), which can be modulated by the electronic structures, charges, and sizes of the entering ligands and of the metal ions. Extension to the self-assembly of more sophisticated bimetallic helicates possessing identical binding sites is discussed, together with the origin of the positively cooperative formation of [Eu2(L3)3].

Journal Article↗
PubMed1997

An iterative algorithm for converting a class II MHC binding motif into a quantitative predictive model.

Biochemists and molecular biologists have suggested motifs for characterizing the binding of peptide fragments and class II major histocompatibility complex (MHC) molecules based on laboratory results and crystal structures. The iterative algorithm presented here converts a suggested motif into a quantitative data-based model. The database accessed consists of peptide fragments known to bind or not bind to class II MHC molecules of particular haplotypes. Stepwise discriminant analysis is utilized to increase or decrease motif coefficients until the resulting motif classifies all binders and non-binders correctly. Stepwise discriminant analysis is a standard multivariate statistical procedure and is available in comprehensive commercial statistical packages. Program 7M of BMDP Statistical Software was used in this study.

Algorithms↗
PubMed2000

A quantitative genetic model for analyzing species differences in outcrossing species.

A genetic model based on a two-level intra- and interspecific mating design is proposed to estimate the genetic architecture of species differences and heterosis for outcrossing species. The underlying genetic analyses make use of classical quantitative genetic theories and recent results from molecular genetic studies. Gene effects across different quantitative trait loci (QTL) can be approximated by a geometric series. Under natural selection, gene effects are often associated with allele frequencies in a particular way, which can be approximated by the gamma distribution. By incorporating these approximations into family structural analyses in the mating design, we are able to estimate a number of genetic parameters that contribute to quantitative genetic variation based on a nonlinear optimization approach. These parameters include the number of QTL, their gene effects, and their allele frequencies in the parental populations. We perform simulation studies and illustrate an example to demonstrate the statistical property and procedure of the method.

Alleles↗
PubMed1992

A quantitative in vitro model for silicone oil emulsification. Role of blood constituents.

To understand why some patients seem to be protected from emulsification and others are not, the authors developed an in vitro model for quantitative analysis of silicone oil emulsification. The pro-emulsifying potential of substances and blood components that may have access to the vitreous cavity in a patient's eye was analyzed. In this model, red blood cell ghosts had the highest emulsifying effect; plasma and lymphocytes also had a significant emulsifying effect. Phospholipids in membranes and other soluble blood components may play important roles in this process. These results suggest the importance of avoiding and removing hemorrhage and avoiding inflammation when silicone oil is used in vitreoretinal surgery.

Blood Cells↗
PubMed1995

Squamous cell carcinoma growth in irradiated tissue: a murine model for quantitative assessment of treatment.

Locoregional recurrent and distant metastases from squamous cell carcinomas, despite multimodality therapy, remain troublesome clinical realities. Discrepancies in success rates of various surgery and radiation treatment regimens dealing with these problems are confusing to the clinician attempting to recommend the most beneficial treatments. There is a need for an experimental model to assess therapeutic effectiveness quantitatively from which guidelines for developing clinical trials may be suggested. In this study, we provide such a model. We injected DBA-2 mice with defined numbers of KLN-205 squamous carcinoma cells to obtain baseline growth characteristics; 216 animals had no previous irradiation. The remaining 131 received 30 Gy irradiation to the right leg 50 days before injection of the tumor cells. Tumor incidence, growth and number, and location of tumor metastasis were determined in both previously irradiated and nonirradiated groups. The data demonstrate a growth-retardant effect on tumor groups by the previous irradiation (tumor bed effect). The data also show that the incidence of hematogenously spread metastases was more frequent in mice in which tumors developed in previously irradiated tissue than in mice with tumors in nonirradiated tissue.

Animals↗
PubMed2000

Competitive speciation in quantitative genetic models.

We study sympatric speciation due to competition in an environment with a broad distribution of resources. We assume that the trait under selection is a quantitative trait, and that mating is assortative with respect to this trait. Our model alternates selection according to Lotka-Volterra-type competition equations, with reproduction using the ideas of quantitative genetics. The recurrence relations defined by these equations are studied numerically and analytically. We find that when a population enters a new environment, with a broad distribution of unexploited food sources, the population distribution broadens under a variety of conditions, with peaks at the edge of the distribution indicating the formation of subpopulations. After a long enough time period, the population can split into several subpopulations with little gene flow between them.

Animals↗
PubMed1985

A mathematical model to quantitate histamine release from basophils challenged in vitro with insect venom.

Using a two parameter mathematical model, it was possible to describe clinically obtained data from histamine release (HR) in vitro as a response to basophils challenged by insect venom. The Gompertz function used in this model not only reflects the observed HR data but can be used to predict maximal HR values from initial lower antigen concentrations HR determinations. The model was used to calculate the concentration of venom antigens releasing 25% of total intracellular histamine (HR25). This is clinically significant in that while knowledge of the HR25, or any other reference fraction, facilitates comparisons between allergic patients, it is impossible to empirically administer venom antigen concentrations that will produce exactly HR25 in a given clinical setting.

Adult↗
PubMed2006

A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription.

MOTIVATION: Quantitative estimation of the regulatory relationship between transcription factors and genes is a fundamental stepping stone when trying to develop models of cellular processes. This task, however, is difficult for a number of reasons: transcription factors' expression levels are often low and noisy, and many transcription factors are post-transcriptionally regulated. It is therefore useful to infer the activity of the transcription factors from the expression levels of their target genes. RESULTS: We introduce a novel probabilistic model to infer transcription factor activities from microarray data when the structure of the regulatory network is known. The model is based on regression, retaining the computational efficiency to allow genome-wide investigation, but is rendered more flexible by sampling regression coefficients independently for each gene. This allows us to determine the strength with which a transcription factor regulates each of its target genes, therefore providing a quantitative description of the transcriptional regulatory network. The probabilistic nature of the model also means that we can associate credibility intervals to our estimates of the activities. We demonstrate our model on two yeast datasets. In both cases the network structure was obtained using chromatin immunoprecipitation data. We show how predictions from our model are consistent with the underlying biology and offer novel quantitative insights into the regulatory structure of the yeast cell. AVAILABILITY: MATLAB code is available from http://umber.sbs.man.ac.uk/resources/puma.

Computer Simulation↗
PubMed1980

A quantitative structural model of the testis of fertile males with normal sperm counts.

The morphology of testicular biopsies of 8 healthy fertile men with proven normal sperm counts was studied using stereological techniques. Quantitative estimations were made of different cellular compartments in the testicular biopsies. The experimental errors of observation, homogeneity of the section, accuracy of the measurements and errors caused during the preparation of the sections were studied. A stereological model of the human testis comprising all compartments was designed. The present observations on the stereological parameters were compared with the results in literature; generally a good agreement was found. This stereological model enabled the authors to establish the quantitative correlations that exist between the separate compartments of the human testis. The tubular length density was positively correlated with the tubular surface density. The tubular surface density showed a negative correlation with the volume density of the germinal cell nuclei. The tubular volume density showed a negative correlation with the volume density of the Leydig cells. The intra-tubular volume density correlated negatively with the volume density of the Leydig cells and with the volume density of the remaining extra-tubular tissue. The intra-tubular tissue density correlated negatively with the volume density of the intra-tubular space.

Biopsy↗
PubMed2003

Quantitative microbiologic models for preterm delivery.

Preterm delivery (PTD) is the leading cause of infant morbidity and mortality in the United States. An epidemiological association between PTD and various bacteria that are part of the vaginal microflora has been reported. No single bacterial species has been identified as being causally associated with PTD, suggesting a multifactorial etiology. Quantitative microbiologic cultures have been used previously to define normal vaginal microflora in a predictive model. These techniques have been applied to vaginal swab cultures from pregnant women in an effort to develop predictive microbiologic models for PTD. Logistic regression analysis with microbiologic information was performed for various risk groups, and the probability of a PTD was calculated for each subject. Four predictive models were generated by using the quantitative microbiologic data. The area under the curve (AUC) for the receiver operating curves ranged from 0.74 to 0.94, with confidence intervals (CI) ranging from 0.62 to 1. The model for the previous PTD risk group with the highest percentage of PTDs had an AUC of 0.91 (CI, 0.79 to 1). It may be possible to predict PTD by using microbiologic risk factors measured once the gestation period has reached the 20-week time point.

Bacteria↗
PubMed2003

Non-peptide angiotensin II receptor antagonists: chemical feature based pharmacophore identification.

Chemical feature based pharmacophore models were elaborated for angiotensin II receptor subtype 1 (AT(1)) antagonists using both a quantitative and a qualitative approach (Catalyst HypoGen and HipHop algorithms, respectively). The training sets for quantitative model generation consisted of 25 selective AT(1) antagonists exhibiting IC(50) values ranging from 1.3 nM to 150 microM. Additionally, a qualitative pharmacophore hypothesis was derived from multiconformational structure models of the two highly active AT(1) antagonists 4u (IC(50) = 0.2 nM) and 3k (IC(50) = 0.7 nM). In the case of the quantitative model, the best pharmacophore hypothesis consisted of a five-features model (Hypo1: seven points, one hydrophobic aromatic, one hydrophobic aliphatic, a hydrogen bond acceptor, a negative ionizable function, and an aromatic plane function). The best qualitative model consisted of seven features (Hypo2: 11 points, two aromatic rings, two hydrogen bond acceptors, a negative ionizable function, and two hydrophobic functions). The obtained pharmacophore models were validated on a wide set of test molecules. They were shown to be able to identify a range of highly potent AT(1) antagonists, among those a number of recently launched drugs and some candidates presently undergoing clinical tests and/or development phases. The results of our study provide confidence for the utility of the selected chemical feature based pharmacophore models to retrieve structurally diverse compounds with desired biological activity by virtual screening.

Acrylates↗