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At least 739 records · Page 41Linked to original sources

PubMed2006

Model predictions of metal speciation in freshwaters compared to measurements by in situ techniques.

Measurements of trace metal species in situ in a softwater river, a hardwater lake, and a hardwater stream were compared to the equilibrium distribution of species calculated using two models, WHAM 6, incorporating humic ion binding model VI and visual MINTEQ incorporating NICA-Donnan. Diffusive gradients in thin films (DGT) and voltammetry at a gel integrated microelectrode (GIME) were used to estimate dynamic species that are both labile and mobile. The Donnan membrane technique (DMT) and hollow fiber permeation liquid membrane (HFPLM) were used to measure free ion activities. Predictions of dominant metal species using the two models agreed reasonably well, even when colloidal oxide components were considered. Concentrations derived using GIME were generally lower than those from DGT, consistent with calculations of the lability criteria that take into account the smaller time window available forthe fluxto GIME. Model predictions of free ion activities generally did not agree with measurements, highlighting the need for further work and difficulties in obtaining appropriate input data.

Benzopyrans↗

PubMed1998

A three-state receptor model: predictions of multiple agonist pharmacology for the same receptor type.

Recent studies have demonstrated that activation of the same G-protein coupled receptor can generate different agonist pharmacology depending on the signaling pathway(s) to which it couples. Two types of behavior have been exemplified; differences in affinity order, and differences in efficacy order with the same affinity order. The two-state model of receptor activation cannot explain these data, since a single active receptor state cannot couple differently to the two response pathways for different ligands. We have therefore extended the two-state model to a three-state model in which receptors exist in three states: an inactive state, R, and two different active states, R* and R**. The model has two modes, the 'intact mode', in which all the equilibria are linked; and the 'isolated mode' in which the two response pathways are isolated from each other, giving effectively two separate two-state systems. In the 'intact mode' the same agonist affinity order is predicted for both response pathways, but a different efficacy order. In the 'isolated mode', since the equilibria are no longer linked, the model predicts that a different affinity order may be obtained for the two pathways. Owing to the linkage of all the equilibria in the intact three-state model the level of constitutive activity through one pathway can affect the direction of agonism through the other pathway, resulting in the conversion of an inverse agonist into a positive agonist. This change in the direction of agonism is also predicted to occur when the two response pathways are isolated. The three-state model therefore predicts that agonists, acting at the same receptor, may show different affinity orders and different efficacy orders depending upon which response is measured and the assay system used, and also predicts that inverse agonism may be system dependent.

Animals↗

PubMed1979

Prediction models in small area estimation.

Finite population estimation problems are formulated as prediction problems under superpopulation models. For linear regression models, a general theorem on optimal linear estimation is presented. The theorem is applied to simple cross-classification models to generate and analyze various statistics for estimating small area totals. These statistics include the synthetic and composite estimators, as well as some interesting alternatives.

Humans↗

PubMedDate not supplied

Peer rejection, aggressive or withdrawn behavior, and psychological maladjustment from ages 5 to 12: an examination of four predictive models.

Findings yielded a comprehensive portrait of the predictive relations among children's aggressive or withdrawn behaviors, peer rejection, and psychological maladjustment across the 5-12 age period. Examination of peer rejection in different variable contexts and across repeated intervals throughout childhood revealed differences in the timing, strength, and consistency of this risk factor as a distinct (additive) predictor of externalizing versus internalizing problems. In conjunction with aggressive behavior, peer rejection proved to be a stronger additive predictor of externalizing problems during early rather than later childhood. Relative to withdrawn behavior, rejection's efficacy as a distinct predictor of internalizing problems was significant early in childhood and increased progressively thereafter. These additive path models fit the data better than did disorder-driven or transactional models.

Adaptation, Psychological↗

PubMed2004

Combined discrete particle and continuum model predicting solid-state fermentation in a drum fermentor.

The development of mathematical models facilitates industrial (large-scale) application of solid-state fermentation (SSF). In this study, a two-phase model of a drum fermentor is developed that consists of a discrete particle model (solid phase) and a continuum model (gas phase). The continuum model describes the distribution of air in the bed injected via an aeration pipe. The discrete particle model describes the solid phase. In previous work, mixing during SSF was predicted with the discrete particle model, although mixing simulations were not carried out in the current work. Heat and mass transfer between the two phases and biomass growth were implemented in the two-phase model. Validation experiments were conducted in a 28-dm3 drum fermentor. In this fermentor, sufficient aeration was provided to control the temperatures near the optimum value for growth during the first 45-50 hours. Several simulations were also conducted for different fermentor scales. Forced aeration via a single pipe in the drum fermentors did not provide homogeneous cooling in the substrate bed. Due to large temperature gradients, biomass yield decreased severely with increasing size of the fermentor. Improvement of air distribution would be required to avoid the need for frequent mixing events, during which growth is hampered. From these results, it was concluded that the two-phase model developed is a powerful tool to investigate design and scale-up of aerated (mixed) SSF fermentors.

Aspergillus oryzae↗

PubMed1997

Analysis of comparative modeling predictions for CASP2 targets 1, 3, 9, and 17.

Comparative modeling targets 1, 3, 9 and 17 were predicted by alignment of multiple sequences and structures, when available, followed by minimization using the program AMMP. The minimization used improved potentials, and distance restraints for regions of common structure. New prediction procedures were evaluated. Three tested solvent corrections did not significantly improve the predictions. Target 17 had 85.3% sequence identity with the parent and no insertions or deletions. The prediction had a root-mean-square deviation from target 17 of 0.56 A on C alpha atoms, and 0.59 A for the ligand atoms, which verified the accuracy of the minimization. Targets 1, 3, and 9 had 36.4%, 46.7%, and 33.3% identity with the parent sequences, and predictions resulted in root-mean-square deviations for 79-85% of C alpha atoms of 1.49, 1.11, and 1.24 A, respectively. Conformational differences between parent and target crystal structures were difficult to predict. The use of distance restraints and multiple structures improved the positioning of gaps in sequence alignment. Distance restraints did not overcome errors in sequence alignment or ambiguities due to conformational variation in proteins. Predictions for targets 3 and 9 successfully reduced large deviations between parent and target structures.

Animals↗

PubMed1991

Classification tree prediction models for dental caries from clinical, microbiological, and interview data.

Caries prediction by Classification And Regression Tree (CART) analysis is an appropriate and powerful alternative or complement to the commonly used classification methods of logistic regression and discriminant analysis, both parametric and nonparametric. The binary classification tree method discussed in this article is designed for complex data and does not require assumptions about the predictor variables or about the presence or absence of interactions among the predictor variables. Furthermore, the results give insight into the structures and interactions in the data and are easy to interpret and apply. In preliminary applications of the CART algorithms to data from The University of North Carolina Caries Risk Assessment Study, the method produced prediction rules having sensitivities and specificities that were similar to or slightly better than those associated with logistic and discriminant analyses. The classification trees constructed tended to involve far fewer predictor variables than required for adequate logistic and discriminant models. For example, for first-grade children in Aiken, South Carolina, nine variables were used to define a prediction rule having 64% sensitivity and 86% specificity. Ten-fold cross-validation estimates for future data were 58% and 79%, respectively. For first-grade children in Portland, Maine, two variables were used to define a prediction rule having 62% sensitivity and 77% specificity. The cross-validation estimates for future data were 58% and 78%, respectively. A brief, and previously unavailable, explanation of the CART method is given for the special case of a dichotomous outcome variable.

Child↗

PubMed2006

Gray correlation analysis and prediction models of living refuse generation in Shanghai city.

A better understanding of the factors that affect the generation of municipal living refuse (MLF) and the accurate prediction of its generation are crucial for municipal planning projects and city management. Up to now, most of the design efforts have been based on a rough prediction of MLF without any actual support. In this paper, based on published data of socioeconomic variables and MLF generation from 1990 to 2003 in the city of Shanghai, the main factors that affect MLF generation have been quantitatively studied using the method of gray correlation coefficient. Several gray models, such as GM(1,1), GIM(1), GPPM(1) and GLPM(1), have been studied, and predicted results are verified with subsequent residual test. Results show that, among the selected seven factors, consumption of gas, water and electricity are the largest three factors affecting MLF generation, and GLPM(1) is the optimized model to predict MLF generation. Through this model, the predicted MLF generation in 2010 in Shanghai will be 7.65 million tons. The methods and results developed in this paper can provide valuable information for MLF management and related municipal planning projects.

China↗

PubMed2002

Refinement and field validation of a biotic ligand model predicting acute copper toxicity to Daphnia magna.

A previously developed biotic ligand model (BLM) was validated for its capacity to predict acute 48-h EC(50) values of copper to Daphnia magna in 25 reconstituted media with different pH values and concentrations of artificial dissolved organic carbon, Ca, Mg and Na. Before the BLM validation, fitting of measured (with a copper ion-selective electrode) and calculated (with the BLM) Cu(2+)-activity was performed by adjusting the WHAM model V (i.e. the metal-organic speciation part of the BLM) copper-proton exchange constant to pK(MHA)=1.9. Using this value, the 48-h EC(50) values observed agreed very well with BLM-predicted EC(50) values for tests performed at pH<8, but not at all for tests performed at pH>8. Additional experiments demonstrated that this was due to toxicity of the CuCO(3) complex, which is the most abundant inorganic copper species at pH>8. This was incorporated into the initial BLM by allowing the binding of CuCO(3) (next to Cu(2+) and CuOH(+)) to the biotic ligand of D. magna. The affinity of CuOH(+) and CuCO(3) for the biotic ligand was approximately five- and 10-fold lower than that of Cu(2+), respectively. With the refined BLM, 48-h EC(50) values could be accurately predicted within a factor of two not only in all 25 reconstituted media, but also in 19 natural waters. This validated and refined BLM could support efforts to improve the ecological relevance of risk assessment procedures applied at present.

Animals↗

PubMed2005

Two modes of motion of the alligator lizard cochlea: measurements and model predictions.

Measurements of motion of an in vitro preparation of the alligator lizard basilar papilla in response to sound demonstrate elliptical trajectories. These trajectories are consistent with the presence of both a translational and rotational mode of motion. The translational mode is independent of frequency, and the rotational mode has a displacement peak near 5 kHz. These measurements can be explained by a simple mechanical system in which the basilar papilla is supported asymmetrically on the basilar membrane. In a quantitative model, the translational admittance is compliant while the rotational admittance is second order. Best-fit model parameters are consistent with estimates based on anatomy and predict that fluid flow across hair bundles is a primary source of viscous damping. The model predicts that the rotational mode contributes to the high-frequency slopes of auditory nerve fiber tuning curves, providing a physical explanation for a low-pass filter required in models of this cochlea. The combination of modes makes the sensitivity of hair bundles more uniform with radial position than that which would result from pure rotation. A mechanical analogy with the organ of Corti suggests that these two modes of motion may also be present in the mammalian cochlea.

Animals↗

PubMed1999

Identification of responders to a therapy: an example of validation of a predictive model.

The general objective of randomized clinical trials is to assess if the treatment effect on a given population is clinically meaningful. In this way, one obtains an average estimate of the treatment effect over the trial population. However, a growing need for medical practitioners is to be able to predict with sufficient precision the efficiency of a given treatment for a given patient. There is little information in the literature about this issue. We have previously proposed a treatment-startified Cox model including interaction between treatment and patient's covariates, to identify and predict the responders to a therapy. In this paper, we focus on the assessment of the predictive power of the model. The performance of the predictive model for a population and for an individual was statistically validated internally and externally from several aspects. The prediction correlates well with the observation. Thus, we suggest that this approach would be useful in identifying and predicting the responders to a therapy, subject to an appropriate and more extensive validation process in real setting.

Female↗

PubMed2005

Predictive model of blood-brain barrier penetration of organic compounds.

AIM: To build up a theoretical model of organic compounds for the prediction of the activity of small molecules through the blood-brain barrier (BBB) in drug design. METHODS: A training set of 37 structurally diverse compounds was used to construct quantitative structure-activity relationship (QSAR) models. Intermolecular and intramolecular solute descriptors were calculated using molecular mechanics, molecular dynamics simulations, quantum chemistry and so on. The QSAR models were optimized using multidimensional linear regression fitting and stepwise method. A test set of 8 compounds was evaluated using the models as part of a validation process. RESULTS: Significant QSAR models (R=0.955, s=0.232) of the BBB penetration of organic compounds were constructed. BBB penetration was found to depend upon the polar surface area, the octanol/water partition coefficient, Balaban Index, the strength of a small molecule to combine with the membrane-water complex, and the changeability of the structure of a solute-membrane-water complex. CONCLUSION: The QSAR models indicate that the distribution of organic molecules through BBB is not only influenced by organic solutes themselves, but also relates to the properties of the solute-membrane-water complex, that is, interactions of the molecule with the phospholipid-rich regions of cellular membranes.

Blood-Brain Barrier↗

PubMed2003

Conjugation of catechols by recombinant human sulfotransferases, UDP-glucuronosyltransferases, and soluble catechol O-methyltransferase: structure-conjugation relationships and predictive models.

Conjugation of a structurally diverse set of 53 catechol compounds was studied in vitro using six recombinant human sulfotransferases (SULTs), five UDP-glucuronosyltransferases (UGT) and the soluble form of catechol O-methyltransferase (S-COMT) as catalyst. The catechol set comprised endogenous compounds, such as catecholamines and catecholestrogens, drugs, natural plant constituents, and other catechols with diverse substituent properties and substitution patterns. Most of the catechols studied were substrates of S-COMT and four SULT isoforms (1A1, 1A2, 1A3, and 1B1), but the rates of conjugation varied considerably, depending on the substrate structure and the enzyme form. SULT1E1 sulfated fewer catechols. Only low activities were observed for SULT1C2. UGT1A9 glucuronidated catechols representing various structural classes, and almost half of the studied compounds were glucuronidated at a high rate. The other UGT enzymes (1A1, 1A6, 2B7, and 2B15) showed narrower substrate specificity for catechols, but each glucuronidated some catechols at a high rate. Dependence of specificity and rate of conjugation on the molecular structure of the substrate was characterized by structure-activity relationship analysis and quantitative structure-activity relationship modeling. Twelve structural descriptors were used to characterize lipophilicity/polar interaction properties, steric properties, and electronic effects of the substituents modifying the catechol structure. PLS models explaining more than 80% and predicting more than 70% of the variance in conjugation activity were derived for the representative enzyme forms SULT1A3, UGT1A9, and S-COMT. Several structural factors governing the conjugation of catechol hormones, metabolites, and drugs were identified. The results have significant implications for predicting the metabolic fate of catechols.

Catechol O-Methyltransferase↗

PubMed2002

A novel predictive model of outcome in de novo AML based on S-phase activity and proliferative response of blast cells to haemopoietic growth factors.

This study assesses whether the kinetic response of AML cells to HGFs might help to predict initial clinical outcome of treatment in de novo AML in association with age, FAB type and karyotype. Best subset regression analysis indicated optimal variables to develop models to predict prognosis. High S-phase in surviving cells following 7 days incubation in SFM, resistance to stimulation by G+GM-CSF and poor karyotype taken in combination correctly predicted outcome in 83% of patients. The importance of high SFM S-phase may be to indicate autonomous proliferation therefore a leukemic clone more likely to regenerate following therapy at the expense of normal haemopoiesis. Kinetic studies of AML cells may be a useful predictor of outcome in addition to other more established prognostic factors.

Adult↗

PubMed1986

Predictive models for human glucose-6-phosphate dehydrogenase deficiency.

The present paper has discussed available test systems for determination of the response of G-6-PD-deficient human erythrocytes to environmental agents. The limitations and advantages of each model have been examined, and the results of research using each model have been presented. The future development of suitable animal models or in vitro test systems may rely on advances in fields such as genetics and biochemistry. Genetic engineering may allow researchers to develop cells with a genetic deficiency of G-6-PD. These deficient cells could then be used to simulate human G-6-PD-deficient erythrocyte responses to various agents. Advances in biochemistry, in areas such as metabolism and enzymology, may also have an impact on future test systems. Due to the fact that present model systems are limited and their predictions often unreliable, the establishment of safe environmental health standards will depend upon advances in modern science and the converging of developments from various disciplines.

Animals↗

PubMed2000

Coupling estimated effects of QTLs for physiological traits to a crop growth model: predicting yield variation among recombinant inbred lines in barley.

Advances in the use of molecular markers to elucidate the inheritance of quantitative traits enable the integration of genetic information on physiological traits into crop growth models. The objective of this study was to assess the ability of a crop growth model with QTL-based estimates of physiological input parameters to predict the yield of recombinant inbred lines (RILs) of barley. The model used predicts yield as spike biomass accumulated over the post-flowering period. We describe a two-stage procedure for predicting trait values from estimated additive and epistatic effects of QTLs. Values of physiological traits estimated by that procedure or measured in the field were used as input to the crop growth model. The output values (yield and shoot biomass) from the growth model using these two types of input values were highly correlated, indicating that QTL information can successfully replace measured input parameters. With the current crop growth model, however, both types of input values often resulted in large discrepancies between observed and predicted values. Improvement of performance may be achieved by incorporating physiological processes not yet included in the model. The prospects of using QTL-based predictions of model-input traits to identify new, high yielding barley genotypes are discussed.

Chromosome Mapping↗

PubMed1999

The validity of medical history, classic symptoms, and chest radiographs in predicting pulmonary tuberculosis: derivation of a pulmonary tuberculosis prediction model.

STUDY OBJECTIVE: To improve the respiratory isolation policy for patients with suspected pulmonary tuberculosis (TB). DESIGN: Prospective, descriptive, French multicenter study. SETTING: Emergence of nosocomial outbreaks of TB. PATIENTS: All consecutive patients admitted with suspicion of pulmonary TB. MEASUREMENTS AND RESULTS: Medical history, social factors, symptoms, and chest radiograph (CXR) pattern (symptoms and CXR both scored as typical of pulmonary TB, compatible, negative, or atypical) were obtained on admission. Serial morning sputa were collected. Of the 211 patients, 47 (22.3%) had culture-proven pulmonary TB, including 31 (14.7%) with a positive smear. Mean age was 46.2 years; 52 patients were HIV positive (24.6%). The sensitivity of the respiratory isolation policy was 71.4%, specificity was 51.7%, negative predictive value (NPV) was 88.2%, and positive predictive value (PPV) was 26.3%. On univariate analysis, predictive factors of culture-proven pulmonary TB were CXR (p < 0.00001), symptoms (p = 0.0004), age (mean, 40.8 years for TB patients vs 47.5 years for non-TB patients; p = 0.04), absence of HIV infection (89.4% vs 71.3%; p = 0.01), immigrant status (72% vs 55%; p = 0.03), and bacillus Calmette-Guérin status (p = 0.025). On multivariate analysis, CXR pattern (p < 0.00001), HIV infection (p = 0.002), and symptoms (p = 0.009) remained independently predictive. Based on these data, a model was proposed using a receiver operating characteristics curve. In the derivation cohort, the sensitivity and NPV of the model in detecting smear-positive pulmonary TB would have been 100%. The specificity and PPV would have been 48.4% and 25%, respectively. The model performed less well when evaluated on two retrospective groups, but its sensitivity remained above that of the current respiratory isolation policy (91.1% and 82.4% for the retrospective groups vs 71.1% for the current policy). CONCLUSIONS: Improved interpretation of clinical and radiologic data available on patient admission could improve adequacy of respiratory isolation. A prediction model is proposed.

BCG Vaccine↗

PubMed2005

Is phenol condensation one of the major pathways in the formation of polychlorinated dibenzofurans in municipal waste incinerators?: Model prediction vs. field observation.

The role of phenol condensation pathways in the formation of polychlorinated dibenzofurans (PCDF) in a municipal waste incinerator was assessed by comparing predicted PCDF homologue and isomer patterns with those obtained from the incinerator. A two-phenol condensation model, dependent only on the distribution of phenols, was used to predict the distributions of PCDF congeners in the incinerator. Complete distributions of phenols and PCDF congeners were obtained from the incinerator. To quantify the degree of agreement between obtained isomer distributions and those predicted by the model, R-squared values from linear correlations were calculated for the dichlorinated- through hexachlorinated-isomers. They ranged from 0.001 to 0.1. Agreement between obtained and predicted PCDF isomers was very poor for all homologues, suggesting that phenol condensation pathways are unlikely to be the primary route in the formation of PCDF in the incinerator. However, dibenzofuran (DF) is likely to be produced from a condensation of two phenols. This paper shows the use of PCDF homologue and isomer patterns calculated by the two-phenol condensation model for testing PCDF formation mechanism attribution in a municipal waste incinerator.

Air Pollutants↗