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PubMed2002

A predictive fatigue model--I: Predicting the effect of stimulation frequency and pattern on fatigue.

Previously we developed a mathematical force- and fatigue-model system that could predict fatigue produced by a wide range of frequencies and pulse patterns. However, the models tended to overestimate the forces produced by higher frequency trains. This paper presents modifications to our previously developed force- and fatigue-model system to improve the accuracy in predicting forces during repetitive activation of human skeletal muscle. By comparing the predictions produced by the modified force and fatigue models to those by our previous models, the modification appears to be successful. The current force- and fatigue-model system accounts for about 93% variance in experimental data produced by fatigue protocols consisting of trains with a wide range of frequencies and pulse patterns. In addition, the present models successfully predict the effect of stimulation frequency and pulse pattern on muscle fatigue. The success of our current force- and fatigue-model system suggests its potential use in helping to identify the optimal activation pattern to use during the clinical application of functional electrical stimulation.

Algorithms↗

PubMed2004

Why savannah monitor lizards hyperventilate during activity: a comparison of model predictions and experimental data.

The functional and structural factors that limit maximal oxygen uptake (VO2 max) in lizards are not completely understood. Using an integrative model describing the interactive nature of the individual oxygen transport conductances, we performed an analysis of the oxygen transport system in the highly aerobic lizard Varanus exanthematicus with specific reference to the sensitivity of VO2 max to potential limitations in the ventilatory system. Our analysis predicts that DLO2 must increase more than three-fold at VO2 max and even with this increase in DLO2 , the VO2 max may be sensitive to factors that alter lung ventilation and/or lower lung PO2. To test the predictions of the model analysis, we experimentally determined the effects of reducing inspired O2 on VO2 max during treadmill exercise. We conclude from both our theoretical and experimental analyses that V. exanthematicus operates near the functional limits of its lung.

Animals↗

PubMed1994

Referral selection bias in the Medicare hospital mortality prediction model: are centers of referral for Medicare beneficiaries necessarily centers of excellence?

OBJECTIVE: Although the Health Care Financing Administration (HCFA) uses Medicare hospital mortality data as a measure of hospital quality of care, concerns have been raised regarding the validity of this concept. A problem that has not been fully evaluated in these data is the potential confounding effect of illness severity factors associated with referral selection and hospital mortality on comparisons of risk-adjusted hospital mortality. We address this issue. DATA SOURCES AND STUDY SETTING: We analyzed the 1988 Medicare hospitalization data file (MEDPAR). We selected data on patients treated at the two Mayo Clinic-associated hospitals in Rochester, Minnesota, and a group of seven other hospitals that treat many patients from large geographic areas. These hospitals have had observed mortality rates substantially lower than those predicted by the HCFA model for the period 1987-1990. STUDY DESIGN: Using the multiple logistic regression model applied by HCFA to the 1988 data, we evaluated the relationship between distance from patient residence to the admitting hospital and risk-adjusted hospital mortality. PRINCIPAL FINDINGS: Among patients admitted to Mayo Rochester-affiliated hospitals, residence outside Olmsted County, Minnesota was independently associated with a 33 percent lower 30-day mortality rate (p < .001) than that associated with residence in Olmsted County. When patients at Mayo hospitals were stratified by residence (Olmsted County versus non-Olmsted County), the observed mortality was similar to that predicted for community patients (9.6 percent versus 10.2 percent, p = .26), whereas hospital mortality for referral patients was substantially lower than predicted (5.0 percent versus 7.5 percent, p = < .001). After incorporation of the HCFA risk adjustment methods, distance from patient residence to the hospitals was also independently associated with mortality among the Mayo Rochester-affiliated hospitals and seven other referral center hospitals. CONCLUSIONS: The HCFA Medicare hospital mortality model should be used with extreme caution to evaluate hospital quality of care for national referral centers because of residual confounding due to severity of illness factors associated with geographic referral that are inadequately captured in the extant prediction model.

Aged↗

PubMed2001

Computational modeling predicts the structure and dynamics of chromatin fiber.

BACKGROUND: The compact form of the chromatin fiber is a critical regulator of fundamental processes such as transcription and replication. These reactions can occur only when the fiber is unraveled and the DNA strands contained within are exposed to interact with nuclear proteins. While progress on identifying the biochemical mechanisms that control localized folding and hence govern access to genetic information continues, the internal structure of the chromatin fiber, let alone the structural pathways for folding and unfolding, remain unknown. RESULTS: To offer structural insights into how this nucleoprotein complex might be organized, we present a macroscopic computer model describing the mechanics of the chromatin fiber on the polymer level. We treat the core particles as electrostatically charged disks linked via charged elastic DNA segments and surrounded by a microionic hydrodynamic solution. Each nucleosome unit is represented by several hundred charges optimized so that the effective Debye-Hückel electrostatic field matches the field predicted by the nonlinear Poisson-Boltzmann equation. On the basis of Brownian dynamics simulations, we show that oligonucleosomes condense and unfold in a salt-dependent manner analogous to the chromatin fiber. CONCLUSIONS: Our predicted chromatin model shows good agreement with experimental diffusion coefficients and small-angle X-ray scattering data. A fiber of width 30 nm, organized in a compact helical zigzag pattern with about 4 nucleosomes per 10 nm, naturally emerges from a repeating nucleosome folding motif. This fiber has a cross-sectional radius of gyration of R(c) = 8.66 nm, in close agreement with corresponding values for rat thymus and chicken erythrocyte chromatin (8.82 and 8.5 nm, respectively).

Algorithms↗

PubMed1996

Model predictions of myoelectrical activity of the small bowel.

A mathematical model for the periodic electrical activity of a functional unit of the small intestine is developed. Based on real morphological and electrophysiological data, the model assumes that: the functional unit is an electromyogenic syncytium; the kinetics of L, T-type Ca2+, mixed Ca(2+)-dependent K+, potential sensitive K+ and Cl- channels determines electrical activity of the functional unit; the basic neural circuit, represented by a single cholinergic neurone, provides an excitatory input to the functional unit via receptor-linked L-type Ca2+ channels. Numerical simulation of the model has shown that it is capable of displaying the slow waves and that slight modifications of some of the parameters result in different electrical responses. The effects of the variations of the main parameters have been analyzed for their ability to reproduce various electrical patterns. The results are in good qualitative and quantitative agreement with results of experiments conducted on the small intestine.

Acetylcholine↗

PubMed2005

A multivariate regression model predicted falls in residents living in intermediate hostel care.

BACKGROUND AND OBJECTIVE: To evaluate whether individual falls risk could be predicted in a frail elderly population. STUDY DESIGN AND SETTING: We developed and tested an assessment tool and falls risk score for predicting falls based on a multivariate regression model in a prospective cohort study of intermediate care residents. RESULTS: During the follow-up period, 1,736 falls by 1,107 subjects were recorded with an average of 170 falls per 100 person-years. Fifty percent of the study population had at least one fall within a year. Significant independent risk factors were poor balance, cognitive impairment, incontinence, higher illness severity rating, and older age. Twenty-two percent of participants with a falls risk score > or =7 accounted for 42% of the total falls, with a falls rate of 317 per 100 person-years. This rate was a sixfold increase from the falls rate of 52 per 100 person-years observed in participants with a score < 3. A high score (> or =7) indicated almost a 2 in 3 chance of falling, while a low score (<3) indicated approximately a 1 in 7 chance of falling within 6 months. CONCLUSION: The assessment tool and falls risk score could identify individuals in this frail elderly population at high risk of falls.

Accidental Falls↗

PubMed2006

Describing the component dynamics in miscible polymer blends: towards a fully predictive model.

We have recently proposed [D. Cangialosi et al., J. Chem. Phys. 123, 144908 (2005)] an extension of the Adam-Gibbs [J. Chem. Phys. 43, 139 (1965)] theory, combined with the concept of self-concentration, to describe the temperature dependence of the relaxation time for the component segmental dynamics in miscible polymer blends. Thus, we were able to obtain the dynamics of each component in the blend starting from the knowledge of the dynamic and thermodynamic data of the pure polymers, with a single fitting parameter (alpha) which had to be obtained from the fitting of the experimental data. In the present work we demonstrate that this model is also suitable to describe the polymer segmental dynamics in concentrated polymer solutions. From this result we have developed a new route for determining the value of the alpha parameter associated with any given polymer. Once this value is known for the two components of a possible polymer blend, our model for polymer blends dynamics becomes fully predictive.

Journal Article↗

PubMed2004

Pharmacokinetic model-predicted anticancer drug concentrations in human tumors.

In an era when molecular and targeted anticancer therapeutics is a major focus and when understanding drug dynamics in tumor is critical, it seems advantageous to be able to relate drug concentrations in tumors to corresponding biological end points. To that end, a novel method, based on physiologically based hybrid pharmacokinetic models, is presented to predict human tumor drug concentrations. Such models consist of a forcing function, describing the plasma drug concentration-time profile, which is linked to a model describing drug disposition in tumors. The hybrid models are originally derived from preclinical data and then scaled to humans. Integral to the scale-up procedure is the ability to derive human forcing functions directly from clinical pharmacokinetic data. Three examples of this approach are presented based on preclinical investigations with carboplatin, topotecan, and temozolomide. Translation of these preclinical hybrid models to humans used a Monte Carlo simulation technique that accounted for intrasubject and intersubject variability. Different pharmacokinetic end points, such as the AUC tumor, were extracted from the simulated human tumor drug concentrations to show how the predicted drug concentrations might be used to select drug-dosing regimens. It is believed that this modeling strategy can be used as an aid in the drug development process by providing key insights into drug disposition in tumors and by offering a foundation to optimize drug regimen design.

Animals↗

PubMed1997

Validation of a predictive model of idiopathic membranous nephropathy: its clinical and research implications.

Although a number of factors have consistently correlated with progression to chronic renal insufficiency (CRI) in idiopathic membranous glomerulonephropathy (IMGN), they appear late, are not quantitative in nature and have not been validated. We have determined that the highest sustained six-month period of proteinuria is an important predictor of progression. Using multiple logistic modelling, the only additional prognostic variables of importance in 184 Canadian patients were the initial creatinine clearance and the rate of change in function over this six-month interval. Independent data from Italy (101 patients) and Finland (78 patients) were obtained for comparison. Sensitivity, specificity, negative and positive predictive values and overall accuracy, as well as Pearson's goodness-of-fit and Harrell's "C" statistic were used to assess the fits of the model. Accuracy of prediction was > or = 85% in all three countries. Pearson's Chi-square goodness-of-fit showed good agreement across the spectrum and Harrell's "C" statistic was > or = 90%. Therefore, a predictive, semiquantitative algorithm in IMGN has been validated. Its relevance in patient management and in clinical trials is illustrated.

Algorithms↗

PubMed1997

Application of an iterative approach for development of a microbial model predicting the shelf-life of packed fish.

An iterative approach was used to develop a microbial model for shelf-life prediction of cod fillets packed in modified atmospheres. The effect of temperature (0-15 degrees C) and CO2 (0-100%) on growth of the specific spoilage organism, Photobacterium phosphoreum, was studied in packed cod and in liquid media. P. phosphoreum was a dominant part of the spoilage microflora of packed cod stored at the extremes of the range of conditions studied. The organism is therefore likely to be important for spoilage and the development of a microbial model within this domain seems relevant. A liquid medium was developed to provide growth kinetics of P. phosphoreum similar to those observed in packed cod. Using this medium, the effect of temperature and CO2 on the maximum specific growth rate of Photobacterium phosphoreum was determined by absorbance measurements and modelled by a square root equation and by a polynomial equation. Product validation studies were carried out during summer and winter using naturally contaminated packed cod fillets which were stored at constant and at changing temperatures. The shelf-life of the packed fillets was predicted on the basis of the initial numbers of P. phosphoreum, product temperature profiles and the level of CO2 in the modified atmosphere. The average deviations between shelf-life determined by sensory evaluation and shelf-life predicted by the square root equation and by the polynomial equation were 17% and 9%, respectively.

Animals↗

PubMed1999

A new predictive model for insulin-dependent diabetes mellitus susceptibility based on combinations of molecular HLA-DRB1 and HLA-DQB1 pockets.

With a view to establishing an accurate evaluation of the genetic predisposition to insulin-dependent type I diabetes (IDDM), we have built a model based on the characteristics of the relevant pockets of HLA-DR and -DQ molecules. Three independent populations were investigated. Group I and group II were Caucasoids, while group III was Japanese, including a total of 1,166 IDDM patients and 2,391 healthy controls. We formulate the hypothesis that suceptibility to IDDM is not only explained by the absence of Aspartate 57 (negative charge) from pocket 9 of DQB1 (P9DQ), but also by the presence of an electric charge (+/- vs. neutral), generated by residues 70, 71 and 74 in pockets 4 of DRB1 (P4DR) and DQB1 (P4DQ) molecules. The respective weight of each pocket, was evaluated in a multivariate analysis based on the logistic regression method. The 4 components (2 loci and 2 pockets) were systematically analysed in the computer model. It was clearly shown that the structural characteristics of pockets P9DQ-P4DR and, to a lesser degree that of P4DQ, account for IDDM predisposition. On applying the model to the whole international series, it appears that the highest risk concerns individuals with P9DQ non-Asp 57 and both the charged P4 of DRB1 and P4 of DQB1, conferring a 80% prediction of susceptibility. Conversely, P9DQ Asp and neutral P4DR and P4DQ give the lowest risk with a predictive value of 5%. This model of risk susceptibility prediction fits remarkably well with the observed distribution in a worldwide study. It allows a better evaluation of the respective role of HLA-DR and -DQ molecules as a major component of susceptibility to IDDM.

Alleles↗

PubMed2002

Effects of temperature, water activity, and syrup film composition on the growth of Wallemia sebi: development and assessment of a model predicting growth lags in syrup agar and crystalline sugar.

We investigated the effects of temperature, water activity (a(w)), and syrup film composition on the CFU growth of Wallemia sebi in crystalline sugar. At a high a(w) (0.82) at both high (20 degrees C) and low (10 degrees C) temperatures, the CFU growth of W. sebi in both white and extrawhite sugar could be described using a modified Gompertz model. At a low a(w) (0.76), however, the modified Gompertz model could not be fitted to the CFU data obtained with the two sugars due to long CFU growth lags and low maximum specific CFU growth rates of W. sebi at 20 degrees C and due to the fact that growth did not occur at 10 degrees C. At an a(w) of 0.82, regardless of the temperature, the carrying capacity (i.e., the cell concentration at t = infinity) of extrawhite sugar was lower than that of white sugar. Together with the fact that the syrup film of extrawhite sugar contained less amino-nitrogen relative to other macronutrients than the syrup film of white sugar, these results suggest that CFU growth of W. sebi in extrawhite sugar may be nitrogen limited. We developed a secondary growth model which is able to predict colony growth lags of W. sebi on syrup agar as a function of temperature and a(w). The ability of this model to predict CFU growth lags of W. sebi in crystalline sugar was assessed.

Agar↗

PubMed2005

Uranium speciation in moorland river water samples: a comparison of experimental results and computer model predictions.

An on-line method has been developed for separating inorganic and organic bound uranium species present in river water samples. The method utilised a small chelating resin (Hyphan) column incorporated into the sample introduction manifold of an ICP-MS instrument. The method was evaluated for samples from rivers on Dartmoor (Devon, UK), an area of granite overlain with peat bogs. The results indicate that organic-uranium species form a major proportion (80%) of the total dissolved uranium present. Further work with synthetic water samples indicated that the level of dissolved organic carbon played a greater role in determining the level of organic-uranium species than did sample pH. Computer models for the water samples were constructed using the WHAM program (incorporating uranium data from the Nuclear Energy Agency Thermochemical Database project) in order to predict the levels of organic-uranium species that would form. By varying the proportion of humic and fulvic acids used in the humic component, predictions within 10% of the experimental results were obtained. The program did exhibit a low bias at higher pH values (7.5) and low organic carbon concentrations (0.5 microg ml(-1)), but under the natural conditions prevalent in the Dartmoor water samples, the model predictions were successful.

Benzopyrans↗

PubMed2002

Crucial stages of protein folding through a solvable model: predicting target sites for enzyme-inhibiting drugs.

An exactly solvable model based on the topology of a protein native state is applied to identify bottlenecks and key sites for the folding of human immunodeficiency virus type 1 (HIV-1) protease. The predicted sites are found to correlate well with clinical data on resistance to Food and Drug Administration-approved drugs. It has been observed that the effects of drug therapy are to induce multiple mutations on the protease. The sites where such mutations occur correlate well with those involved in folding bottlenecks identified through the deterministic procedure proposed in this study. The high statistical significance of the observed correlations suggests that the approach may be promisingly used in conjunction with traditional techniques to identify candidate locations for drug attacks.

Amino Acids↗

PubMed2003

Comparison of Cox regression with other methods for determining prediction models and nomograms.

PURPOSE: There is controversy as to whether artificial neural networks and other machine learning methods provide predictions that are more accurate than those provided by traditional statistical models when applied to censored data. MATERIALS AND METHODS: Several machine learning prediction methods are compared with Cox proportional hazards regression using 3 large urological datasets. As a measure of predictive ability, discrimination that is similar to an area under the receiver operating characteristic curve is computed for each. RESULTS: In all 3 datasets Cox regression provided comparable or superior predictions compared with neural networks and other machine learning techniques. In general, this finding is consistent with the literature. CONCLUSIONS: Although theoretically attractive, artificial neural networks and other machine learning techniques do not often provide an improvement in predictive accuracy over Cox regression.

Brachytherapy↗

PubMed2006

Predicting 5-fluorouracil chemosensitivity of liver metastases from colorectal cancer using primary tumor specimens: three-gene expression model predicts clinical response.

We identified genes related to 5-fluorouracil (5-FU) sensitivity in colorectal cancer and utilized these genes for predicting the 5-FU sensitivity of liver metastases. Eighty-one candidate genes involved in 5-FU resistance in gastric and colon cancer cell lines were previously identified using a cDNA microarray. In this study, the mRNA expression levels of these 81 selected genes and the genes of 5-FU-related enzymes, including thymidylate synthase (TS), dihydropyrimidine dehydrogenase (DPD) and orotate phosphoribosyltransferase (OPRT), were measured using real-time quantitative RT-PCR assays of surgically resected materials from primary colorectal tumors in 22 patients. Clinical responses were estimated by evaluating the effects of 5-FU-based hepatic artery injection (HAI) chemotherapy for synchronous liver metastases. Four genes (TNFRSF1B, SLC35F5, NAG-1 and OPRT) had significantly different expression profiles in 5-FU-nonresponding and responding tumors (p < 0.05). A "Response Index" system using three genes (TNFRSF1B, SLC35F5 and OPRT) was then developed using a discriminate analysis; the results were well correlated with the individual chemosensitivities. Among the 11 cases with positive scores in our response index, 9 achieved a reduction in their liver metastases after 5-FU-based chemotherapy, whereas only 1 of the 11 cases with negative scores responded well to chemotherapy. Our "Response Index" system, consisting of TNFRSF1B, SLC35F5 and OPRT, has great potential for predicting the efficacy of 5-FU-based chemotherapy against liver metastases from colorectal cancer.

Aged↗

PubMed2001

Individual changes in clozapine levels after smoking cessation: results and a predictive model.

Published reports document 20-40% lower mean serum clozapine concentrations in smokers compared with nonsmokers due to enzyme induction. Despite the increase in nonsmoking psychiatric facilities in the United States, previous studies have not tracked individual changes in serum clozapine levels after smoking cessation. Clozapine level changes were analyzed in 11 patients at Oregon State Hospital who were on stable clozapine doses, before and after implementation of a hospital-wide nonsmoking policy. A mean increase in clozapine levels of 71.9% (442.4 ng/ml +/- 598.8 ng/ml) occurred upon smoking cessation (p < .034) from a baseline level of 550.2 ng/ml (+/- 160.18 ng/ml). One serious adverse event, aspiration pneumonia, was associated with a nonsmoking serum clozapine level of 3066 ng/ml. Elimination of statistically extreme results generated a mean increase of 57.4 % or 284.1 ng/ml (+/- 105.2 ng/ml) for the remaining cases (p < .001) and permitted construction of a linear model which explains 80.9% of changes in clozapine levels upon smoking cessation (F = 34.9;p = .001): clozapine level as nonsmoker = 45.3 + 1.474 (clozapine level as smoker). These findings suggest that significant increases in clozapine levels upon smoking cessation may be predicted by use of a model. Those with high baseline levels should be monitored for serious adverse events.

Adult↗

PubMed1994

In vivo metabolism of butadiene by mice and rats: a comparison of physiological model predictions and experimental data.

1,3-Butadiene (BD), a rodent carcinogen, is metabolized to mutagenic and potentially DNA-reactive epoxides, including butadiene monoepoxide (BMO) and butadiene diepoxide. A physiological model containing five tissue groups (liver, lung, fat, slowly perfused tissues and rapidly perfused tissues) and blood was developed to describe uptake and metabolism of inhaled BD and BMO. Maximal rates for hepatic and pulmonary metabolism of BD and hepatic metabolism of BMO incorporated into the model were extrapolated from in vitro data (Csanády et al., Carcinogenesis, 13, 1143-1153, 1992). Apparent enzyme affinities used in the model were identified to the values measured in vitro. Model stimulations for BD and BMO uptake were compared to results from experiments in which groups of male Sprague-Dawley rats and B6C3F1 mice were exposed to initial concentrations of 50-5000 p.p.m. BD in closed chamber experiments and published data on BMO uptake by rats and mice. Metabolic rate constants extrapolated from in vitro data stimulated both BMO and BD uptake from closed chambers. The Vmax for hepatic metabolism of BD extrapolated from in vitro studies was 62 mumol/kg/h for rats and 340 mumol/kg/h for mice, while the Vmax for pulmonary metabolism of BD was 1.0 and 22 for rats and mice, respectively. These results demonstrate the usefulness of data derived in vitro for predicting in vivo behavior. Model simulations were also conducted in which only hepatic metabolism of BD was incorporated. These simulations underestimated BD uptake for mice, but not rats. Inclusion of in vitro-derived rates of pulmonary metabolism of BD into the model improved the fit to the data for mice. Since mice, but not rats, develop lung tumors after exposure to BD, these results point to the need for further characterize the metabolic capacity and target cells in the lung for BD and its metabolites. Once characterized, these models can be extended to predict in vivo behavior of BD in humans.

Animals↗