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PubMed2002

Genealogical process on a correlated fitness landscape.

We study with extensive numerical simulation the genealogical process of 2N haploid genetic sequences. The sequences are under selective pressure, and fitness values are assigned at random, but with a tunable degree of correlation to the fitness values of closely related sequences. The genealogies that we observe can be classified into three different categories, corresponding to different regimes of the mutation rate. At low mutation rates, the sequences remain localized around a small number of central sequences, which leads to trees with short pairwise distances and slow turnover of the most recent common ancestor of the population. At high mutation rates, we observe trees similar (but not identical) to those of neutral evolution. In this regime, the population drifts rapidly, and selection does not influence the distribution of fitness values in the population. The third regime, for intermediate mutation rates, is only found in strongly correlated landscapes. It resembles the one for high mutation rates in that the population drifts rapidly, but nevertheless selection still shapes the distribution of fitness values.

Animals↗

PubMed1994

Primary human herpesvirus-6 infection is frequently overlooked as a cause of febrile fits in young children.

Sera from 248 children aged 30-179 weeks were tested retrospectively for human herpesvirus-6 (HHV-6) IgG antibody avidity. Twenty-five children presented with febrile fits, in one case with a rash, exanthem subitum resulting from primary HHV-6 infection was diagnosed at the time, but in the others HHV-6 was not considered in the differential diagnosis even though two patients had a rash. In fact, five of the 25 patients experienced primary infection as shown by low avidity HHV-6 antibody. Although nine other of these patients were seronegative in the acute phase of the illness, and unfortunately convalescent sera were not available to confirm primary HHV-6 infection, seronegativity was clearly a risk factor for febrile fits (P = 0.03, odds ratio 3.14 for all children; P = 0.002, odds ratio 7.20 for children aged 70-179 weeks), and primary HHV-6 infection was a very likely diagnosis. The remaining 11 children had high avidity antibody, so HHV-6 was excluded as a cause of their febrile fits. HHV-6 may frequently be a cause of febrile fits, often without the typical rash of exanthem subitum, and this diagnosis is often overlooked by clinicians.

Antibodies, Viral↗

PubMed1993

Dual energy x-ray absorptiometry of implanted femora after cemented and press-fit total hip arthroplasty in a canine model.

The effect of a press-fit and cemented titanium alloy endoprosthesis on the measurement of bone mineral density (BMD) of the proximal femur in a canine model with dual energy x-ray absorptiometry (DXA) was determined. Seven regions of interest, corresponding to zones 1-7 according to Gruen et al., were measured. Eight unpaired femora were scanned with DXA before implantation (five separate scans per femur), after press-fitting with a titanium alloy femoral component (five separate scans per femur); and after cementing with the same component (five separate scans per femur). When the titanium alloy endoprosthesis was press-fit, the BMD of five of seven regions of the proximal femur increased significantly (range, 2.7-23.1%; mean, 11.2%), although the mean precision error of this measurement was not altered (before implantation, 1.1%; after press-fit 1.8%). Cementing of the implant caused a variable effect on BMD, resulting in a decrease in distal regions where cortical bone was relatively thin compared with the cement mantle (regions 3, 4, and 5) and in an increase in the other regions. Cementing of the implant significantly increased the mean precision error of measurement to 7.2% (range, 1.1-12.6%).

Absorptiometry, Photon↗

PubMed2003

Crystallization kinetics of amorphous nifedipine studied by model-fitting and model-free approaches.

The crystallization of amorphous nifedipine was studied using hot-stage microscopy (HSM), powder X-ray diffractometry (PXRD), and differential scanning calorimetry (DSC). The kinetic data obtained from DSC studies under isothermal and nonisothermal conditions were examined using both model-fitting and model-free approaches. Evaluation of 16 different models showed that model A4 (Avrami-Erofeev, n = 4) to be most appropriate for crystallization in the conversion range 0.05-0.80. This choice was based on the goodness of fit, the residual plots, and the guidance provided by the model-free approach. The model-free approach indicated that the activation energy decreases slightly as the crystallization proceeds. This variation of the activation energy with the extent of conversion determines the range of conversion over which a model can be fit, and the magnitude of the activation energy helps in the selection of the best model. The model-free approach gives much better predictions than the model of best fit and allows the experimental kinetic function to be numerically evaluated. At the early stage (alpha = 0-0.6), the numerically reconstructed model is almost identical to A4, but gradually approaches A3 (Avrami-Erofeev, n = 3) as the crystallization progresses (alpha = 0.6-0.8) and deviates from both models near the end of the reaction. This behavior may be explained by the relative contributions of nucleation and crystal growth at different stages of the reaction.

Calorimetry, Differential Scanning↗

PubMed2005

Tooth caries detection by curve fitting of laser-induced fluorescence emission: a comparative evaluation with reflectance spectroscopy.

BACKGROUND AND OBJECTIVES: Nitrogen laser-induced fluorescence (LIF) spectra of sound tooth consists of two broad bands centered at 440 and 490 nm, with two apparent side bands on either side. In order to locate the exact peak position of these bands and to effectively utilize the LIF spectral signatures for detection of tooth caries, the LIF spectra were curve-fitted using Gaussian spectral functions and the results were compared with those from diffuse reflectance spectral measurements. STUDY DESIGN/MATERIALS AND METHODS: The excitation light at 337.1 nm was guided to the sound and caries-affected tooth samples through the central fiber of the fiber-optic probe of a laser-induced fluorescence reflectance spectroscopy (LIFRS) system. Six surrounding fibers of the probe collect tooth fluorescence or diffuse reflectance from the lesion and direct it to a miniature spectrometer. The in vitro spectra were obtained from healthy enamel, dentin, and pulp level tooth caries. RESULTS: As compared to sound tooth, the caries tooth showed lower fluorescence and reflectance intensities in the 350-700 nm region. The deconvoluted peaks in the LIF spectra of sound tooth were found centered at 403.80, 434.20, 486.88, and 522.45 nm, whereas in the case of pulp level caries, a new peak was observed at 636.78 nm. Curve-fitted parameters, such as peak center, Gaussian curve area, full width at half intensity maximum (FWHM), and their ratios, were also found to vary with the stage of tooth caries. The ratios involving the 435 nm band, such as F405/F435, F435/F490, and F435/F525 ratios derived from curve-fitted areas and amplitudes, were found to be sensitive to discriminate between sound, dentin, and pulp level caries. Among the various diffuse reflectance spectral intensity ratios, the R500/R700 was found to be most sensitive to distinguish between pulp and dentin level caries. CONCLUSIONS: Nitrogen laser-excited fluorescence spectral studies were found to be more suited for detection of caries lesions. The LIF measurement with spectral analysis, done by curve fitting, outscores the diffuse reflectance methodology and shows the potential to screen different levels of tooth decay in a clinical setting.

Dental Caries↗

PubMed1992

Determination of concentrations by time domain fitting of proton NMR echo signals using prior knowledge.

A fast and flexible time domain iterative fitting procedure that can be used to fit free induction decays as well as echo-like signals is described. Damping constants of the first and second part of the echo do not have to be identical. Prior knowledge can be used to diminish the number of parameters to be fitted, which results in an improved accuracy. It is shown how prior knowledge is mathematically incorporated in the Gauss-Newton method. From proton NMR measurements of model solutions actual prior knowledge is extracted. With this knowledge relative concentrations are determined from a mixture of metabolites. The fitted results agree with the true values within the margins of the noise. After some minor changes the same prior knowledge was successfully used to analyze a series of in vivo rat brain measurements.

Magnetic Resonance Spectroscopy↗

PubMedDate not supplied

Medication and fitness to drive.

PURPOSE: The aim of this study is to analyze the consumption patterns of medicaments among motor vehicle drivers who attend 'Medical Driving Test Centres' and the relation between habitual consumption of medicaments and fitness to drive. METHODS: The study was carried out on 8043 drivers who attended 25 Medical Driving Test Centres. RESULTS: 24.7% of drivers chronically consume medicaments while 6.8% consume medicaments along with alcohol every day. Of those who chronically consume medicaments with a warning about the medications on driving, 65.8% were considered 'fit' to drive, 27.3% 'fit with restrictions', 5.1% 'suspended' and 0.4% 'unfit'. CONCLUSIONS: The results show how frequent the consumption of medicaments along with alcohol is and that the great majority of drivers who take medicaments are considered fit to drive.

Adolescent↗

PubMed2005

Weaknesses of goodness-of-fit tests for evaluating propensity score models: the case of the omitted confounder.

PURPOSE: Propensity scores are used in observational studies to adjust for confounding, although they do not provide control for confounders omitted from the propensity score model. We sought to determine if tests used to evaluate logistic model fit and discrimination would be helpful in detecting the omission of an important confounder in the propensity score. METHODS: Using simulated data, we estimated propensity scores under two scenarios: (1) including all confounders and (2) omitting the binary confounder. We compared the propensity score model fit and discrimination under each scenario, using the Hosmer-Lemeshow goodness-of-fit (GOF) test and the c-statistic. We measured residual confounding in treatment effect estimates adjusted by the propensity score omitting the confounder. RESULTS: The GOF statistic and discrimination of propensity score models were the same for models excluding an important predictor of treatment compared to the full propensity score model. The GOF test failed to detect poor model fit for the propensity score model omitting the confounder. C-statistics under both scenarios were similar. Residual confounding was observed from using the propensity score excluding the confounder (range: 1-30%). CONCLUSIONS: Omission of important confounders from the propensity score leads to residual confounding in estimates of treatment effect. However, tests of GOF and discrimination do not provide information to detect missing confounders in propensity score models. Our findings suggest that it may not be necessary to compute GOF statistics or model discrimination when developing propensity score models.

Confounding Factors, Epidemiologic↗

PubMed2002

Goodness-of-fit processes for logistic regression: simulation results.

In this paper we use simulations to compare the performance of new goodness-of-fit tests based on weighted statistical processes to three currently available tests: the Hosmer-Lemeshow decile-of-risk test; the Pearson chi-square, and the unweighted sum-of-squares tests. The simulations demonstrate that all tests have the correct size. The power for all tests to detect lack-of-fit due to an omitted quadratic term with a sample of size 100 is close to or exceeds 50 per cent to detect moderate departures from linearity and is over 90 per cent for these same alternatives for sample size 500. All tests have low power with sample size 100 to detect lack-of-fit due to an omitted interaction between a dichotomous and continuous covariate, while the power exceeds 80 per cent to detect extreme interaction with a sample size of 500. The power is low to detect any alternative link function with sample size 100 and for most alternative links for sample size 500. Only in the case of sample size 500 and an extremely asymmetric link function is the power over 80 per cent. The results from these simulations show that no single test, new or current, performs best in detecting lack-of-fit due to an omitted covariate or incorrect link function. However, one of the new weighted tests has power comparable to other tests in all settings simulated and had the highest power in the difficult case of an omitted interaction term. We illustrate the tests within the context of a model for factors associated with abstinence from drug use in a randomized trial of residential treatment programmes. We conclude the paper with a summary and specific recommendations for practice.

Computer Simulation↗

PubMed2003

Assessment of diagnostic markers by goodness-of-fit tests.

Receiver operating characteristic (ROC) curves are useful statistical tools used to assess the precision of diagnostic markers or to compare new diagnostic markers with old ones. The most common index employed for these purposes is the area under the ROC curve (theta) and several statistical tests exist that test the null hypotheses H(0): theta= 0.5 or H(0): theta1=theta2, in the case of two-marker comparisons, against alternatives of interest. In this paper we show that goodness-of-fit of uniformity of the distribution of the false positive (true positive) rates can be used instead of tests based on the area index. A semi-parametric approach is based on a completely specified distribution of marker measurements for either the healthy (F) or diseased (G) subjects, and this is extended to the two-marker case. We then extend to the one- and two-marker case when neither distribution is specified (the non-parametric case). In general, ROC-based tests are more powerful than goodness-of-fit tests for location differences between the distributions of healthy and diseased subjects. However ROC-based tests are less powerful when location-scale differences exist (producing ROC curves that cross the diagonal) and are incapable of discriminating between healthy and diseased samples when theta=0.5 but F not equal G. In these cases, goodness-of-fit tests have a distinct advantage over ROC-based tests. In conclusion, ROC methodology should be used with recognition of its potential limitations and should be replaced by goodness-of-fit tests when appropriate. The latter are a viable alternative and can be used as a 'black box' or as an exploratory first step in the evaluation of novel diagnostic markers.

Biomarkers↗

PubMed1990

A two-step method for understanding and fitting growth curve models.

With data from a repeated measures design, analysts often overlook growth curve analysis based on the Potthoff-Roy model. The reluctance to perform a growth analysis may result partially from unfamiliarity with the technique, and partially from the lack of readily available computational programs to fit the models. Although growth curve analysis has traditionally appeared as a special technique in multivariate analysis, one can fit the models with the use of two simple ideas: transformation of variables, and weighted least squares (WLS). When presented in this manner, growth models are a natural extension of univariate repeated measures models. Growth curve analyses share with univariate analyses the common objective to limit estimation to a parsimonious set of parameters that characterize the response profiles. One can readily fit models with commonly available software. The two-step methodology also allows the fit of more general growth models that are appropriate when groups have different shape profiles. Two examples illustrate this approach to growth curve analysis.

Animals↗

PubMed2002

Two goodness-of-fit tests for logistic regression models with continuous covariates.

Assessing goodness-of-fit in logistic regression models can be problematic, in that commonly used deviance or Pearson chi-square statistics do not have approximate chi-square distributions, under the null hypothesis of no lack of fit, when continuous covariates are modelled. We present two easy to implement test statistics similar to the deviance and Pearson chi-square tests that are appropriate when continuous covariates are present. The methodology uses an approach similar to that incorporated by the Hosmer and Lemeshow goodness-of-fit test in that observations are classified into distinct groups according to fitted probabilities, allowing sufficient cell sizes for chi-square testing. The major difference is that the proposed tests perform this grouping within the cross-classification of all categorical covariates in the model and, in some situations, allow for a more powerful assessment of where model predicted and observed counts may differ. A variety of simulations are performed comparing the proposed tests to the Hosmer-Lemeshow test.

Aortic Aneurysm, Abdominal↗

PubMed1993

Prediction of protein structure by evaluation of sequence-structure fitness. Aligning sequences to contact profiles derived from three-dimensional structures.

The problem of protein structure prediction is formulated here as that of evaluating how well an amino acid sequence fits a hypothetical structure. The simplest and most complicated approaches, secondary structure prediction and all-atom free energy calculations, can be viewed as sequence-structure fitness problems. Here, an approach of intermediate complexity is described, which involves; (1) description of a protein structure in terms of contact interface vectors, with both intra-protein and protein-solvent contacts counted, (2) derivation of sequence preferences for 2 up to 29 contact interface types, (3) generation of numerous hypothetical model structures by placing the input sequence into a large set of known three-dimensional structures in all possible alignments, (4) evaluation of these models by summing the sequence preferences over all structural positions and (5) choice of predicted three-dimensional structure as that with the best sequence-structure fitness. Evolutionary information is incorporated by using position-dependent core weights derived from multiple sequence alignments. A number of tests of the method are performed: (1) evaluation of cyclic shifts of a sequence in its native structure; (2) alignment of a sequence in its native structure, allowing gaps; (3) alignment search with a sequence or sequence fragment in a database of structures; and (4) alignment search with a structure in a database of sequences. The main results are: (1) a native sequence can very well find its native structure among a large number of alternatives, in correct alignment; (2) substructures, such as (beta alpha)n units, can be detected in spite of very low sequence similarity; (3) remote homologous can be detected, with some dependence on the set of parameters used; (4) contact interface parameters are clearly superior to classical secondary structure parameters; (5) a simple interface description in terms of just two states, protein-protein and protein-water contacts, performs surprisingly well; (6) the use of core weights considerably improves accuracy in detection of remote homologues; (7) based on a sequence database search with a myoglobin contact profile, the C-terminal domain of a viral origin of replication binding protein is predicted to have an all-helical fold. The sequence-structure fitness concept is sufficiently general to accommodate a large variety of protein structure prediction methods, including new models of intermediate complexity currently being developed.

Amino Acid Sequence↗

PubMed2002

Resistance to extinction of low fitness virus subjected to plaque-to-plaque transfers: diversification by mutation clustering.

Plaque-to-plaque transfers of RNA viruses lead to accumulation of mutations and fitness decrease. To test whether continuing plaque-to-plaque transfers would lead to viral extinction, we have subjected several low fitness foot-and-mouth disease virus (FMDV) clones to up to 130 successive plaque transfers, and have analyzed the evolution of plaque titers and genomic nucleotide sequences. No case of viral extinction could be documented. Some low fitness clones that posses an internal poly(A) tract evaded extinction by modifying the length or base composition of the poly(A) tract. The comparison of entire genomic sequences of FMDV clones at increasing plaque transfer number revealed that mutations accumulated at a uniform rate, and that they were distributed unevenly along the genome. Clusters of mutations were identified at different genomic sites in two plaque transfer lineages. Mutation clustering appears to occur stochastically and could not be related to fixation of compensatory mutations. The results document resistance of viral clones to extinction, and suggest that mutation clustering may be a mechanism of genetic diversification of low fitness virus.

Animals↗

PubMed2001

Time averaging and fitting of nonlinear metabolic changes: the issue of the time index choice applied to 31P MRS investigation of muscle energetics.

We present an exact analytical method dedicated to fitting time-dependent exponential-like changes in MR spectra. As an illustration, this method has been applied to fitting metabolic changes recorded by 31P MRS in human skeletal muscle occurring during a rest-exercise-recovery protocol. When recording metabolic changes with the accumulative method, the time averaging of the MR signals implies the choice of a time index for fitting any changes in the features of the associated MR spectra. A critical examination of the different ways (constant, linear, and exponential) of choosing the time index is reported. By numerical analysis, we have calculated the errors generated by the three methods and we have compared their sensitivity to noise. In the case of skeletal muscle, both constant and linear methods introduce large and uncontrolled errors for the whole set of metabolic parameters derived from [PCr] changes. In contrast, the exponential method affords a reliable estimation of critical parameters in muscle bioenergetics in both normal and pathological situations. This method is very easy to implement and provides an exact analytical solution to fitting changes in MR spectra recorded by the accumulative method.

Computer Simulation↗

PubMed2000

Contact Transformations and Determinable Parameters in Spectroscopic Fitting Hamiltonians.

In recent least-squares fits of torsion-rotation spectra of acetaldehyde and methanol it was found possible to adjust more fourth-order parameters than would be expected from traditional contact-transformation considerations. To investigate this discrepancy between theory and practice we have carried out numerical fitting experiments on the simpler three-dimensional (three-Eulerian-angle) asymmetric rotor problem, using J </= 20 unitless energy levels generated artificially from a full orthorhombic Hamiltonian with quadratic through octic operators in the angular momentum components. Results are analyzed using the condition number kappa of the least-squares matrix, which is a measure of its invertibility in the presence of round-off and other errors. When kappa is very large, parameters must be removed from the fit until kappa becomes acceptably small, corresponding to procedures which lead to reduced Hamiltonians in molecular spectroscopy. We find that under certain circumstances kappa can be decreased to an acceptable level for Hamiltonians which are only partially reduced when compared to Watson A and S reductions. Some insight into this behavior is obtained from classical mechanics and from the concept of delayed contact transformations. Transferring this numerical and algebraic understanding to the more complicated four-dimensional methyl-top internal rotor problem supports the empirical observation that presently existing data sets for methanol and acetaldehyde are most efficiently fit using partially reduced Hamiltonians and further suggests that expanding the methanol data set to transitions involving levels of higher J, K, and v(t) would favor even more strongly the use of partially reduced fourth-order Hamiltonians.

Journal Article↗

PubMed1994

Koinophilia replaces random mating in populations subject to mutations with randomly varying fitnesses.

Koinophilia, the avoidance of sexual mates bearing strange phenotypic features, or displaying odd behaviour, would, if it evolved, profoundly influence the evolutionary process. A stochastic computer model was therefore devised to investigate the evolution of an initially rare koinophilic trait in panmictic populations, subject to mutations with randomly varying fitnesses. Individual genomes consisted of 50 genes. Mutations occurred at a rate of 0.005, 0.01 or 0.02 per gene per generation. The mean and maximum fitness of mutations could be varied, as could the proportion of beneficial mutations. The carriers of the koinophilic trait avoided, with adjustable degrees of intensity, mates displaying unusual phenotypic features (traits with population frequencies < 0.5); panmictic individuals mated randomly. The results show that koinophilia tends to replace panmixis whenever the preference for common phenotypic traits is strongly expressed, when few mutations are beneficial (1% instead of 10%), or when the maximum fitness of mutations is low (1.2 instead of 2.0). The mutation rate and mean fitness of mutations had only minor effects on the relative advantage of koinophilia.

Animals↗

PubMed2000

Fitness of human immunodeficiency virus type 1 protease inhibitor-selected single mutants.

Human immunodeficiency virus type 1 (HIV-1) evolution under chemotherapeutic selection pressure in vivo involves a complex interplay between an increasing magnitude of drug resistance and changes in viral replicative capacity. To examine the replicative fitness of HIV-1 mutants with single, drug-selected substitutions in protease (PR), we constructed virus that contained the most common mutations in indinavir-selected clinical isolates, PR M46I and V82T, and the most common polymorphic change in drug-naïve patients, PR L63P. These mutants were competed in vitro in the absence of drug against the otherwise isogenic WT virus (NL4-3). Phenotypic drug susceptibility was determined with a recombinant virus assay using a single cycle of virus growth. PR M46I and L63P were as fit as WT. However, PR V82T was out-competed by WT. None of these mutants had appreciable phenotypic resistance to any of the protease inhibitors, including indinavir. The PRV82T mutant was hypersusceptible to saquinavir. Thus, the impaired fitness of the V82T single mutant is consistent with its low frequency in protease inhibitor-naïve patients. The similar fitness of WT (NL4-3), L63P, and M46I is consistent with the common occurrence of L63P in the absence of protease inhibitor-selection pressure, but not with the rare detection of M46I in drug-naïve patients.

Drug Resistance, Microbial↗