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This article concerns construction of a confidence surface for tangential slopes of the dose-response surface of a combination therapy to identify where response increases as a function of drug dosage. This approach extends to the assessment of the effectiveness of the combination therapy.
Comparison of 317 gene pairs in human and mouse that were duplicated after the most recent common ancestor of the two species was used to search for candidates that may have undergone functional differentiation. Even when corrected for multiple tests, Tajima's relative rate test showed significant rate differences in 36% of cases for which the test was applicable. However, a significant result in this case was increasingly likely as the sequence length increased; thus, a statistically significant result of a relative rate test may not be biologically meaningful. We used regression methods to provide more robust methods of testing for functionally differentiated gene pairs, which take into account the variation in the entire data set by examination of residuals from regression-identified gene pairs with unusually high nonsynonymous divergence from a reference sequence and from each other. This approach identified six duplicate gene pairs that appeared to be candidates for functional differentiation as a result of positive Darwinian selection.
A single nucleotide polymorphism in the promoter of the multifunctional cytokine Interleukin 4 (IL4) affects the binding of NFAT, a key transcriptional activator of IL4 in T cells. This regulatory polymorphism influences the balance of cytokine signaling in the immune system, with important consequences-positive and negative-for human health. We determined that the NFAT binding site is unique to humans; it arose by point mutation along the lineage separating humans from other great apes. We show that its frequency distribution among human subpopulations has been shaped by the balance of selective forces on IL4's diverse roles. New statistical approaches, based on parametric and nonparametric comparisons to neutral variants typed in the same individuals, indicate that differentiation among subpopulations at the IL4 promoter polymorphism is too great to be attributed to neutral drift. The allele frequencies of this binding site represent local adaptation to diverse pathogenic challenges; disease states associated with the common derived allele are side-effects of positive selection on other IL4 functions.
The aims of this prospective study were to explore in subjects with psychosis participating in a rehabilitation program whether cognitive performances at baseline predicted (i) psychosocial functioning over a 15-16 month follow-up; (ii) improvement in psychosocial functioning over the rehabilitation program. Visuo-spatial tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were administered to assess cognitive performance in 55 subjects with schizophrenia spectrum disorders who completed a rehabilitation program. The Multnomah Community Ability Scale (MCAS) was used to measure dimensions of community functioning. One subscale of the Client's Assessment of Strengths, Interests, and Goals (CASIG) provided a measure of subjective quality of life (QoL). Improvement was defined as a 15% or more increase in psychosocial scores between baseline and follow-up. Worse baseline sustained attention predicted better self-rated quality of life, and better baseline visual memory predicted better community functioning over the rehabilitation follow-up period, in particular, higher autonomy in activities of daily living, and less physical and psychiatric symptoms that could interfere with rehabilitation. Baseline cognitive performances predicted community functioning improvement during the follow-up period: visual memory predicted improvement in daily living autonomy and in social competence; sustained attention predicted improvement in behavioral problems (such as medication compliance, collaboration with treatment providers or impulse control) and social competence; planning performances predicted improvement in social competence. These cognitive functions could be specifically targeted in a rehabilitation program aimed at enhancing functioning in those particular dimensions.
The concomitantly variable codons hypothesis of DNA substitution argues that at any time only a fraction of the codons in a gene are capable of accepting a mutation. However, as mutations are fixed at some positions in a gene, the sites that are potentially variable also change because of changed functional constraints. This hypothesis has been termed the "covarion" hypothesis or when the model is applied to nucleotides, the "covariotide" hypothesis. The covarion-covariotide model has proven to be remarkably difficult to test. Here I examine a covariotide hypothesis for 11 genes using a likelihood ratio test. I show that in nine of the genes examined a covariotide model provides a better explanation of the data than a model that does not allow constraints to change over time.
The genetic analysis of characters that change as a function of some independent and continuous variable has received increasing attention in the biological and statistical literature. Previous work in this area has focused on the analysis of normally distributed characters that are directly observed. We propose a framework for the development and specification of models for a quantitative genetic analysis of function-valued characters that are not directly observed, such as genetic variation in age-specific mortality rates or complex threshold characters. We employ a hybrid Markov chain Monte Carlo algorithm involving a Monte Carlo EM algorithm coupled with a Markov chain approximation to the likelihood, which is quite robust and provides accurate estimates of the parameters in our models. The methods are investigated using simulated data and are applied to a large data set measuring mortality rates in the fruit fly, Drosophila melanogaster.
With parametric cure models, we can express survival parameters (e.g. cured fraction, location and scale parameters) as functions of covariates. These models can measure survival from a specific disease process, either by examining deaths due to the cause under study (cause-specific survival), or by comparing all deaths to those in a matched control population (relative survival). We present a binomial maximum likelihood algorithm to be used for actuarial data, where follow-up times are grouped into specific intervals. Our algorithm provides simultaneous maximum likelihood estimates for all the parameters of a cure model and can be used for cause-specific or relative survival analysis with a variety of survival distributions. Current software does not provide the flexibility of this unified approach.
A group of Dutch harbor workers involved in loading and unloading bulk products from sea vessels such as coal, cokes, and some other products like alumina, borax, phosphate ore, and vermiculite was studied. Exposures were characterized by personal and environmental monitoring. This information was subsequently used to estimate several dust exposure indices and to study relationships with lung function variables and respiratory symptoms. Average respirable dust exposure levels ranged from 0.3-4.0 mg/m3. Workers involved in unloading products from sea vessels were exposed to the highest dust levels. Supervisors and workers with tasks in the dock had an intermediate to low exposure. Office workers had the lowest exposure to respirable dust. Inhalable dust levels were considerably higher and average exposures ranged from 0.3-80 mg/m3. The ranking of occupational titles by inhalable dust exposure was almost identical to the rank order of respirable dust levels. Workers with higher current and cumulative dust exposures tended to have a lower lung function, and only shortness of breath had a statistically significant relationship with current and cumulative inhalable dust exposure. In general, relationships between lung function and inhalable dust levels tended to be somewhat stronger in terms of statistical significance, because inhalable dust is an estimate of dust deposition in the upper airways and lung function is a measurable parameter of airway obstruction in that region. However, the differences with respirable dust were minimal, and variability in dust exposure levels was extremely large for this population. It was concluded that harbor workers involved in unloading ships containing coal and various kinds of ore can be exposed to high dust levels. Relationships between dust exposure and lung function illustrate that these exposures are a respiratory hazard. Our finding that inhalable dust levels have a somewhat stronger relationship with lung function level than respirable dust levels deserves further attention.
Multistage mathematical models of carcinogenesis (when applied to tumor incidence data) have historically assumed that the growth kinetics of cells in the malignant state are disregarded and the formation of a single malignant cell is equated with the emergence of a detectable tumor. The justification of this simplification is, from a mathematical point of view, to make the estimation of tumor incidence rates tractable. However, analytical forms are not mandatory in the estimation of tumor incidence rates. Portier et al.(1996b, Math. Biosci. 135, 129-146) have demonstrated the utility of the Kolmogorov backward equations in numerically calculating tumor incidence. By extending their results, the cumulative distribution function of the time to a small observable tumor may be numerically obtained.
In this article, we investigate the properties of the posterior distribution under the uniform improper prior for two commonly used proportional hazards models; the Weibull regression model and the extreme value regression model. We allow the observations to be right censored. We obtain sufficient conditions for the existence of the posterior moment generating function of the regression coefficients. A dataset involving a lung cancer clinical trial and a simulation are presented to illustrate our results.
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In functional magnetic resonance imaging, voxel time courses after Fourier or non-Fourier "image reconstruction" are complex valued as a result of phase imperfections due to magnetic field inhomogeneities. Nearly all fMRI studies derive functional "activation" based on magnitude voxel time courses [Bandettini, P., Jesmanowicz, A., Wong, E., Hyde, J.S., 1993. Processing strategies for time-course data sets in functional MRI of the human brain. Magn. Reson. Med. 30 (2): 161-173 and Cox, R.W., Jesmanowicz, A., Hyde, J.S., 1995. Real-time functional magnetic resonance imaging. Magn. Reson. Med. 33 (2): 230-236]. Here, we propose to directly model the entire complex or bivariate data rather than just the magnitude-only data. A nonlinear multiple regression model is used to model activation of the complex signal, and a likelihood ratio test is derived to determine activation in each voxel. We investigate the performance of the model on a real dataset, then compare the magnitude-only and complex models under varying signal-to-noise ratios in a simulation study with varying activation contrast effects.
The ordered subsets EM (OSEM) algorithm has enjoyed considerable interest for emission image reconstruction due to its acceleration of the original EM algorithm and ease of programming. The transmission EM reconstruction algorithm converges very slowly and is not used in practice. In this paper, we introduce a simultaneous update algorithm called separable paraboloidal surrogates (SPS) that converges much faster than the transmission EM algorithm. Furthermore, unlike the 'convex algorithm' for transmission tomography, the proposed algorithm is monotonic even with nonzero background counts. We demonstrate that the ordered subsets principle can also be applied to the new SPS algorithm for transmission tomography to accelerate 'convergence', albeit with similar sacrifice of global convergence properties as for OSEM. We implemented and evaluated this ordered subsets transmission (OSTR) algorithm. The results indicate that the OSTR algorithm speeds up the increase in the objective function by roughly the number of subsets in the early iterates when compared to the ordinary SPS algorithm. We compute mean square errors and segmentation errors for different methods and show that OSTR is superior to OSEM applied to the logarithm of the transmission data. However, penalized-likelihood reconstructions yield the best quality images among all other methods tested.
In this study, we explored how the concept of the process partition may be applied to phylogenetic analysis. Sequence data were gathered from 23 species and subspecies of the swallowtail butterfly genus Papilio, as well as from two outgroup species from the genera Eurytides and Pachliopta. Sequence data consisted of 1,010 bp of the nuclear protein-coding gene elongation factor-1 alpha (EF-1 alpha) as well as the entire sequences (a total of 2,211 bp) of the mitochondrial protein-coding genes cytochrome oxidase I and cytochrome oxidase II (COI and COII). In order to examine the interaction between the nuclear and mitochondrial partitions in a combined analysis, we used a method of visualizing branch support as a function of partition weight ratios. We demonstrated how this method may be used to diagnose error at different levels of a tree in a combined maximum-parsimony analysis. Further, we assessed patterns of evolution within and between subsets of the data by implementing a multipartition maximum-likelihood model to estimate evolutionary parameters for various putative process partitions. COI third positions have an estimated average substitution rate more than 15 times that of EF-1 alpha, while COII third positions have an estimated average substitution rate more than 22 times that of EF-1 alpha. Ultimately, we found that although the mitochondrial and nuclear data were not significantly incongruent, homoplasy in the fast-evolving mitochondrial data confounded the resolution of basal relationships in the combined unweighted parsimony analysis despite the fact that there was relatively strong support for the relationships in the nuclear data. We conclude that there may be shortcomings to the methods of "total evidence" and "conditional combination" because they may fail to detect or accommodate the type of confounding bias we found in our data.
The statistical properties of the EEG and the MEG are described mathematically as the result of randomly distributed dipoles. These dipoles represent the interactions of cortical neurons. For certain dipole distributions, the first- and second-order moments of the electric and magnetic fields are derived analytically. If the dipoles are in a spherical volume conductor and have no preference for any direction, the variance of a differentially measured EEG-signal is only a function of the electrode distance. In this paper, the theoretically derived variance function will be compared with EEG- and MEG-measurements. It is shown that a dipole with a fixed position and a randomly fluctuating amplitude is an adequate model for the alpha-rhythm. An expression for the covariance between the magnetic field and a differentially measured EEG-signal is derived. This covariance is considered as a function of the magnetometer position, and is compared with the measurements of Chapman et al. [23]. The theory can be used to obtain a (spatial) covariance matrix of the background noise, which occurs in evoked potential measurements. Such a covariance matrix can be used to obtain a maximum likelihood estimator of the dipole parameters in evoked potential studies, to evaluate the merits of the so-called "Laplacian derivation," and for the interpolation of electromagnetic data.
To understand how body composition relates to functional impairment, the authors examined cross-sectional associations of absolute and relative measures of fat and lean mass with physical performance and self-reported functional limitation. The sample consisted of a community-based cohort of 1,655 older women and men from Sonoma, California, who had complete baseline data in 1993-1994 on body composition, physical performance, and functional limitation. Physical performance was assessed by walking speed and grip strength, while global functional limitation, across several domains, was assessed by self-report using standard questions. Lean mass and fat mass were estimated from bioelectric impedance using population-specific prediction equations derived from dual x-ray energy absorptiometry. Higher fat mass was associated with slower walking speed and greater likelihood of functional limitation, while higher lean mass was generally associated only with increased grip strength. A higher lean mass-to-fat mass ratio, a relative measure of body composition, was associated with faster walking speed and less limitation. These findings suggest that fat mass negatively impacts some domains of physical performance and overall functioning, while lean mass is less significant in absolute terms but is important relative to amount of body fat.
In a medical study we are often interested in graphically displaying the relationship between continuous variables and clinical events indicating disease progression. Often, it is reasonable to make the minimal assumption that the risk of progression is an arbitrary monotone function of the continuous variable. Sometimes the continuous variable is a disease marker which is recorded longitudinally, and so the goal is to provide a graphical display of the relationship between the hazard for progression and the most recent measurement of the longitudinal marker. For example, we know that for a patient with HIV infection, declining CD4 count is associated with an increased risk of opportunistic infection. The goal of this paper is to extend isotonic regression techniques to failure time data with a continuous covariate, to obtain a non-parametric estimate for the hazard of disease progression as a monotonic function of the continuous variable. We propose two methods for modelling the relationship of the hazard and covariate: the first assumes that the hazard is constant over time, and the second allows the hazard to be an arbitrary function of time. These methods will be applied to graphically display the risk for an AIDS patient of an opportunistic infection as a function of CD4 count.
Atypical antipsychotics account for more than 60% of antipsychotic prescriptions written for the treatment of schizophrenia. While switching from one antipsychotic to another is a dynamic process, there has been no research on individual patient and institutional characteristics that predict antipsychotic switching. VA national administrative data were used to identify patients (n = 9660) with schizophrenia maintained on antipsychotic medication. Logistic regression was used to identify predictors of medication switching. Independent variables included information about service utilization, sociodemographic and clinical variables as well as institutional characteristics. This model was repeated for more specific switches between classes of medications and between specific medications. High levels of outpatient and inpatient service use were the most powerful predictors of switching. Sociodemographic, institutional, diagnostic, and functional measures were also predictive in some cases. Controlling for independent sociodemographic, diagnostic, and functional measures, frequency of clinical contact was the most robust predictor of switching antipsychotics.