Antimicrobial breakpoint estimation accounting for variability in pharmacokinetics

Background  

Pharmacokinetic and pharmacodynamic (PK/PD) indices are increasingly being used in the microbiological field to assess the efficacy of a dosing regimen. In contrast to methods using MIC, PK/PD-based methods reflect in vivo conditions and are more predictive of efficacy. Unfortunately, they entail the use of one PK-derived value such as AUC or Cmax and may thus lead to biased efficiency information when the variability is large. The aim of the present work was to evaluate the efficacy of a treatment by adjusting classical breakpoint estimation methods to the situation of variable PK profiles.     

Sparse inverse covariance estimation with the graphical lasso

We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm--the graphical lasso--that is remarkably fast: It solves a 1000-node problem ( approximately 500,000 parameters) in at most a minute and is 30-4000 times faster than competing methods. It also provides a conceptual link between the exact problem and the approximation suggested by Meinshausen and Bühlmann (2006). We illustrate the method on some cell-signaling data from proteomics.     

Accounting for variability in sample size estimation with applications to nonadherence and estimation of variance and effect size

We consider sample size calculations for testing differences in means between two samples and allowing for different variances in the two groups. Typically, the power functions depend on the sample size and a set of parameters assumed known, and the sample size needed to obtain a prespecified power is calculated. Here, we account for two sources of variability: we allow the sample size in the power function to be a stochastic variable, and we consider estimating the parameters from preliminary data. An example of the first source of variability is nonadherence (noncompliance). We assume that the proportion of subjects who will adhere to their treatment regimen is not known before the study, but that the proportion is a stochastic variable with a known distribution. Under this assumption, we develop simple closed form sample size calculations based on asymptotic normality. The second source of variability is in parameter estimates that are estimated from prior data. For example, we account for variability in estimating the variance of the normal response from existing data which are assumed to have the same variance as the study for which we are calculating the sample size. We show that we can account for the variability of the variance estimate by simply using a slightly larger nominal power in the usual sample size calculation, which we call the calibrated power. We show that the calculation of the calibrated power depends only on the sample size of the existing data, and we give a table of calibrated power by sample size. Further, we consider the calculation of the sample size in the rarer situation where we account for the variability in estimating the standardized effect size from some existing data. This latter situation, as well as several of the previous ones, is motivated by sample size calculations for a Phase II trial of a malaria vaccine candidate.     

Transition states for protein folding have native topologies despite high structural variability

We present a structural analysis of the folding transition states of three SH3 domains. Our results reveal that the secondary structure is not yet fully formed at this stage of folding and that the solvent is only partially excluded from the interior of the protein. Comparison of the members of the transition state ensemble with a database of native folds shows that, despite substantial local variability, the transition state structures can all be classified as having the topology characteristic of an SH3 domain. Our results suggest a mechanism for folding in which the formation of a network of interactions among a subset of hydrophobic residues ensures that the native topology is generated. Such a mechanism enables high fidelity in folding while minimizing the need to establish a large number of specific interactions in the conformational search.     

Sparse representation of brain aging: extracting covariance patterns from structural MRI

An enhanced understanding of how normal aging alters brain structure is urgently needed for the early diagnosis and treatment of age-related mental diseases. Structural magnetic resonance imaging (MRI) is a reliable technique used to detect age-related changes in the human brain. Currently, multivariate pattern analysis (MVPA) enables the exploration of subtle and distributed changes of data obtained from structural MRI images. In this study, a new MVPA approach based on sparse representation has been employed to investigate the anatomical covariance patterns of normal aging. Two groups of participants (group 1:290 participants; group 2:56 participants) were evaluated in this study. These two groups were scanned with two 1.5 T MRI machines. In the first group, we obtained the discriminative patterns using a t-test filter and sparse representation step. We were able to distinguish the young from old cohort with a very high accuracy using only a few voxels of the discriminative patterns (group 1:98.4%; group 2:96.4%). The experimental results showed that the selected voxels may be categorized into two components according to the two steps in the proposed method. The first component focuses on the precentral and postcentral gyri, and the caudate nucleus, which play an important role in sensorimotor tasks. The strongest volume reduction with age was observed in these clusters. The second component is mainly distributed over the cerebellum, thalamus, and right inferior frontal gyrus. These regions are not only critical nodes of the sensorimotor circuitry but also the cognitive circuitry although their volume shows a relative resilience against aging. Considering the voxels selection procedure, we suggest that the aging of the sensorimotor and cognitive brain regions identified in this study has a covarying relationship with each other.     

Evolutionary Sparse Learning for Phylogenomics

We introduce a supervised machine learning approach with sparsity constraints for phylogenomics, referred to as evolutionary sparse learning (ESL). ESL builds models with genomic loci—such as genes, proteins, genomic segments, and positions—as parameters. Using the Least Absolute Shrinkage and Selection Operator, ESL selects only the most important genomic loci to explain a given phylogenetic hypothesis or presence/absence of a trait. ESL models do not directly involve conventional parameters such as rates of substitutions between nucleotides, rate variation among positions, and phylogeny branch lengths. Instead, ESL directly employs the concordance of variation across sequences in an alignment with the evolutionary hypothesis of interest. ESL provides a natural way to combine different molecular and nonmolecular data types and incorporate biological and functional annotations of genomic loci in model building. We propose positional, gene, function, and hypothesis sparsity scores, illustrate their use through an example, and suggest several applications of ESL. The ESL framework has the potential to drive the development of a new class of computational methods that will complement traditional approaches in evolutionary genomics, particularly for identifying influential loci and sequences given a phylogeny and building models to test hypotheses. ESL’s fast computational times and small memory footprint will also help democratize big data analytics and improve scientific rigor in phylogenomics.     

Motions and structural variability within toxins: implication for their use as scaffolds for protein engineering

Animal toxins are small proteins built on the basis of a few disulfide bonded frameworks. Because of their high variability in sequence and biologic function, these proteins are now used as templates for protein engineering. Here we report the extensive characterization of the structure and dynamics of two toxin folds, the "three-finger" fold and the short alpha/beta scorpion fold found in snake and scorpion venoms, respectively. These two folds have a very different architecture; the short alpha/beta scorpion fold is highly compact, whereas the "three-finger" fold is a beta structure presenting large flexible loops. First, the crystal structure of the snake toxin alpha was solved at 1.8-A resolution. Then, long molecular dynamics simulations (10 ns) in water boxes of the snake toxin alpha and the scorpion charybdotoxin were performed, starting either from the crystal or the solution structure. For both proteins, the crystal structure is stabilized by more hydrogen bonds than the solution structure, and the trajectory starting from the X-ray structure is more stable than the trajectory started from the NMR structure. The trajectories started from the X-ray structure are in agreement with the experimental NMR and X-ray data about the protein dynamics. Both proteins exhibit fast motions with an amplitude correlated to their secondary structure. In contrast, slower motions are essentially only observed in toxin alpha. The regions submitted to rare motions during the simulations are those that exhibit millisecond time-scale motions. Lastly, the structural variations within each fold family are described. The localization and the amplitude of these variations suggest that the regions presenting large-scale motions should be those tolerant to large insertions or deletions.     

Genome variability and capsid structural constraints of hepatitis a virus

The number of synonymous mutations per synonymous site (K(s)), the number of nonsynonymous mutations per nonsynonymous site (K(a)), and the codon usage statistic (N(c)) were calculated for several hepatitis A virus (HAV) isolates. While K(s) was similar to those of poliovirus (PV) and foot-and-mouth disease virus (FMDV), K(a) was 1 order of magnitude lower. The N(c) parameter provides information on codon usage bias and decreases when bias increases. The N(c) value in HAV was about 38, while in PV and FMDV, it was about 53. The emergence of 22 rare codons in front of 8 in PV and 7 in FMDV was detected. Most of the conserved rare codons of the P1 region were strategically located at the carboxy borders of beta barrels and alpha helices, their potential function being the assurance of proper folding of the capsid proteins through a decrease in the translation speed. This strategic location was not observed for amino acids encoded by the conserved rare codons of the 3D region. The percentage of bases with low pairing number values was higher in the latter region, suggesting a role of the conserved rare codons in the maintenance of RNA structure. Many of the rare codons in HAV are among the most frequent in humans, unlike in PV or in FMDV. This fact may be explained by the lack of cellular shutoff in HAV. One hypothesis is that HAV has evolved in order to avoid competition with its host for cellular tRNAs.     

Extension and structural variability of the antithrombin-binding sequence in heparin

Oligosaccharides with different affinities for antithrombin were isolated following partial deaminative cleavage of pig mucosal heparin with nitrous acid. The smallest high-affinity component obtained was previously identified as an octasaccharide with the predominant structure: (Formula: see text). The interaction of this octasaccharide, and of deca- and dodecasaccharides containing the same octasaccharide sequence, with antithrombin was studied by spectroscopic techniques. The near-ultraviolet difference spectra, circular dichroism spectra, and fluorescence enhancements induced by adding these oligosaccharides to antithrombin differed only slightly from the corresponding parameters measured in the presence of undegraded high-affinity heparin. Moreover, the binding constants obtained for the oligosaccharides and for high-affinity heparin were similar (1.0-2.9 X 10(7) M-1 at I = 0.3). In contrast, two hexasaccharides corresponding to units 1-6 and 3-8, respectively, of the above sequence showed about a 1000-fold lower affinity for antithrombin, and also induced considerably different spectral perturbations in antithrombin. Since the 1-6 hexasaccharide contains a reducing-terminal anhydromannose residue instead of the N-sulfated glucosamine unit 6 of the intact sequence, these results strongly support our previous conclusion that the N-sulfate group at position 6 is essential to the interaction with antithrombin. The low affinity of the hexasaccharide 3-8 provides further evidence that a pentasaccharide sequence 2-6 constitutes the actual antithrombin-binding region in the heparin molecule. Structural analysis of the various oligosaccharides revealed natural variants with an N-sulfate group substituted for the N-acetyl group at position 2. The preponderance of N-acetyl over N-sulfate groups at this position may be rationalized in terms of the mechanism of heparin biosynthesis, assuming that the D-gluco configuration of unit 3 is an essential feature of the antithrombin-binding region.     

The estimation of relative site variability among aligned homologous protein sequences

MOTIVATION: Maximum likelihood-based methods to estimate site by site substitution rate variability in aligned homologous protein sequences rely on the formulation of a phylogenetic tree and generally assume that the patterns of relative variability follow a pre-determined distribution. We present a phylogenetic tree-independent method to estimate the relative variability of individual sites within large datasets of homologous protein sequences. It is based upon two simple assumptions. Firstly that substitutions observed between two closely related sequences are likely, in general, to occur at the most variable sites. Secondly that non-conservative amino acid substitutions tend to occur at more variable sites. Our methodology makes no assumptions regarding the underlying pattern of relative variability between sites. RESULTS: We have compared, using data simulated under a non-gamma distributed model, the performance of this approach to that of a maximum likelihood method that assumes gamma distributed rates. At low mean rates of evolution our method inferred site by site relative substitution rates more accurately than the maximum likelihood approach in the absence of prior assumptions about the relationships between sequences. Our method does not directly account for the effects of mutational saturation, However, we have incorporated an 'ad-hoc' modification that allows the accurate estimation of relative site variability in fast evolving and saturated datasets.     

Sparse Coding Models Can Exhibit Decreasing Sparseness while Learning Sparse Codes for Natural Images

The sparse coding hypothesis has enjoyed much success in predicting response properties of simple cells in primary visual cortex (V1) based solely on the statistics of natural scenes. In typical sparse coding models, model neuron activities and receptive fields are optimized to accurately represent input stimuli using the least amount of neural activity. As these networks develop to represent a given class of stimulus, the receptive fields are refined so that they capture the most important stimulus features. Intuitively, this is expected to result in sparser network activity over time. Recent experiments, however, show that stimulus-evoked activity in ferret V1 becomes less sparse during development, presenting an apparent challenge to the sparse coding hypothesis. Here we demonstrate that some sparse coding models, such as those employing homeostatic mechanisms on neural firing rates, can exhibit decreasing sparseness during learning, while still achieving good agreement with mature V1 receptive field shapes and a reasonably sparse mature network state. We conclude that observed developmental trends do not rule out sparseness as a principle of neural coding per se: a mature network can perform sparse coding even if sparseness decreases somewhat during development. To make comparisons between model and physiological receptive fields, we introduce a new nonparametric method for comparing receptive field shapes using image registration techniques.     

DNA structural variability as a factor in gene expression and evolution

Redundant DNA can buffer sequence dependent structural deviations from an ideal double helix. Buffering serves a mechanistic function by reducing extraneous conformational effects which could interfere with readout or which would impose energetic constraints on evolution. It also serves an evolutionary function by allowing for gradual variations in conformation-dependent regulation of gene expression. Such gradualism is critical for the rate of evolution. The buffer structure concept provides a new interpretation for repetitive DNA and for exons and introns.     

WebVar: A resource for the rapid estimation of relative site variability from multiple sequence alignments

WebVar is an online resource that provides estimates of relative site variability from multiple alignments of homologous protein or nucleic acid sequences. WebVar provides a variety of graphic and textual representations of estimates, designed to assist in phylogenetic analysis. AVAILABILITY: The WebVar server is located at http://www.pesolelab.it/Tools/WebVar.html     

Redox potentials of the photosynthetic bacterial cytochromes c2 and the structural bases for variability.

The cytochromes c2 of the Rhodospirillaceae show a much greater variation in redox potential and its pH dependence than the mitochondrial cytochromes c that have been studied. It is proposed that the range of redox potential for cytochromes c2 functioning as the immediate electron donor to photo-oxidised bacteriochlorophyll may be 345-395 mV at pH 5. Closely related cytochromes c2 with different redox potentials show patterns of amino acid substitution which are consistent with changes in hydrophobicity near the haem being at least a partial determinant of redox potential. More distantly related cytochromes are difficult to compare because of the large number of amino acid substitutions and the probability that there are subtle changes in overall peptide chain folding. The redox potential versus pH curves can be analysed in terms of either one ionisation in the oxidised form or two in the oxidised form and one in the reduced. The pK in the oxidised form at higher pH values can be correlated with the pK for the disappearance or shift of the near infrared absorption band located near 695 nm. The structural bases of these ionisations are not known but the possible involvement of the haem propionate residues is discussed.