Bayesian signal extraction from noisy FT NMR spectra

Summary The statistical interpretation of the histogram representation of NMR spectra is described, leading to an estimation of the probability density function of the noise. The white-noise and Gaussian hypotheses are discussed, and a new estimator of the noise standard deviation is derived from the histogram strategy. The Bayesian approach to NMR signal detection is presented. This approach homogeneously combines prior knowledge, obtained from the histogram strategy, together with the posterior information resulting from the test of presence of a set of reference shapes in the neighbourhood of each data point. This scheme leads to a new strategy in the local detection of NMR signals in 2D and 3D spectra, which is illustrated by a complete peak-picking algorithm.     

Variation, natural selection, and information content--a simulation

In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms that propel biological evolution. Variation implies changes in the gene pool of a population, enlarging the genetic variability from which natural selection can choose. But in the absence of natural selection, variation causes dissipation and randomization. Natural selection, in contrast, constrains this variability by decreasing the survival and fertility of the less-adapted organisms. The objective of this study is to propose a highly simplified simulation of variation and natural selection, and to relate the observed evolutionary changes in a population to its information content. The model involves an imaginary population of individuals. A quantifiable character allows the individuals to be categorized into bins. The distribution of bins (a histogram) was assumed to be Gaussian. The content of each bin was calculated after one to twelve cycles, each cycle spanning N generations (N being undefined). In a first study, selection was simulated in the absence of variation. This was modeled by assuming a differential fertility factor F that increased linearly from the lower bins (F<1.00) to the higher bins (F>1.00). The fertility factor was applied as a multiplication factor during each cycle. Several ranges of fertility were investigated. The resulting histograms became skewed to the right. In a second study, variation was simulated in the absence of selection. This was modeled by assuming that during each cycle each bin lost a fixed percentage of its content (variation factor Y) to its two adjacent bins. The resulting histograms became broader and flatter, while retaining their bilateral symmetry. Different values of Y were monitored. In a third study, various values of F and Y were combined. Our model allows the straightforward application of Shannon's equation and the calculation of a Shannon-entropy (SE) values for each histogram. Natural selection was, thus, shown to result in a progressive decrease in SE as a function of F. In other words, natural selection, when acting alone, progressively increased the information content of the population. In contrast, variation resulted in a progressive increase in SE as a function of Y. In other words, variation acting alone progressively decreased the information content of a population. When both factors, F and Y, were applied simultaneously, their relative weight determined the progressive change in SE.     

Lipid packing determines protein-membrane interactions: Challenges for apolipoprotein A-I and high density lipoproteins

Protein and protein-lipid interactions, with and within specific areas in the cell membrane, are critical in order to modulate the cell signaling events required to maintain cell functions and viability. Biological bilayers are complex, dynamic platforms, and thus in vivo observations usually need to be preceded by studies on model systems that simplify and discriminate the different factors involved in lipid-protein interactions. Fluorescence microscopy studies using giant unilamellar vesicles (GUVs) as membrane model systems provide a unique methodology to quantify protein binding, interaction, and lipid solubilization in artificial bilayers. The large size of lipid domains obtainable on GUVs, together with fluorescence microscopy techniques, provides the possibility to localize and quantify molecular interactions. Fluorescence Correlation Spectroscopy (FCS) can be performed using the GUV model to extract information on mobility and concentration. Two-photon Laurdan Generalized Polarization (GP) reports on local changes in membrane water content (related to membrane fluidity) due to protein binding or lipid removal from a given lipid domain. In this review, we summarize the experimental microscopy methods used to study the interaction of human apolipoprotein A-I (apoA-I) in lipid-free and lipid-bound conformations with bilayers and natural membranes. Results described here help us to understand cholesterol homeostasis and offer a methodological design suited to different biological systems.     

Overview of commercial treatment planning systems for targeted radionuclide therapy

IntroductionTargeted Radionuclide Therapy (TRT) is a branch of cancer medicine dealing with the therapeutic use of radioisotopes associated with biological vectors accumulating in the tumors/targets, indicated as Molecular Radiotherapy (MRT), or directly injected into the arteries that supply blood to liver tumour vasculature, indicated as Selective RT (SRT). The aim of this work is to offer a panoramic view on the increasing number of commercially-available TRT treatment planning systems (TPSs).Materials and methodsA questionnaire was sent to manufacturers' representatives. Academic software were not considered. Questions were grouped as follows: general information, clinical workflow, calibration procedure, image processing/reconstruction, image registration and segmentation tools, time-activity curve (TAC) fitting and absorbed dose calculation.ResultsAll software reported have CE-marking. TPSs were divided between SRT-dedicated software [4] and MRT [5] dosimetry software. In SRT, since no kinetic process is involved, absorbed dose calculation does not require TAC fitting, and image registration is not fully developed in all TPS. All software requires a radionuclide-specific calibration. In SRT, a relative image calibration can be obtained by scaling the counts to a known activity. Automated VOI contouring and rigid/deformable propagation between different acquisitions time-points is implemented in most TPSs, although DICOM export is rare. Different TAC fits are available depending on the number of time-points. Voxel S-value and Local deposition methods are the most frequent dosimetric approaches; dose-voxel kernel convolution and semi-Monte Carlo method are also available.ConclusionsAvailable TPSs allows performing personalized dosimetry in clinical practice. Individual variations in methodology/algorithms must be considered in the standardisation/harmonization processes.     

Beyond Flory's Theory: A Computer Aided Phenomenology for Polymers

Abstract

Extending the histogram method of Ferrenberg and Swendsen to the problem of a SAW in a bad solvent, we obtain a new expression for the free energy of such a system, which fits very properly the numerical results of our Monte Carlo simulations. The basic difference with Flory's theory lies in the reference system: instead of considering random walks (RW) we start with self-avoiding walks (SAW) for which we already proposed a model expression for the distribution of the radius of gyration. This distribution is universal for any class of homo- or heteropolymers and contains all the information concerning the excluded volume problem. For homopolymers we consider the standard case where attractive nearest neighbours interactions simulate a bad solvent. At a given radius of gyration r we compute the density of states P(r, m) for an interacting self avoiding walk (ISAW) as a function of its number of contacts m. We build a microscopic phenomenology for P(r, m) based on a factorisation procedure: P(r, m) is split into an a priori probability P(r) of finding a SAW with a given r, and a conditional probability P(m/r) of finding such a conformation with m contacts. A complete scaling is given for P(r) whereas P(m/r) is found to be well approximated by a gaussian distribution. Scaling laws for the first two cumulants of P(m/r) are exhibited from a finite-size scaling analysis. The theta-point temperature is recovered along with its dependence on the polymer length and the free energy of the globule phase is well reproduced. This approach is shown to be generalizable to heteropolymers by merely replacing m by u, the energy per monomer, and computing the density of states P(r, u) at a given r. The case of sequenced and random copolymers is examined with special attention to polyampholytes.     

Enhancement of Hounsfield unit distribution in cone-beam CT images for adaptive radiation therapy: Evaluation of a hybrid correction approach

PurposeThis study aims to evaluate the accuracy of a hybrid approach combining the histogram matching (HM) and the multilevel threshold (MLT) to correct the Hounsfield Unit (HU) distribution in cone-beam CT (CBCT) images.Methods and MaterialsCBCT images acquired for ten prostate cancer patients were processed by matching their histograms to those of deformed planning CT (pCT) images obtained after applying a deformable registration (DR) process. Then, HU values corresponding to five tissue types in the pCT were assigned to the obtained CBCT images (CBCT_HM-MLT). Finally, the CBCT_HM-MLT images were compared to the deformed pCT visually and using different statistical metrics.ResultsThe visual assessment and the profiles comparison showed that the high discrepancies in the CBCT images were significantly reduced when using the proposed approach. Furthermore, the correlation values indicated that the CBCT_HM-MLT were in good agreement with the deformed pCT with correlation values ranging from 0.9893 to 0.9962. In addition, the root mean squared error (RMSE) over the entire volume was reduced from 64.15 ± 9.50 to 51.20 ± 6.76 HU. Similarly, the mean absolute error in specific tissue classes was significantly reduced especially in the soft tissue-air interfaces. These results confirmed that applying MLT after HM worked better than using only HM for which the correlation values were ranging from 0.9878 to 0.9955 and the RMSE was 55.95 ± 10.43 HU.ConclusionEvaluation of the proposed approach showed that the HM + MLT correction can improve the HU distribution in the CBCT images and generate corrected images in good agreement with the pCT.