Assessing Thermochemical Properties of Materials through Ab initio Quantum-mechanical Methods: The Case of α-Al2O3

The thermochemical behavior of α-Al2O3 corundum in the whole temperature range 0–2317 K (melting point) and under pressures up to 12 GPa is predicted by applying ab initio methods based on the density functional theory (DFT), the use of a local basis set and periodic-boundary conditions. Thermodynamic properties are treated both within and beyond the harmonic approximation to the lattice potential. In particular, a recent implementation of the quasi-harmonic approximation, in the Crystal program, is here shown to provide a reliable description of the thermal expansion coefficient, entropy, constant-volume and constant-pressure specific heats, and temperature dependence of the bulk modulus, nearly up to the corundum melting temperature. This is a remarkable outcome suggesting α-Al2O3 to be an almost perfect quasi-harmonic crystal. The effect of using different computational parameters and DFT functionals belonging to different levels of approximations on the accuracy of the thermal properties is tested, providing a reference for further studies involving alumina polymorphs and, more generally, quasi-ionic minerals

Modelling of a standard gas mixtures generator with computational fluid dynamics

Monitoring VOC for climate change and for indoor and outdoor air quality at trace level concentrations need reference standard materials at high metrological performance. To improve this performance, the description of phenomena involved in mixtures generation by rigorous models is mandatory. A model to describe diffusion cells of a primary generator was developed and validated with experimental data. A good agreement was found between the uncertainties of measurements and calculations

Tetrahedrally bonded ternary amorphous semiconductor alloys

The properties of tetrahedrally bonded ternary amorphous semiconductors a-CSiSn:H and a-CSiGe:H are reviewed with particular emphasis on the temperature dependence of dark conductivity and the coordination in random networks. It is shown here that the dark conductivity as a function of the temperature strongly depends on the carbon content and, more precisely, on the proportion of sp3 and sp2 sites in the carbon. Ternary alloys with different carbon contents are compared to binary alloys using the average coordination number. The ternary alloys have an average coordination number close to the optimal value predicted for amorphous covalent networks

Impact of constitutional copy number variants on biological pathway evolution

Background: Inherited Copy Number Variants (CNVs) can modulate the expression levels of individual genes. However, little is known about how CNVs alter biological pathways and how this varies across different populations. To trace potential evolutionary changes of well-described biological pathways, we jointly queried the genomes and the transcriptomes of a collection of individuals with Caucasian, Asian or Yoruban descent combining high-resolution array and sequencing data. Results: We implemented an enrichment analysis of pathways accounting for CNVs and genes sizes and detected significant enrichment not only in signal transduction and extracellular biological processes, but also in metabolism pathways. Upon the estimation of CNV population differentiation (CNVs with different polymorphism frequencies across populations), we evaluated that 22% of the pathways contain at least one gene that is proximal to a CNV (CNV-gene pair) that shows significant population differentiation. The majority of these CNV-gene pairs belong to signal transduction pathways and 6% of the CNV-gene pairs show statistical association between the copy number states and the transcript levels. Conclusions: The analysis suggested possible examples of positive selection within individual populations including NF-kB, MAPK signaling pathways, and Alu/L1 retrotransposition factors. Altogether, our results suggest that constitutional CNVs may modulate subtle pathway changes through specific pathway enzymes, which may become fixed in some populations

A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays

BACKGROUND: Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA) experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples. RESULTS: We propose an extension of the well-known Naïve Bayes classifier, which accounts for biological heterogeneity in a probabilistic framework, relying on Bayesian hierarchical models. The model, which can be efficiently learned from the training dataset, exploits a closed-form of classification equation, thus providing no additional computational cost with respect to the standard Naïve Bayes classifier. We validated the approach on several simulated datasets comparing its performances with the Naïve Bayes classifier. Moreover, we demonstrated that explicitly dealing with heterogeneity can improve classification accuracy on a TMA prostate cancer dataset. CONCLUSION: The proposed Hierarchical Naïve Bayes classifier can be conveniently applied in problems where within sample heterogeneity must be taken into account, such as TMA experiments and biological contexts where several measurements (replicates) are available for the same biological sample. The performance of the new approach is better than the standard Naïve Bayes model, in particular when the within sample heterogeneity is different in the different classes

Optimizing copy number variation analysis using genome-wide short sequence oligonucleotide arrays

The detection of copy number variants (CNV) by array-based platforms provides valuable insight into understanding human diversity. However, suboptimal study design and data processing negatively affect CNV assessment. We quantitatively evaluate their impact when short-sequence oligonucleotide arrays are applied (Affymetrix Genome-Wide Human SNP Array 6.0) by evaluating 42 HapMap samples for CNV detection. Several processing and segmentation strategies are implemented, and results are compared to CNV assessment obtained using an oligonucleotide array CGH platform designed to query CNVs at high resolution (Agilent). We quantitatively demonstrate that different reference models (e.g. single versus pooled sample reference) used to detect CNVs are a major source of inter-platform discrepancy (up to 30%) and that CNVs residing within segmental duplication regions (higher reference copy number) are significantly harder to detect (P < 0.0001). After adjusting Affymetrix data to mimic the Agilent experimental design (reference sample effect), we applied several common segmentation approaches and evaluated differential sensitivity and specificity for CNV detection, ranging 39–77% and 86–100% for non-segmental duplication regions, respectively, and 18–55% and 39–77% for segmental duplications. Our results are relevant to any array-based CNV study and provide guidelines to optimize performance based on study-specific objectives

A model for the generic alpha relaxation of viscous liquids

Dielectric measurements on molecular liquids just above the glass transition indicate that alpha relaxation is characterized by a generic high-frequency loss varying as $\omega^{-1/2}$, whereas deviations from this come from one or more low-lying beta processes [Olsen et al, Phys. Rev. Lett. {\bf 86} (2001) 1271]. Assuming that long-wavelength fluctuations dominate the dynamics, a model for the dielectric alpha relaxation based on the simplest coupling between the density and dipole density fields is proposed here. The model, which is solved in second order perturbation theory in the Gaussian approximation, reproduces the generic features of alpha relaxation

SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines

Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line can be simultaneously studied in multiple research laboratories throughout the world, theoretically generating results that are directly comparable. One important assumption in this paradigm is that researchers are working with the same cells. However, recent work using high throughput genomic analyses questions the accuracy of this assumption. Observations by our group and others suggest that experiments reported in the scientific literature may contain pre-analytic errors due to inaccurate identities of the cell lines employed. To address this problem, we developed a simple approach that enables an accurate determination of cell line identity by genotyping 34 single nucleotide polymorphisms (SNPs). Here, we describe the empirical development of a SNP panel identification assay (SPIA) compatible with routine use in the laboratory setting to ensure the identity of tumor cell lines and human tumor samples throughout the course of long term research use

Evaluation of [C(sp3)/[C(sp2)] ratio in diamondlike films through the use of a complex dielectric constant

The evaluation of the amount of tetrahedral and trigonal cross-linking, that is, the sp3- and sp2-hybridized carbon, is of great importance in understanding the properties of amorphous carbon films. In this paper we report a method for deducing the [sp3]/[sp2] ratio from the experimental values of the complex dielectric constant as obtained by optical transmittance and reflectance measurements. We assume a Gaussian-like distribution of π and π* electronic densities of states in order to fit the contribution of π→π* to the imaginary part, ε2, of the dielectric constant in the low-energy region. Through the Kramers-Kronig relationships we deduce the corresponding values of the real part ε1 of the dielectric constant for such transitions. By subtracting these values from the measured ε1 we deduce the contribution of σ→σ* to ε1. The Wemple-Didomenico model has been used to obtain the dispersion energy and the average excitation energy. Knowing the plasmon energies, we apply the ‘‘f-sum rule'' to deduce the [sp3]/[sp2] ratio. The method applied to a-C:H films deposited by rf diode sputtering provides results in agreement with those obtained by other techniques

ABEMUS: platform specific and data informed detection of somatic SNVs in cfDNA

MOTIVATION: The use of liquid biopsies for cancer patients enables the non-invasive tracking of treatment response and tumor dynamics through single or serial blood drawn tests. Next generation sequencing assays allow for the simultaneous interrogation of extended sets of somatic single nucleotide variants (SNVs) in circulating cell free DNA (cfDNA), a mixture of DNA molecules originating both from normal and tumor tissue cells. However, low circulating tumor DNA (ctDNA) fractions together with sequencing background noise and potential tumor heterogeneity challenge the ability to confidently call SNVs. RESULTS: We present a computational methodology, called Adaptive Base Error Model in Ultra-deep Sequencing data (ABEMUS), which combines platform-specific genetic knowledge and empirical signal to readily detect and quantify somatic SNVs in cfDNA. We tested the capability of our method to analyze data generated using different platforms with distinct sequencing error properties and we compared ABEMUS performances with other popular SNV callers on both synthetic and real cancer patients sequencing data. Results show that ABEMUS performs better in most of the tested conditions proving its reliability in calling low variant allele frequencies somatic SNVs in low ctDNA levels plasma samples. AVAILABILITY: ABEMUS is cross-platform and can be installed as R package. The source code is maintained on Github at http://github.com/cibiobcg/abemus and it is also available at CRAN official R repository. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online