Diffusion of hydrogen in crystalline silicon

The coefficient of diffusion of hydrogen in crystalline silicon is calculated using tight-binding molecular dynamics. Our results are in good quantitative agreement with an earlier study by Panzarini and Colombo [Phys. Rev. Lett. 73, 1636 (1994)]. However, while our calculations indicate that long jumps dominate over single hops at high temperatures, no abrupt change in the diffusion coefficient can be observed with decreasing temperature. The (classical) Arrhenius diffusion parameters, as a consequence, should extrapolate to low temperatures.Comment: 4 pages, including 5 postscript figures; submitted to Phys. Rev. B Brief Repor

Magnetic properties of Sm-Co thin films grown on MgO(100) deposited from a single alloy target

Quantum Matter and Optic

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Incorporating gene co-expression network in identification of cancer prognosis markers

<p>Abstract</p> <p>Background</p> <p>Extensive biomedical studies have shown that clinical and environmental risk factors may not have sufficient predictive power for cancer prognosis. The development of high-throughput profiling technologies makes it possible to survey the whole genome and search for genomic markers with predictive power. Many existing studies assume the interchangeability of gene effects and ignore the coordination among them.</p> <p>Results</p> <p>We adopt the weighted co-expression network to describe the interplay among genes. Although there are several different ways of defining gene networks, the weighted co-expression network may be preferred because of its computational simplicity, satisfactory empirical performance, and because it does not demand additional biological experiments. For cancer prognosis studies with gene expression measurements, we propose a new marker selection method that can properly incorporate the network connectivity of genes. We analyze six prognosis studies on breast cancer and lymphoma. We find that the proposed approach can identify genes that are significantly different from those using alternatives. We search published literature and find that genes identified using the proposed approach are biologically meaningful. In addition, they have better prediction performance and reproducibility than genes identified using alternatives.</p> <p>Conclusions</p> <p>The network contains important information on the functionality of genes. Incorporating the network structure can improve cancer marker identification.</p

Reducing unnecessary prescriptions of antibiotics for acute cough: Adaptation of a leaflet aimed at Turkish immigrants in Germany

<p>Abstract</p> <p>Background</p> <p>The reduction in the number of unnecessary prescriptions of antibiotics has become one of the most important objectives for primary health care. German GPs report that they are under "pressure to prescribe" antibiotics particularly in consultations with Turkish immigrants. And so a qualitative approach was used to learn more about the socio-medical context of Turkish patients in regard to acute coughs. A German leaflet designed to improve the doctor-patient communication has been positively tested and then adapted for Turkish patients.</p> <p>Methods</p> <p>The original leaflet was first translated into Turkish. Then 57 patients belonging to 8 different GPs were interviewed about the leaflet using a semi-standardised script. The material was audio recorded, fully transcribed, and analysed by three independent researchers. As a first step a comprehensive content analysis was performed. Secondly, elements crucial to any Turkish version of the leaflet were identified.</p> <p>Results</p> <p>The interviews showed that the leaflets' messages were clearly understood by all patients irrespective of age, gender, and educational background. We identified no major problems in the perception of the translated leaflet but identified several minor points which could be improved. We found that patients were starting to reconsider their attitudes after reading the leaflet.</p> <p>Conclusion</p> <p>The leaflet successfully imparted relevant and new information to the target patients. A qualitative approach is a feasible way to prove general acceptance and provides additional information for its adaptation to medico-cultural factors.</p

Genomic aberrations relate early and advanced stage ovarian cancer

Background Because of the distinct clinical presentation of early and advanced stage ovarian cancer, we aim to clarify whether these disease entities are solely separated by time of diagnosis or whether they arise from distinct molecular events. Methods Sixteen early and sixteen advanced stage ovarian carcinomas, matched for histological subtype and differentiation grade, were included. Genomic aberrations were compared for each early and advanced stage ovarian cancer by array comparative genomic hybridization. To study how the aberrations correlate to the clinical characteristics of the tumors we clustered tumors based on the genomic aberrations. Results The genomic aberration patterns in advanced stage cancer equalled those in early stage, but were more frequent in advanced stage (p=0.012). Unsupervised clustering based on genomic aberrations yielded two clusters that significantly discriminated early from advanced stage (p= 0.001), and that did differ significantly in survival (p= 0.002). These clusters however did give a more accurate prognosis than histological subtype or differentiation grade. Conclusion This study indicates that advanced stage ovarian cancer either progresses from early stage or from a common precursor lesion but that they do not arise from distinct carcinogenic molecular events. Furthermore, we show that array comparative genomic hybridization has the potential to identify clinically distinct patients

Accounting for uncertainty when assessing association between copy number and disease: a latent class model

<p>Abstract</p> <p>Background</p> <p>Copy number variations (CNVs) may play an important role in disease risk by altering dosage of genes and other regulatory elements, which may have functional and, ultimately, phenotypic consequences. Therefore, determining whether a CNV is associated or not with a given disease might be relevant in understanding the genesis and progression of human diseases. Current stage technology give CNV probe signal from which copy number status is inferred. Incorporating uncertainty of CNV calling in the statistical analysis is therefore a highly important aspect. In this paper, we present a framework for assessing association between CNVs and disease in case-control studies where uncertainty is taken into account. We also indicate how to use the model to analyze continuous traits and adjust for confounding covariates.</p> <p>Results</p> <p>Through simulation studies, we show that our method outperforms other simple methods based on inferring the underlying CNV and assessing association using regular tests that do not propagate call uncertainty. We apply the method to a real data set in a controlled MLPA experiment showing good results. The methodology is also extended to illustrate how to analyze aCGH data.</p> <p>Conclusion</p> <p>We demonstrate that our method is robust and achieves maximal theoretical power since it accommodates uncertainty when copy number status are inferred. We have made <monospace>R</monospace> functions freely available.</p

PIN71 QUALITY OF LIFE (QOL) AND OTHER ENDPOINTS COMPARISON IN THE TREATMENT OF FACIAL LIPOATROPHY WITH INJECTION OF POLY-L-LACTIC ACID

Context: Longitudinal data on bone mineral density(BMD) in children and adolescents with Prader-Willi Syndrome (PWS) during long-term GH treatment are not available. Objective: This study aimed to determine effects of long-term GH treatment and puberty on BMD of total body (BMDTB), lumbar spine (BMDLS), and bone mineral apparent density of the lumbar spine (BMAD(LS)) in children with PWS. Design and Setting: This was a prospective longitudinal study of a Dutch PWS cohort. Participants: Seventy-seven children with PWS who remained prepubertal during GH treatment for 4 years and 64 children with PWS who received GH treatment for 9 years participated in the study. Intervention: The children received GH treatment, 1 mg/m(2)/day (congruent to 0.035 mg/kg/d). Main Outcome Measures: BMDTB, BMDLS, and BMAD(LS) was measured by using the same dual-energy x-ray absorptiometry machine for all annual measurements. Results: In the prepubertal group, BMDTB standard deviation score (SDS) and BMDLSSDS significantly increased during 4 years of GH treatment whereas BMAD(LS)SDS remained stable. During adolescence, BMDTBSDS and BMAD(LS)SDS decreased significantly, in girls from the age of 11 years and in boys from the ages of 14 and 16 years, respectively, but all BMD parameters remained within the normal range. Higher Tanner stages tended to be associated with lower BMDTBSDS (P = .083) and a significantly lowerBMAD(LS)SDS (P = .016). After 9 years of GH treatment, lean body mass SDS was the most powerful predictor of BMDTBSDS and BMDLSSDS in adolescents with PWS. Conclusions: This long-term GH study demonstrates that BMDTB, BMDLS, and BMAD(LS) remain stable in prepubertal children with PWS but decreases during adolescence, parallel to incomplete pubertal development. Based on our findings, clinicians should start sex hormone therapy from the age of 11 years in girls and 14 years in boys unless there is a normal progression of puberty

SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data

<p>Abstract</p> <p>Background</p> <p>Censored data are increasingly common in many microarray studies that attempt to relate gene expression to patient survival. Several new methods have been proposed in the last two years. Most of these methods, however, are not available to biomedical researchers, leading to many re-implementations from scratch of ad-hoc, and suboptimal, approaches with survival data.</p> <p>Results</p> <p>We have developed SignS (Signatures for Survival data), an open-source, freely-available, web-based tool and R package for gene selection, building molecular signatures, and prediction with survival data. SignS implements four methods which, according to existing reviews, perform well and, by being of a very different nature, offer complementary approaches. We use parallel computing via MPI, leading to large decreases in user waiting time. Cross-validation is used to asses predictive performance and stability of solutions, the latter an issue of increasing concern given that there are often several solutions with similar predictive performance. Biological interpretation of results is enhanced because genes and signatures in models can be sent to other freely-available on-line tools for examination of PubMed references, GO terms, and KEGG and Reactome pathways of selected genes.</p> <p>Conclusion</p> <p>SignS is the first web-based tool for survival analysis of expression data, and one of the very few with biomedical researchers as target users. SignS is also one of the few bioinformatics web-based applications to extensively use parallelization, including fault tolerance and crash recovery. Because of its combination of methods implemented, usage of parallel computing, code availability, and links to additional data bases, SignS is a unique tool, and will be of immediate relevance to biomedical researchers, biostatisticians and bioinformaticians.</p

Detection of recurrent copy number alterations in the genome: taking among-subject heterogeneity seriously

Se adjunta un fichero pdf con los datos de investigación titulado "Supplementary Material for \Detection of Recurrent Copy Number Alterations in the Genome: taking among-subject heterogeneity seriously"Background: Alterations in the number of copies of genomic DNA that are common or recurrent among diseased individuals are likely to contain disease-critical genes. Unfortunately, defining common or recurrent copy number alteration (CNA) regions remains a challenge. Moreover, the heterogeneous nature of many diseases requires that we search for common or recurrent CNA regions that affect only some subsets of the samples (without knowledge of the regions and subsets affected), but this is neglected by most methods. Results: We have developed two methods to define recurrent CNA regions from aCGH data. Our methods are unique and qualitatively different from existing approaches: they detect regions over both the complete set of arrays and alterations that are common only to some subsets of the samples (i.e., alterations that might characterize previously unknown groups); they use probabilities of alteration as input and return probabilities of being a common region, thus allowing researchers to modify thresholds as needed; the two parameters of the methods have an immediate, straightforward, biological interpretation. Using data from previous studies, we show that we can detect patterns that other methods miss and that researchers can modify, as needed, thresholds of immediate interpretability and develop custom statistics to answer specific research questions. Conclusion: These methods represent a qualitative advance in the location of recurrent CNA regions, highlight the relevance of population heterogeneity for definitions of recurrence, and can facilitate the clustering of samples with respect to patterns of CNA. Ultimately, the methods developed can become important tools in the search for genomic regions harboring disease-critical genesFunding provided by Fundación de Investigación Médica Mutua Madrileña. Publication charges covered by projects CONSOLIDER: CSD2007-00050 of the Spanish Ministry of Science and Innovation and by RTIC COMBIOMED RD07/0067/0014 of the Spanish Health Ministr