Magnetism of isolated Mn12 single-molecule magnets detected by magnetic circular dichroism: Observation of spin tunneling with a magneto-optical technique

We report magnetic and magneto-optical measurements of two Mn12 single-molecule magnet derivatives isolated in organic glasses. Field-dependent magnetic circular dichroism (MCD) intensity curves (hysteresis cycles) are found to be essentially identical to superconducting quantum interference device magnetization results and provide experimental evidence for the potential of the optical technique for magnetic characterization. Optical observation of magnetic tunneling has been achieved by studying the decay of the MCD signal at weak applied magnetic field

Magnetism of isolated Mn12 single-molecule magnets detected by magnetic circular dichroism: Observation of spin tunneling with a magneto-optical technique

We report magnetic and magneto-optical measurements of two Mn12 single-molecule magnet derivatives isolated in organic glasses. Field-dependent magnetic circular dichroism (MCD) intensity curves (hysteresis cycles) are found to be essentially identical to superconducting quantum interference device magnetization results and provide experimental evidence for the potential of the optical technique for magnetic characterization. Optical observation of magnetic tunneling has been achieved by studying the decay of the MCD signal at weak applied magnetic field

Reconciling phonological neighborhood effects in speech production through single trial analysis

A crucial step for understanding how lexical knowledge is represented is to describe the relative similarity of lexical items, and how it influences language processing. Previous studies of the effects of form similarity on word production have reported conflicting results, notably within and across languages. The aim of the present study was to clarify this empirical issue to provide specific constraints for theoretical models of language production. We investigated the role of phonological neighborhood density in a large-scale picture naming experiment using fine-grained statistical models. The results showed that increasing phonological neighborhood density has a detrimental effect on naming latencies, and re-analyses of independently obtained data sets provide supplementary evidence for this effect. Finally, we reviewed a large body of evidence concerning phonological neighborhood density effects in word production, and discussed the occurrence of facilitatory and inhibitory effects in accuracy measures. The overall pattern shows that phonological neighborhood generates two opposite forces, one facilitatory and one inhibitory. In cases where speech production is disrupted (e.g. certain aphasic symptoms), the facilitatory component may emerge, but inhibitory processes dominate in efficient naming by healthy speakers. These findings are difficult to accommodate in terms of monitoring processes, but can be explained within interactive activation accounts combining phonological facilitation and lexical competition.

Force Spectroscopy with Dual-Trap Optical Tweezers: Molecular Stiffness Measurements and Coupled Fluctuations Analysis

ABSTRACT Dual-trap optical tweezers are often used in high-resolution measurements in single-molecule biophysics. Such measurements can be hindered by the presence of extraneous noise sources, the most prominent of which is the coupling of fluctuations along different spatial directions, which may affect any optical tweezers setup. In this article, we analyze, both from the theoretical and the experimental points of view, the most common source for these couplings in dual-trap optical-tweezers setups: the misalignment of traps and tether. We give criteria to distinguish different kinds of misalignment, to estimate their quantitative relevance and to include them in the data analysis. The experimental data is obtained in a, to our knowledge, novel dual-trap optical-tweezers setup that directly measures forces. In the case in which misalignment is negligible, we provide a method to measure the stiffness of traps and tether based on variance analysis. This method can be seen as a calibration technique valid beyond the linear trap region. Our analysis is then employed to measure the persistence length of dsDNA tethers of three different lengths spanning two orders of magnitude. The effective persistence length of such tethers is shown to decrease with the contour length, in accordance with previous studies.

Control of optical fields and single photon emitters by advanced nanoantenna structures

The control of optical fields on the nanometre scale is becoming an increasingly important tool in many fields, ranging from channelling light delivery in photovoltaics and light emitting diodes to increasing the sensitivity of chemical sensors to single molecule levels. The ability to design and manipulate light fields with specific frequency and space characteristics is explored in this project. We present an alternative realisation of Extraordinary Optical Transmission (EOT) that requires only a single aperture and a coupled waveguide. We show how this waveguide-resonant EOT improves the transmissivity of single apertures. An important technique in imaging is Near-Field Scanning Optical Microscopy (NSOM); we show how waveguide-resonant EOT and the novel probe design assist in improving the efficiency of NSOM probes by two orders of magnitude, and allow the imaging of single molecules with an optical resolution of as good as 50 nm. We show how optical antennas are fabricated into the apex of sharp tips and can be used in a near-field configuration.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Gene Set Analysis for improving genetic association studies

Introduction. Genetic epidemiology is focused on the study of the genetic causes that determine health and diseases in populations. To achieve this goal a common strategy is to explore differences in genetic variability between diseased and nondiseased individuals. Usual markers of genetic variability are single nucleotide polymorphisms (SNPs) which are changes in just one base in the genome. The usual statistical approach in genetic epidemiology study is a marginal analysis, where each SNP is analyzed separately for association with the phenotype. Motivation. It has been observed, that for common diseases the single-SNP analysis is not very powerful for detecting genetic causing variants. In this work, we consider Gene Set Analysis (GSA) as an alternative to standard marginal association approaches. GSA aims to assess the overall association of a set of genetic variants with a phenotype and has the potential to detect subtle effects of variants in a gene or a pathway that might be missed when assessed individually. Objective. We present a new optimized implementation of a pair of gene set analysis methodologies for analyze the individual evidence of SNPs in biological pathways. We perform a simulation study for exploring the power of the proposed methodologies in a set of scenarios with different number of causal SNPs under different effect sizes. In addition, we compare the results with the usual single-SNP analysis method. Moreover, we show the advantage of using the proposed gene set approaches in the context of an Alzheimer disease case-control study where we explore the Reelin signal pathway.

A targeted association study of immunity genes and networks suggests novel associations with placental malaria infection

A large proportion of the death toll associated with malaria is a consequence of malaria infection during pregnancy, causing up to 200,000 infant deaths annually. We previously published the first extensive genetic association study of placental malaria infection, and here we extend this analysis considerably, investigating genetic variation in over 9,000 SNPs in more than 1,000 genes involved in immunity and inflammation for their involvement in susceptibility to placental malaria infection. We applied a new approach incorporating results from both single gene analysis as well as gene-gene interactionson a protein-protein interaction network. We found suggestive associations of variants in the gene KLRK1 in the single geneanalysis, as well as evidence for associations of multiple members of the IL-7/IL-7R signalling cascade in the combined analysis. To our knowledge, this is the first large-scale genetic study on placental malaria infection to date, opening the door for follow-up studies trying to elucidate the genetic basis of this neglected form of malaria.

Susceptibilitat genètica al càncer gàstric: caracterització de les interaccions de segon ordre entre gens i variants identificades en l’estudi EPIC‐EURGAST

En aquest Treball de Final de Grau s’exposen els resultats de l’anàlisi de les dades genètiques del projecte EurGast2 "Genetic susceptibility, environmental exposure and gastric cancer risk in an European population”, estudi cas‐control niat a la cohort europea EPIC “European Prospective lnvestigation into Cancer and Nutrition”, que té per objectiu l’estudi dels factors genètics i ambientals associats amb el risc de desenvolupar càncer gàstric (CG). A partir de les dades resultants de l’estudi EurGast2, en el què es van analitzar 1.294 SNPs en 365 casos de càncer gàstric i 1.284 controls en l’anàlisi Single SNP previ, la hipòtesi de partida del present Treball de Final de Grau és que algunes variants amb un efecte marginal molt feble, però que conjuntament amb altres variants estarien associades al risc de CG, podrien no haver‐se detectat. Així doncs, l’objectiu principal del projecte és la identificació d’interaccions de segon ordre entre variants genètiques de gens candidats implicades en la carcinogènesi de càncer gàstric. L’anàlisi de les interaccions s’ha dut a terme aplicant el mètode estadístic Model‐based Multifactor Dimensionality Reduction Method (MB‐MDR), desenvolupat per Calle et al. l’any 2008 i s’han aplicat dues metodologies de filtratge per seleccionar les interaccions que s’exploraran: 1) filtratge d’interaccions amb un SNP significatiu en el Single SNP analysis i 2) filtratge d’interaccions segons la mesura Sinèrgia. Els resultats del projecte han identificat 5 interaccions de segon ordre entre SNPs associades significativament amb un major risc de desenvolupar càncer gàstric, amb p‐valor inferior a 10‐4. Les interaccions identificades corresponen a interaccions entre els gens MPO i CDH1, XRCC1 i GAS6, ADH1B i NR5A2 i IL4R i IL1RN (que s’ha validat en les dues metodologies de filtratge). Excepte CDH1, cap altre d’aquests gens s’havia associat significativament amb el CG o prioritzat en les anàlisis prèvies, el que confirma l’interès d’analitzar les interaccions genètiques de segon ordre. Aquestes poden ser un punt de partida per altres anàlisis destinades a confirmar gens putatius i a estudiar a nivell biològic i molecular els mecanismes de carcinogènesi, i orientades a la recerca de noves dianes terapèutiques i mètodes de diagnosi i pronòstic més eficients.

Substrate-selective repair and restart of replication forks by DNA translocases

Stalled replication forks are sources of genetic instability. Multiple fork-remodeling enzymes are recruited to stalled forks, but how they work to promote fork restart is poorly understood. By combining ensemble biochemical assays and single-molecule studies with magnetic tweezers, we show that SMARCAL1 branch migration and DNA-annealing activities are directed by the single-stranded DNA-binding protein RPA to selectively regress stalled replication forks caused by blockage to the leading-strand polymerase and to restore normal replication forks with a lagging-strand gap. We unveil the molecular mechanisms by which RPA enforces SMARCAL1 substrate preference. E. coli RecG acts similarly to SMARCAL1 in the presence of E. coli SSB, whereas the highly related human protein ZRANB3 has different substrate preferences. Our findings identify the important substrates of SMARCAL1 in fork repair, suggest that RecG and SMARCAL1 are functional orthologs, and provide a comprehensive model of fork repair by these DNA translocases.

Counter-propagating dual-trap optical tweezers based on linear momentum conservation

We present a dual-trap optical tweezers setup which directly measures forces using linear momentum conservation. The setup uses a counter-propagating geometry, which allows momentum measurement on each beam separately. The experimental advantages of this setup include low drift due to all-optical manipulation, and a robust calibration (independent of the features of the trapped object or buffer medium) due to the force measurement method. Although this design does not attain the high-resolution of some co-propagating setups, we show that it can be used to perform different single molecule measurements: fluctuation-based molecular stiffness characterization at different forces and hopping experiments on molecular hairpins. Remarkably, in our setup it is possible to manipulate very short tethers (such as molecular hairpins with short handles) down to the limit where beads are almost in contact. The setup is used to illustrate a novel method for measuring the stiffness of optical traps and tethers on the basis of equilibrium force fluctuations, i.e., without the need of measuring the force vs molecular extension curve. This method is of general interest for dual trap optical tweezers setups and can be extended to setups which do not directly measure forces.

The determinants of the prevalence of single mothers: A cross-country analysis

This paper examines the effect of public assistance, labor market and marriage marketconditions on the prevalence of single mother families across countries and over time. Amultinomial logit derived from a random utility approach is estimated using individualleveldata for 14 countries. I find evidence that increases in the level of public support are significantly and positively associated with a higher incidence of both never marriedand divorced mothers. The results also suggest that single mothers are more prevalentwhen female wages are lower. Higher male earnings and employment opportunities in awoman s marriage market appear to lead to fewer never married mothers, but more divorced mothers. Higher child support or alimony payments are associated with a higher prevalence of divorced mothers.

Raman scattering and photoluminescence analysis of silicon on insulator structures obtained by single and multiple oxygen implants

An analysis of silicon on insulator structures obtained by single and multiple implants by means of Raman scattering and photoluminescence spectroscopy is reported. The Raman spectra obtained with different excitation powers and wavelengths indicate the presence of a tensile strain in the top silicon layer of the structures. The comparison between the spectra measured in both kinds of samples points out the existence in the multiple implant material of a lower strain for a penetration depth about 300 nm and a higher strain for higher penetration depths. These results have been correlated with transmission electron microscopy observations, which have allowed to associate the higher strain to the presence of SiO2 precipitates in the top silicon layer, close to the buried oxide. The found lower strain is in agreement with the better quality expected for this material, which is corroborated by the photoluminescence data.

Factors affecting visual analysis in single-case designs

Visual inspection remains the most frequently applied method for detecting treatment effects in single-case designs. The advantages and limitations of visual inference are here discussed in relation to other procedures for assessing intervention effectiveness. The first part of the paper reviews previous research on visual analysis, paying special attention to the validation of visual analysts" decisions, inter-judge agreement, and false alarm and omission rates. The most relevant factors affecting visual inspection (i.e., effect size, autocorrelation, data variability, and analysts" expertise) are highlighted and incorporated into an empirical simulation study with the aim of providing further evidence about the reliability of visual analysis. Our results concur with previous studies that have reported the relationship between serial dependence and increased Type I rates. Participants with greater experience appeared to be more conservative and used more consistent criteria when assessing graphed data. Nonetheless, the decisions made by both professionals and students did not match sufficiently the simulated data features, and we also found low intra-judge agreement, thus suggesting that visual inspection should be complemented by other methods when assessing treatment effectiveness.

The single principle of compositional data analysis, continuing fallacies, confusionsand misunderstandings and some suggested remedies

In any discipline, where uncertainty and variability are present, it is important to haveprinciples which are accepted as inviolate and which should therefore drive statisticalmodelling, statistical analysis of data and any inferences from such an analysis.Despite the fact that two such principles have existed over the last two decades andfrom these a sensible, meaningful methodology has been developed for the statisticalanalysis of compositional data, the application of inappropriate and/or meaninglessmethods persists in many areas of application. This paper identifies at least tencommon fallacies and confusions in compositional data analysis with illustrativeexamples and provides readers with necessary, and hopefully sufficient, arguments topersuade the culprits why and how they should amend their ways