Privacy-Aware Peer-to- Peer Content Distribution Using Automatically Recombined Fingerprints

Peer-reviewed

Multilocus sequence analysis reveals the genetic diversity of European fruit tree phytoplasmas and supports the existence of inter-species recombination

The genetic diversity of three temperate fruit tree phytoplasmas ‘Candidatus Phytoplasma prunorum’, ‘Ca. P. mali’ and ‘Ca. P. pyri’ has been established by multilocus sequence analysis. Among the four genetic loci used, the genes imp and aceF distinguished 30 and 24 genotypes, respectively, and showed the highest variability. Percentage of substitution for imp ranged from 50 to 68% according to species. Percentage of substitution varied between 9 and 12% for aceF, whereas it was between 5 and 6% for pnp and secY. In the case of ‘Ca P. prunorum’ the three most prevalent aceF genotypes were detected in both plants and insect vectors, confirming that the prevalent isolates are propagated by insects. The four isolates known to be hypo-virulent had the same aceF sequence, indicating a possible monophyletic origin. Haplotype network reconstructed by eBURST revealed that among the 34 haplotypes of ‘Ca. P. prunorum’, the four hypo-virulent isolates also grouped together in the same clade. Genotyping of some Spanish and Azerbaijanese ‘Ca. P. pyri’ isolates showed that they shared some alleles with ‘Ca. P. prunorum’, supporting for the first time to our knowledge, the existence of inter-species recombination between these two species.

Calorimetry of dehydrogenation and dangling-bond recombination in several hydrogenated amorphous silicon materials

Differential scanning calorimetry (DSC) was used to study the dehydrogenation processes that take place in three hydrogenated amorphous silicon materials: nanoparticles, polymorphous silicon, and conventional device-quality amorphous silicon. Comparison of DSC thermograms with evolved gas analysis (EGA) has led to the identification of four dehydrogenation processes arising from polymeric chains (A), SiH groups at the surfaces of internal voids (A'), SiH groups at interfaces (B), and in the bulk (C). All of them are slightly exothermic with enthalpies below 50 meV/H atoms , indicating that, after dissociation of any SiH group, most dangling bonds recombine. The kinetics of the three low-temperature processes [with DSC peak temperatures at around 320 (A),360 (A'), and 430°C (B)] exhibit a kinetic-compensation effect characterized by a linea relationship between the activation entropy and enthalpy, which constitutes their signature. Their Si-H bond-dissociation energies have been determined to be E (Si-H)0=3.14 (A), 3.19 (A'), and 3.28 eV (B). In these cases it was possible to extract the formation energy E(DB) of the dangling bonds that recombine after Si-H bond breaking [0.97 (A), 1.05 (A'), and 1.12 (B)]. It is concluded that E(DB) increases with the degree of confinement and that E(DB)>1.10 eV for the isolated dangling bond in the bulk. After Si-H dissociation and for the low-temperature processes, hydrogen is transported in molecular form and a low relaxation of the silicon network is promoted. This is in contrast to the high-temperature process for which the diffusion of H in atomic form induces a substantial lattice relaxation that, for the conventional amorphous sample, releases energy of around 600 meV per H atom. It is argued that the density of sites in the Si network for H trapping diminishes during atomic diffusion

Size-dependent recombination dynamics in ZnO nanowires.

A deep understanding of the recombination dynamics of ZnO nanowires NWs is a natural step for a precise design of on-demand nanostructures based on this material system. In this work we investigate the influence of finite-size on the recombination dynamics of the neutral bound exciton around 3.365 eV for ZnO NWs with different diameters. We demonstrate that the lifetime of this excitonic transition decreases with increasing the surface-to-volume ratio due to a surface induced recombination process. Furthermore, we have observed two broad transitions around 3.341 and 3.314 eV, which were identified as surface states by studying the dependence of their life time and intensitiy with the NWs dimensions.

Direct modulation of electroluminescence from silicon nanocrystals beyond radiative recombination rates

We propose a light emitting transistor based on silicon nanocrystals provided with 200 Mbits/ s built-in modulation. Suppression of electroluminescence from silicon nanocrystals embedded into the gate oxide of a field effect transistor is achieved by fast Auger quenching. In this process, a modulating drain signal causes heating of carriers in the channel and facilitates the charge injection into the nanocrystals. This excess of charge enables fast nonradiative processes that are used to obtain 100% modulation depths at modulating voltages of 1 V.

The effect of recombination in Aeromonas

Although several approaches have been attempted, the estimation of recombination frequencies in natural populations ofbacteria remains challenging. Previous studies have demonstrated awide variety of situations among bacterial species, ranging from theclonal diversification of Salmonella or Escherichia coli, which aremainly due to mutation, to the frequent recombination found inNeisseria gonorrhoeae or Helicobacter pylori. Most of the populationstudies done with bacterial species suggest that recombination occursin nature but that it is infrequent compared to mutation. Consequently,bacterial populations consist largely of independent clonal lineages.Our research suggests little or null influence of recombination in thegenetic structure of "Aeromonas hydrophila Species Complex", despite the presence of some strains with recombinant gene fragments.

The effect of recombination in Aeromonas

Although several approaches have been attempted, the estimation of recombination frequencies in natural populations ofbacteria remains challenging. Previous studies have demonstrated awide variety of situations among bacterial species, ranging from theclonal diversification of Salmonella or Escherichia coli, which aremainly due to mutation, to the frequent recombination found inNeisseria gonorrhoeae or Helicobacter pylori. Most of the populationstudies done with bacterial species suggest that recombination occursin nature but that it is infrequent compared to mutation. Consequently,bacterial populations consist largely of independent clonal lineages.Our research suggests little or null influence of recombination in thegenetic structure of "Aeromonas hydrophila Species Complex", despite the presence of some strains with recombinant gene fragments.

Analysis of meiotic recombination in 22q11.2, a region that frequently undergoes deletions and duplications

Background: The 22q11.2 deletion syndrome is the most frequent genomic disorder with an estimated frequency of 1/4000 live births. The majority of patients (90%) have the same deletion of 3 Mb (Typically Deleted Region, TDR) that results from aberrant recombination at meiosis between region specific low-copy repeats (LCRs). Methods: As a first step towards the characterization of recombination rates and breakpoints within the 22q11.2 region we have constructed a high resolution recombination breakpoint map based on pedigree analysis and a population-based historical recombination map based on LD analysis. Results: Our pedigree map allows the location of recombination breakpoints with a high resolution (potential recombination hotspots), and this approach has led to the identification of 5 breakpoint segments of 50 kb or less (8.6 kb the smallest), that coincide with historical hotspots. It has been suggested that aberrant recombination leading to deletion (and duplication) is caused by low rates of Allelic Homologous Recombination (AHR) within the affected region. However, recombination rate estimates for 22q11.2 region show that neither average recombination rates in the 22q11.2 region or within LCR22-2 (the LCR implicated in most deletions and duplications), are significantly below chromosome 22 averages. Furthermore, LCR22-2, the repeat most frequently implicated in rearrangements, is also the LCR22 with the highest levels of AHR. In addition, we find recombination events in the 22q11.2 region to cluster within families. Within this context, the same chromosome recombines twice in one family; first by AHR and in the next generation by NAHR resulting in an individual affected with the del22q11.2 syndrome. Conclusion: We show in the context of a first high resolution pedigree map of the 22q11.2 region that NAHR within LCR22 leading to duplications and deletions cannot be explained exclusively under a hypothesis of low AHR rates. In addition, we find that AHR recombination events cluster within families. If normal and aberrant recombination are mechanistically related, the fact that LCR22s undergo frequent AHR and that we find familial differences in recombination rates within the 22q11.2 region would have obvious health-related implications.

Recombination dynamics in ZnO nanowires: Surfaces states versus mode quality factor

In this work, we investigate the influence of finite size on the recombinations dynamics of ZnO nanowires. We demonstrate that diameter as well as lenght of nanowires determine the lifetime of the neutral donor bound excitons. Our findings suggest that while the length is mainly responsible for different mode quality factors of the cavity-like nanowires, the diameter determines the influence of surface states as alternative recombinations channels for the optical modes trapped in the nanocavity. In addition, comparing nanowires grown using different catalyst we show that the surfaces states strongly depend on each precursor characteristics.

Fingerprinting automático de contenidos digitales inspirado en las secuencias de ADN

Peer-reviewed

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Nutrimetabolomics fingerprinting to identify biomarkers of bread exposure in a free-living population from the PREDIMED study cohort

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (n = 56), white-bread consumers (n = 48) and whole-grain bread consumers (n = 51). The most differential metabolites (variable importance for projection ≥1.5) included compounds originating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3-indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-α-acetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95 % CI)] of combined models ranged from 77.8 % (69.1 86.4 %) to 93.7 % (89.4 98.1 %), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6 69.7 %) to 78.4 % (69.8 87.1 %). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, andmany others, offer tremendous promise for the personalized treatment of cancer. Thesetechnologies measure the amount of specific proteins, RNA, DNA or other moleculartargets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumorspecimens are heterogeneous; an individual specimen typically contains unknownamounts of multiple tissues types. Thus, the measured molecular concentrations resultfrom an unknown mixture of tissue types, and must be normalized to account for thecomposition of the mixture.For example, a breast tumor biopsy may contain normal, dysplastic and cancerousepithelial cells, as well as stromal components (fatty and connective tissue) and bloodand lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic andcancerous epithelial cells. The remaining tissue components serve to “contaminate”the signal of interest. The proportion of each of the tissue components changes asa function of patient characteristics (e.g., age), and varies spatially across the tumorregion. Because each of the tissue components produces a different molecular signature,and the amount of each tissue type is specimen dependent, we must estimate the tissuecomposition of the specimen, and adjust the molecular signal for this composition.Using the idea of a chemical mass balance, we consider the total measured concentrationsto be a weighted sum of the individual tissue signatures, where weightsare determined by the relative amounts of the different tissue types. We develop acompositional source apportionment model to estimate the relative amounts of tissuecomponents in a tumor specimen. We then use these estimates to infer the tissuespecificconcentrations of key molecular targets for sub-typing individual tumors. Weanticipate these specific measurements will greatly improve our ability to discriminatebetween different classes of tumors, and allow more precise matching of each patient tothe appropriate treatment

Multifunctionality and Diversity in Bacterial Biofilms

Bacteria are highly diverse and drive a bulk of ecosystem processes. Analysis of relationships between diversity and single specific ecosystem processes neglects the possibility that different species perform multiple functions at the same time. The degradation of dissolved organic carbon (DOC) followed by respiration is a key bacterial function that is modulated by the availability of DOC and the capability to produce extracellular enzymes. In freshwater ecosystems, biofilms are metabolic hotspots and major sites of DOC degradation. We manipulated the diversity of biofilm forming communities which were fed with DOC differing in availability. We characterized community composition using molecular fingerprinting (T-RFLP) and measured functioning as oxygen consumption rates, the conversion of DOC in the medium, bacterial abundance and the activities of five specific enzymes. Based on assays of the extracellular enzyme activity, we calculated how the likelihood of sustaining multiple functions was affected by reduced diversity. Carbon source and biofilm age were strong drivers of community functioning, and we demonstrate how the likelihood of sustaining multifunctionality decreases with decreasing diversity