229 research outputs found
Integrated approach for metabolite identification in LC-MS
No full textAnnotation of peaks and rapid identification of metabolites is currently still a major bottle-neck in mass spectrometry (MS) based metabolomics. Despite
numerous new algorithms and software packages published in recent years, including attempts at de-novo identification and modeling, the workhorse of
the trade remains mass-to-mass and retention time (RT) matching of observed and reference library peaks, including, when available, MS/MS data which
is used for confirmation. In this work, we present a rational, statistically based expansion of the used approach using orthogonal computational modules
and accumulation of independent evidence to achieve automatic high confidence identifications of metabolites in LC-MS data
Triage of the <i>Gaia</i> DR3 astrometric orbits. II:A census of white dwarfs
No full textThe third data release of Gaia was the first to include orbital solutions assuming non-single stars. Here, we apply the astrometric triage technique of Shahaf et al. to identify binary star systems with companions that are not single main-sequence stars. Gaia's synthetic photometry of these binaries is used to distinguish between systems likely to have white-dwarf companions and those that may be hierarchical triples. The study uncovered a population of nearly binaries, characterized by orbital separations on the order of an astronomical unit, in which the faint astrometric companion is probably a white dwarf. This sample increases the number of orbitally solved binary systems of this type by about two orders of magnitude. Remarkably, over 110 of these systems exhibit significant ultraviolet excess flux, confirming this classification and, in some cases, indicating their relatively young cooling ages. We show that the sample is not currently represented in synthetic binary populations, and is not easily reproduced by available binary population synthesis codes. Therefore, it challenges current binary evolution models, offering a unique opportunity to gain insights into the processes governing white-dwarf formation, binary evolution, and mass transfer
Triage of the Gaia DR3 astrometric orbits. II. A census of white dwarfs
No full textThe third data release of Gaia was the first to include orbital solutions
assuming non-single stars. Here, we apply the astrometric triage technique of
Shahaf et al. to identify binary star systems with companions that are not
single main-sequence stars. Gaia's synthetic photometry of these binaries is
used to distinguish between systems likely to have white-dwarf companions and
those that may be hierarchical triples. The study uncovered a population of
nearly 3200 binaries, characterised by orbital separations on the order of an
astronomical unit, in which the faint astrometric companion is probably a white
dwarf. This sample increases the number of orbitally solved binary systems of
this type by about two orders of magnitude. Remarkably, over 110 of these
systems exhibit significant ultraviolet excess flux, confirming this
classification and, in some cases, indicating their relatively young cooling
ages. We show that the sample is not currently represented in synthetic binary
populations, and is not easily reproduced by available binary population
synthesis codes. Therefore, it challenges current binary evolution models,
offering a unique opportunity to gain insights into the processes governing
white-dwarf formation, binary evolution, and mass transfer.Comment: Accepted to MNRAS. See the arXiv submission files for the full tables
A1 and A
Ig gene diversification and selection in follicular lymphoma, diffuse large B cell lymphoma and primary central nervous system lymphoma revealed by lineage tree and mutation analyses
No full textFollicular lymphoma (FL), diffuse large B cell lymphoma (DLBCL) and primary central nervous system lymphoma are B cell malignancies. FL and DLBCL have a germinal center origin. We have applied mutational analyses and a novel algorithm for quantifying shape properties of mutational lineage trees to investigate the nature of the diversification, somatic hypermutation and selection processes that affect B cell clones in these malignancies and reveal whether they differ from normal responses. Lineage tree analysis demonstrated higher diversification and mutations per cell in the lymphoma clones. This was caused solely by the longer diversification times of the malignant clones, as their recent diversification processes were similar to those of normal responses, implying similar mutation frequencies. Since previous analyses of antigen-driven selection were shown to yield false positives, we performed a corrected analysis of replacement and silent mutation patterns, which revealed selection against replacement mutations in the framework regions, responsible for the structural integrity of the B cell receptor, but not for positive selection for replacements in the complementary determining regions. Most replacements, however, were neutral or conservative, suggesting that if at all selection operates in these malignancies it is for structural B cell receptor integrity but not for antigen binding
The WEIZMASS spectral library for high-confidence metabolite identification
No full text<p>Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.</p
Do Things Feel Different from a Distance? Exploring the Role of Self-Distance in Cognitive Reappraisal and Emotion Regulation
No full textIn a diary study, students in romantic relationships will be randomly assigned to reflect on daily conflicts with their partner from a self-distanced or a self-immersed perspective. Then, they will rate emotions and a short version of engagement and emotion regulation questionnaire (ERQ-S). Before and after the diary, participants will report a single recent conflict with their partner and rate relationship satisfaction, as well as emotions, wise reasoning, forgiveness and ERQ-S to examine changes in these outcomes as a result of the self-distancing training
Immunoglobulin variable-region gene mutational lineage tree analysis: application to autoimmune diseases
No full textLineage trees have frequently been drawn to illustrate diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. In order to extract more information from IGV sequences, we developed a novel mathematical method for analyzing the graphical properties of IgV gene lineage trees, allowing quantification of the differences between the dynamics of SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we investigated trees generated from published IGV sequence data from B cell clones participating in autoimmune responses in patients with Myasthenia Gravis (MG), Rheumatoid Arthritis (RA), and Sjögren's Syndrome (SS). At present, as no standards exist for cell sampling and sequence extraction methods, data obtained by different research groups from two studies of the same disease often vary considerably. Nevertheless, based on comparisons of data groups within individual studies, we show here that lineage trees from different individual patients are often similar and can be grouped together, as can trees from two different tissues in the same patient, and even from IgG- and IgA-expressing B cell clones. Additionally, lineage trees from most studies reflect the chronic character of autoimmune diseases
Ba Enrichment in Gaia MS+WD Binaries: Tracing <i>s</i>-process Element Production
No full textA large population of intermediate-separation binaries, consisting of a main-sequence (MS) star and a white dwarf (WD), recently emerged from Gaia's third data release (DR3), posing challenges to current models of binary evolution. Here we examine the s-process element abundances in these systems using data from GALAH DR3. Following refined sample analysis with parameter estimates based on GALAH spectra, we find a distinct domain where enhanced s-process elemental abundances depend on both the WD mass and metallicity, consistent with parameter spaces identified in previous asymptotic giant branch (AGB) nucleosynthesis studies having higher s-process yields. Notably, these enhanced abundances show no correlation with the systems' orbital parameters, supporting a history of accretion in intermediate-separation MS+WD systems. Consequently, our results form direct observational evidence of a connection between AGB masses and s-process yields. We conclude by showing that the GALAH DR3 survey includes numerous Ba dwarf stars, within and beyond the mass range covered in our current sample, which can further elucidate s-process element distributions in MS+WD binaries
Meta-Level Techniques for Planning, Search, and Scheduling
No full textMetareasoning is a core idea in AI at that captures the essence of being both human and intelligent. This idea is that much can be gained by thinking (reasoning) about one's own thinking. In the context of search and planning, metareasoning concerns with making explicit decisions about computation steps, by comparing their `cost' in computational resources, against the gain they can be expected to make towards advancing the search for solution (or plan) and thus making better decisions. To apply metareasoning, a meta-level problem needs to be defined and solved with respect to a specific framework or algorithm. In some cases, these meta-level problems can be very hard to solve. Yet, even a fast-to-compute approximation of meta-level problems can yield good results and improve the algorithms to which they are applied. This paper provides an overview of different settings in which we applied metareasoning to improve search, planning and scheduling
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