2,632 research outputs found
Expanding the Reach of Alternative Dispute Resolution in Bankruptcy: The Legal and Practical Bases for the Use of Mediation and Other Forms of ADR
Gaussian Process Modelling for Improved Resolution in Faraday Depth Reconstruction
The incomplete sampling of data in complex polarization measurements from
radio telescopes negatively affects both the rotation measure (RM) transfer
function and the Faraday depth spectra derived from these data. Such gaps in
polarization data are mostly caused by flagging of radio frequency interference
and their effects worsen as the percentage of missing data increases. In this
paper we present a novel method for inferring missing polarization data based
on Gaussian processes (GPs). Gaussian processes are stochastic processes that
enable us to encode prior knowledge in our models. They also provide a
comprehensive way of incorporating and quantifying uncertainties in regression
modelling. In addition to providing non-parametric model estimates for missing
values, we also demonstrate that Gaussian process modelling can be used for
recovering rotation measure values directly from complex polarization data, and
that inferring missing polarization data using this probabilistic method
improves the resolution of reconstructed Faraday depth spectra.Comment: 16 pages, 10 figures, submitted to MNRA
Transport of ER Vesicles on Actin Filaments in Neurons by Myosin V
Axoplasmic organelles in the giant axon of the squid have been shown to move on both actin filaments and microtubules and to switch between actin filaments and microtubules during fast axonal transport. The objectives of this investigation were to identify the specific classes of axoplasmic organelles that move on actin filaments and the myosin motors involved. We developed a procedure to isolate endoplasmic reticulum (ER) from extruded axoplasm and to reconstitute its movement in vitro. The isolated ER vesicles moved on exogenous actin filaments adsorbed to coverslips in an ATP-dependent manner without the addition of soluble factors. Therefore myosin was tightly bound and not extracted during isolation. These vesicles were identified as smooth ER by use of an antibody to an ER-resident protein, ERcalcistorin/protein disulfide isomerase (EcaSt/PDI). Furthermore, an antibody to squid myosin V was used in immunogold EM studies to show that myosin V localized to these vesicles. The antibody was generated to a squid brain myosin (p196) that was classified as myosin V based on comparisons of amino acid sequences of tryptic peptides of this myosin with those of other known members of the myosin V family. Dual labeling with the squid myosin V antibody and a kinesin heavy chain antibody showed that the two motors colocalized on the same vesicles. Finally, antibody inhibition experiments were performed with two myosin V-specific antibodies to show that myosin V motor activity is required for transport of vesicles on actin filaments in axoplasm. One antibody was made to a peptide in the globular tail domain and the other to the globular head fragment of myosin V. Both antibodies inhibited vesicle transport on actin filaments by greater than 90% compared to controls. These studies provide the first direct evidence that ER vesicles are transported on actin filaments by myosin V. These data confirm the role of actin filaments in fast axonal transport and provide support for the dual filament model of vesicle transport
Modeling peptide fragmentation with dynamic Bayesian networks for peptide identification
Motivation: Tandem mass spectrometry (MS/MS) is an indispensable technology for identification of proteins from complex mixtures. Proteins are digested to peptides that are then identified by their fragmentation patterns in the mass spectrometer. Thus, at its core, MS/MS protein identification relies on the relative predictability of peptide fragmentation. Unfortunately, peptide fragmentation is complex and not fully understood, and what is understood is not always exploited by peptide identification algorithms
Targeted online liquid chromatography electron capture dissociation mass spectrometry for the localization of sites of in vivo phosphorylation in human Sprouty2
We demonstrate a strategy employing collision-induced dissociation for phosphopeptide discovery, followed by targeted electron capture dissociation (ECD) for site localization. The high mass accuracy and low background noise of the ECD mass spectra allow facile sequencing of coeluting isobaric phosphopeptides, with up to two isobaric phosphopeptides sequenced from a single mass spectrum. In contrast to the previously described neutral loss of dependent ECD method, targeted ECD allows analysis of both phosphotyrosine peptides and lower abundance phosphopeptides. The approach was applied to phosphorylation analysis of human Sprouty2, a regulator of receptor tyrosine kinase signaling. Fifteen sites of phosphorylation were identified, 11 of which are novel
Immunometabolic Signatures Predict Risk of Progression to Active Tuberculosis and Disease Outcome
A standardized framing for reporting protein identifications in mzIdentML 1.2
Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software
Current challenges in software solutions for mass spectrometry-based quantitative proteomics
This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.
A high-throughput de novo sequencing approach for shotgun proteomics using high-resolution tandem mass spectrometry
<p>Abstract</p> <p>Background</p> <p>High-resolution tandem mass spectra can now be readily acquired with hybrid instruments, such as LTQ-Orbitrap and LTQ-FT, in high-throughput shotgun proteomics workflows. The improved spectral quality enables more accurate <it>de novo </it>sequencing for identification of post-translational modifications and amino acid polymorphisms.</p> <p>Results</p> <p>In this study, a new <it>de novo </it>sequencing algorithm, called Vonode, has been developed specifically for analysis of such high-resolution tandem mass spectra. To fully exploit the high mass accuracy of these spectra, a unique scoring system is proposed to evaluate sequence tags based primarily on mass accuracy information of fragment ions. Consensus sequence tags were inferred for 11,422 spectra with an average peptide length of 5.5 residues from a total of 40,297 input spectra acquired in a 24-hour proteomics measurement of <it>Rhodopseudomonas palustris</it>. The accuracy of inferred consensus sequence tags was 84%. According to our comparison, the performance of Vonode was shown to be superior to the PepNovo v2.0 algorithm, in terms of the number of <it>de novo </it>sequenced spectra and the sequencing accuracy.</p> <p>Conclusions</p> <p>Here, we improved <it>de novo </it>sequencing performance by developing a new algorithm specifically for high-resolution tandem mass spectral data. The Vonode algorithm is freely available for download at <url>http://compbio.ornl.gov/Vonode</url>.</p
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