2,976 research outputs found
Northern Steamship Company: The depreciation problem in the nineteenth century
In 1889 a New Zealand company had to write down its paid-up capital by 27 percent, because, the Chairman stated, previous management had failed to allow for depreciation as an expense. An investigation was conducted to see if this capital reduction could have been avoided had the company followed modern depreciation policy. This revealed that the failure to depreciate adequately was not the main cause of the capital reduction, other firms followed the same practice and contemporary English legislation did not permit depreciation as a tax deductible item, while United States courts were rejecting depreciation as a valid expense
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
Highly chlorinated PCBs inhibit the human xenobiotic response mediated by the steroid and xenobiotic receptor (SXR).
Polychlorinated biphenyls (PCBs) are a family of persistent organic contaminants suspected to cause adverse effects in wildlife and humans. In rodents, PCBs bind to the aryl hydrocarbon (AhR) and pregnane X receptors (PXR) inducing the expression of catabolic cytochrome p450 enzymes of the CYP1A and 3A families. We found that certain highly chlorinated PCBs are potent activators of rodent PXR but antagonize its human ortholog, the steroid and xenobiotic receptor (SXR), inhibiting target gene induction. Thus, exposure to PCBs may blunt the human xenobiotic response, inhibiting the detoxification of steroids, bioactive dietary compounds, and xenobiotics normally mediated by SXR. The antagonistic PCBs are among the most stable and abundant in human tissues. These findings have important implications for understanding the biologic effects of PCB exposure and the use of animal models to predict the attendant risk
Network-assisted protein identification and data interpretation in shotgun proteomics
Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. Usually, only individual proteins with strong experimental evidence, that is, confident proteins, are reported, whereas many possible proteins of biological interest are eliminated. We have developed a clique-enrichment approach (CEA) to rescue eliminated proteins by incorporating the relationship among proteins as embedded in a protein interaction network. In several data sets tested, CEA increased protein identification by 8ā23% with an estimated accuracy of 85%. Rescued proteins were supported by existing literature or transcriptome profiling studies at similar levels as confident proteins and at a significantly higher level than abandoned ones. Applying CEA on a breast cancer data set, rescued proteins coded by well-known breast cancer genes. In addition, CEA generated a network view of the proteins and helped show the modular organization of proteins that may underpin the molecular mechanisms of the disease
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