3,451 research outputs found
How does insect resistance to phosphine affect insect control costs of stored-grain?
Crop Production/Industries,
Identification of proteins in the postsynaptic density fraction by mass spectrometry
Our understanding of the organization of postsynaptic signaling systems at excitatory synapses has been aided by the identification of proteins in the postsynaptic density (PSD) fraction, a subcellular fraction enriched in structures with the morphology of PSDs. In this study, we have completed the identification of most major proteins in the PSD fraction with the use of an analytical method based on mass spectrometry coupled with searching of the protein sequence databases. At least one protein in each of 26 prominent protein bands from the PSD fraction has now been identified. We found 7 proteins not previously known to be constituents of the PSD fraction and 24 that had previously been associated with the PSD by other methods. The newly identified proteins include the heavy chain of myosin-Va (dilute myosin), a motor protein thought to be involved in vesicle trafficking, and the mammalian homolog of the yeast septin protein cdc10, which is important for bud formation in yeast. Both myosin-Va and cdc10 are threefold to fivefold enriched in the PSD fraction over brain homogenates. Immunocytochemical localization of myosin-Va in cultured hippocampal neurons shows that it partially colocalizes with PSD-95 at synapses and is also diffusely localized in cell bodies, dendrites, and axons. Cdc10 has a punctate distribution in cell bodies and dendrites, with some of the puncta colocalizing with PSD-95. The results support a role for myosin-Va in transport of materials into spines and for septins in the formation or maintenance of spines
Stellar and Planetary Properties of K2 Campaign 1 Candidates and Validation of 17 Planets, Including a Planet Receiving Earth-like Insolation
The extended Kepler mission, K2, is now providing photometry of new fields
every three months in a search for transiting planets. In a recent study,
Foreman-Mackey and collaborators presented a list of 36 planet candidates
orbiting 31 stars in K2 Campaign 1. In this contribution, we present stellar
and planetary properties for all systems. We combine ground-based
seeing-limited survey data and adaptive optics imaging with an automated
transit analysis scheme to validate 21 candidates as planets, 17 for the first
time, and identify 6 candidates as likely false positives. Of particular
interest is K2-18 (EPIC 201912552), a bright (K=8.9) M2.8 dwarf hosting a 2.23
\pm 0.25 R_Earth planet with T_eq = 272 \pm 15 K and an orbital period of 33
days. We also present two new open-source software packages which enable this
analysis. The first, isochrones, is a flexible tool for fitting theoretical
stellar models to observational data to determine stellar properties using a
nested sampling scheme to capture the multimodal nature of the posterior
distributions of the physical parameters of stars that may plausibly be
evolved. The second is vespa, a new general-purpose procedure to calculate
false positive probabilities and statistically validate transiting exoplanets.Comment: 17 pages, 5 figures, 5 tables, accepted for publication in the
Astrophysical Journal. Updated to closely reflect published version in ApJ
(2015, 809, 25
Liraglutide and renal outcomes in type 2 diabetes
In a randomized, controlled trial that compared liraglutide, a glucagon-like peptide 1 analogue, with placebo in patients with type 2 diabetes and high cardiovascular risk who were receiving usual care, we found that liraglutide resulted in lower risks of the primary end point (nonfatal myocardial infarction, nonfatal stroke, or death from cardiovascular causes) and death. However, the long-term effects of liraglutide on renal outcomes in patients with type 2 diabetes are unknown
The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing
Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model), generalizing our previous approach (Ising model) that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these) predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = −0.74, p = 3.6×10−6) are strongly correlated, and this was further strengthened in the regularized Ising model (r = −0.83, p = 3.7×10−12). Performance of the Potts model (r = −0.73, p = 9.7×10−9) was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion, and harnessing this knowledge for immunogen design
Neutrino-Lepton Masses, Zee Scalars and Muon g-2
Evidence for neutrino oscillations is pointing to the existence of tiny but
finite neutrino masses. Such masses may be naturally generated via radiative
corrections in models such as the Zee model where a singlet Zee-scalar plays a
key role. We minimally extend the Zee model by including a right-handed singlet
neutrino \nu_R. The radiative Zee-mechanism can be protected by a simple U(1)_X
symmetry involving only the \nu_R and a Zee-scalar. We further construct a
class of models with a single horizontal U(1)_FN (a la Frogatt-Nielsen) such
that the mass patterns of the neutrinos and leptons are naturally explained. We
then analyze the muon anomalous magnetic moment (g-2) and the flavor changing
\mu --> e\gamma decay. The \nu_R interaction in our minimal extension is found
to induce the BNL g-2 anomaly, with a light charged Zee-scalar of mass 100-300
GeV.Comment: Version for Phys. Rev. Lett. (typos corrected, minor refinements
Complex Probabilities on R^N as Real Probabilities on C^N and an Application to Path Integrals
We establish a necessary and sufficient condition for averages over complex
valued weight functions on R^N to be represented as statistical averages over
real, non-negative probability weights on C^N. Using this result, we show that
many path-integrals for time-ordered expectation values of bosonic degrees of
freedom in real-valued time can be expressed as statistical averages over
ensembles of paths with complex-valued coordinates, and then speculate on
possible consequences of this result for the relation between quantum and
classical mechanics.Comment: 4 pages, 0 figure
The XMM Cluster Survey: Evidence for energy injection at high redshift from evolution of the X-ray luminosity-temperature relation
We measure the evolution of the X-ray luminosity-temperature (L_X-T) relation
since z~1.5 using a sample of 211 serendipitously detected galaxy clusters with
spectroscopic redshifts drawn from the XMM Cluster Survey first data release
(XCS-DR1). This is the first study spanning this redshift range using a single,
large, homogeneous cluster sample. Using an orthogonal regression technique, we
find no evidence for evolution in the slope or intrinsic scatter of the
relation since z~1.5, finding both to be consistent with previous measurements
at z~0.1. However, the normalisation is seen to evolve negatively with respect
to the self-similar expectation: we find E(z)^{-1} L_X = 10^{44.67 +/- 0.09}
(T/5)^{3.04 +/- 0.16} (1+z)^{-1.5 +/- 0.5}, which is within 2 sigma of the zero
evolution case. We see milder, but still negative, evolution with respect to
self-similar when using a bisector regression technique. We compare our results
to numerical simulations, where we fit simulated cluster samples using the same
methods used on the XCS data. Our data favour models in which the majority of
the excess entropy required to explain the slope of the L_X-T relation is
injected at high redshift. Simulations in which AGN feedback is implemented
using prescriptions from current semi-analytic galaxy formation models predict
positive evolution of the normalisation, and differ from our data at more than
5 sigma. This suggests that more efficient feedback at high redshift may be
needed in these models.Comment: Accepted for publication in MNRAS; 12 pages, 6 figures; added
references to match published versio
Centerscope
Centerscope, formerly Scope, was published by the Boston University Medical Center "to communicate the concern of the Medical Center for the development and maintenance of improved health care in contemporary society.
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