22,292 research outputs found
A switch element in the autophagy E2 Atg3 mediates allosteric regulation across the lipidation cascade
Autophagy depends on the E2 enzyme, Atg3, functioning in a conserved E1-E2-E3 trienzyme cascade that catalyzes lipidation of Atg8-family ubiquitin-like proteins (UBLs). Molecular mechanisms underlying Atg8 lipidation remain poorly understood despite association of Atg3, the E1 Atg7, and the composite E3 Atg12-Atg5-Atg16 with pathologies including cancers, infections and neurodegeneration. Here, studying yeast enzymes, we report that an Atg3 element we term E123IR (E1, E2, and E3-interacting region) is an allosteric switch. NMR, biochemical, crystallographic and genetic data collectively indicate that in the absence of the enzymatic cascade, the Atg3(E123IR) makes intramolecular interactions restraining Atg3's catalytic loop, while E1 and E3 enzymes directly remove this brace to conformationally activate Atg3 and elicit Atg8 lipidation in vitro and in vivo. We propose that Atg3's E123IR protects the E2 similar to UBL thioester bond from wayward reactivity toward errant nucleophiles, while Atg8 lipidation cascade enzymes induce E2 active site remodeling through an unprecedented mechanism to drive autophagy
Specific heat and thermal conductivity of ferromagnetic magnons in Yttrium Iron Garnet
The specific heat and thermal conductivity of the insulating ferrimagnet
YFeO (Yttrium Iron Garnet, YIG) single crystal were measured
down to 50 mK. The ferromagnetic magnon specific heat shows a
characteristic dependence down to 0.77 K. Below 0.77 K, a downward
deviation is observed, which is attributed to the magnetic dipole-dipole
interaction with typical magnitude of 10 eV. The ferromagnetic magnon
thermal conductivity does not show the characteristic
dependence below 0.8 K. To fit the data, both magnetic defect
scattering effect and dipole-dipole interaction are taken into account. These
results complete our understanding of the thermodynamic and thermal transport
properties of the low-lying ferromagnetic magnons.Comment: 5 pages, 5 figure
The S=1/2 chain in a staggered field: High-energy bound-spinon state and the effects of a discrete lattice
We report an experimental and theoretical study of the antiferromagnetic
S=1/2 chain subject to uniform and staggered fields. Using inelastic neutron
scattering, we observe a novel bound-spinon state at high energies in the
linear chain compound CuCl2 * 2((CD3)2SO). The excitation is explained with a
mean-field theory of interacting S=1/2 fermions and arises from the opening of
a gap at the Fermi surface due to confining spinon interactions. The mean-field
model also describes the wave-vector dependence of the bound-spinon states,
particularly in regions where effects of the discrete lattice are important. We
calculate the dynamic structure factor using exact diagonalization of finite
length chains, obtaining excellent agreement with the experiments.Comment: 16 pages, 7 figures, accepted by Phys. Rev.
Nodeless superconductivity in Ca3Ir4Sn13: evidence from quasiparticle heat transport
We report resistivity and thermal conductivity measurements
on CaIrSn single crystals, in which superconductivity with K was claimed to coexist with ferromagnetic spin-fluctuations. Among
three crystals, only one crystal shows a small hump in resistivity near 20 K,
which was previously attributed to the ferromagnetic spin-fluctuations. Other
two crystals show the Fermi-liquid behavior at low temperature.
For both single crystals with and without the resistivity anomaly, the residual
linear term is negligible in zero magnetic field. In low fields,
shows a slow field dependence. These results demonstrate that
the superconducting gap of CaIrSn is nodeless, thus rule out
nodal gap caused by ferromagnetic spin-fluctuations.Comment: 5 pages, 4 figure
Functional Modeling of Plant Growth Dynamics
Recent advances in automated plant phenotyping have enabled the collection of time series measurements from the same plants of a wide range of traits at different developmental time scales. The availability of time series phenotypic datasets has increased interest in statistical approaches for comparing patterns of change among different plant genotypes and different treatment conditions. Two widely used methods of modeling growth with time are pointwise analysis of variance (ANOVA) and parametric sigmoidal curve fitting. Pointwise ANOVA yields discontinuous growth curves, which do not reflect the true dynamics of growth patterns in plants. In contrast, fitting a parametric model to a time series of observations does capture the trend of growth; however, these models require assumptions regarding the true pattern of plant growth. Depending on the species, treatment regime, and subset of the plant life cycle sampled, these assumptions will not always hold true. We have developed a different approach—functional ANOVA—which yields continuous growth curves without requiring assumptions regarding patterns of plant growth. We compared and validated this approach using data from an experiment measuring the growth of two maize (Zea mays L. ssp. mays) genotypes under two water availability treatments during a 21-d period. Functional ANOVA enables a nonparametric estimation of the dynamics of changes in plant traits with time without assumptions regarding curve shape. In addition to estimating smooth curves of trait values with time, functional ANOVA also estimates the derivatives of these curves, e.g., growth rates, simultaneously. Using two different subsampling strategies, we demonstrate that this functional ANOVA method enables the comparison of growth curves among plants phenotyped on non-overlapping days with little reduction in estimation accuracy. This means that functional ANOVA based approaches can allow larger numbers of samples and biological replicates to be scored in a single experiment given fixed amounts of phenotyping infrastructure and personnel
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