A suite of software for processing MicroED data of extremely small protein crystals.

Electron diffraction of extremely small three-dimensional crystals (MicroED) allows for structure determination from crystals orders of magnitude smaller than those used for X-ray crystallography. MicroED patterns, which are collected in a transmission electron microscope, were initially not amenable to indexing and intensity extraction by standard software, which necessitated the development of a suite of programs for data processing. The MicroED suite was developed to accomplish the tasks of unit-cell determination, indexing, background subtraction, intensity measurement and merging, resulting in data that can be carried forward to molecular replacement and structure determination. This ad hoc solution has been modified for more general use to provide a means for processing MicroED data until the technique can be fully implemented into existing crystallographic software packages. The suite is written in Python and the source code is available under a GNU General Public License

Proton-coupled sugar transport in the prototypical major facilitator superfamily protein XylE.

The major facilitator superfamily (MFS) is the largest collection of structurally related membrane proteins that transport a wide array of substrates. The proton-coupled sugar transporter XylE is the first member of the MFS that has been structurally characterized in multiple transporting conformations, including both the outward and inward-facing states. Here we report the crystal structure of XylE in a new inward-facing open conformation, allowing us to visualize the rocker-switch movement of the N-domain against the C-domain during the transport cycle. Using molecular dynamics simulation, and functional transport assays, we describe the movement of XylE that facilitates sugar translocation across a lipid membrane and identify the likely candidate proton-coupling residues as the conserved Asp27 and Arg133. This study addresses the structural basis for proton-coupled substrate transport and release mechanism for the sugar porter family of proteins

Grover's Quantum Search Algorithm and Diophantine Approximation

In a fundamental paper [Phys. Rev. Lett. 78, 325 (1997)] Grover showed how a quantum computer can find a single marked object in a database of size N by using only O(N^{1/2}) queries of the oracle that identifies the object. His result was generalized to the case of finding one object in a subset of marked elements. We consider the following computational problem: A subset of marked elements is given whose number of elements is either M or K, M<K, our task is to determine which is the case. We show how to solve this problem with a high probability of success using only iterations of Grover's basic step (and no other algorithm). Let m be the required number of iterations; we prove that under certain restrictions on the sizes of M and K the estimation m < (2N^{1/2})/(K^{1/2}-M^{1/2}) obtains. This bound sharpens previous results and is known to be optimal up to a constant factor. Our method involves simultaneous Diophantine approximations, so that Grover's algorithm is conceptualized as an orbit of an ergodic automorphism of the torus. We comment on situations where the algorithm may be slow, and note the similarity between these cases and the problem of small divisors in classical mechanics.Comment: 8 pages, revtex, Title change

Genetic analysis of milk yield in first-lactation Holstein-Friesian in Ethiopia: A lactation average vs random regression test-day model analysis

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Structure of amyloid-β (20-34) with Alzheimer's-associated isomerization at Asp23 reveals a distinct protofilament interface.

Amyloid-β (Aβ) harbors numerous posttranslational modifications (PTMs) that may affect Alzheimer's disease (AD) pathogenesis. Here we present the 1.1 Å resolution MicroED structure of an Aβ 20-34 fibril with and without the disease-associated PTM, L-isoaspartate, at position 23 (L-isoAsp23). Both wild-type and L-isoAsp23 protofilaments adopt β-helix-like folds with tightly packed cores, resembling the cores of full-length fibrillar Aβ structures, and both self-associate through two distinct interfaces. One of these is a unique Aβ interface strengthened by the isoaspartyl modification. Powder diffraction patterns suggest a similar structure may be adopted by protofilaments of an analogous segment containing the heritable Iowa mutation, Asp23Asn. Consistent with its early onset phenotype in patients, Asp23Asn accelerates aggregation of Aβ 20-34, as does the L-isoAsp23 modification. These structures suggest that the enhanced amyloidogenicity of the modified Aβ segments may also reduce the concentration required to achieve nucleation and therefore help spur the pathogenesis of AD

Paper Session II-A - ISOBUS A Faster, Better, Cheaper Tool for Space Flight Experiments

Space exploration and related investigations have been suffering from programmatic inefficiencies inherent to customized projects. One-of-a-kind space investigations such as experiments, installations, platforms, and missions all lack the profit-driven architectures and money-making methodologies that characterize commercial enterprise. The foundation of long-tenm commercial success is in the smart and efficient utilization of capital investment. An enterprise that throws away its tools, its infrastructure, its expertise, and its capital, every time it completes a project is not likely to be able to afford to do so again and again. When resources are scarce, one must utilize them efficiently. Proven commercial methodologies such as standardization, mass production, miniaturization, modular interchangeability, and reusability . of tools, facilities, and resources are the principal techniques by which products can be created faster-better-cheaper. Commercial investigators in intensely competitive fields, such as biotechnology, have successfully applied these principles to their experimental setups, tools, and support systems. We must similarly employ commercial principles if we are to survive the expensive challenge of future space exploration. This paper introduces a faster-bettercheaper\u27\u27 approach for space investigators. The approach employs a tool called ISOBUS

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted Data

We provide a framework for solving inverse problems with diffusion models learned from linearly corrupted data. Our method, Ambient Diffusion Posterior Sampling (A-DPS), leverages a generative model pre-trained on one type of corruption (e.g. image inpainting) to perform posterior sampling conditioned on measurements from a potentially different forward process (e.g. image blurring). We test the efficacy of our approach on standard natural image datasets (CelebA, FFHQ, and AFHQ) and we show that A-DPS can sometimes outperform models trained on clean data for several image restoration tasks in both speed and performance. We further extend the Ambient Diffusion framework to train MRI models with access only to Fourier subsampled multi-coil MRI measurements at various acceleration factors (R=2, 4, 6, 8). We again observe that models trained on highly subsampled data are better priors for solving inverse problems in the high acceleration regime than models trained on fully sampled data. We open-source our code and the trained Ambient Diffusion MRI models: https://github.com/utcsilab/ambient-diffusion-mri .Comment: Pre-print, work in progres