Controlling antiferromagnetic domains in patterned La0.7Sr0.3FeO3 thin films

Transition metal oxide thin films and heterostructures are promising platforms to achieve full control of the antiferromagnetic (AFM) domain structure in patterned features as needed for AFM spintronic devices. In this work, soft x-ray photoemission electron microscopy was utilized to image AFM domains in micromagnets patterned into La0.7Sr0.3FeO3 (LSFO) thin films and La0.7Sr0.3MnO3 (LSMO)/LSFO superlattices. A delicate balance exists between magnetocrystalline anisotropy, shape anisotropy, and exchange interactions such that the AFM domain structure can be controlled using parameters such as LSFO and LSMO layer thickness, micromagnet shape, and temperature. In LSFO thin films, shape anisotropy gains importance only in micromagnets where at least one extended edge is aligned parallel to an AFM easy axis. In contrast, in the limit of ultrathin LSFO layers in the LSMO/LSFO superlattice, shape anisotropy effects dominate such that the AFM spin axes at micromagnet edges can be aligned along any in-plane crystallographic direction

A microfluidics and agent-based modeling framework for investigating spatial organization in bacterial colonies: The case of Pseudomonas Aeruginosa amd H1-type VI secretion interactions

The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models

Video frame prediction of microbial growth with a recurrent neural network

The recent explosion of interest and advances in machine learning technologies has opened the door to new analytical capabilities in microbiology. Using experimental data such as images or videos, machine learning, in particular deep learning with neural networks, can be harnessed to provide insights and predictions for microbial populations. This paper presents such an application in which a Recurrent Neural Network (RNN) was used to perform prediction of microbial growth for a population of two Pseudomonas aeruginosa mutants. The RNN was trained on videos that were acquired previously using fluorescence microscopy and microfluidics. Of the 20 frames that make up each video, 10 were used as inputs to the network which outputs a prediction for the next 10 frames of the video. The accuracy of the network was evaluated by comparing the predicted frames to the original frames, as well as population curves and the number and size of individual colonies extracted from these frames. Overall, the growth predictions are found to be accurate in metrics such as image comparison, colony size, and total population. Yet, limitations exist due to the scarcity of available and comparable data in the literature, indicating a need for more studies. Both the successes and challenges of our approach are discussed

Microstructural and Rheological Transitions in Bacterial Biofilms

Abstract Biofilms are aggregated bacterial communities structured within an extracellular matrix (ECM). ECM controls biofilm architecture and confers mechanical resistance against shear forces. From a physical perspective, biofilms can be described as colloidal gels, where bacterial cells are analogous to colloidal particles distributed in the polymeric ECM. However, the influence of the ECM in altering the cellular packing fraction (ϕ) and the resulting viscoelastic behavior of biofilm remains unexplored. Using biofilms of Pantoea sp. (WT) and its mutant (ΔUDP), the correlation between biofilm structure and its viscoelastic response is investigated. Experiments show that the reduction of exopolysaccharide production in ΔUDP biofilms corresponds with a seven‐fold increase in ϕ, resulting in a colloidal glass‐like structure. Consequently, the rheological signatures become altered, with the WT behaving like a weak gel, whilst the ΔUDP displayed a glass‐like rheological signature. By co‐culturing the two strains, biofilm ϕ is modulated which allows us to explore the structural changes and capture a change in viscoelastic response from a weak to a strong gel, and to a colloidal glass‐like state. The results reveal the role of exopolysaccharide in mediating a structural transition in biofilms and demonstrate a correlation between biofilm structure and viscoelastic response

Controlling the switching field in nanomagnets by means of domain-engineered antiferromagnets

Using soft x-ray spectromicroscopy, we investigate the magnetic domain structure in embedded nanomagnets defined in La$_{0.7}$Sr$_{0.3}$MnO$_3$ thin films and LaFeO$_3$/La$_{0.7}$Sr$_{0.3}$MnO$_3$ bilayers. We find that shape-controlled antiferromagnetic domain states give rise to a significant reduction of the switching field of the rectangular nanomagnets. This is discussed in the framework of competition between an intrinsic spin-flop coupling and shape anisotropy. The data demonstrates that shape effects in antiferromagnets may be used to control the magnetic properties in nanomagnets

The Evolution of Wide Binary Stars

We study the orbital evolution of wide binary stars in the solar neighborhood due to gravitational perturbations from passing stars. We include the effects of the Galactic tidal field and continue to follow the stars after they become unbound. For a wide variety of initial semi-major axes and formation times, we find that the number density (stars per unit logarithmic interval in projected separation) exhibits a minimum at a few times the Jacobi radius r_J, which equals 1.7 pc for a binary of solar-mass stars. The density peak interior to this minimum arises from the primordial distribution of bound binaries, and the exterior density, which peaks at \sim 100--300 pc separation, arises from formerly bound binaries that are slowly drifting apart. The exterior peak gives rise to a significant long-range correlation in the positions and velocities of disk stars that should be detectable in large astrometric surveys such as GAIA that can measure accurate three-dimensional distances and velocities.Comment: 36 pages, 9 figures, accepted by MNRAS, typos correcte

Nanostructured complex oxides as a route towards thermal behavior in artificial spin ice systems

We have used soft x-ray photoemission electron microscopy to image the magnetization of single domain La$_{0.7}$Sr$_{0.3}$MnO$_{3}$ nano-islands arranged in geometrically frustrated configurations such as square ice and kagome ice geometries. Upon thermal randomization, ensembles of nano-islands with strong inter-island magnetic coupling relax towards low-energy configurations. Statistical analysis shows that the likelihood of ensembles falling into low-energy configurations depends strongly on the annealing temperature. Annealing to just below the Curie temperature of the ferromagnetic film (T$_{C}$ = 338 K) allows for a much greater probability of achieving low energy configurations as compared to annealing above the Curie temperature. At this thermally active temperature of 325 K, the ensemble of ferromagnetic nano-islands explore their energy landscape over time and eventually transition to lower energy states as compared to the frozen-in configurations obtained upon cooling from above the Curie temperature. Thus, this materials system allows for a facile method to systematically study thermal evolution of artificial spin ice arrays of nano-islands at temperatures modestly above room temperature.Comment: 4 figures and 9 supplemental figure

Spin-Flop Coupling and Exchange Bias in Embedded Complex Oxide Micromagnets

The magnetic domains of embedded micromagnets with 2  μm×2  μm dimensions defined in epitaxial La0.7Sr0.3MnO3 (LSMO) thin films and LaFeO3/LSMO bilayers were investigated using soft x-ray magnetic microscopy. Square micromagnets aligned with their edges parallel to the easy axes of LSMO provide an ideal experimental geometry for probing the influence of interface exchange coupling on the magnetic domain patterns. The observation of unique domain patterns not reported for ferromagnetic metal microstructures, namely divergent antiferromagnetic vortex domains and "Z"-type domains, suggests the simultaneous presence of spin-flop coupling and local exchange bias in this system

NEMF mutations that impair ribosome-associated quality control are associated with neuromuscular disease.

A hallmark of neurodegeneration is defective protein quality control. The E3 ligase Listerin (LTN1/Ltn1) acts in a specialized protein quality control pathway-Ribosome-associated Quality Control (RQC)-by mediating proteolytic targeting of incomplete polypeptides produced by ribosome stalling, and Ltn1 mutation leads to neurodegeneration in mice. Whether neurodegeneration results from defective RQC and whether defective RQC contributes to human disease have remained unknown. Here we show that three independently-generated mouse models with mutations in a different component of the RQC complex, NEMF/Rqc2, develop progressive motor neuron degeneration. Equivalent mutations in yeast Rqc2 selectively interfere with its ability to modify aberrant translation products with C-terminal tails which assist with RQC-mediated protein degradation, suggesting a pathomechanism. Finally, we identify NEMF mutations expected to interfere with function in patients from seven families presenting juvenile neuromuscular disease. These uncover NEMF's role in translational homeostasis in the nervous system and implicate RQC dysfunction in causing neurodegeneration