Powdery mildew effectors AVRA1 and BEC1016 target the ER J-domain protein HvERdj3B required for immunity in barley

The barley powdery mildew fungus, Blumeria hordei (Bh), secretes hundreds of candidate secreted effector proteins (CSEPs) to facilitate pathogen infection and colonization. One of these, CSEP0008, is directly recognized by the barley nucleotide-binding leucine-rich-repeat (NLR) receptor MLA1 and therefore is designated AVRA1. Here, we show that AVRA1 and the sequence-unrelated Bh effector BEC1016 (CSEP0491) suppress immunity in barley. We used yeast two-hybrid next-generation interaction screens (Y2H-NGIS), followed by binary Y2H and in planta protein-protein interactions studies, and identified a common barley target of AVRA1 and BEC1016, the endoplasmic reticulum (ER)-localized J-domain protein HvERdj3B. Silencing of this ER quality control (ERQC) protein increased Bh penetration. HvERdj3B is ER luminal, and we showed using split GFP that AVRA1 and BEC1016 translocate into the ER signal peptide-independently. Overexpression of the two effectors impeded trafficking of a vacuolar marker through the ER; silencing of HvERdj3B also exhibited this same cellular phenotype, coinciding with the effectors targeting this ERQC component. Together, these results suggest that the barley innate immunity, preventing Bh entry into epidermal cells, requires ERQC. Here, the J-domain protein HvERdj3B appears to be essential and can be regulated by AVRA1 and BEC1016. Plant disease resistance often occurs upon direct or indirect recognition of pathogen effectors by host NLR receptors. Previous work has shown that AVRA1 is directly recognized in the cytosol by the immune receptor MLA1. We speculate that the AVRA1 J-domain target being inside the ER, where it is inapproachable by NLRs, has forced the plant to evolve this challenging direct recognition.

Multi-level prediction of substance use: Interaction of white matter integrity, resting-state connectivity and inhibitory control measured repeatedly in every-day life

Substance use disorders are characterized by inhibition deficits related to disrupted connectivity in white matter pathways, leading via interaction to difficulties in resisting substance use. By combining neuroimaging with smartphone-based ecological momentary assessment (EMA), we questioned how biomarkers moderate inhibition deficits to predict use. Thus, we aimed to assess white matter integrity interaction with everyday inhibition deficits and related resting-state network connectivity to identify multi-dimensional predictors of substance use. Thirty-eight patients treated for alcohol, cannabis or tobacco use disorder completed 1 week of EMA to report substance use five times and complete Stroop inhibition testing twice daily. Before EMA tracking, participants underwent resting state functional MRI and diffusion tensor imaging (DTI) scanning. Regression analyses were conducted between mean Stroop performances and whole-brain fractional anisotropy (FA) in white matter. Moderation testing was conducted between mean FA within significant clusters as moderator and the link between momentary Stroop performance and use as outcome. Predictions between FA and resting-state connectivity strength in known inhibition-related networks were assessed using mixed modelling. Higher FA values in the anterior corpus callosum and bilateral anterior corona radiata predicted higher mean Stroop performance during the EMA week and stronger functional connectivity in occipital-frontal-cerebellar regions. Integrity in these regions moderated the link between inhibitory control and substance use, whereby stronger inhibition was predictive of the lowest probability of use for the highest FA values. In conclusion, compromised white matter structural integrity in anterior brain systems appears to underlie impairment in inhibitory control functional networks and compromised ability to refrain from substance use.

Synthesis and Growth of Green Graphene from Biochar Revealed by Magnetic Properties of Iron Catalyst

Understanding the mechanism of iron-catalyzed graphitization of biomass is an important step for the large-scale synthesis of green graphene. Although iron is known to be the most active transition metal for the catalytic graphitization of cellulose-derived biochar, the direct effect of the iron molecular structure on the formation of highly graphitic carbon remains elusive. Here, biochar was produced from pyrolysis of iron-impregnated cellulose at three different temperatures (1000, 1400, and 1800 °C). X-ray diffraction, X-ray photoelectron spectroscopy, and magnetic measurements were used to probe changes in biochar nanostructure catalyzed by the inclusion of iron. An increase of pyrolysis temperature led to an increase in the iron particle size and the degree of iron reduction, as well as the formation of larger graphitic carbon crystallite sizes, and these two attributes of iron were seen to positively affect the biochar graphitization usually challenging under 2000 °C.

Beyond Janus Geometry: Characterization of Flow Fields around Nonspherical Photocatalytic Microswimmers

Catalytic microswimmers that move by a phoretic mechanism in response to a self-induced chemical gradient are often obtained by the design of spherical janus microparticles, which suffer from multi-step fabrication and low yields. Approaches that circumvent laborious multi-step fabrication include the exploitation of the possibility of nonuniform catalytic activity along the surface of irregular particle shapes, local excitation or intrinsic asymmetry. Unfortunately, the effects on the generation of motion remain poorly understood. In this work, single crystalline BiVO₄ microswimmers are presented that rely on a strict inherent asymmetry of charge-carrier distribution under illumination. The origin of the asymmetrical flow pattern is elucidated because of the high spatial resolution of measured flow fields around pinned BiVO₄ colloids. As a result the flow from oxidative to reductive particle sides is confirmed. Distribution of oxidation and reduction reactions suggests a dominant self-electrophoretic motion mechanism with a source quadrupole as the origin of the induced flows. It is shown that the symmetry of the flow fields is broken by self-shadowing of the particles and synthetic surface defects that impact the photocatalytic activity of the microswimmers. The results demonstrate the complexity of symmetry breaking in nonspherical microswimmers and emphasize the role of self-shadowing for photocatalytic microswimmers. The findings are leading the way toward understanding of propulsion mechanisms of phoretic colloids of various shapes.

HectoSTAR μLED Optoelectrodes for Large-Scale, High-Precision In Vivo Opto-Electrophysiology

Dynamic interactions within and across brain areas underlie behavioral and cognitive functions. To understand the basis of these processes, the activities of distributed local circuits inside the brain of a behaving animal must be synchronously recorded while the inputs to these circuits are precisely manipulated. Even though recent technological advances have enabled such large-scale recording capabilities, the development of the high-spatiotemporal-resolution and large-scale modulation techniques to accompany those recordings has lagged. A novel neural probe is presented in this work that enables simultaneous electrical monitoring and optogenetic manipulation of deep neuronal circuits at large scales with a high spatiotemporal resolution. The "hectoSTAR" micro-light-emitting-diode (μLED) optoelectrode features 256 recording electrodes and 128 stimulation μLEDs monolithically integrated on the surface of its four 30-µm thick silicon micro-needle shanks, covering a large volume with 1.3-mm × 0.9-mm cross-sectional area located as deep as 6 mm inside the brain. The use of this device in behaving mice for dissecting long-distance network interactions across cortical layers and hippocampal regions is demonstrated. The recording-and-stimulation capabilities hectoSTAR μLED optoelectrodes enables will open up new possibilities for the cellular and circuit-based investigation of brain functions in behaving animals.

A comprehensive tool box for large animal studies of intervertebral disc degeneration

Preclinical studies involving large animal models aim to recapitulate the clinical situation as much as possible and bridge the gap from benchtop to bedside. To date, studies investigating intervertebral disc (IVD) degeneration and regeneration in large animal models have utilized a wide spectrum of methodologies for outcome evaluation. This paper aims to consolidate available knowledge, expertise, and experience in large animal preclinical models of IVD degeneration to create a comprehensive tool box of anatomical and functional outcomes. Herein, we present a Large Animal IVD Scoring Algorithm based on three scales: macroscopic (gross morphology, imaging, and biomechanics), microscopic (histological, biochemical, and biomolecular analyses), and clinical (neurologic state, mobility, and pain). The proposed algorithm encompasses a stepwise evaluation on all three scales, including spinal pain assessment, and relevant structural and functional components of IVD health and disease. This comprehensive tool box was designed for four commonly used preclinical large animal models (dog, pig, goat, and sheep) in order to facilitate standardization and applicability. Furthermore, it is intended to facilitate comparison across studies while discerning relevant differences between species within the context of outcomes with the goal to enhance veterinary clinical relevance as well. Current major challenges in pre-clinical large animal models for IVD regeneration are highlighted and insights into future directions that may improve the understanding of the underlying pathologies are discussed. As such, the IVD research community can deepen its exploration of the molecular, cellular, structural, and biomechanical changes that occur with IVD degeneration and regeneration, paving the path for clinically relevant therapeutic strategies.