Observation of Moment-Dependent and Field-Driven Unidirectional Magnetoresistance in CoFeB/InSb/CdTe Heterostructures.

Magnetoresistance effects are crucial for understanding the charge-spin transport as well as propelling the advancement of spintronic applications. Here, we report the coexistence of magnetic-moment-dependent (MD) and magnetic-field-driven (FD) unidirectional magnetoresistance (UMR) effects in CoFeB/InSb/CdTe heterostructures. The strong spin-orbital coupling of InSb and the matched impedance at the CoFeB/InSb interface warrant a distinct MD-UMR effect at room temperature, while the interaction between the in-plane magnetic field and the Rashba effect at the InSb/CdTe interface induces the marked FD-UMR signal that dominates the high-field region. Moreover, owning to different spin scattering mechanisms, these two types of non-reciprocal charge transports show opposite polarities with respect to the magnetic field direction, which further enables an effective phase modulation of the angular-dependent magnetoresistance. The demonstration of the tunable UMR response validates our CoFeB/InSb/CdTe system as a suitable integrated building block for multifunctional spintronic memory and sensor designs.

The role of microglia in neuronal and cognitive function during high altitude acclimatization.

Due to their interactions with the neurovasculature, microglia are implicated in maladaptive responses to hypobaric hypoxia at high altitude (HA). To explore these interactions at HA, pharmacological depletion of microglia with the colony-stimulating factor-1 receptor inhibitor, PLX5622, was employed in male C57BL/6J mice maintained at HA or sea level (SL) for 3-weeks, followed by assessment of ex-vivo hippocampal long-term potentiation (LTP), fear memory recall and microglial dynamics/physiology. Our findings revealed that microglia depletion decreased LTP and reduced glucose levels by 25% at SL but did not affect fear memory recall. At HA, the absence of microglia did not significantly alter HA associated deficits in fear memory or HA mediated decreases in peripheral glucose levels. In regard to microglial dynamics in the cortex, HA enhanced microglial surveillance activity, ablation of microglia resulted in increased chemotactic responses and decreased microglia tip proliferation during ball formation. In contrast, vessel ablation increased cortical microglia tip path tortuosity. In the hippocampus, changes in microglial dynamics were only observed in response to vessel ablation following HA. As the hippocampus is critical for learning and memory, poor hippocampal microglial context-dependent adaptation may be responsible for some of the enduring neurological deficits associated with HA.

Robust Field-Free Switching Using Large Unconventional Spin-Orbit Torque in an All-Van der Waals Heterostructure.

The emerging all-van der Waals (vdW) magnetic heterostructure provides a new platform to control the magnetization by the electric field beyond the traditional spintronics devices. One promising strategy is using unconventional spin-orbit torque (SOT) exerted by the out-of-plane polarized spin current to enable deterministic magnetization switching and enhance the switching efficiency. However, in all-vdW heterostructures, large unconventional SOT remains elusive and the robustness of the field-free switching against external magnetic field has not been examined, which hinders further applications. Here, the study demonstrates the field-free switching in an all-vdW heterostructure combining a type-II Weyl semimetal TaIrTe4 and above-room-temperature ferromagnet Fe3GaTe2. The fully field-free switching can be achieved at 2.56 × 1010 A m-2 at 300 K and a large SOT effective field efficiency of the out-of-plane polarized spin current generated by TaIrTe4 is determined to be 0.37. Moreover, it is found that the switching polarity cannot be changed until the external in-plane magnetic field reaches 252 mT, indicating a robust switching against the magnetic field. The numerical simulation suggests the large unconventional SOT reduces the switching current density and enhances the robustness of the switching. The work shows that all-vdW heterostructures are promising candidates for future highly efficient and stable SOT-based devices.

Efficient Generation of Out-of-Plane Polarized Spin Current in Polycrystalline Heavy Metal Devices with Broken Electric Symmetries.

Spin currents of perpendicularly polarized spins (z spins) have received blooming interest for the potential in energy-efficient spin-orbit torque switching of perpendicular magnetization in the absence of a magnetic field. However, generation of z spins is limited mainly to magnetically or crystallographically low-symmetry single crystals that are hardly compatible with the integration to semiconductor circuits. This work reports efficient generation of z spins in sputter-deposited polycrystalline heavy metal devices via a new mechanism of broken electric symmetries in both the transverse and perpendicular directions. Both the damping-like and field-like spin-orbit torques of z spins can be tuned significantly by varying the degree of the electric asymmetries via the length, width, and thickness of devices as well as by varying the type of the heavy metals. The presence of z spins also enables deterministic, nearly-full, external-magnetic-field-free switching of a uniform perpendicularly magnetized FeCoB layer, the core structure of magnetic tunnel junctions, with high coercivity at a low current density. These results establish the first universal, energy-efficient, integration-friendly approach to generate z-spin current by electric asymmetry design for dense and low-power spin-torque memory and computing technologies and will stimulate investigation of z-spin currents in various polycrystalline materials.

Decoding the Epigenetic Landscape: Insights into 5mC and 5hmC Patterns in Mouse Cortical Cell Types.

The DNA modifications, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), represent powerful epigenetic regulators of temporal and spatial gene expression. Yet, how the cooperation of these genome-wide, epigenetic marks determine unique transcriptional signatures across different brain cell populations is unclear. Here we applied Nanopore sequencing of native DNA to obtain a complete, genome-wide, single-base resolution atlas of 5mC and 5hmC modifications in neurons, astrocytes and microglia in the mouse cortex (99% genome coverage, 40 million CpG sites). In tandem with RNA sequencing, analysis of 5mC and 5hmC patterns across cell types reveals astrocytes drive uniquely high brain 5hmC levels and support two decades of research regarding methylation patterns, gene expression and alternative splicing, benchmarking this resource. As such, we provide the most comprehensive DNA methylation data in mouse brain as an interactive, online tool (NAM-Me, https://olsenlab.shinyapps.io/NAMME/) to serve as a resource dataset for those interested in the methylome landscape.

ABDS: a bioinformatics tool suite for analyzing biologically diverse samples.

Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups.

Full electrical manipulation of perpendicular exchange bias in ultrathin antiferromagnetic film with epitaxial strain.

Achieving effective manipulation of perpendicular exchange bias effect remains an intricate endeavor, yet it stands a significance for the evolution of ultra-high capacity and energy-efficient magnetic memory and logic devices. A persistent impediment to its practical applications is the reliance on external magnetic fields during the current-induced switching of exchange bias in perpendicularly magnetized structures. This study elucidates the achievement of a full electrical manipulation of the perpendicular exchange bias in the multilayers with an ultrathin antiferromagnetic layer. Owing to the anisotropic epitaxial strain in the 2-nm-thick IrMn3 layer, the considerable exchange bias effect is clearly achieved at room temperature. Concomitantly, a specific global uncompensated magnetization manifests in the IrMn3 layer, facilitating the switching of the irreversible portion of the uncompensated magnetization. Consequently, the perpendicular exchange bias can be manipulated by only applying pulsed current, notably independent of the presence of any external magnetic fields.

Norepinephrine changes behavioral state via astroglial purinergic signaling.

Both neurons and glia communicate via diffusible neuromodulatory substances, but the substrates of computation in such neuromodulatory networks are unclear. During behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine drives fast excitation and delayed inhibition of behavior and circuit activity. We find that the inhibitory arm of this feedforward motif is implemented by astroglial purinergic signaling. Neuromodulator imaging, behavioral pharmacology, and perturbations of neurons and astroglia reveal that norepinephrine triggers astroglial release of adenosine triphosphate, extracellular conversion into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. This work, along with a companion piece by Lefton and colleagues demonstrating an analogous pathway mediating the effect of norepinephrine on synaptic connectivity in mice, identifies a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in norepinephrine-mediated behavioral and brain state transitions.

DDN3.0: determining significant rewiring of biological network structure with differential dependency networks.

MOTIVATION: Complex diseases are often caused and characterized by misregulation of multiple biological pathways. Differential network analysis aims to detect significant rewiring of biological network structures under different conditions and has become an important tool for understanding the molecular etiology of disease progression and therapeutic response. With few exceptions, most existing differential network analysis tools perform differential tests on separately learned network structures that are computationally expensive and prone to collapse when grouped samples are limited or less consistent. RESULTS: We previously developed an accurate differential network analysis method-differential dependency networks (DDN), that enables joint learning of common and rewired network structures under different conditions. We now introduce the DDN3.0 tool that improves this framework with three new and highly efficient algorithms, namely, unbiased model estimation with a weighted error measure applicable to imbalance sample groups, multiple acceleration strategies to improve learning efficiency, and data-driven determination of proper hyperparameters. The comparative experimental results obtained from both realistic simulations and case studies show that DDN3.0 can help biologists more accurately identify, in a study-specific and often unknown conserved regulatory circuitry, a network of significantly rewired molecular players potentially responsible for phenotypic transitions. AVAILABILITY AND IMPLEMENTATION: The Python package of DDN3.0 is freely available at https://github.com/cbil-vt/DDN3. A user's guide and a vignette are provided at https://ddn-30.readthedocs.io/.

Fast, Accurate, and Versatile Data Analysis Platform for the Quantification of Molecular Spatiotemporal Signals.

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce Activity Quantification and Analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine learning techniques. It decomposes complex live imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, and imaging modalities. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, and distinct sensorimotor signal propagation patterns in the mouse spinal cord.

An inducible genetic tool to track and manipulate specific microglial states reveals their plasticity and roles in remyelination.

Recent single-cell RNA sequencing studies have revealed distinct microglial states in development and disease. These include proliferative-region-associated microglia (PAMs) in developing white matter and disease-associated microglia (DAMs) prevalent in various neurodegenerative conditions. PAMs and DAMs share a similar core gene signature. However, the extent of the dynamism and plasticity of these microglial states, as well as their functional significance, remains elusive, partly due to the lack of specific tools. Here, we generated an inducible Cre driver line, Clec7a-CreERT2, that targets PAMs and DAMs in the brain parenchyma. Utilizing this tool, we profiled labeled cells during development and in several disease models, uncovering convergence and context-dependent differences in PAM and DAM gene expression. Through long-term tracking, we demonstrated microglial state plasticity. Lastly, we specifically depleted DAMs in demyelination, revealing their roles in disease recovery. Together, we provide a versatile genetic tool to characterize microglial states in CNS development and disease.

Imaging the extracellular matrix in live tissues and organisms with a glycan-binding fluorophore.

All multicellular systems produce and dynamically regulate extracellular matrices (ECM) that play important roles in both biochemical and mechanical signaling. Though the spatial arrangement of these extracellular assemblies is critical to their biological functions, visualization of ECM structure is challenging, in part because the biomolecules that compose the ECM are difficult to fluorescently label individually and collectively. Here, we present a cell-impermeable small molecule fluorophore, termed Rhobo6, that turns on and red shifts upon reversible binding to glycans. Given that most ECM components are densely glycosylated, the dye enables wash-free visualization of ECM, in systems ranging from in vitro substrates to in vivo mouse mammary tumors. Relative to existing techniques, Rhobo6 provides a broad substrate profile, superior tissue penetration, nonperturbative labeling, and negligible photobleaching. This work establishes a straightforward method for imaging the distribution of ECM in live tissues and organisms, lowering barriers for investigation of extracellular biology.

The impact of intermittent hypoxemia on type 1 retinopathy of prematurity in preterm infants.

BACKGROUND: Intermittent hypoxemia (IH) may influence retinopathy of prematurity (ROP) development in preterm infants, however, previous studies had mixed results. This study tests the hypothesis that increased IH is associated with Type 1 ROP; a stage beyond which treatment is indicated. METHODS: IH was quantified by continuously monitoring oxygen saturation (SpO2) using high-resolution pulse oximeters during the first 10 weeks of life. Statistical analyses assessed the relationship and predictive ability of weekly and cumulative IH for Type 1 ROP development. RESULTS: Most analyses showed no association between IH and Type 1 ROP adjusting for gestational age (GA) and birth weight (BW). However, cumulative IH of longer duration during weeks 5-10, 6-10, and 7-10 were significantly associated with Type 1 ROP adjusting for GA and BW, e.g., the adjusted odds ratio of Type 1 ROP was 2.01 (p = 0.03) for every 3.8 seconds increase in IH duration from week 6-10. IH did not provide statistically significant added predictive ability above GA and BW. CONCLUSIONS: For most analyses there was no significant association between IH and Type 1 ROP adjusting for GA and BW. However, infants with longer IH duration during the second month of life had higher risk for Type 1 ROP. IMPACT: The relationship and predictive ability of intermittent hypoxemia (IH) on retinopathy of prematurity (ROP) is controversial. This study shows no significant association between IH events and Type 1 ROP after adjusting for gestational age (GA) and birth weight (BW), except for cumulative IH of longer duration in the second month of life. In this cohort, IH does not provide a statistically significant improvement in ROP prediction over GA and BW. This study is the first to assess the cumulative impact of IH measures on Type 1 ROP. Interventions for reducing IH duration during critical postnatal periods may improve ROP outcomes.

Conservation of neuron-astrocyte coordinated activity among sensory processing centers of the developing brain.

Afferent neurons in developing sensory organs exhibit a prolonged period of burst firing prior to the onset of sensory experience. This intrinsically generated activity propagates from the periphery through central processing centers to promote the survival and physiological maturation of neurons and refine their synaptic connectivity. Recent studies in the auditory system indicate that these bursts of action potentials also trigger metabotropic glutamate receptor-mediated calcium increases within astrocytes that are spatially and temporally correlated with neuronal events; however, it is not known if this phenomenon occurs in other sensory modalities. Here we show using in vivo simultaneous imaging of neuronal and astrocyte calcium activity in awake mouse pups that waves of retinal ganglion cell activity induce spatially and temporally correlated waves of astrocyte activity in the superior colliculus that depend on metabotropic glutamate receptors mGluR5 and mGluR3. Astrocyte calcium transients reliably occurred with each neuronal wave, but peaked more than one second after neuronal events. Despite differences in the temporal features of spontaneous activity in auditory and visual processing regions, individual astrocytes exhibited similar overall calcium activity patterns, providing a conserved mechanism to synchronize neuronal and astrocyte maturation within discrete sensory domains.

Data science and its future in large neuroscience collaborations.

The rise of large scientific collaborations in neuroscience requires systematic, scalable, and reliable data management. How this is best done in practice remains an open question. To address this, we conducted a data science survey among currently active U19 grants, funded through the NIH's BRAIN Initiative. The survey was answered by both data science liaisons and Principal Investigators, speaking for ~500 researchers across 21 nation-wide collaborations. We describe the tools, technologies, and methods currently in use, and identify several shortcomings of current data science practice. Building on this survey, we develop plans and propose policies to improve data collection, use, publication, reuse and training in the neuroscience community.

Restricted Boltzmann Machines Implemented by Spin-Orbit Torque Magnetic Tunnel Junctions.

Artificial intelligence has surged forward with the advent of generative models, which rely heavily on stochastic computing architectures enhanced by true random number generators with adjustable sampling probabilities. In this study, we develop spin-orbit torque magnetic tunnel junctions (SOT-MTJs), investigating their sigmoid-style switching probability as a function of the driving voltage. This feature proves to be ideally suited for stochastic computing algorithms such as the restricted Boltzmann machines (RBM) prevalent in pretraining processes. We exploit SOT-MTJs as both stochastic samplers and network nodes for RBMs, enabling the implementation of RBM-based neural networks to achieve recognition tasks for both handwritten and spoken digits. Moreover, we further harness the weights derived from the preceding image and speech training processes to facilitate cross-modal learning from speech to image generation. Our results clearly demonstrate that these SOT-MTJs are promising candidates for the development of hardware accelerators tailored for Boltzmann neural networks and other stochastic computing architectures.

Direct and Inverse Spin Splitting Effects in Altermagnetic RuO2.

Recently, the altermagnetic materials with spin splitting effect (SSE), have drawn significant attention due to their potential to the flexible control of the spin polarization by the Néel vector. Here, the direct and inverse altermagnetic SSE (ASSE) in the (101)-oriented RuO2 film with the tilted Néel vector are reported. First, the spin torque along the x-, y-, and z-axis is detected from the spin torque-induced ferromagnetic resonance (ST-FMR), and the z-spin torque emerges when the electric current is along the [010] direction, showing the anisotropic spin splitting of RuO2. Further, the current-induced modulation of damping is used to quantify the damping-like torque efficiency (ξDL) in RuO2/Py, and an anisotropic ξDL is obtained and maximized for the current along the [010] direction, which increases with the reduction of the temperature, indicating the present of ASSE. Next, by way of spin pumping measurement, the inverse altermagnetic spin splitting effect (IASSE) is studied, which also shows a crystal direction-dependent anisotropic behavior and temperature-dependent behavior. This work gives a comprehensive study of the direct and inverse ASSE effects in the altermagnetic RuO2, inspiring future altermagnetic materials and devices with flexible control of spin polarization.

Probability-Distribution-Configurable True Random Number Generators Based on Spin-Orbit Torque Magnetic Tunnel Junctions.

The incorporation of randomness into stochastic computing can provide ample opportunities for applications such as simulated annealing, non-polynomial hard problem solving, and Bayesian neuron networks. In these cases, a considerable number of random numbers with an accurate and configurable probability distribution function (PDF) are indispensable. Preferably, these random numbers are provided at the hardware level to improve speed, efficiency, and parallelism. In this paper, how spin-orbit torque magnetic tunnel junctions (SOT-MTJs) with high barriers are suitable candidates for the desired true random number generators is demonstrated. Not only do these SOT-MTJs perform excellently in speed and endurance, but their randomness can also be conveniently and precisely controlled by a writing voltage, which makes them a well-performed Bernoulli bit. By utilizing these SOT-MTJ-based Bernoulli bits, any PDF, including Gaussian, uniform, exponential, Chi-square, and even arbitrarily defined distributions can be realized. These PDF-configurable true random number generators can then promise to advance the development of stochastic computing and broaden the applications of the SOT-MTJs.

Wearable fiber-free optical sensor for continuous monitoring of neonatal cerebral blood flow and oxygenation.

BACKGROUND: Unstable cerebral hemodynamics places preterm infants at high risk of brain injury. We adapted an innovative, fiber-free, wearable diffuse speckle contrast flow-oximetry (DSCFO) device for continuous monitoring of both cerebral blood flow (CBF) and oxygenation in neonatal piglets and preterm infants. METHODS: DSCFO uses two small laser diodes as focused-point and a tiny CMOS camera as a high-density two-dimensional detector to detect spontaneous spatial fluctuation of diffuse laser speckles for CBF measurement, and light intensity attenuations for cerebral oxygenation measurement. The DSCFO was first validated against the established diffuse correlation spectroscopy (DCS) in neonatal piglets and then utilized for continuous CBF and oxygenation monitoring in preterm infants during intermittent hypoxemia (IH) events. RESULTS: Significant correlations between the DSCFO and DCS measurements of CBF variations in neonatal piglets were observed. IH events induced fluctuations in CBF, cerebral oxygenation, and peripheral cardiorespiratory vitals in preterm infants. However, no consistent correlation patterns were observed among peripheral and cerebral monitoring parameters. CONCLUSIONS: This pilot study demonstrated the feasibility of DSCFO technology to serve as a low-cost wearable sensor for continuous monitoring of multiple cerebral hemodynamic parameters. The results suggested the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations. IMPACT: The innovative DSCFO technology may serve as a low-cost wearable sensor for continuous bedside monitoring of multiple cerebral hemodynamic parameters in neonatal intensive care units. Concurrent DSCFO and DCS measurements of CBF variations in neonatal piglet models generated consistent results. No consistent correlation patterns were observed among peripheral and cerebral monitoring parameters in preterm neonates, suggesting the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations during IH events. Integrating and correlating multiple cerebral functional parameters with clinical outcomes may identify biomarkers for prediction and management of IH associated brain injury.