Rapid Time Scale Research Articles

Unusually Slow Spike Frequency Adaptation in Deep Cerebellar Nuclei Neurons Preserves Linear Transformations on the Subsecond Timescale.

Purkinje cells (PCs) are spontaneously active neurons of the cerebellar cortex that inhibit glutamatergic projection neurons within the deep cerebellar nuclei (DCN) that provide the primary cerebellar output. Brief reductions of PC firing rapidly increase DCN neuron firing. However, prolonged reductions of PC inhibition, as seen in some disease states, certain types of transgenic mice, during optogenetic suppression of PC firing, and in acute slices of the cerebellum, do not lead to large, sustained increases in DCN firing. Here we test whether DCN neurons undergo spike frequency adaptation that could account for these properties. We perform current-clamp recordings at near physiological temperature in acute brain slices from mice of both sexes to examine how DCN neurons respond to prolonged depolarizations. DCN neuron adaptation is exceptionally slow and bidirectional. A depolarizing current step evokes large initial increases in firing that decay to ∼20% of the initial increase within ∼10 s. We find that spike frequency adaptation in DCN neurons is mediated by a novel mechanism that is independent of the most promising candidates, including calcium entry and Na+-activated potassium channels mediated by Slo2.1 and Slo2.2 Slow adaptation allows DCN neurons to gradually and bidirectionally adapt to prolonged currents but to respond linearly to current injection on rapid timescales. This suggests that an important consequence of slow adaptation is that DCN neurons respond linearly to the rate of PC firing on rapid timescales but adapt to slow firing rate changes of PCs on long timescales.SIGNIFICANCE STATEMENT Excitatory neurons in the cerebellar nuclei provide the primary output from the cerebellum. This study finds that these neurons exhibit very slow bidirectional spike frequency adaptation that has important implications for cerebellar function. This mechanism allows neurons in the cerebellar nuclei to adapt to long-lasting changes in synaptic drive while also remaining responsive to short-term changes in excitatory or inhibitory drive.

Dwarf AGNs from Optical Variability for the Origins of Seeds (DAVOS): insights from the dark energy survey deep fields

ABSTRACT We present a sample of 706, z < 1.5 active galactic nuclei (AGNs) selected from optical photometric variability in three of the Dark Energy Survey (DES) deep fields (E2, C3, and X3) over an area of 4.64 deg2. We construct light curves using difference imaging aperture photometry for resolved sources and non-difference imaging PSF photometry for unresolved sources, respectively, and characterize the variability significance. Our DES light curves have a mean cadence of 7 d, a 6-yr baseline, and a single-epoch imaging depth of up to g ∼ 24.5. Using spectral energy distribution (SED) fitting, we find 26 out of total 706 variable galaxies are consistent with dwarf galaxies with a reliable stellar mass estimate ($M_{\ast }\lt 10^{9.5}\, {\rm M}_\odot$; median photometric redshift of 0.9). We were able to constrain rapid characteristic variability time-scales (∼ weeks) using the DES light curves in 15 dwarf AGN candidates (a subset of our variable AGN candidates) at a median photometric redshift of 0.4. This rapid variability is consistent with their low black hole (BH) masses. We confirm the low-mass AGN nature of one source with a high S/N optical spectrum. We publish our catalogue, optical light curves, and supplementary data, such as X-ray properties and optical spectra, when available. We measure a variable AGN fraction versus stellar mass and compare to results from a forward model. This work demonstrates the feasibility of optical variability to identify AGNs with lower BH masses in deep fields, which may be more ‘pristine’ analogues of supermassive BH seeds.

Remembering the pattern: A longitudinal case study on statistical learning in spatial navigation and memory consolidation

Distinct brain systems are thought to support statistical learning over different timescales. Regularities encountered during online perceptual experience can be acquired rapidly by the hippocampus. Further processing during offline consolidation can establish these regularities gradually in cortical regions, including the medial prefrontal cortex (mPFC). These mechanisms of statistical learning may be critical during spatial navigation, for which knowledge of the structure of an environment can facilitate future behavior. Rapid acquisition and prolonged retention of regularities have been investigated in isolation, but how they interact in the context of spatial navigation is unknown. We had the rare opportunity to study the brain systems underlying both rapid and gradual timescales of statistical learning using intracranial electroencephalography (iEEG) longitudinally in the same patient over a period of three weeks. As hypothesized, spatial patterns were represented in the hippocampus but not mPFC for up to one week after statistical learning and then represented in the mPFC but not hippocampus two and three weeks after statistical learning. Taken together, these findings suggest that the hippocampus may contribute to the initial extraction of regularities prior to cortical consolidation.

The ALPINE–ALMA [C ii] Survey: The Infrared–Radio Correlation and Active Galactic Nucleus Fraction of Star-forming Galaxies at z ∼ 4.4–5.9

We present the radio properties of 66 spectroscopically confirmed normal star-forming galaxies (SFGs) at 4.4 < z < 5.9 in the COSMOS field that were [C ii]-detected in the Atacama Large Millimeter/submillimeter Array Large Program to INvestigate [C ii] at Early times (ALPINE). We separate these galaxies (“C ii-detected-all”) into lower-redshift (“C ii-detected-lz”; 〈z〉 = 4.5) and higher-redshift (“C ii-detected-hz”; 〈z〉 = 5.6) subsamples, and stack multiwavelength imaging for each subsample from X-ray to radio bands. A radio signal is detected in the stacked 3 GHz images of the C ii-detected-all and lz samples at ≳3σ. We find that the infrared–radio correlation of our sample, quantified by q TIR, is lower than the local relation for normal SFGs at a ∼3σ significance level, and is instead broadly consistent with that of bright submillimeter galaxies at 2 < z < 5. Neither of these samples show evidence of dominant active galactic nucleus activity in their stacked spectral energy distributions (SEDs), UV spectra, or stacked X-ray images. Although we cannot rule out the possible effects of the assumed spectral index and applied infrared SED templates in causing these differences, at least partially, the lower obscured fraction of star formation than at lower redshift can alleviate the tension between our stacked q TIRs and those of local normal SFGs. It is possible that the dust buildup, which primarily governs the infrared emission, in addition to older stellar populations, has not had enough time to occur fully in these galaxies, whereas the radio emission can respond on a more rapid timescale. Therefore, we might expect a lower q TIR to be a general property of high-redshift SFGs.

Advancing High-Resolution Imaging of Virus Assemblies in Liquid and Ice.

Interest in liquid-electron microscopy (liquid-EM) has skyrocketed in recent years as scientists can now observe real-time processes at the nanoscale. It is extremely desirable to pair high-resolution cryo-EM information with dynamic observations as many events occur at rapid timescales - in the millisecond range or faster. Improved knowledge of flexible structures can also assist in the design of novel reagents to combat emerging pathogens, such as SARS-CoV-2. More importantly, viewing biological materials in a fluid environment provides a unique glimpse of their performance in the human body. Presented here are newly developed methods to investigate the nanoscale properties of virus assemblies in liquid and vitreous ice. To accomplish this goal, well-defined samples were used as model systems. Side-by-side comparisons of sample preparation methods and representative structural information are presented. Sub-nanometer features are shown for structures resolved in the range of ~3.5-Å-10 Å. Other recent results that support this complementary framework include dynamic insights of vaccine candidates and antibody-based therapies imaged in liquid. Overall, these correlative applications advance our ability to visualize molecular dynamics, providing a unique context for their use in human health and disease.

Nanopore Analysis as a Tool for Studying Rapid Holliday Junction Dynamics and Analyte Binding.

Holliday junctions (HJs) are an important class of nucleic acid structure utilized in DNA break repair processes. As such, these structures have great importance as therapeutic targets and for understanding the onset and development of various diseases. Single-molecule fluorescence resonance energy transfer (smFRET) has been used to study HJ structure-fluctuation kinetics, but given the rapid time scales associated with these kinetics (approximately sub-milliseconds) and the limited bandwidth of smFRET, these studies typically require one to slow down the structure fluctuations using divalent ions (e.g., Mg2+). This modification limits the ability to understand and model the underlying kinetics associated with HJ fluctuations. We address this here by utilizing nanopore sensing in a gating configuration to monitor DNA structure fluctuations without divalent ions. A nanopore analysis shows that HJ fluctuations occur on the order of 0.1-10 ms and that the HJ remains locked in a single conformation with short-lived transitions to a second conformation. It is not clear what role the nanopore plays in affecting these kinetics, but the time scales observed indicate that HJs are capable of undergoing rapid transitions that are not detectable with lower bandwidth measurement techniques. In addition to monitoring rapid HJ fluctuations, we also report on the use of nanopore sensing to develop a highly selective sensor capable of clear and rapid detection of short oligo DNA strands that bind to various HJ targets.

Beyond sex and aggression: testosterone rapidly matches behavioural responses to social context and tries to predict the future.

Although androgens are widely studied in the context of aggression, androgenic influences on prosocial behaviours have been less explored. We examined testosterone's (T) influence on prosocial and aggressive responses in a positively valenced social context (interacting with a pairbond partner) and a negatively valenced context (interacting with an intruder) in socially monogamous Mongolian gerbils. T increased and decreased prosocial responses in the same individuals towards a pairbond partner and an intruder, respectively, both within 30 min, but did not affect aggression. T also had persistent effects on prosocial behaviour; males in which T initially increased prosocial responses towards a partner continued to exhibit elevated prosocial responses towards an intruder male days later until a second T injection rapidly eliminated those responses. Thus, T surges can rapidly match behaviour to current social context, as well as prime animals for positive social interactions in the future. Neuroanatomically, T rapidly increased hypothalamic oxytocin, but not vasopressin, cellular responses during interactions with a partner. Together, our results indicate that T can facilitate and inhibit prosocial behaviours depending on social context, that it can influence prosocial responses across rapid and prolonged time scales, and that it affects oxytocin signalling mechanisms that could mediate its context-dependent behavioural influences.

APPsα Rescues Tau-Induced Synaptic Pathology.

Alzheimer's disease (AD) is histopathologically characterized by Aβ plaques and the accumulation of hyperphosphorylated Tau species, the latter also constituting key hallmarks of primary tauopathies. Whereas Aβ is produced by amyloidogenic APP processing, APP processing along the competing nonamyloidogenic pathway results in the secretion of neurotrophic and synaptotrophic APPsα. Recently, we demonstrated that APPsα has therapeutic effects in transgenic AD model mice and rescues Aβ-dependent impairments. Here, we examined the potential of APPsα to mitigate Tau-induced synaptic deficits in P301S mice (both sexes), a widely used mouse model of tauopathy. Analysis of synaptic plasticity revealed an aberrantly increased LTP in P301S mice that could be normalized by acute application of nanomolar amounts of APPsα to hippocampal slices, indicating a homeostatic function of APPsα on a rapid time scale. Further, AAV-mediated in vivo expression of APPsα restored normal spine density of CA1 neurons even at stages of advanced Tau pathology not only in P301S mice, but also in independent THY-Tau22 mice. Strikingly, when searching for the mechanism underlying aberrantly increased LTP in P301S mice, we identified an early and progressive loss of major GABAergic interneuron subtypes in the hippocampus of P301S mice, which may lead to reduced GABAergic inhibition of principal cells. Interneuron loss was paralleled by deficits in nest building, an innate behavior highly sensitive to hippocampal impairments. Together, our findings indicate that APPsα has therapeutic potential for Tau-mediated synaptic dysfunction and suggest that loss of interneurons leads to disturbed neuronal circuits that compromise synaptic plasticity as well as behavior.SIGNIFICANCE STATEMENT Our findings indicate, for the first time, that APPsα has the potential to rescue Tau-induced spine loss and abnormal synaptic plasticity. Thus, APPsα might have therapeutic potential not only because of its synaptotrophic functions, but also its homeostatic capacity for neuronal network activity. Hence, APPsα is one of the few molecules which has proven therapeutic effects in mice, both for Aβ- and Tau-dependent synaptic impairments and might therefore have therapeutic potential for patients suffering from AD or primary tauopathies. Furthermore, we found in P301S mice a pronounced reduction of inhibitory interneurons as the earliest pathologic event preceding the accumulation of hyperphosphorylated Tau species. This loss of interneurons most likely disturbs neuronal circuits that are important for synaptic plasticity and behavior.

Alignment of fractures on Bennu’s boulders indicative of rapid asteroid surface evolution

On asteroids, fractures develop due to stresses driven by diurnal temperature variations at spatial scales ranging from sub-millimetres to metres. However, the timescales of such rock fracturing by thermal fatigue are poorly constrained by observations. Here we analyse images of the asteroid (101955) Bennu obtained by the Origins, Spectral Interpretation, Resource Identification and Security-Regolith Explorer (OSIRIS-REx) mission and show that metre-scale fractures on the boulders exposed at the surface have a preferential meridional orientation, consistent with cracking induced by diurnal temperature variations. Using an analytical model of fracture propagation, we suggest that fractures the length of those on Bennu’s boulders can be produced in 104–105 years. This is a comparable or shorter timescale than mass movement processes that act to expose fresh surfaces and reorient boulders and any preferential direction signature. We propose that boulder surface fracturing happens rapidly compared with the lifetime in near-Earth space of Bennu and other carbonaceous asteroids. The damage due to this space-weathering process has consequences for the material properties of these asteroids, with implications for the preservation of the primordial signature acquired during the accretional phases in the protoplanetary disk of our solar system. Fractures on the asteroid Bennu imaged by the OSIRIS-REx spacecraft are consistent with cracking induced by diurnal temperature variations over geologically rapid timescales.

Assessment and improvement of k-ω-γ model for separation-induced transition prediction

The purpose of this work is to improve the k-ω-γ transition model for separation-induced transition prediction. The fundamental cause of the excessively small separation bubble predicted by k-ω-γ model is scrutinized from the perspective of model construction. On the basis, three rectifications are conducted to improve the k-ω-γ model for separation-induced transition. Firstly, a damping function is established via comparing the molecular diffusion timescale with the rapid pressure-strain timescale. The damping function is applied to prevent the effective length scale from incorrect distribution near the leading edge of the separation bubble. Secondly, the pressure gradient parameter λζ, is proposed as an indicator for local susceptibility to the separation instability. Additionally, λζ,-based separation intermittency γsep is constructed to accelerate the substantial growth of turbulent kinetic energy after flow separation. The improved model appropriate for both low- and high-speed flow has been calibrated against a variety of diverse and challenging experiments, including the subsonic T3L plate, Aerospatial A airfoil, transonic NLR-7301 airfoil and deformed hypersonic inflatable aerodynamic decelerator aeroshell. The improved model is strictly based on local variables and Galilean invariance. Besides, the proposed improvement for k-ω-γ model can be fairly convenient to incorporate into other existing intermittency-based transition models.

High-Throughput Measurement and Machine Learning-Based Prediction of Collision Cross Sections for Drugs and Drug Metabolites.

Drug metabolite identification is a bottleneck of drug metabolism studies due to the need for time-consuming chromatographic separation and structural confirmation. Ion mobility-mass spectrometry (IM-MS), on the other hand, separates analytes on a rapid (millisecond) time scale and enables the measurement of collision cross section (CCS), a unique physical property related to an ion's gas-phase size and shape, which can be used as an additional parameter for identification of unknowns. A current limitation to the application of IM-MS to the identification of drug metabolites is the lack of reference CCS values. In this work, we assembled a large-scale database of drug and drug metabolite CCS values using high-throughput in vitro drug metabolite generation and a rapid IM-MS analysis with automated data processing. Subsequently, we used this database to train a machine learning-based CCS prediction model, employing a combination of conventional 2D molecular descriptors and novel 3D descriptors, achieving high prediction accuracies (0.8-2.2% median relative error on test set data). The inclusion of 3D information in the prediction model enables the prediction of different CCS values for different protomers, conformers, and positional isomers, which is not possible using conventional 2D descriptors. The prediction models, dmCCS, are available at https://CCSbase.net/dmccs_predictions.

Valproic Acid Reduces Neuroinflammation to Provide Retinal Ganglion Cell Neuroprotection in the Retina Axotomy Model.

Neuroinflammation is a critical and targetable pathogenic component of neurodegenerative diseases, including glaucoma, the leading cause of irreversible blindness. Valproic acid has previously been demonstrated to reduce neuroinflammation and is neuroprotective in a number of experimental settings. To determine whether valproic acid can limit retinal neuroinflammation and protect retinal neurons we used an ex vivo retina explant (axotomy) model to isolate resident glial responses from blood-derived monocytes. Neuroinflammatory status was defined using high resolution confocal imaging with 3D morphological reconstruction and cytokine protein arrays. Valproic acid significantly reduced microglia and astrocyte morphological changes, consistent with a reduction in pro-inflammatory phenotypes. Cytokine profiling demonstrated that valproic acid significantly attenuated or prevented expression of pro-inflammatory cytokines in injured retina. This identifies that the retinal explant model as a useful tool to explore resident neuroinflammation in a rapid timescale whilst maintaining a complex system of cell interactions and valproic acid as a useful drug to further explore anti-neuroinflammatory strategies in retinal disease.

Cross-Frequency Brain Network Dynamics Support Pitch Change Detection.

Processing auditory sequences involves multiple brain networks and is crucial to complex perception associated with music appreciation and speech comprehension. We used time-resolved cortical imaging in a pitch change detection task to detail the underlying nature of human brain network activity, at the rapid time scales of neurophysiology. In response to tone sequence presentation to the participants, we observed slow inter-regional signaling at the pace of tone presentations (2-4 Hz) that was directed from auditory cortex toward both inferior frontal and motor cortices. Symmetrically, motor cortex manifested directed influence onto auditory and inferior frontal cortices via bursts of faster (15-35 Hz) activity. These bursts occurred precisely at the expected latencies of each tone in a sequence. This expression of interdependency between slow/fast neurophysiological activity yielded a form of local cross-frequency phase-amplitude coupling in auditory cortex, which strength varied dynamically and peaked when pitch changes were anticipated. We clarified the mechanistic relevance of these observations in relation to behavior by including a group of individuals afflicted by congenital amusia, as a model of altered function in processing sound sequences. In amusia, we found a depression of inter-regional slow signaling toward motor and inferior frontal cortices, and a chronic overexpression of slow/fast phase-amplitude coupling in auditory cortex. These observations are compatible with a misalignment between the respective neurophysiological mechanisms of stimulus encoding and internal predictive signaling, which was absent in controls. In summary, our study provides a functional and mechanistic account of neurophysiological activity for predictive, sequential timing of auditory inputs.SIGNIFICANCE STATEMENT Auditory sequences are processed by extensive brain networks, involving multiple systems. In particular, fronto-temporal brain connections participate in the encoding of sequential auditory events, but so far, their study was limited to static depictions. This study details the nature of oscillatory brain activity involved in these inter-regional interactions in human participants. It demonstrates how directed, polyrhythmic oscillatory interactions between auditory and motor cortical regions provide a functional account for predictive timing of incoming items in an auditory sequence. In addition, we show the functional relevance of these observations in relation to behavior, with data from both normal hearing participants and a rare cohort of individuals afflicted by congenital amusia, which we considered here as a model of altered function in processing sound sequences.

Temporal variations in the composition of Cretaceous Cordilleran arc volcanism through a high-frequency record of bentonites

Continental arc volcanism generates a wide diversity of magma compositions, but the tempos of compositional variation are unclear. Here, we investigate a 7-million year record of volcanic ash layers in the Cretaceous Eagle Ford Group, which was deposited in the Western Interior Seaway in western North America. Low oxygen conditions prevented significant bioturbation, allowing for the preservation of hundreds of thin volcanic ash layers in the form of bentonites. A drill core with an established high-resolution age model provides an opportunity to investigate temporal changes in ash composition on <100 kyr timescales. Because of intense alteration during diagenesis, ash protolith compositions were reconstructed from Ti/Zr. We first show that Ti and Zr had limited mobility during diagenesis. We then show, based on a compilation of data from unaltered volcanic rocks from six continental arcs, that the relationship between Ti/Zr and SiO2 is similar across continental arcs from different times and geographic locations, confirming that Ti/Zr is a robust differentiation index and indirect measure of SiO2. Applying an empirical Ti/Zr-SiO2 relationship to Ti/Zr measurements of 52 Eagle Ford bentonites allowed for reconstruction of ash protolith SiO2. Ash compositions vary from basalt/basaltic andesite to dacite/rhyolite, but the variations are not random. Ash compositions fluctuate between periods of high silica (>60 wt. % SiO2) and low silica (<60 wt. %) volcanism over ∼100 kyr timescales. If the temporal variability of these ashes represents broad snapshots of the Cordilleran continental arc, these results suggest that continental arc systems may undergo episodic changes in the extent of magmatic differentiation or the nature of eruption on rapid (<100 kyr) timescales.

Constraining the timescales of mafic magmatism of the Central Karoo Large Igneous Province using high precision U-Pb zircon geochronology

AbstractRecent U-Pb high-precision geochronological studies have shown rapid emplacement of the intrusive doleritic component of the Karoo Large Igneous Province (KLIP) in Southern Africa. However, these studies focused on a relatively small geographic and altitudinal region of the KLIP. Additionally, the timing of initiation of extrusive volcanism, preserved in the Drakensberg-Lesotho highlands and its relationship to the intrusive suite, has only been imprecisely constrained by Ar-Ar dates. Here, we present new high-resolution U-Pb zircon ages on dolerite sills and dykes from across the central eastern Karoo Basin (South Africa) at elevations between mean sea level and 1 560 m, as well as U-Pb detrital zircon data that can be used to estimate the maximum age of volcaniclastic deposition near the base of the extrusive component of the KLIP. Dolerite samples were taken across two areas: (1) thick dykes exposed along the coast of the Indian Ocean to ~1 600 m flanking the Drakensberg Escarpment in the Eastern Cape; and (2) sills between 20 and 220 m below surface, in a borehole core within the interior of the Karoo Basin, 400 km hinterland from the coastline. Our estimated dolerite emplacement ages span a range of ca. 80 thousand years (Kyr), between 183.122 ± 0.029/-0.061 and 183.042 ± 0.042/-0.072 million years ago (Ma), and fall within the 331 +60/-54 Kyr age range previously established for magmatism related to the KLIP, despite the marked increase in sampling coverage in terms of area and altitude in this study. Therefore, KLIP geochronology is consistent with other LIPS such as the Siberian and Deccan Traps that supports the hypothesis of rapid emplacement timescales (&amp;lt;1 Myr). Additionally, these data are consistent with, but better delineate that the KLIP in southern Africa appears to be ca. 500 Kyr older than the main phase of magmatism in the Ferrar LIP of Antarctica. Detrital zircons from the basal volcanic sequence of the Drakensberg Group exhibit age peaks at ca. 1 and 0.5 Ga, typical of the surrounding Namaqua-Natal and Pan-African basement rocks, as well as younger peaks at ca. 260 and 200 Ma that likely relate to source provenances from south-western Gondwana and reworking of the Karoo Supergroup sedimentary rocks. High-precision U-Pb dates of the youngest zircon grains result in a maximum depositional age for the basal pyroclastics of 185.25 ± 0.25 Ma, allowing for a ca. 2 Myr offset with the intrusive Karoo dolerite suite.

Acceleration and cooling of the corona during X-ray flares from the Seyfert galaxy I Zw 1

ABSTRACTWe report on X-ray flares that were observed from the active galactic nucleus I Zwicky 1 (I Zw 1) in 2020 January by the NuSTAR and XMM-Newton observatories. The X-ray spectrum is well-described by a model comprised of the continuum emission from the corona and its reflection from the accretion disc around a rapidly spinning (a &amp;gt; 0.94) black hole. In order to model the broadband spectrum, it is necessary to account for the variation in ionization across the disc. Analysis of the X-ray spectrum in time periods before, during and after the flares reveals the underlying changes to the corona associated with the flaring. During the flares, the reflection fraction drops significantly, consistent with the acceleration of the corona away from the accretion disc. We find the first evidence that during the X-ray flares, the temperature drops from $140_{-20}^{+100}$ keV before to $45_{-9}^{+40}$ keV during the flares. The profile of the iron K line reveals the emissivity profile of the accretion disc, showing it to be illuminated by a compact corona extending no more than $7_{-2}^{+4}$ rg over the disc before the flares, but with tentative evidence that the corona expands as it is accelerated during the flares. Once the flares subsided, the corona had collapsed to a radius of $6_{-2}^{+2}$ rg. The rapid time-scale of the flares suggests that they arise within the black hole magnetosphere rather than in the accretion disc, and the variation of the corona is consistent with the continuum arising from the Comptonization of seed photons from the disc.

Metal (hydr)oxide surface precipitates and their effects on potassium sorption.

Surface precipitation has been shown to occur on rapid time scales in clay and metal oxide mineral systems. The formation of surface precipitates is hypothesized to present new potential sorption sites for potassium (K), where K can become incorporated into newly formed interlayer spaces (e.g., between tetrahedral-octahedral-tetrahedral stacked sheets). The objective of this study is to determine the effects of newly formed mineral surface precipitates on K sorption. Potassium adsorption experiments were conducted by utilizing Al2O3 and SiO2 sorbents in the presence of various cations (magnesium, zinc, and nickel) that helped to catalyze the formation of surface precipitates. Dissolved concentrations of elements were monitored via inductively coupled plasma optical emission spectrometry (ICP-OES). Solids were characterized via X-ray diffraction (XRD), and K surface complexation was analyzed via X-ray absorption near edge structure (XANES) spectroscopy. X-ray diffraction analysis indicated bayerite, layered double hydroxides (LDH), and silicated LDH were formed as reaction products, thus creating new surface sites for potential K adsorption. The presence of Si increased K adsorption perhaps due to its role in the formation of LDH surface precipitates. When the differences between observed and theoretical surface area normalized K sorption densities were averaged, a 31% increase in K adsorption was observed in the presence of Si. XANES analysis indicated that the binding mechanism of K to Si is different than that of K to Al, perhaps due to the presence of inner-sphere complexation of K to Al-oxide. Samples reacted for one month versus one week yielded more intense XANES post-edge peaks which indicated that the K sorption complex changes over time. Overall, our findings provide novel insights into the mechanisms of K fixation in soil and has high implication in providing improved K fertilizer recommendation to growers.

Single-Molecular Quantification of Flowering Control Proteins Within Nuclear Condensates in Live Whole Arabidopsis Root.

Here we describe the coupled standardization of two complementary fluorescence imaging techniques and apply it to liquid-liquid phase-separated condensates formed from an EGFP fluorescent reporter of flowering control locus A (FCA), a protein that associates with chromosomal DNA in plants during epigenetic regulation of the flowering process. First, we use home-built single-molecule Slimfield microscopy to establish a fluorescent protein standard. This sample comprises live yeast cells expressing Mig1 protein, a metabolic regulator which localizes to the nucleus under conditions of high glucose, fused to the same type of EGFP label as for the FCA fusion construct. Then we employ commercial confocal AiryScan microscopy to study the same standard. Finally, we demonstrate how to quantify FCA-EGFP nuclear condensates in intact root tips at rapid timescales and apply this calibration. This method is a valuable approach to obtaining single-molecule precise stoichiometry and copy number estimates of protein condensates that are integrated into the chromosome architecture of plants, using confocal instrumentation that lacks de facto single-molecule detection sensitivity.

Evidence for a compact object in the aftermath of the extragalactic transient AT2018cow

The brightest fast blue optical transients (FBOTs) are mysterious extragalactic explosions that may represent a new astrophysical phenomenon1. Their fast time to maximum brightness of less than a week, decline over several months, and atypical optical spectra and evolution are difficult to explain within the context of the core collapse of massive stars, which are powered by radioactive decay of 56Ni and evolve more slowly2,3. AT2018cow (at a redshift of 0.014) is an extreme FBOT in terms of rapid evolution and high luminosity4–7. Here we present evidence for a high-amplitude quasiperiodic oscillation of AT2018cow’s soft X-rays with a frequency of 224 Hz (at a 3.7σ significance level or false alarm probability of 0.02%) and fractional root-mean-squared amplitude of >30%. This signal is found in the average power density spectrum taken over the entire 60-day outburst and suggests a highly persistent signal that lasts for a billion cycles. The high frequency (rapid timescale) of 224 Hz (4.4 ms) argues for a compact object in AT2018cow, which could be a neutron star or black hole with a mass less than 850 solar masses. If the quasiperiodic oscillation is equivalent to the spin period of a neutron star, we can set limits on the star’s magnetic field strength. Our work highlights a new way of using high-time-resolution X-ray observations to study FBOTs. A high-frequency quasiperiodic oscillation in the soft X-rays from unusual transient AT2018cow points towards the presence of a compact object in the remnant: either a neutron star with spin period of 4 ms or a low-mass black hole.

Resolving catastrophic error bursts from cosmic rays in large arrays of superconducting qubits

Scalable quantum computing can become a reality with error correction, provided coherent qubits can be constructed in large arrays. The key premise is that physical errors can remain both small and sufficiently uncorrelated as devices scale, so that logical error rates can be exponentially suppressed. However, energetic impacts from cosmic rays and latent radioactivity violate both of these assumptions. An impinging particle ionizes the substrate, radiating high energy phonons that induce a burst of quasiparticles, destroying qubit coherence throughout the device. High-energy radiation has been identified as a source of error in pilot superconducting quantum devices, but lacking a measurement technique able to resolve a single event in detail, the effect on large scale algorithms and error correction in particular remains an open question. Elucidating the physics involved requires operating large numbers of qubits at the same rapid timescales as in error correction, exposing the event's evolution in time and spread in space. Here, we directly observe high-energy rays impacting a large-scale quantum processor. We introduce a rapid space and time-multiplexed measurement method and identify large bursts of quasiparticles that simultaneously and severely limit the energy coherence of all qubits, causing chip-wide failure. We track the events from their initial localised impact to high error rates across the chip. Our results provide direct insights into the scale and dynamics of these damaging error bursts in large-scale devices, and highlight the necessity of mitigation to enable quantum computing to scale.