Retinomorphic Motion Detector Fabricated with Organic Infrared Semiconductors

Organic retinomorphic sensors offer the advantage of in-sensor processing to filter out redundant static backgrounds and are well suited for motion detection. To improve this promising structure, here, the key role of interfacial energetics in promoting charge accumulation to raise the inherent photoresponse of the light-sensitive capacitor is studied. Specifically, incorporating appropriate interfacial layers around the photoactive layer is crucial to extend the carrier lifetime, as confirmed by intensity-modulated photovoltage spectroscopy. Compared to its photodiode counterpart, the retinomorphic sensor shows better detectivity and response speed due to the additional insulating layer, which reduces the dark current and the RC time constant. Lastly, three retinomorphic sensors are integrated into a line array to demonstrate the detection of movement speed and direction, showing the potential of retinomorphic designs for efficient motion tracking.

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

Proposed three-phenylalanine motif involved in magnetoreception signalling of an Actinopterygii protein expressed in mammalian cells

Studies at the cellular and molecular level of magnetoreception-sensing and responding to magnetic fields-are a relatively new research area. It appears that different mechanisms of magnetoreception in animals evolved from different origins, and, therefore, many questions about its mechanisms remain left open. Here we present new information regarding the Electromagnetic Perceptive Gene (EPG) from Kryptopterus vitreolus that may serve as part of the foundation to understanding and applying magnetoreception. Using HaloTag coupled with fluorescent ligands and phosphatidylinositol specific phospholipase C we show that EPG is associated with the membrane via glycosylphosphatidylinositol anchor. EPG's function of increasing intracellular calcium was also used to generate an assay using GCaMP6m to observe the function of EPG and to compare its function with that of homologous proteins. It was also revealed that EPG relies on a motif of three phenylalanine residues to function-stably swapping these residues using site directed mutagenesis resulted in a loss of function in EPG. This information not only expands upon our current understanding of magnetoreception but may provide a foundation and template to continue characterizing and discovering more within the emerging field.

Assembly archetypes in ecological communities

An instrumental discovery in comparative and developmental biology is the existence of assembly archetypes that synthesize the vast diversity of organisms' body plans-from legs and wings to human arms-into simple, interpretable and general design principles. Here, we combine a novel mathematical formalism based on category theory with experimental data to show that similar 'assembly archetypes' exist at the larger organization scale of ecological communities when assembling a species pool across diverse environmental contexts, particularly when species interactions are highly structured. We applied our formalism to clinical data discovering two assembly archetypes that differentiate between healthy and unhealthy human gut microbiota. The concept of assembly archetypes and the methods to synthesize them can pave the way to discovering the general assembly principles of the ecological communities we observe in nature.

Robust evidence for bats as reservoir hosts is lacking in most African virus studies: a review and call to optimize sampling and conserve bats

Africa experiences frequent emerging disease outbreaks among humans, with bats often proposed as zoonotic pathogen hosts. We comprehensively reviewed virus-bat findings from papers published between 1978 and 2020 to evaluate the evidence that African bats are reservoir and/or bridging hosts for viruses that cause human disease. We present data from 162 papers (of 1322) with original findings on (1) numbers and species of bats sampled across bat families and the continent, (2) how bats were selected for study inclusion, (3) if bats were terminally sampled, (4) what types of ecological data, if any, were recorded and (5) which viruses were detected and with what methodology. We propose a scheme for evaluating presumed virus-host relationships by evidence type and quality, using the contrasting available evidence for Orthoebolavirus versus Orthomarburgvirus as an example. We review the wording in abstracts and discussions of all 162 papers, identifying key framing terms, how these refer to findings, and how they might contribute to people's beliefs about bats. We discuss the impact of scientific research communication on public perception and emphasize the need for strategies that minimize human-bat conflict and support bat conservation. Finally, we make recommendations for best practices that will improve virological study metadata.

Quantifying the ultrafast and steady-state molecular reduction potential of a plasmonic photocatalyst

Plasmonic materials are promising photocatalysts as they are well suited to convert light into hot carriers and heat. Hot electron transfer is suggested as the driving force in many plasmon-driven reactions. However, to date, there are no direct molecular measures of the rate and yield of plasmon-to-molecule electron transfer or energy of these electrons on the timescale of plasmon decay. Here, we use ultrafast and spectroelectrochemical surface-enhanced Raman spectroscopy to quantify electron transfer from a plasmonic substrate to adsorbed methyl viologen molecules. We observe a reduction yield of 2.4 to 3.5% on the picosecond timescale, with plasmon-induced potentials ranging from [Formula: see text]3.1 to [Formula: see text]4.5 mV. Excitingly, some of these reduced species are stabilized and persist for tens of minutes. This work provides concrete metrics toward optimizing material-molecule interactions for efficient plasmon-driven photocatalysis.

Reinforcement-based processes actively regulate motor exploration along redundant solution manifolds

From a baby's babbling to a songbird practising a new tune, exploration is critical to motor learning. A hallmark of exploration is the emergence of random walk behaviour along solution manifolds, where successive motor actions are not independent but rather become serially dependent. Such exploratory random walk behaviour is ubiquitous across species' neural firing, gait patterns and reaching behaviour. The past work has suggested that exploratory random walk behaviour arises from an accumulation of movement variability and a lack of error-based corrections. Here, we test a fundamentally different idea-that reinforcement-based processes regulate random walk behaviour to promote continual motor exploration to maximize success. Across three human reaching experiments, we manipulated the size of both the visually displayed target and an unseen reward zone, as well as the probability of reinforcement feedback. Our empirical and modelling results parsimoniously support the notion that exploratory random walk behaviour emerges by utilizing knowledge of movement variability to update intended reach aim towards recently reinforced motor actions. This mechanism leads to active and continuous exploration of the solution manifold, currently thought by prominent theories to arise passively. The ability to continually explore muscle, joint and task redundant solution manifolds is beneficial while acting in uncertain environments, during motor development or when recovering from a neurological disorder to discover and learn new motor actions.

Signatures of adaptive decreased virulence of deformed wing virus in an isolated population of wild honeybees (Apis mellifera)

Understanding the ecological and evolutionary processes that drive host-pathogen interactions is critical for combating epidemics and conserving species. The Varroa destructor mite and deformed wing virus (DWV) are two synergistic threats to Western honeybee (Apis mellifera) populations across the globe. Distinct honeybee populations have been found to self-sustain despite Varroa infestations, including colonies within the Arnot Forest outside Ithaca, NY, USA. We hypothesized that in these bee populations, DWV has been selected to produce an avirulent infection phenotype, allowing for the persistence of both host and disease-causing agents. To investigate this, we assessed the titre of viruses in bees from the Arnot Forest and managed apiaries, and assessed genomic variation and virulence differences between DWV isolates. Across groups, we found viral abundance was similar, but DWV genotypes were distinct. We also found that infections with isolates from the Arnot Forest resulted in higher survival and lower rates of symptomatic deformed wings, compared to analogous isolates from managed colonies, providing preliminary evidence to support the hypothesis of adaptive decreased viral virulence. Overall, this multi-level investigation of virus genotype and phenotype indicates that host ecological context can be a significant driver of viral evolution and host-pathogen interactions in honeybees.

Examining indicators of complex network vulnerability across diverse attack scenarios

Complex networks capture the structure, dynamics, and relationships among entities in real-world networked systems, encompassing domains like communications, society, chemistry, biology, ecology, politics, etc. Analysis of complex networks lends insight into the critical nodes, key pathways, and potential points of failure that may impact the connectivity and operational integrity of the underlying system. In this work, we investigate the topological properties or indicators, such as shortest path length, modularity, efficiency, graph density, diameter, assortativity, and clustering coefficient, that determine the vulnerability to (or robustness against) diverse attack scenarios. Specifically, we examine how node- and link-based network growth or depletion based on specific attack criteria affect their robustness gauged in terms of the largest connected component (LCC) size and diameter. We employ partial least squares discriminant analysis to quantify the individual contribution of the indicators on LCC preservation while accounting for the collinearity stemming from the possible correlation between indicators. Our analysis of 14 complex network datasets and 5 attack models invariably reveals high modularity and disassortativity to be prime indicators of vulnerability, corroborating prior works that report disassortative modular networks to be particularly susceptible to targeted attacks. We conclude with a discussion as well as an illustrative example of the application of this work in fending off strategic attacks on critical infrastructures through models that adaptively and distributively achieve network robustness.

How contact can promote societal change amid conflict: An intergroup contact field experiment in Nigeria

Intergroup contact, originally designed as a tool for prejudice reduction, offers a promising means to resolve intergroup conflict. Evidence for contact-based interventions to improve intergroup relations is sparse, however, with most studies focusing only on the individuals who directly engage in contact. We test the ability of a contact-based intervention to promote peace between conflicting groups with a field experiment in Nigeria, where farmer and pastoralist communities are embroiled in a deadly conflict over land use. We examine the effectiveness of the contact intervention on the wider population-not just those directly engaged in contact-using surveys, direct observation of behavior in markets and social events, and a behavioral game. We find those who lived in the communities that received the intervention had more positive intergroup attitudes and feelings of physical security, as well as were more likely to engage in voluntary intergroup contact measured through self-reports and observed behavior in markets. Exploratory analyses show that those who directly participated in the program and those who were exposed to it by living in the communities where activities were taking place changed similarly with regard to attitudes and perceptions of security, but not with regard to behaviors, indicating the spread to the wider community was likely due to norm change. These results suggest that contact interventions can have wider societal change and reduce the barriers to peace between conflicting groups.

Vestiges of impact-driven three-phase mixing in the chemistry and structure of Earth's mantle

Highly siderophile elements (HSEs; namely Ru, Rh, Pd, Re, Os, Ir, Pt, and Au) in Earth's mantle require the addition of metals after the formation of Earth's core. Early, large collisions have the potential to deliver metals, but the details of their mixing with Earth's mantle remain unresolved. As a large projectile disrupts and penetrates Earth's mantle, a fraction of its metallic core may directly merge with Earth's core. Ensuing gravitational instabilities remove the remaining projectile's core stranded in Earth's mantle, leaving the latter deprived of HSEs. Here, we propose a framework that can efficiently retain the metallic components during large impacts. The mechanism is based on the ubiquitous presence of a partially molten region in the mantle beneath an impact-generated magma ocean, and it involves rapid three-phase flow with solid silicate, molten silicate, and liquid metal as well as long-term mixing by mantle convection. In addition, large low-shear-velocity provinces in the lower mantle may originate from compositional heterogeneities resulting from the proposed three-phase flow during high-energy collisions.

Bayesian group testing with dilution effects

A Bayesian framework for group testing under dilution effects has been developed, using lattice-based models. This work has particular relevance given the pressing public health need to enhance testing capacity for coronavirus disease 2019 and future pandemics, and the need for wide-scale and repeated testing for surveillance under constantly varying conditions. The proposed Bayesian approach allows for dilution effects in group testing and for general test response distributions beyond just binary outcomes. It is shown that even under strong dilution effects, an intuitive group testing selection rule that relies on the model order structure, referred to as the Bayesian halving algorithm, has attractive optimal convergence properties. Analogous look-ahead rules that can reduce the number of stages in classification by selecting several pooled tests at a time are proposed and evaluated as well. Group testing is demonstrated to provide great savings over individual testing in the number of tests needed, even for moderately high prevalence levels. However, there is a trade-off with higher number of testing stages, and increased variability. A web-based calculator is introduced to assist in weighing these factors and to guide decisions on when and how to pool under various conditions. High-performance distributed computing methods have also been implemented for considering larger pool sizes, when savings from group testing can be even more dramatic.

Strain-Induced Electronic Structure Modulation on MnO2 Nanosheet by Ir Incorporation for Efficient Water Oxidation in Acid

Oxygen electrochemistry plays a key role in renewable energy technologies, such as fuel cells and electrolyzers, but its slow kinetics limits the performance and the commercialization of such devices. Here, a strained MnO2 nanosheet induced by Ir incorporation is developed with optimized electronic structure by a simple hydrothermal method. With the incorporation of Ir, the strain induces elongated Mn─O bond length, and thereby tuning the electronic structure to favor the oxygen evolution reaction (OER) performance. The obtained catalyst exhibits an excellent mass activity of 5681 A g-1 at an overpotential of 300 mV in 0.5 m H2 SO4 , and reaches 50 and 100 mA cm-2 at overpotentials of only 240 and 277 mV, respectively. The catalyst is also stable even at 300 mA cm-2 in 0.5 m H2 SO4 . Using the nanosheet as the OER catalyst and the Pt/C as the hydrogen evolution reaction catalyst, a two-electrode electrolyzer achieves 10 mA cm-2 with only a cell voltage of 1.453 V for overall water splitting in 0.5 m H2 SO4 . This strategy enables the material with high feasibility for practical applications on hydrogen production.

Structure, dynamics and free energy studies on the effect of point mutations on SARS-CoV-2 spike protein binding with ACE2 receptor

The ongoing COVID-19 pandemic continues to infect people worldwide, and the virus continues to evolve in significant ways which can pose challenges to the efficiency of available vaccines and therapeutic drugs and cause future pandemic. Therefore, it is important to investigate the binding and interaction of ACE2 with different RBD variants. A comparative study using all-atom MD simulations was conducted on ACE2 binding with 8 different RBD variants, including N501Y, E484K, P479S, T478I, S477N, N439K, K417N and N501Y-E484K-K417N on RBD. Based on the RMSD, RMSF, and DSSP results, overall the binding of RBD variants with ACE2 is stable, and the secondary structure of RBD and ACE2 are consistent after the point mutation. Besides that, a similar buried surface area, a consistent binding interface and a similar amount of hydrogen bonds formed between RBD and ACE2 although the exact residue pairs on the binding interface were modified. The change of binding free energy from point mutation was predicted using the free energy perturbation (FEP) method. It is found that N501Y, N439K, and K417N can strengthen the binding of RBD with ACE2, while E484K and P479S weaken the binding, and S477N and T478I have negligible effect on the binding. Point mutations modified the dynamic correlation of residues in RBD based on the dihedral angle covariance matrix calculation. Doing dynamic network analysis, a common intrinsic network community extending from the tail of RBD to central, then to the binding interface region was found, which could communicate the dynamics in the binding interface region to the tail thus to the other sections of S protein. The result can supply unique methodology and molecular insight on studying the molecular structure and dynamics of possible future pandemics and design novel drugs.

Global trade network patterns are coupled to fisheries sustainability

The rapid development of seafood trade networks alongside the decline in biomass of many marine populations raises important questions about the role of global trade in fisheries sustainability. Mounting empirical and theoretical evidence shows the importance of trade development on commercially exploited species. However, there is limited understanding of how the development of trade networks, such as differences in connectivity and duration, affects fisheries sustainability. In a global analysis of over 400,000 bilateral trade flows and stock status estimates for 876 exploited fish and marine invertebrates from 223 territories, we reveal patterns between seafood trade network indicators and fisheries sustainability using a dynamic panel regression analysis. We found that fragmented networks with strong connectivity within a group of countries and weaker links between those groups (modularity) are associated with higher relative biomass. From 1995 to 2015, modularity fluctuated, and the number of trade connections (degree) increased. Unlike previous studies, we found no relationship between the number or duration of trade connections and fisheries sustainability. Our results highlight the need to jointly investigate fisheries and trade. Improved coordination and partnerships between fisheries authorities and trade organizations present opportunities to foster more sustainable fisheries.

Asymmetric Active Sites for Boosting Oxygen Evolution Reaction

Transition metal-nitrogen-carbon materials with atomically dispersed active sites are promising catalysts for oxygen evolution reaction (OER) since they combine the strengths of both homogeneous and heterogeneous catalysts. However, the canonically symmetric active site usually exhibits poor OER intrinsic activity due to its excessively strong or weak oxygen species adsorption. Here, a catalyst with asymmetric MN4 sites based on the 3-s-triazine of g-C3 N4 (termed as a-MN4 @NC) is proposed. Compared to symmetric, the asymmetric active sites directly modulate the oxygen species adsorption via unifying planar and axial orbitals (dx2 -y2 , dz2 ), thus enabling higher OER intrinsic activity. In Silico screening suggested that cobalt has the best OER activity among familiar nonprecious transition metal. These experimental results suggest that the intrinsic activity of asymmetric active sites (179 mV overpotential at onset potential) is enhanced by 48.4% compared to symmetric under similar conditions. Remarkably, a-CoN4 @NC showed excellent activity in alkaline water electrolyzer (AWE) device as OER catalyst, the electrolyzer only required 1.7 V and 2.1 V respectively to reach the current density of 150 mA cm-2 and 500 mA cm-2 . This work opens an avenue for modulating the active sites to obtain high intrinsic electrocatalytic performance including, but not limited to, OER.

Controversies and progress on standardization of large-scale brain network nomenclature

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

Estimating SARS-CoV-2 seroprevalence

Governments and public health authorities use seroprevalence studies to guide responses to the COVID-19 pandemic. Seroprevalence surveys estimate the proportion of individuals who have detectable SARS-CoV-2 antibodies. However, serologic assays are prone to misclassification error, and non-probability sampling may induce selection bias. In this paper, non-parametric and parametric seroprevalence estimators are considered that address both challenges by leveraging validation data and assuming equal probabilities of sample inclusion within covariate-defined strata. Both estimators are shown to be consistent and asymptotically normal, and consistent variance estimators are derived. Simulation studies are presented comparing the estimators over a range of scenarios. The methods are used to estimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in New York City, Belgium, and North Carolina.

Comprehensive Social Trait Judgments From Faces in Autism Spectrum Disorder

Processing social information from faces is difficult for individuals with autism spectrum disorder (ASD). However, it remains unclear whether individuals with ASD make high-level social trait judgments from faces in the same way as neurotypical individuals. Here, we comprehensively addressed this question using naturalistic face images and representatively sampled traits. Despite similar underlying dimensional structures across traits, online adult participants with self-reported ASD showed different judgments and reduced specificity within each trait compared with neurotypical individuals. Deep neural networks revealed that these group differences were driven by specific types of faces and differential utilization of features within a face. Our results were replicated in well-characterized in-lab participants and partially generalized to more controlled face images (a preregistered study). By investigating social trait judgments in a broader population, including individuals with neurodevelopmental variations, we found important theoretical implications for the fundamental dimensions, variations, and potential behavioral consequences of social cognition.

Quantifying the effect of an endo-vaginal probe on position of the pelvic floor viscera and muscles

INTRODUCTION AND HYPOTHESIS

Endovaginal ultrasound has long been hypothesized to have a significant effect on locations of what it visualizes. However, little work has directly quantified its effect. This study aimed to quantify it.

METHODS

This cross-sectional study consisted of 20 healthy asymptomatic volunteers who underwent both endovaginal ultrasound and MRI. The urethra, vagina, rectum, pelvic floor, and pubic bone were segmented in both ultrasound and MRI using 3DSlicer. Then, using 3DSlicer's transform tool the volumes were rigidly aligned based on the posterior curvature of the pubic bone. The organs were then split into thirds along their long axis to compare their distal, middle, and proximal sections. Using Houdini, we compared the location of the centroid of each of the urethra, vagina, and rectum and the surface-to-surface difference of the urethra and rectum. The anterior curvature of the pelvic floor was also compared. Normality of all variables was assessed by Shapiro-Wilk test.

RESULTS

The largest amount of surface-to-surface distance was observed in the proximal region for the urethra and rectum. Across all three organs, the majority of the deviation was in the anterior direction for geometries obtained from ultrasound versus those from MRI. For each subject, the trace defining the midline of the levator plate was more anterior for ultrasound compared to MRI.

CONCLUSIONS

While it has often been assumed that placing a probe in the vagina probably distorts the anatomy, this study quantified the distortion and displacement of the pelvic viscera. This allows for better interpretation of clinical and research findings based on this modality.

Elevational range extension of the Puna Mouse, Punomys (Cricetidae), with the first record of the genus from Chile

We report an elevational record for the Andean sigmodontine Puna Mouse Punomys, which is also the first record of the genus in Chile. The record is based on a mummified specimen that we discovered at an elevation of 5,461 m (17,917 feet) in the caldera of Volcán Acamarachi, Región de Antofagasta, Chile. Results of a morphological assessment suggest that the specimen can be provisionally referred to the species P. lemminus. This new record also extends the known geographic distribution of the genus by 700 km to the south and brings the known Chilean mammal richness to a total of 170 living species and 88 genera. This finding highlights the need for increased survey efforts in more remote, high-elevation regions and demonstrates that there is still much to be learned about the mammal fauna of the Andean Altiplano.

Composition Based Oxidation State Prediction of Materials Using Deep Learning Language Models

Oxidation states (OS) are the charges on atoms due to electrons gained or lost upon applying an ionic approximation to their bonds. As a fundamental property, OS has been widely used in charge-neutrality verification, crystal structure determination, and reaction estimation. Currently, only heuristic rules exist for guessing the oxidation states of a given compound with many exceptions. Recent work has developed machine learning models based on heuristic structural features for predicting the oxidation states of metal ions. However, composition-based oxidation state prediction still remains elusive so far, which has significant implications for the discovery of new materials for which the structures have not been determined. This work proposes a novel deep learning-based BERT transformer language model BERTOS for predicting the oxidation states for all elements of inorganic compounds given only their chemical composition. This model achieves 96.82% accuracy for all-element oxidation states prediction benchmarked on the cleaned ICSD dataset and achieves 97.61% accuracy for oxide materials. It is also demonstrated how it can be used to conduct large-scale screening of hypothetical material compositions for materials discovery.

Pushing the limits of detectability: mixed dark matter from strong gravitational lenses

One of the frontiers for advancing what is known about dark matter lies in using strong gravitational lenses to characterize the population of the smallest dark matter haloes. There is a large volume of information in strong gravitational lens images - the question we seek to answer is to what extent we can refine this information. To this end, we forecast the detectability of a mixed warm and cold dark matter scenario using the anomalous flux ratio method from strong gravitational lensed images. The halo mass function of the mixed dark matter scenario is suppressed relative to cold dark matter but still predicts numerous low-mass dark matter haloes relative to warm dark matter. Since the strong lensing signal receives a contribution from a range of dark matter halo masses and since the signal is sensitive to the specific configuration of dark matter haloes, not just the halo mass function, degeneracies between different forms of suppression in the halo mass function, relative to cold dark matter, can arise. We find that, with a set of lenses with different configurations of the main deflector and hence different sensitivities to different mass ranges of the halo mass function, the different forms of suppression of the halo mass function between the warm dark matter model and the mixed dark matter model can be distinguished with 40 lenses with Bayesian odds of 30:1.

Probing the physiological role of the plastid outer-envelope membrane using the oemiR plasmid collection

Plastids are the site of complex biochemical pathways, most prominently photosynthesis. The organelle evolved through endosymbiosis with a cyanobacterium, which is exemplified by the outer envelope membrane that harbors more than 40 proteins in Arabidopsis. Their evolutionary conservation indicates high significance for plant cell function. While a few proteins are well-studied as part of the protein translocon complex the majority of outer envelope protein functions is unclear. Gaining a deeper functional understanding has been complicated by the lack of observable loss-of-function mutant phenotypes, which is often rooted in functional genetic redundancy. Therefore, we designed outer envelope-specific artificial micro RNAs (oemiRs) capable of downregulating transcripts from several loci simultaneously. We successfully tested oemiR function by performing a proof-of-concept screen for pale and cold-sensitive mutants. An in-depth analysis of pale mutant alleles deficient in the translocon component TOC75 using proteomics provided new insights into putative compensatory import pathways. The cold stress screen not only recapitulated 3 previously known phenotypes of cold-sensitive mutants but also identified 4 mutants of additional oemiR outer envelope loci. Altogether our study revealed a role of the outer envelope to tolerate cold conditions and showcasts the power of the oemiR collection to research the significance of outer envelope proteins.

Genome assembly of the foot-flagging frog, Staurois parvus: a resource for understanding mechanisms of behavior

Elaborate and skilled movements of the body have been selected in a variety of species as courtship and rivalry signals. One roadblock in studying these behaviors has been a lack of resources for understanding how they evolved at the genetic level. The Bornean rock frog (Staurois parvus) is an ideal species in which to address this issue. Males wave their hindlimbs in a "foot-flagging" display when competing for mates. The evolution of foot flagging in S. parvus and other species is accompanied by increases in the expression of the androgen receptor gene within its neuromuscular system, but it remains unclear what genetic or transcriptional changes are associated with this behavioral phenotype. We have now assembled the genome of S. parvus, resulting in 3.98 Gbp of 22,402 contigs with an N50 of 611,229 bp. The genome will be a resource for finding genes related to the physiology underlying foot flagging and to adaptations of the neuromuscular system. As a first application of the genome, we also began work in comparative genomics and differential gene expression analysis. We show that the androgen receptor is diverged from other anuran species, and we identify unique expression patterns of genes in the spinal cord and leg muscle that are important for axial patterning, cell specification and morphology, or muscle contraction. This genome will continue to be an important tool for future -omics studies to understand the evolution of elaborate signaling behaviors in this and potentially related species.

Long-read genome assemblies for the study of chromosome expansion: Drosophila kikkawai, Drosophila takahashii, Drosophila bipectinata, and Drosophila ananassae

Flow cytometry estimates of genome sizes among species of Drosophila show a 3-fold variation, ranging from ∼127 Mb in Drosophila mercatorum to ∼400 Mb in Drosophila cyrtoloma. However, the assembled portion of the Muller F element (orthologous to the fourth chromosome in Drosophila melanogaster) shows a nearly 14-fold variation in size, ranging from ∼1.3 Mb to >18 Mb. Here, we present chromosome-level long-read genome assemblies for 4 Drosophila species with expanded F elements ranging in size from 2.3 to 20.5 Mb. Each Muller element is present as a single scaffold in each assembly. These assemblies will enable new insights into the evolutionary causes and consequences of chromosome size expansion.

Rehydration of Freeze Substituted Brain Tissue for Pre-embedding Immunoelectron Microscopy

Electron microscopy (EM) volume reconstruction is a powerful tool for investigating the fundamental structure of brain circuits, but the full potential of this technique is limited by the difficulty of integrating molecular information. High quality ultrastructural preservation is necessary for EM reconstruction, and intact, highly contrasted cell membranes are essential for following small neuronal processes through serial sections. Unfortunately, the antibody labeling methods used to identify most endogenous molecules result in compromised morphology, especially of membranes. Cryofixation can produce superior morphological preservation and has the additional advantage of allowing indefinite storage of valuable samples. We have developed a method based on cryofixation that allows sensitive immunolabeling of endogenous molecules, preserves excellent ultrastructure, and is compatible with high-contrast staining for serial EM reconstruction.

Using Focused Ion Beam Time-of-Flight Secondary Ion Mass Spectrometry to Depth Profile Nanoparticles in Polymer Nanocomposites

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a versatile surface-sensitive technique for characterizing both hard and soft matter. Its chemical and molecular specificity, high spatial resolution, and superior sensitivity make it an ideal method for depth profiling polymeric systems, including those comprised of both inorganic and organic constituents (i.e., polymer nanocomposites, PNCs). To best utilize ToF-SIMS for characterizing PNCs, experimental conditions must be optimized to minimize challenges such as the matrix effect and charge accumulation. Toward that end, we have successfully used ToF-SIMS with a Xe+ focused ion beam to depth profile silica nanoparticles grafted with poly(methyl methacrylate) (PMMA-NP) in a poly(styrene-ran-acrylonitrile) matrix film by selecting conditions that address charge compensation and the primary incident beam angles. By tracking the sputtered Si+ species and fitting the resultant concentration profile, the diffusion coefficient of PMMA-NP was determined to be D = 2.4 × 10-14 cm2/s. This value of D lies between that measured using Rutherford backscattering spectrometry (6.4 × 10-14 cm2/s) and the value predicted by the Stokes-Einstein model (2.5 × 10-15 cm2/s). With carefully tuned experimental parameters, ToF-SIMS holds great potential for quantitatively characterizing the nanoparticles at the surfaces and interfaces within PNC materials as well as soft matter in general.

Ultrasound-Responsive Nanobubbles for Combined siRNA-Cerium Oxide Nanoparticle Delivery to Bone Cells

This study aims to present an ultrasound-mediated nanobubble (NB)-based gene delivery system that could potentially be applied in the future to treat bone disorders such as osteoporosis. NBs are sensitive to ultrasound (US) and serve as a controlled-released carrier to deliver a mixture of Cathepsin K (CTSK) siRNA and cerium oxide nanoparticles (CeNPs). This platform aimed to reduce bone resorption via downregulating CTSK expression in osteoclasts and enhance bone formation via the antioxidant and osteogenic properties of CeNPs. CeNPs were synthesized and characterized using transmission electron microscopy and X-ray photoelectron spectroscopy. The mixture of CTSK siRNA and CeNPs was adsorbed to the surface of NBs using a sonication method. The release profiles of CTSK siRNA and CeNPs labeled with a fluorescent tag molecule were measured after low-intensity pulsed ultrasound (LIPUS) stimulation using fluorescent spectroscopy. The maximum release of CTSK siRNA and the CeNPs for 1 mg/mL of NB-(CTSK siRNA + CeNPs) was obtained at 2.5 nM and 1 µg/mL, respectively, 3 days after LIPUS stimulation. Then, Alizarin Red Staining (ARS) was applied to human bone marrow-derived mesenchymal stem cells (hMSC) and tartrate-resistant acid phosphatase (TRAP) staining was applied to human osteoclast precursors (OCP) to evaluate osteogenic promotion and osteoclastogenic inhibition effects. A higher mineralization and a lower number of osteoclasts were quantified for NB-(CTSK siRNA + CeNPs) versus control +RANKL with ARS (p < 0.001) and TRAP-positive staining (p < 0.01). This study provides a method for the delivery of gene silencing siRNA and CeNPs using a US-sensitive NB system that could potentially be used in vivo and in the treatment of bone fractures and disorders such as osteoporosis.

Iterated Clique Reductions in Vertex Weighted Coloring for Large Sparse Graphs

The Minimum Vertex Weighted Coloring (MinVWC) problem is an important generalization of the classic Minimum Vertex Coloring (MinVC) problem which is NP-hard. Given a simple undirected graph G=(V,E), the MinVC problem is to find a coloring s.t. any pair of adjacent vertices are assigned different colors and the number of colors used is minimized. The MinVWC problem associates each vertex with a positive weight and defines the weight of a color to be the weight of its heaviest vertices, then the goal is the find a coloring that minimizes the sum of weights over all colors. Among various approaches, reduction is an effective one. It tries to obtain a subgraph whose optimal solutions can conveniently be extended into optimal ones for the whole graph, without costly branching. In this paper, we propose a reduction algorithm based on maximal clique enumeration. More specifically our algorithm utilizes a certain proportion of maximal cliques and obtains lower bounds in order to perform reductions. It alternates between clique sampling and graph reductions and consists of three successive procedures: promising clique reductions, better bound reductions and post reductions. Experimental results show that our algorithm returns considerably smaller subgraphs for numerous large benchmark graphs, compared to the most recent method named RedLS. Also, we evaluate individual impacts and some practical properties of our algorithm. Furthermore, we have a theorem which indicates that the reduction effects of our algorithm are equivalent to that of a counterpart which enumerates all maximal cliques in the whole graph if the run time is sufficiently long.

mRNA decapping activators Pat1 and Dhh1 regulate transcript abundance and translation to tune cellular responses to nutrient availability

We have examined the roles of yeast mRNA decapping-activators Pat1 and Dhh1 in repressing the translation and abundance of specific mRNAs in nutrient-replete cells using ribosome profiling, RNA-Seq, CAGE analysis of capped mRNAs, RNA Polymerase II ChIP-Seq, and TMT-mass spectrometry of mutants lacking one or both factors. Although the Environmental Stress Response (ESR) is activated in dhh1Δ and pat1Δ mutants, hundreds of non-ESR transcripts are elevated in a manner indicating cumulative repression by Pat1 and Dhh1 in wild-type cells. These mRNAs show both reduced decapping and diminished transcription in the mutants, indicating that impaired mRNA turnover drives transcript derepression in cells lacking Dhh1 or Pat1. mRNA degradation stimulated by Dhh1/Pat1 is not dictated by poor translation nor enrichment for suboptimal codons. Pat1 and Dhh1 also collaborate to reduce translation and protein production from many mRNAs. Transcripts showing concerted translational repression by Pat1/Dhh1 include mRNAs involved in cell adhesion or utilization of the poor nitrogen source allantoin. Pat1/Dhh1 also repress numerous transcripts involved in respiration, catabolism of non-preferred carbon or nitrogen sources, or autophagy; and we obtained evidence for elevated respiration and autophagy in the mutants. Thus, Pat1 and Dhh1 function as post-transcriptional repressors of multiple pathways normally activated only during nutrient limitation.

Everything is Infinite: Children's Beliefs About Endless Space, Time, and Number

How do children form beliefs about the infinity of space, time, and number? We asked whether children held similar beliefs about infinity across domains, and whether beliefs in infinity for domains like space and time might be scaffolded upon numerical knowledge (e.g., knowledge successors within the count list). To test these questions, 112 U.S. children (aged 4;0-7;11) completed an interview regarding their beliefs about infinite space, time, and number. We also measured their knowledge of counting, and other factors that might impact performance on linguistic assessments of infinity belief (e.g., working memory, ability to respond to hypothetical questions). We found that beliefs about infinity were very high across all three domains, suggesting that infinity beliefs may arise early in development for space, time, and number. Second, we found that-across all three domains-children were more likely to believe that it is always possible to add a unit than to believe that the domain is endless. Finally, we found that understanding the rules underlying counting predicted children's belief that it is always possible to add 1 to any number, but did not predict any of the other elements of infinity belief.

Luminescence and Stability of 1,4,5-Triaryl-1,2,3-Triazoles

The fluorescence, phosphorescence, and photochemical properties of di- and triaryl-substituted-1,2,3-triazoles are reported in this work. The ease of synthesis of regioisomers of substituted triazoles enables a systematic study on the correlation between regiochemistry and excited state properties, which include the solvent dependence of fluorescence, energy gap between singlet and triplet emitters, and propensity to photon-triggered transformations. The triazoles that carry electron (e)-donor and e-acceptor aryl substituents show high fluorescence quantum yields in weakly polar solvents and exhibit solvent-dependent fluorescence. The luminescence properties of these compounds in glass matrices at 77 K are characterized. The thermal and photo-stability, two parameters that are crucial to their potential utilities in optical devices, of these compounds are determined. The position of the e-donor substituent has a significant impact on the fluorescence emission energy and solvent sensitivity, singlet-triplet energy gap, and photochemical reactivity and stability. The experimental observations on the structural correlation with the photophysical and photochemical properties are explained by quantum chemical calculations. This study provides a rationale on the placement of substituent on a donor-acceptor type fluorophore to maneuver a range of photo-related properties.

What's in a mate? Social pairing decisions and spatial cognitive ability in food-caching mountain chickadees

While researchers have investigated mating decisions for decades, gaps remain in our understanding of how behaviour influences social mate choice. We compared spatial cognitive performance and food caching propensity within social pairs of mountain chickadees inhabiting differentially harsh winter climates to understand how these measures contribute to social mate choice. Chickadees rely on specialized spatial cognitive abilities to recover food stores and survive harsh winters, and females can discriminate among males with varying spatial cognition. Because spatial cognition and caching propensity are critical for survival and likely heritable, pairing with a mate with such enhanced traits may provide indirect benefits to offspring. Comparing the behaviour of social mates, we found that spatial cognitive performance approached a significant correlation within pairs at low, but not at high elevation. We found no correlation within pairs in spatial reversal cognitive performance at either elevation; however, females at high elevation tended to perform better than their social mates. Finally, we found that caching propensity correlated within pairs at low, while males cached significantly more food than their social mates at high elevations. These results suggest that cognition and caching propensity may influence social mating decisions, but only in certain environments and for some aspects of cognition.

Design and fabrication of carbon fiber lattices using 3D weaving

We present a method of designing and fabricating 3D carbon fiber lattices. The lattice design and fabrication is based on crocheting and sewing techniques, where carbon fiber tow is woven through two parallel carbon fiber grids and reinforced with vertical carbon fiber tubes. Compression testing is then performed on three different designs, and these results are compared to other similar lattice structures, finding that the lattices perform similarly to comparable lattices. Finite element analysis is also performed to validate the experimental findings, and provides some insight into the experimental results. The process presented here allows for more design flexibility than other current methods. For example, within a single lattice, different density weave patterns can be used to address specific load requirements. Though fabricated manually here, this process can also be automated for large scale production. With this design flexibility, simplified fabrication, and high strength, the lattices proposed here offer an advantage as compared to similar existing structures.

Structural Similarities and Overlapping Activities among Dihydroflavonol 4-Reductase, Flavanone 4-Reductase, and Anthocyanidin Reductase Offer Metabolic Flexibility in the Flavonoid Pathway

Flavonoids are potent antioxidants that play a role in defense against pathogens, UV-radiation, and the detoxification of reactive oxygen species. Dihydroflavonol 4-reductase (DFR) and flavanone 4-reductase (FNR) reduce dihydroflavonols and flavanones, respectively, using NAD(P)H to produce flavan-(3)-4-(di)ols in flavonoid biosynthesis. Anthocyanidin reductase (ANR) reduces anthocyanidins to flavan-3-ols. In addition to their sequences, the 3D structures of recombinant DFR, FNR and ANR from sorghum and switchgrass showed a high level of similarity. The catalytic mechanism, substrate-specificity and key residues of three reductases were deduced from crystal structures, site-directed mutagenesis, molecular docking, kinetics, and thermodynamic ana-lyses. Although DFR displayed its highest activity against dihydroflavonols, it also showed activity against flavanones and anthocyanidins. It was inhibited by the flavonol quercetin and high concentrations of dihydroflavonols/flavonones. SbFNR1 and SbFNR2 did not show any activity against dihydroflavonols. However, SbFNR1 displayed activity against flavanones and ANR activity against two anthocyanidins, cyanidin and pelargonidin. Therefore, SbFNR1 and SbFNR2 could be specific ANR isozymes without delphinidin activity. Sorghum has high concentrations of 3-deoxyanthocyanidins in vivo, supporting the observed high activity of SbDFR against flavonols. Mining of expression data indicated substantial induction of these three reductase genes in both switchgrass and sorghum in response to biotic stress. Key signature sequences for proper DFR/ANR classification are proposed and could form the basis for future metabolic engineering of flavonoid metabolism.

Targeted RNA condensation in living cells via genetically encodable triplet repeat tags

Living systems contain various membraneless organelles that segregate proteins and RNAs via liquid-liquid phase separation. Inspired by nature, many protein-based synthetic compartments have been engineered in vitro and in living cells. Here, we introduce a genetically encoded CAG-repeat RNA tag to reprogram cellular condensate formation and recruit various non-phase-transition RNAs for cellular modulation. With the help of fluorogenic RNA aptamers, we have systematically studied the formation dynamics, spatial distributions, sizes and densities of these cellular RNA condensates. The cis- and trans-regulation functions of these CAG-repeat tags in cellular RNA localization, life time, RNA-protein interactions and gene expression have also been investigated. Considering the importance of RNA condensation in health and disease, we expect that these genetically encodable modular and self-assembled tags can be widely used for chemical biology and synthetic biology studies.

Tracing the birth of structural domains from loops during protein evolution

The structures and functions of proteins are embedded into the loop scaffolds of structural domains. Their origin and evolution remain mysterious. Here, we use a novel graph-theoretical approach to describe how modular and non-modular loop prototypes combine to form folded structures in protein domain evolution. Phylogenomic data-driven chronologies reoriented a bipartite network of loops and domains (and its projections) into 'waterfalls' depicting an evolving 'elementary functionome' (EF). Two primordial waves of functional innovation involving founder 'p-loop' and 'winged-helix' domains were accompanied by an ongoing emergence and reuse of structural and functional novelty. Metabolic pathways expanded before translation functionalities. A dual hourglass recruitment pattern transferred scale-free properties from loop to domain components of the EF network in generative cycles of hierarchical modularity. Modeling the evolutionary emergence of the oldest P-loop and winged-helix domains with AlphFold2 uncovered rapid convergence towards folded structure, suggesting that a folding vocabulary exists in loops for protein fold repurposing and design.

Highly Conductive Polyoxanorbornene-Based Polymer Electrolyte for Lithium-Metal Batteries

This present study illustrates the synthesis and preparation of polyoxanorbornene-based bottlebrush polymers with poly(ethylene oxide) (PEO) side chains by ring-opening metathesis polymerization for solid polymer electrolytes (SPE). In addition to the conductive PEO side chains, the polyoxanorbornene backbones may act as another ion conductor to further promote Li-ion movement within the SPE matrix. These results suggest that these bottlebrush polymer electrolytes provide impressively high ionic conductivity of 7.12 × 10-4 S cm-1 at room temperature and excellent electrochemical performance, including high-rate capabilities and cycling stability when paired with a Li metal anode and a LiFePO4 cathode. The new design paradigm, which has dual ionic conductive pathways, provides an unexplored avenue for inventing new SPEs and emphasizes the importance of molecular engineering to develop highly stable and conductive polymer electrolytes for lithium-metal batteries (LMB).

Testing for the Markov property in time series via deep conditional generative learning

The Markov property is widely imposed in analysis of time series data. Correspondingly, testing the Markov property, and relatedly, inferring the order of a Markov model, are of paramount importance. In this article, we propose a nonparametric test for the Markov property in high-dimensional time series via deep conditional generative learning. We also apply the test sequentially to determine the order of the Markov model. We show that the test controls the type-I error asymptotically, and has the power approaching one. Our proposal makes novel contributions in several ways. We utilise and extend state-of-the-art deep generative learning to estimate the conditional density functions, and establish a sharp upper bound on the approximation error of the estimators. We derive a doubly robust test statistic, which employs a nonparametric estimation but achieves a parametric convergence rate. We further adopt sample splitting and cross-fitting to minimise the conditions required to ensure the consistency of the test. We demonstrate the efficacy of the test through both simulations and the three data applications.

Complex Oxides for Brain-Inspired Computing: A Review

The fields of brain-inspired computing, robotics, and, more broadly, artificial intelligence (AI) seek to implement knowledge gleaned from the natural world into human-designed electronics and machines. In this review, the opportunities presented by complex oxides, a class of electronic ceramic materials whose properties can be elegantly tuned by doping, electron interactions, and a variety of external stimuli near room temperature, are discussed. The review begins with a discussion of natural intelligence at the elementary level in the nervous system, followed by collective intelligence and learning at the animal colony level mediated by social interactions. An important aspect highlighted is the vast spatial and temporal scales involved in learning and memory. The focus then turns to collective phenomena, such as metal-to-insulator transitions (MITs), ferroelectricity, and related examples, to highlight recent demonstrations of artificial neurons, synapses, and circuits and their learning. First-principles theoretical treatments of the electronic structure, and in situ synchrotron spectroscopy of operating devices are then discussed. The implementation of the experimental characteristics into neural networks and algorithm design is then revewed. Finally, outstanding materials challenges that require a microscopic understanding of the physical mechanisms, which will be essential for advancing the frontiers of neuromorphic computing, are highlighted.

Interlocus Gene Conversion, Natural Selection, and Paralog Homogenization

Following a duplication, the resulting paralogs tend to diverge. While mutation and natural selection can accelerate this process, they can also slow it. Here, we quantify the paralog homogenization that is caused by point mutations and interlocus gene conversion (IGC). Among 164 duplicated teleost genes, the median percentage of postduplication codon substitutions that arise from IGC rather than point mutation is estimated to be between 7% and 8%. By differentiating between the nonsynonymous codon substitutions that homogenize the protein sequences of paralogs and the nonhomogenizing nonsynonymous substitutions, we estimate the homogenizing nonsynonymous rates to be higher for 163 of the 164 teleost data sets as well as for all 14 data sets of duplicated yeast ribosomal protein-coding genes that we consider. For all 14 yeast data sets, the estimated homogenizing nonsynonymous rates exceed the synonymous rates.

The neural code for "face cells" is not face-specific

Face cells are neurons that respond more to faces than to non-face objects. They are found in clusters in the inferotemporal cortex, thought to process faces specifically, and, hence, studied using faces almost exclusively. Analyzing neural responses in and around macaque face patches to hundreds of objects, we found graded response profiles for non-face objects that predicted the degree of face selectivity and provided information on face-cell tuning beyond that from actual faces. This relationship between non-face and face responses was not predicted by color and simple shape properties but by information encoded in deep neural networks trained on general objects rather than face classification. These findings contradict the long-standing assumption that face versus non-face selectivity emerges from face-specific features and challenge the practice of focusing on only the most effective stimulus. They provide evidence instead that category-selective neurons are best understood by their tuning directions in a domain-general object space.

Magneto-Mechanical Bilayer Metamaterial with Global Area-Preserving Density Tunability for Acoustic Wave Regulation

2D metamaterials have immense potential in acoustics, optics, and electromagnetic applications due to their unique properties and ability to conform to curved substrates. Active metamaterials have attracted significant research attention because of their on-demand tunable properties and performances through shape reconfigurations. 2D active metamaterials often achieve active properties through internal structural deformations, which lead to changes in overall dimensions. This demands corresponding alterations of the conforming substrate, or the metamaterial fails to provide complete area coverage, which can be a significant limitation for their practical applications. To date, achieving area-preserving active 2D metamaterials with distinct shape reconfigurations remains a prominent challenge. In this paper, magneto-mechanical bilayer metamaterials are presented that demonstrate area density tunability with area-preserving capability. The bilayer metamaterials consist of two arrays of magnetic soft materials with distinct magnetization distributions. Under a magnetic field, each layer behaves differently, which allows the metamaterial to reconfigure its shape into multiple modes and to significantly tune its area density without changing its overall dimensions. The area-preserving multimodal shape reconfigurations are further exploited as active acoustic wave regulators to tune bandgaps and wave propagations. The bilayer approach thus provides a new concept for the design of area-preserving active metamaterials for broader applications.

Viscoelasticity enhances collective motion of bacteria

Bacteria form human and animal microbiota. They are the leading causes of many infections and constitute an important class of active matter. Concentrated bacterial suspensions exhibit large-scale turbulent-like locomotion and swarming. While the collective behavior of bacteria in Newtonian fluids is relatively well understood, many fundamental questions remain open for complex fluids. Here, we report on the collective bacterial motion in a representative biological non-Newtonian viscoelastic environment exemplified by mucus. Experiments are performed with synthetic porcine gastric mucus, natural cow cervical mucus, and a Newtonian-like polymer solution. We have found that an increase in mucin concentration and, correspondingly, an increase in the suspension's elasticity monotonously increases the length scale of collective bacterial locomotion. On the contrary, this length remains practically unchanged in Newtonian polymer solution in a wide range of concentrations. The experimental observations are supported by computational modeling. Our results provide insight into how viscoelasticity affects the spatiotemporal organization of bacterial active matter. They also expand our understanding of bacterial colonization of mucosal surfaces and the onset of antibiotic resistance due to swarming.

Brief Submotor-Threshold Electrical Stimulation Applied Synchronously Over Wrist Flexor and Extensor Muscles does Not Suppress Essential Tremor, Independent of Stimulation Frequency

Background

Electrical stimulation of muscles below motoneuron threshold has shown potential as a low-cost and minimally invasive treatment for Essential Tremor (ET). Prior studies have stimulated wrist flexor and extensor muscles synchronously with diverging results, calling for further investigation. Also, prior studies have only used a narrow range of stimulation parameters, so stimulation parameters have not been optimized. Our purpose was to further investigate synchronous submotor stimulation and identify the effect of stimulation frequency on tremor suppression.

Methods

We quantified the effect of brief, synchronous stimulation at 15 different frequencies from 10-150 Hz applied over wrist flexors and extensors on both tremor power and frequency in 20 ET patients. We compared tremor power and frequency from hand acceleration and sEMG between pre-, per-, and post-stimulation phases.

Results

Our stimulation paradigm did not result in significant tremor suppression or tremor frequency changes at any tested stimulation frequency, showing no significant interaction between phase and stimulation frequency for tremor power measured by either hand acceleration (p = 0.69) or sEMG (p = 0.07). Additionally, the effect of phase interacting with stimulation frequency on tremor frequency was statistically insignificant for acceleration (p = 0.64) and sEMG (p = 0.37).

Discussion

We conclude that brief synchronous submotor-threshold stimulation does not reduce tremor in ET patients, independent of stimulation frequency (from 10 to 150 Hz). Our results are consistent with the hypothesis that brief submotor-threshold stimulation suppresses tremor via reciprocal inhibition, which requires asynchronous stimulation. In contrast, it is hypothesized that synchronous stimulation might require longer stimulation durations to affect supraspinal tremor networks.

Highlights

We studied the effects of synchronous submotor electrical stimulation over wrist flexor and extensor muscles on Essential Tremor. Our results indicate that suppressing tremor with brief synchronous stimulation is ineffective. Based on recently hypothesized mechanisms of peripheral tremor suppression, we hypothesize that asynchronous stimulation or long-duration synchronous stimulation are more effective approaches to peripheral tremor suppression.

Synergistic Modulation of Electronic Interaction to Enhance Intrinsic Activity and Conductivity of Fe-Co-Ni Hydroxide Nanotube for Highly Efficient Oxygen Evolution Electrocatalyst

The large-scale hydrogen production and application through electrocatalytic water splitting depends crucially on the development of highly efficient, cost-effective electrocatalysts for oxygen evolution reaction (OER), which, however, remains challenging. Here, a new electrocatalyst of trimetallic Fe-Co-Ni hydroxide (denoted as FeCoNiOx Hy ) with a nanotubular structure is developed through an enhanced Kirkendall process under applied potential. The FeCoNiOx Hy features synergistic electronic interaction between Fe, Co, and Ni, which not only notably increases the intrinsic OER activity of FeCoNiOx Hy by facilitating the formation of *OOH intermediate, but also substantially improves the intrinsic conductivity of FeCoNiOx Hy to facilitate charge transfer and activate catalytic sites through electrocatalyst by promoting the formation of abundant Co3+ . Therefore, FeCoNiOx Hy delivers remarkably accelerated OER kinetics and superior apparent activity, indicated by an ultra-low overpotential potential of 257 mV at a high current density of 200 mA cm-2 . This work is of fundamental and practical significance for synergistic catalysis related to advanced energy conversion materials and technologies.

Neuronal Ndst1 depletion accelerates prion protein clearance and slows neurodegeneration in prion infection

Select prion diseases are characterized by widespread cerebral plaque-like deposits of amyloid fibrils enriched in heparan sulfate (HS), a abundant extracellular matrix component. HS facilitates fibril formation in vitro, yet how HS impacts fibrillar plaque growth within the brain is unclear. Here we found that prion-bound HS chains are highly sulfated, and that the sulfation is essential for accelerating prion conversion in vitro. Using conditional knockout mice to deplete the HS sulfation enzyme, Ndst1 (N-deacetylase / N-sulfotransferase) from neurons or astrocytes, we investigated how reducing HS sulfation impacts survival and prion aggregate distribution during a prion infection. Neuronal Ndst1-depleted mice survived longer and showed fewer and smaller parenchymal plaques, shorter fibrils, and increased vascular amyloid, consistent with enhanced aggregate transit toward perivascular drainage channels. The prolonged survival was strain-dependent, affecting mice infected with extracellular, plaque-forming, but not membrane bound, prions. Live PET imaging revealed rapid clearance of recombinant prion protein monomers into the CSF of neuronal Ndst1- deficient mice, neuronal, further suggesting that HS sulfate groups hinder transit of extracellular prion protein monomers. Our results directly show how a host cofactor slows the spread of prion protein through the extracellular space and identify an enzyme to target to facilitate aggregate clearance.

Water-Induced Separation of Polymers from High Nanoparticle-Content Nanocomposite Films

Polymer nanocomposites with high loadings of nanoparticles (NPs) exhibit exceptional mechanical and transport properties. Separation of polymers and NPs from such nanocomposites is a critical step in enabling the recycling of these components and reducing the potential environmental hazards that can be caused by the accumulation of nanocomposite wastes in landfills. However, the separation typically requires the use of organic solvents or energy-intensive processes. Using polydimethylsiloxane (PDMS)-infiltrated SiO2 NP films, we demonstrate that the polymers can be separated from the SiO2 NP packings when these nanocomposites are exposed to high humidity and water. The findings indicate that the charge state of the NPs plays a significant role in the propensity of water to undergo capillary condensation within the PDMS-filled interstitial pores. We also show that the size of NPs has a crucial impact on the kinetics and extent of PDMS expulsion, illustrating the importance of capillary forces in inducing PDMS expulsion. We demonstrate that the separated polymer can be collected and reused to produce a new nanocomposite film. The work provides insightful guidelines on how to design and fabricate end-of-life recyclable high-performance nanocomposites.

New Chemical Dopant and Counterion Mechanism for Organic Electrochemical Transistors and Organic Mixed Ionic-Electronic Conductors

Organic mixed ionic-electronic conductors (OMIECs) have varied performance requirements across a diverse application space. Chemically doping the OMIEC can be a simple, low-cost approach for adapting performance metrics. However, complex challenges, such as identifying new dopant materials and elucidating design rules, inhibit its realization. Here, these challenges are approached by introducing a new n-dopant, tetrabutylammonium hydroxide (TBA-OH), and identifying a new design consideration underpinning its success. TBA-OH behaves as both a chemical n-dopant and morphology additive in donor acceptor co-polymer naphthodithiophene diimide-based polymer, which serves as an electron transporting material in organic electrochemical transistors (OECTs). The combined effects enhance OECT transconductance, charge carrier mobility, and volumetric capacitance, representative of the key metrics underpinning all OMIEC applications. Additionally, when the TBA+ counterion adopts an "edge-on" location relative to the polymer backbone, Coulombic interaction between the counterion and polaron is reduced, and polaron delocalization increases. This is the first time such mechanisms are identified in doped-OECTs and doped-OMIECs. The work herein therefore takes the first steps toward developing the design guidelines needed to realize chemical doping as a generic strategy for tailoring performance metrics in OECTs and OMIECs.