A fast and responsive voltage indicator with enhanced sensitivity for unitary synaptic events.

A remaining challenge for genetically encoded voltage indicators (GEVIs) is the reliable detection of excitatory postsynaptic potentials (EPSPs). Here, we developed ASAP5 as a GEVI with enhanced activation kinetics and responsivity near resting membrane potentials for improved detection of both spiking and subthreshold activity. ASAP5 reported action potentials (APs) in vivo with higher signal-to-noise ratios than previous GEVIs and successfully detected graded and subthreshold responses to sensory stimuli in single two-photon trials. In cultured rat or human neurons, somatic ASAP5 reported synaptic events propagating centripetally and could detect ∼1-mV EPSPs. By imaging spontaneous EPSPs throughout dendrites, we found that EPSP amplitudes decay exponentially during propagation and that amplitude at the initiation site generally increases with distance from the soma. These results extend the applications of voltage imaging to the quantal response domain, including in human neurons, opening up the possibility of high-throughput, high-content characterization of neuronal dysfunction in disease.

Bayesian hierarchical modeling for bivariate multiscale spatial data with application to blood test monitoring.

Public health spatial data are often recorded at different spatial scales (or geographic regions/divisions) and over different correlated variables. Motivated by data from the Dartmouth Atlas Project, we consider jointly analyzing average annual percentages of diabetic Medicare enrollees who have taken the hemoglobin A1c and blood lipid tests, observed at the hospital service area (HSA) and county levels, respectively. Capitalizing on bivariate relationships between these two scales is not immediate as counties are not nested within HSAs. It is well known that one can improve predictions by leveraging correlations across both variables and scales. There are very few methods available that simultaneously model multivariate and multiscale correlations. We propose three new hierarchical Bayesian models for bivariate multiscale spatial data, extending spatial random effects, multivariate conditional autoregressive (MCAR), and ordered hierarchical models through a multiscale spatial approach. We simulated data from each of the three models and compared the corresponding predictions, and found the computationally intensive multiscale MCAR model is more robust to model misspecification. In an analysis of 2015 Texas Dartmouth Atlas Project data, we produced finer resolution predictions (partitioning of HSAs and counties) than univariate analyses, determined that the novel multiscale MCAR and OH models were preferable via out-of-sample metrics, and determined the HSA with the highest within-HSA variability of hemoglobin A1c blood testing. Additionally, we compare the univariate multiscale models to the bivariate multiscale models and see clear improvements in prediction over univariate analyses.

Identification and Organization of a Postural Anti-Gravity Module in the Cerebellar Vermis.

The cerebellum is known to control the proper balance of isometric muscular contractions that maintain body posture. Current optogenetic manipulations of the cerebellar cortex output, however, have focused on ballistic body movements, examining movement initiation or perturbations. Here, by optogenetic stimulations of cerebellar Purkinje cells, which are the output of the cerebellar cortex, we evaluate body posture maintenance. By sequential analysis of body movement, we dissect the effect of optogenetic stimulation into a directly induced movement that is then followed by a compensatory reflex to regain body posture. We identify a module in the medial part of the anterior vermis which, through multiple muscle tone regulation, is involved in postural anti-gravity maintenance of the body. Moreover, we report an antero-posterior and medio-lateral functional segregation over the vermal lobules IV/V/VI. Taken together our results open new avenues for better understanding of the modular functional organization of the cerebellar cortex and its role in postural anti-gravity maintenance.

Octave-spanning supercontinuum generation in a CMOS-compatible thin Si3N4 waveguide coated with highly nonlinear TeO2.

Supercontinuum generation (SCG) is an important nonlinear optical process enabling broadband light sources for many applications, for which silicon nitride (Si3N4) has emerged as a leading on-chip platform. To achieve suitable group velocity dispersion and high confinement for broadband SCG the Si3N4 waveguide layer used is typically thick (>∼700 nm), which can lead to high stress and cracks unless specialized processing steps are used. Here, we report on efficient octave-spanning SCG in a thinner moderate-confinement 400-nm Si3N4 platform using a highly nonlinear tellurium oxide (TeO2) coating. An octave supercontinuum spanning from 0.89 to 2.11 µm is achieved at a low peak power of 258 W using a 100-fs laser centered at 1565 nm. Our numerical simulations agree well with the experimental results giving a nonlinear parameter of 2.5 ± 0.5 W-1m-1, an increase by a factor of 2.5, when coating the Si3N4 waveguide with a TeO2 film. This work demonstrates highly efficient SCG via effective dispersion engineering and an enhanced nonlinearity in CMOS-compatible hybrid TeO2-Si3N4 waveguides and a promising route to monolithically integrated nonlinear, linear, and active functionalities on a single silicon photonic chip.

Solvent Suppression in Pure Shift NMR.

Intense solvent signals in 1H solution-state NMR experiments typically cause severe distortion of spectra and mask nearby solute signals. It is often infeasible or undesirable to replace a solvent with its perdeuterated form, for example, when analyzing formulations in situ, when exchangeable protons are present, or for practical reasons. Solvent signal suppression techniques are therefore required. WATERGATE methods are well-known to provide good solvent suppression while enabling retention of signals undergoing chemical exchange with the solvent signal. Spectra of mixtures, such as pharmaceutical formulations, are often complicated by signal overlap, high dynamic range, the narrow spectral width of 1H NMR, and signal multiplicity. Here, we show that by combining WATERGATE solvent suppression with pure shift NMR, ultrahigh-resolution 1H NMR spectra can be acquired while suppressing intense solvent signals and retaining exchangeable 1H signals. The new method is demonstrated in the analysis of cyanocobalamin, a vitamin B12 supplement, and of an eye-drop formulation of atropine.

Doubling the life of Cu/ZnO methanol synthesis catalysts via use of Si as a structural promoter to inhibit sintering.

Cu/ZnO/Al2O3 catalysts used to synthesize methanol undergo extensive deactivation during use, mainly due to sintering. Here, we report on formulations wherein deactivation has been substantially reduced by the targeted use of a small quantity of a Si-based promoter, resulting in accrued activity benefits that can exceed a factor of 1.8 versus unpromoted catalysts. This enhanced stability also provides longer lifetimes, up to double that of prior generation catalysts. Detailed characterization of a library of aged catalysts has allowed the most important deactivation mechanisms to be established and the chemical state of the silicon promoter to be identified. We show that silicon is incorporated within the ZnO lattice, providing a pronounced improvement in the hydrothermal stability of this component. These findings have important implications for sustainable methanol production from H2 and CO2.

Synthetic Control of the Defect Structure and Hierarchical Extra-Large-/Small-Pore Microporosity in Aluminosilicate Zeolite SWY.

The SWY-type aluminosilicate zeolite, STA-30, has been synthesized via different routes to understand its defect chemistry and solid acidity. The synthetic parameters varied were the gel aging, the Al source, and the organic structure directing agent. All syntheses give crystalline materials with similar Si/Al ratios (6-7) that are stable in the activated K,H-form and closely similar by powder X-ray diffraction. However, they exhibit major differences in the crystal morphology and in their intracrystalline porosity and silanol concentrations. The diDABCO-C82+ (1,1'-(octane-1,8-diyl)bis(1,4-diazabicyclo[2.2.2]octan)-1-ium)-templated STA-30 samples (but not those templated by bisquinuclidinium octane, diQuin-C82+) possess hierarchical microporosity, consisting of noncrystallographic extra-large micropores (13 Å) that connect with the characteristic swy and gme cages of the SWY structure. This results in pore volumes up to 30% greater than those measured in activated diQuin-C8_STA-30 as well as higher concentrations of silanols and fewer Brønsted acid sites (BASs). The hierarchical porosity is demonstrated by isopentane adsorption and the FTIR of adsorbed pyridine, which shows that up to 77% of the BASs are accessible (remarkable for a zeolite that has a small-pore crystal structure). A structural model of single can/d6r column vacancies is proposed for the extra-large micropores, which is revealed unambiguously by high-resolution scanning transmission electron microscopy. STA-30 can therefore be prepared as a hierarchically porous zeolite via direct synthesis. The additional noncrystallographic porosity and, subsequently, the amount of SiOHs in the zeolites can be enhanced or strongly reduced by the choice of crystallization conditions.

Bayesian models for spatial count data with informative finite populations with application to the American community survey.

The American Community Survey (ACS) is an ongoing program conducted by the US Census Bureau that publishes estimates of important demographic statistics over pre-specified administrative areas. ACS provides spatially referenced count-valued outcomes that are paired with finite populations. For example, the number of people below the poverty line and the total population for each county are estimated by ACS. One common assumption is that the spatially referenced count-valued outcome given the finite population is binomial distributed. This conditionally specified (CS) model does not define the joint relationship between the count-valued outcome and the finite population. Thus, we consider a joint model for the count-valued outcome and the finite population. When cross-dependence in our joint model can be leveraged to 'improve spatial prediction' we say that the finite population is 'informative.' We model the count given the finite population as binomial and the finite population as negative binomial and use multivariate logit-beta prior distributions. This leads to closed-form expressions of the full-conditional distributions for an efficient Gibbs sampler. We illustrate our model through simulations and our motivating application of ACS poverty estimates. These empirical analyses show the benefits of using our proposed model over the more traditional CS binomial model.

Silicon-thulium hybrid microdisk lasers with low threshold and wide emission wavelength range.

We demonstrate low-threshold and wide emission wavelength range hybrid-integrated silicon-thulium microdisk lasers based on a pulley-coupled design. The resonators are fabricated on a silicon-on-insulator platform using a standard foundry process and the gain medium is deposited using a straightforward, low-temperature post-processing step. We show lasing in 40- and 60-µm diameter microdisks with up to 2.6 mW double-sided output power and bidirectional slope efficiencies of up to 13.4% with respect to 1620 nm pump power launched to the bus waveguides. We observe thresholds less than 1 mW versus on-chip pump power and both single-mode and multimode laser emission spanning across wavelengths from 1825 to 1939nm. These low threshold lasers with emissions over a > 100 nm range open the door to monolithic silicon photonic integrated circuits with broadband optical gain and highly compact and efficient light sources in the emerging ∼1.8-2.0 µm wavelength band.

Ultra-selective, ultra-clean 1D rotating-frame Overhauser effect spectroscopy.

An ultra-selective 1D NMR experiment - GEMSTONE-ROESY - enables clear, unambiguous assignment of ROE signals in the not uncommon situation that traditional selective methods fail. Its usefulness is demonstrated in the analysis of the natural products cyclosporin and lacto-N-difucohexaose I, providing detailed insight into the structures and conformations of these molecules.

Hybrid silicon-tellurium-dioxide DBR resonators coated in PMMA for biological sensing.

We report on silicon waveguide distributed Bragg reflector (DBR) cavities hybridized with a tellurium dioxide (TeO2) cladding and coated in plasma functionalized poly (methyl methacrylate) (PMMA) for label free biological sensors. We describe the device structure and fabrication steps, including reactive sputtering of TeO2 and spin coating and plasma functionalization of PMMA on foundry processed Si chips, as well as the characterization of two DBR designs via thermal, water, and bovine serum albumin (BSA) protein sensing. Plasma treatment on the PMMA films was shown to decrease the water droplet contact angle from ∼70 to ∼35°, increasing hydrophilicity for liquid sensing, while adding functional groups on the surface of the sensors intended to assist with immobilization of BSA molecules. Thermal, water and protein sensing were demonstrated on two DBR designs, including waveguide-connected sidewall (SW) and waveguide-adjacent multi-piece (MP) gratings. Limits of detection of 60 and 300 × 10-4 RIU were measured via water sensing, and thermal sensitivities of 0.11 and 0.13 nm/°C were measured from 25-50 °C for SW and MP DBR cavities, respectively. Plasma treatment was shown to enable protein immobilization and sensing of BSA molecules at a concentration of 2 µg/mL diluted in phosphate buffered saline, demonstrating a ∼1.6 nm resonance shift and subsequent full recovery to baseline after stripping the proteins with sodium dodecyl sulfate for a MP DBR device. These results are a promising step towards active and laser-based sensors using rare-earth-doped TeO2 in silicon photonic circuits, which can be subsequently coated in PMMA and functionalized via plasma treatment for label free biological sensing.

KCa1.1 channels contribute to optogenetically driven post-stimulation silencing in cerebellar molecular layer interneurons.

Using cell-attached recordings from molecular layer interneurons (MLI) of the cerebellar cortex of adult mice expressing channel rhodopsin 2, we show that wide-field optical activation induces an increase in firing rate during illumination and a firing pause when the illumination ends (post-stimulation silencing; PSS). Significant spike rate changes with respect to basal firing rate were observed for optical activations lasting 200 ms and 1 s as well as for 1 s long trains of 10 ms pulses at 50 Hz. For all conditions, the net effect of optical activation on the integrated spike rate is significantly reduced because of PSS. Three lines of evidence indicate that this PSS is due to intrinsic factors. Firstly, PSS is induced when the optical stimulation is restricted to a single MLI using a 405-nm laser delivering a diffraction-limited spot at the focal plane. Secondly, PSS is not affected by block of GABA-A or GABA-B receptors, ruling out synaptic interactions amongst MLIs. Thirdly, PSS is mimicked in whole-cell recording experiments by step depolarizations under current clamp. Activation of Ca-dependent K channels during the spike trains appears as a likely candidate to underlie PSS. Using immunocytochemistry, we find that one such channel type, KCa1.1, is present in the somato-dendritic and axonal compartments of MLIs. In cell-attached recordings, charybdotoxin and iberiotoxin significantly reduce the optically induced PSS, while TRAM-34 does not affect it, suggesting that KCa1.1 channels, but not KCa3.1 channels, contribute to PSS.

Application of the TDFA window in true optical time delay systems.

Recent advances in silicon photonic components operating in the thulium-doped fiber amplifier (TDFA) wavelength regime around 2-µm have shown that these wavelengths hold great promise for on-chip photonic systems. Here we present our work on characterizing a Mach-Zehnder interferometer coupled silicon photonic ring resonator operating in the TDFA window for optical time delay applications. We describe the optical transmission and variable time delay properties of the resonator, including a detailed characterization and comparison of the directional coupler and Mach-Zehnder interferometer base components at both 1930 and 1550 nm wavelengths. The results show tuning of a ring from a 190-ps peak time delay at a resonant extinction ratio of 5.1-dB to a 560-ps peak time delay at an extinction ratio of 11.0-dB, in good agreement with optical models of the device. These results demonstrate significant promise towards the future application of TDFA band devices in optical time delay systems.

SUMMIT: An integrative approach for better transcriptomic data imputation improves causal gene identification.

Genes with moderate to low expression heritability may explain a large proportion of complex trait etiology, but such genes cannot be sufficiently captured in conventional transcriptome-wide association studies (TWASs), partly due to the relatively small available reference datasets for developing expression genetic prediction models to capture the moderate to low genetically regulated components of gene expression. Here, we introduce a method, the Summary-level Unified Method for Modeling Integrated Transcriptome (SUMMIT), to improve the expression prediction model accuracy and the power of TWAS by using a large expression quantitative trait loci (eQTL) summary-level dataset. We apply SUMMIT to the eQTL summary-level data provided by the eQTLGen consortium. Through simulation studies and analyses of genome-wide association study summary statistics for 24 complex traits, we show that SUMMIT improves the accuracy of expression prediction in blood, successfully builds expression prediction models for genes with low expression heritability, and achieves higher statistical power than several benchmark methods. Finally, we conduct a case study of COVID-19 severity with SUMMIT and identify 11 likely causal genes associated with COVID-19 severity.

Sustained deep-tissue voltage recording using a fast indicator evolved for two-photon microscopy.

Genetically encoded voltage indicators are emerging tools for monitoring voltage dynamics with cell-type specificity. However, current indicators enable a narrow range of applications due to poor performance under two-photon microscopy, a method of choice for deep-tissue recording. To improve indicators, we developed a multiparameter high-throughput platform to optimize voltage indicators for two-photon microscopy. Using this system, we identified JEDI-2P, an indicator that is faster, brighter, and more sensitive and photostable than its predecessors. We demonstrate that JEDI-2P can report light-evoked responses in axonal termini of Drosophila interneurons and the dendrites and somata of amacrine cells of isolated mouse retina. JEDI-2P can also optically record the voltage dynamics of individual cortical neurons in awake behaving mice for more than 30 min using both resonant-scanning and ULoVE random-access microscopy. Finally, ULoVE recording of JEDI-2P can robustly detect spikes at depths exceeding 400 µm and report voltage correlations in pairs of neurons.

A novel smartphone-based intervention targeting sleep difficulties in individuals experiencing psychosis: A feasibility and acceptability evaluation.

OBJECTIVES: Cognitive Behavioural Therapy (CBT) is an effective psychological intervention for sleep difficulties and has been used successfully in individuals with psychosis. However, access is restricted due to lack of resources and staff training. Delivering CBT for sleep problems using smartphone technology may facilitate wider access. This study aimed to evaluate the feasibility, acceptability and potential usefulness of a guided, smartphone-based CBT intervention targeting sleep disturbance for individuals with psychosis. DESIGN: Participants with psychosis spectrum diagnoses were recruited to a single-arm, uncontrolled study and engaged with the seven-module programme via smartphone app for six weeks with therapist support. METHOD: Feasibility was assessed by rates of referral, recruitment and completion. Acceptability was assessed by app usage, a satisfaction questionnaire and qualitative analysis of participants' semi-structured interview. Pre- and post-intervention assessment of sleep, psychotic experiences, mood, well-being and functioning was conducted. Mean change confidence intervals were calculated and reported as an indication of usefulness. RESULTS: Fourteen individuals consented to participation, and eleven completed the post-intervention assessment. On average, each participant engaged with 5.6 of 7 available modules. Qualitative feedback indicated the intervention was considered helpful and would be recommended to others. Suggested improvements to app design were provided by participants. Potential treatment benefits were observed for sleep difficulties, and all outcomes considered, except frequency of hallucinatory experiences. CONCLUSIONS: It is feasible and acceptable to deliver therapist-guided CBT for sleep problems by smartphone app for individuals with psychosis. This method provides a low-intensity, accessible intervention, which could be offered more routinely. Further research to determine treatment efficacy is warranted.

Thulium-doped tellurium oxide waveguide amplifier with 7.6 dB net gain on a silicon nitride chip: publisher's note.

This publisher's note contains corrections to Opt. Lett.44, 5788 (2019)OPLEDP0146-959210.1364/OL.44.005788.

A gene-level methylome-wide association analysis identifies novel Alzheimer's disease genes.

MOTIVATION: Transcriptome-wide association studies (TWAS) have successfully facilitated the discovery of novel genetic risk loci for many complex traits, including late-onset Alzheimer's disease (AD). However, most existing TWAS methods rely only on gene expression and ignore epigenetic modification (i.e., DNA methylation) and functional regulatory information (i.e., enhancer-promoter interactions), both of which contribute significantly to the genetic basis of AD. RESULTS: We develop a novel gene-level association testing method that integrates genetically regulated DNA methylation and enhancer-target gene pairs with genome-wide association study (GWAS) summary results. Through simulations, we show that our approach, referred to as the CMO (cross methylome omnibus) test, yielded well controlled type I error rates and achieved much higher statistical power than competing methods under a wide range of scenarios. Furthermore, compared with TWAS, CMO identified an average of 124% more associations when analyzing several brain imaging-related GWAS results. By analyzing to date the largest AD GWAS of 71,880 cases and 383,378 controls, CMO identified six novel loci for AD, which have been ignored by competing methods. AVAILABILITY: Software: https://github.com/ChongWuLab/CMO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An Approach to Incorporate Subsampling into a Generic Bayesian Hierarchical Model.

The goal of this paper is to provide a way for Bayesian statisticians to incorporate subsampling directly into the Bayesian hierarchical model of their choosing without imposing additional restrictive model assumptions. We are motivated by the fact that the rise of "big data" has created difficulties for statisticians to directly apply their methods to big datasets. We introduce a "data subset model" to the popular "data model, process model, and parameter model" framework used to summarize Bayesian hierarchical models. The hyperparameters of the data subset model are specified constructively in that they are chosen such that the implied size of the subset satisfies pre-defined computational constraints. Thus, these hyperparameters effectively calibrate the statistical model to the computer itself to obtain predictions/estimations in a pre-specified amount of time. Several properties of the data subset model are provided including: propriety, partial sufficiency, and semi-parametric properties. Simulated datasets will be used to assess the consequences of subsampling, and results will be presented across different computers to show the effect of the computer on the statistical analysis. Additionally, we provide a joint analysis of a high-dimensional dataset (roughly 10 gigabytes) consisting of 2018 5-year period estimates from the US Census Bureau's Public Use Micro-Sample (PUMS).

Empirical Bayesian Analysis Through the Lens of a Particular Class of Constrained Bayesian Hierarchical Models.

Empirical Bayesian analysis is a well-known approach that incorporates an estimator into a Bayesian analysis. In this article, we offer another approach, which has several useful properties. Our solution is based on the framework introduced by Yekutieli (2012) to account for the variability introduced by selecting parameters. Specifically, we assume that the unknown parameter is contained within a ball centered at an estimator, and the radius is given a prior distribution. We refer to our method as the auxiliary parameter constrained Bayesian hierarchical model (C-BHM). This general framework is particularly exciting as traditional empirical Bayesian analysis and parametric Bayesian analysis can be written as special cases. Hence, this C-BHM represents a unifying framework within the area of Bayesian statistics. Several technical results are provided. Furthermore, we show analytically that one can outperform both empirical and fully Bayesian analysis through the Bayes factor. We illustrate the C-BHM to extend the Fay-Herriot model, which is often used in the survey sampling setting. To demonstrate the usefulness of our method we provide simulations and an illustration to data obtained from the U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) program.