Video-rate volumetric neuronal imaging using 3D targeted illumination

Fast volumetric microscopy is required to monitor large-scale neural ensembles with high spatio-temporal resolution. Widefield fluorescence microscopy can image large 2D fields of view at high resolution and speed while remaining simple and costeffective. A focal sweep add-on can further extend the capacity of widefield microscopy by enabling extended-depth-of-field (EDOF) imaging, but suffers from an inability to reject out-of-focus fluorescence background. Here, by using a digital micromirror device to target only in-focus sample features, we perform EDOF imaging with greatly enhanced contrast and signal-to-noise ratio, while reducing the light dosage delivered to the sample. Image quality is further improved by the application of a robust deconvolution algorithm. We demonstrate the advantages of our technique for in vivo calcium imaging in the mouse brain.This work was funded by the National Institutes of Health (R21EY026310) and the National Science Foundation (CBET-1508988). The authors wish to thank E. McCarthy and Prof. M.J. Baum for providing mouse brain slices used in this manuscript, and A. I. Mohammed for providing in vivo mouse brain samples in the early stages of this work. (R21EY026310 - National Institutes of Health; CBET-1508988 - National Science Foundation)Published versio

Experimental analysis of air vortex Impingement through porous screens

This paper presents the experimental analysis of air flow vortex propagation through porous screens. This study is conducted by a new and unique experimental setup for ve- locity measurements and visualization of air vortex interac- tion with porous screen. A custom-made, high-precision vortex generator provides a variety of velocity profiles for vortex generation with an unprecedented level of precision. The flow fields are captured with the use of a fog gener- ator and a high-speed CCD camera. The porous screens are constructed out of acrylic rods with various orientations, thickness, and porosities from rod separation. The results presented in this paper show the effect of porosity and air injection velocity on the behavior of air flow (separation, accumulation), and the transport phenomena of vortex flow while interacting with porous screens

Automatic cell segmentation by adaptive thresholding (ACSAT) for large-scale calcium imaging datasets

Advances in calcium imaging have made it possible to record from an increasingly larger number of neurons simultaneously. Neuroscientists can now routinely image hundreds to thousands of individual neurons. An emerging technical challenge that parallels the advancement in imaging a large number of individual neurons is the processing of correspondingly large datasets. One important step is the identification of individual neurons. Traditional methods rely mainly on manual or semimanual inspection, which cannot be scaled for processing large datasets. To address this challenge, we focused on developing an automated segmentation method, which we refer to as automated cell segmentation by adaptive thresholding (ACSAT). ACSAT works with a time-collapsed image and includes an iterative procedure that automatically calculates global and local threshold values during successive iterations based on the distribution of image pixel intensities. Thus, the algorithm is capable of handling variations in morphological details and in fluorescence intensities in different calcium imaging datasets. In this paper, we demonstrate the utility of ACSAT by testing it on 500 simulated datasets, two wide-field hippocampus datasets, a wide-field striatum dataset, a wide-field cell culture dataset, and a two-photon hippocampus dataset. For the simulated datasets with truth, ACSAT achieved >80% recall and precision when the signal-to-noise ratio was no less than ∼24 dB.DP2 NS082126 - NINDS NIH HHSPublished versio

Discrepancies in autologous bone marrow stem cell trials and enhancement of ejection fraction (DAMASCENE): weighted regression and meta-analysis

Objective To investigate whether discrepancies in trials of use of bone marrow stem cells in patients with heart disease account for the variation in reported effect size in improvement of left ventricular function. Design Identification and counting of factual discrepancies in trial reports, and sample size weighted regression against therapeutic effect size. Meta-analysis of trials that provided sufficient information. Data sources PubMed and Embase from inception to April 2013. Eligibility for selecting studies Randomised controlled trials evaluating the effect of autologous bone marrow stem cells for heart disease on mean left ventricular ejection fraction. Results There were over 600 discrepancies in 133 reports from 49 trials. There was a significant association between the number of discrepancies and the reported increment in EF with bone marrow stem cell therapy (Spearman’s r=0.4, P=0.005). Trials with no discrepancies were a small minority (five trials) and showed a mean EF effect size of −0.4%. The 24 trials with 1-10 discrepancies showed a mean effect size of 2.1%. The 12 with 11-20 discrepancies showed a mean effect of size 3.0%. The three with 21-30 discrepancies showed a mean effect size of 5.7%. The high discrepancy group, comprising five trials with over 30 discrepancies each, showed a mean effect size of 7.7%. Conclusions Avoiding discrepancies is difficult but is important because discrepancy count is related to effect size. The mechanism is unknown but should be explored in the design of future trials because in the five trials without discrepancies the effect of bone marrow stem cell therapy on ejection fraction is zero

Kepler Exoplanet Candidate Host Stars are Preferentially Metal Rich

We find that Kepler exoplanet candidate (EC) host stars are preferentially metal-rich, including the low-mass stellar hosts of small-radius ECs. The last observation confirms a tentative hint that there is a correlation between the metallicity of low-mass stars and the presence of low-mass and small-radius exoplanets. In particular, we compare the J-H--g-r color-color distribution of Kepler EC host stars with a control sample of dwarf stars selected from the ~150,000 stars observed during Q1 and Q2 of the Kepler mission but with no detected planets. We find that at J-H = 0.30 characteristic of solar-type stars, the average g-r color of stars that host giant ECs is 4-sigma redder than the average color of the stars in the control sample. At the same time, the average g-r color of solar-type stars that host small-radius ECs is indistinguishable from the average color of the stars in the control sample. In addition, we find that at J-H = 0.62 indicative of late K dwarfs, the average g-r color of stars that host small-radius ECs is 4-sigma redder than the average color of the stars in the control sample. These offsets are unlikely to be caused by differential reddening, age differences between the two populations, or the presence of giant stars in the control sample. Stellar models suggest that the first color offset is due to a 0.2 dex enhancement in [Fe/H] of the giant EC host population at M_star = 1 M_Sun, while Sloan photometry of M 67 and NGC 6791 suggests that the second color offset is due to a similar [Fe/H] enhancement of the small-radius EC host population at M_star = 0.7 M_Sun. These correlations are a natural consequence of the core-accretion model of planet formation.Comment: 15 pages, 8 figures, and 1 table in emulateapj format; accepted for publication in Ap

Massive Young Stellar Objects in the Galactic Center. I. Spectroscopic Identification from Spitzer/IRS Observations

We present results from our spectroscopic study, using the Infrared Spectrograph (IRS) onboard the Spitzer Space Telescope, designed to identify massive young stellar objects (YSOs) in the Galactic Center (GC). Our sample of 107 YSO candidates was selected based on IRAC colors from the high spatial resolution, high sensitivity Spitzer/IRAC images in the Central Molecular Zone (CMZ), which spans the central ~300 pc region of the Milky Way Galaxy. We obtained IRS spectra over 5um to 35um using both high- and low-resolution IRS modules. We spectroscopically identify massive YSOs by the presence of a 15.4um shoulder on the absorption profile of 15um CO2 ice, suggestive of CO2 ice mixed with CH3OH ice on grains. This 15.4um shoulder is clearly observed in 16 sources and possibly observed in an additional 19 sources. We show that 9 massive YSOs also reveal molecular gas-phase absorption from CO2, C2H2, and/or HCN, which traces warm and dense gas in YSOs. Our results provide the first spectroscopic census of the massive YSO population in the GC. We fit YSO models to the observed spectral energy distributions and find YSO masses of 8 - 23 Msun, which generally agree with the masses derived from observed radio continuum emission. We find that about 50% of photometrically identified YSOs are confirmed with our spectroscopic study. This implies a preliminary star formation rate of ~0.07 Msun/yr at the GC.Comment: Accepted for publication in Ap

The Na+ Channel Inactivation Gate Is a Molecular Complex: A Novel Role of the COOH-terminal Domain

Electrical activity in nerve, skeletal muscle, and heart requires finely tuned activity of voltage-gated Na+ channels that open and then enter a nonconducting inactivated state upon depolarization. Inactivation occurs when the gate, the cytoplasmic loop linking domains III and IV of the α subunit, occludes the open pore. Subtle destabilization of inactivation by mutation is causally associated with diverse human disease. Here we show for the first time that the inactivation gate is a molecular complex consisting of the III-IV loop and the COOH terminus (C-T), which is necessary to stabilize the closed gate and minimize channel reopening. When this interaction is disrupted by mutation, inactivation is destabilized allowing a small, but important, fraction of channels to reopen, conduct inward current, and delay cellular repolarization. Thus, our results demonstrate for the first time that physiologically crucial stabilization of inactivation of the Na+ channel requires complex interactions of intracellular structures and indicate a novel structural role of the C-T domain in this process

Mesozoic–Tertiary exhumation history of the Altai Mountains, northern Xinjiang, China: New constraints from apatite fission track data

This study uses apatite fission track (FT) analysis to constrain the exhumation history of bedrock samples collected from the Altai Mountains in northern Xinjiang, China. Samples were collected as transects across the main structures related to Palaeozoic crustal accretion events. FT results and modeling identify three stages in sample cooling history spanning the Mesozoic and Tertiary. Stage one records rapid cooling to the low temperature part of the fission track partial annealing zone circa 70 ± 10 °C. Stage two, records a period of relative stability with little if any cooling taking place between 75 and 25–20 Ma suggesting the Altai region had been reduced to an area of low relief. Support for this can be found in the adjacent Junngar Basin that received little if any sediment during this interval. Final stage cooling took place in the Miocene at an accelerated rate bringing the sampled rocks to the Earth's surface. This last stage, linked to the far field effects of the Himalayan collision, most likely generated the surface uplift and relief that define the present-day Altai Mountains

Object detection at level crossing using deep learning

Multiple projects within the rail industry across different regions have been initiated to address the issue of over-population. These expansion plans and upgrade of technologies increases the number of intersections, junctions, and level crossings. A level crossing is where a railway line is crossed by a road or right of way on the level without the use of a tunnel or bridge. Level crossings still pose a significant risk to the public, which often leads to serious accidents between rail, road, and footpath users and the risk is dependent on their unpredictable behavior. For Great Britain, there were three fatalities and 385 near misses at level crossings in 2015–2016. Furthermore, in its annual safety report, the Rail Safety and Standards Board (RSSB) highlighted the risk of incidents at level crossings during 2016/17 with a further six fatalities at level crossings including four pedestrians and two road vehicles. The relevant authorities have suggested an upgrade of the existing sensing system and the integration of new novel technology at level crossings. The present work addresses this key issue and discusses the current sensing systems along with the relevant algorithms used for post-processing the information. The given information is adequate for a manual operator to make a decision or start an automated operational cycle. Traditional sensors have certain limitations and are often installed as a “single sensor”. The single sensor does not provide sufficient information; hence another sensor is required. The algorithms integrated with these sensing systems rely on the traditional approach, where background pixels are compared with new pixels. Such an approach is not effective in a dynamic and complex environment. The proposed model integrates deep learning technology with the current Vision system (e.g., CCTV to detect and localize an object at a level crossing). The proposed sensing system should be able to detect and localize particular objects (e.g., pedestrians, bicycles, and vehicles at level crossing areas.) The radar system is also discussed for a “two out of two” logic interlocking system in case of fail-mechanism. Different techniques to train a deep learning model are discussed along with their respective results. The model achieved an accuracy of about 88% from the MobileNet model for classification and a loss metric of 0.092 for object detection. Some related future work is also discussed