Global morphogenetic flow is accurately predicted by the spatial distribution of myosin motors.

During embryogenesis tissue layers undergo morphogenetic flow rearranging and folding into specific shapes. While developmental biology has identified key genes and local cellular processes, global coordination of tissue remodeling at the organ scale remains unclear. Here, we combine in toto light-sheet microscopy of the Drosophila embryo with quantitative analysis and physical modeling to relate cellular flow with the patterns of force generation during the gastrulation process. We find that the complex spatio-temporal flow pattern can be predicted from the measured meso-scale myosin density and anisotropy using a simple, effective viscous model of the tissue, achieving close to 90% accuracy with one time dependent and two constant parameters. Our analysis uncovers the importance of a) spatial modulation of myosin distribution on the scale of the embryo and b) the non-locality of its effect due to mechanical interaction of cells, demonstrating the need for the global perspective in the study of morphogenetic flow

Quantifying function in the zebrafish embryonic heart: a study on the role of timed mechanical cues

2014 Summer.Congenital heart defects are a relatively common problem, yet the cause is unknown in the large majority of cases. A significant amount of past research has shown that there is a link between altered blood-induced mechanical stress and heart development. However, very little research has been done to examine the effect of altered loading timing. During embryonic development, the heart undergoes a drastic change in morphology from its original valveless tube structure to a complete multi-chambered pump with valves. Blood flow dynamics are consequently altered significantly as well. Given the changes occurring through this period, it is hypothesized that significant and persistent decreases in heart function occur when cardiac loading is altered during certain time windows of early development. The main objectives of this work were to (1) develop a methodology to quantify heart function in the embryonic zebrafish from high-speed bright field images, (2) develop a model for temporary and noninvasive alteration of cardiac loading, and (3) apply the methodology to normal and treated embryos to determine whether certain time windows of altered loading are more impactful than others. Results indicated that altered loading during the tube and early looping stages of development produce persistent changes in heart morphology along with accompanying decreases in cardiac function. Altered loading during late cardiac looping resulted in temporary changes in function which did not persist through the latest time point measured. This work has produced extensive tools for quantifying heart function from high speed images and presents a new model for altered cardiac loading in the zebrafish. Results support the hypothesis that the heart is more sensitive to altered loading during certain windows in development. This provides new insight into how congenital defects may develop and sets the stage for future experiments investigating the effects of altered loading on heart development

Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements

In recent years a vast amount of glacier surface velocity data from satellite imagery has emerged based on correlation between repeat images. Thereby, much emphasis has been put on the fast processing of large data volumes and products with complete spatial coverage. The metadata of such measurements are often highly simplified when the measurement precision is lumped into a single number for the whole dataset, although the error budget of image matching is in reality neither isotropic nor constant over the whole velocity field. The spread of the correlation peak of individual image offset measurements is dependent on the image structure and the non-uniform flow of the ice and is used here to extract a proxy for measurement uncertainty. A quantification of estimation error or dispersion for each individual velocity measurement can be important for the inversion of, for instance, rheology, ice thickness and/or bedrock friction. Errors in the velocity data can propagate into derived results in a complex and exaggerating way, making the outcomes very sensitive to velocity noise and outliers. Here, we present a computationally fast method to estimate the matching precision of individual displacement measurements from repeat imaging data, focusing on satellite data. The approach is based upon Gaussian fitting directly on the correlation peak and is formulated as a linear least-squares estimation, making its implementation into current pipelines straightforward. The methodology is demonstrated for Sermeq Kujalleq (Jakobshavn Isbræ), Greenland, a glacier with regions of strong shear flow and with clearly oriented crevasses, and Malaspina Glacier, Alaska. Directionality within an image seems to be the dominant factor influencing the correlation dispersion. In our cases these are crevasses and moraine bands, while a relation to differential flow, such as shear, is less pronounced on the correlation spread.</p

Spatial Frequency-Based Analysis of Mean Red Blood Cell Speed in Single Microvessels: Investigation of Microvascular Perfusion in Rat Cerebral Cortex

BACKGROUND: Our previous study has shown that prenatal exposure to X-ray irradiation causes cerebral hypo-perfusion during the postnatal development of central nervous system (CNS). However, the source of the hypo-perfusion and its impact on the CNS development remains unclear. The present study developed an automatic analysis method to determine the mean red blood cell (RBC) speed through single microvessels imaged with two-photon microscopy in the cerebral cortex of rats prenatally exposed to X-ray irradiation (1.5 Gy). METHODOLOGY/PRINCIPAL FINDINGS: We obtained a mean RBC speed (0.9±0.6 mm/sec) that ranged from 0.2 to 4.4 mm/sec from 121 vessels in the radiation-exposed rats, which was about 40% lower than that of normal rats that were not exposed. These results were then compared with the conventional method for monitoring microvascular perfusion using the arteriovenous transit time (AVTT) determined by tracking fluorescent markers. A significant increase in the AVTT was observed in the exposed rats (1.9±0.6 sec) as compared to the age-matched non-exposed rats (1.2±0.3 sec). The results indicate that parenchyma capillary blood velocity in the exposed rats was approximately 37% lower than in non-exposed rats. CONCLUSIONS/SIGNIFICANCE: The algorithm presented is simple and robust relative to monitoring individual RBC speeds, which is superior in terms of noise tolerance and computation time. The demonstrative results show that the method developed in this study for determining the mean RBC speed in the spatial frequency domain was consistent with the conventional transit time method

Ultrasound transmission tomography : a low-cost realization

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Mapping Atomic Motions with Electrons: Toward the Quantum Limit to Imaging Chemistry

Recent advances in ultrafast electron and X-ray diffraction have pushed imaging of structural dynamics into the femtosecond time domain, that is, the fundamental time scale of atomic motion. New physics can be reached beyond the scope of traditional diffraction or reciprocal space imaging. By exploiting the high time resolution, it has been possible to directly observe the collapse of nearly innumerable possible nuclear motions to a few key reaction modes that direct chemistry. It is this reduction in dimensionality in the transition state region that makes chemistry a transferable concept, with the same class of reactions being applicable to synthetic strategies to nearly arbitrary levels of complexity. The ability to image the underlying key reaction modes has been achieved with resolution to relative changes in atomic positions to better than 0.01 Å, that is, comparable to thermal motions. We have effectively reached the fundamental space-time limit with respect to the reaction energetics and imaging the acting forces. In the process of ensemble measured structural changes, we have missed the quantum aspects of chemistry. This perspective reviews the current state of the art in imaging chemistry in action and poses the challenge to access quantum information on the dynamics. There is the possibility with the present ultrabright electron and X-ray sources, at least in principle, to do tomographic reconstruction of quantum states in the form of a Wigner function and density matrix for the vibrational, rotational, and electronic degrees of freedom. Accessing this quantum information constitutes the ultimate demand on the spatial and temporal resolution of reciprocal space imaging of chemistry. Given the much shorter wavelength and corresponding intrinsically higher spatial resolution of current electron sources over X-rays, this Perspective will focus on electrons to provide an overview of the challenge on both the theory and the experimental fronts to extract the quantum aspects of molecular dynamics

High-resolution characterization of near-surface structures by surface-wave inversions: From dispersion curve to full waveform

Surface waves are widely used in near-surface geophysics and provide a non-invasive way to determine near-surface structures. By extracting and inverting dispersion curves to obtain local 1D S-wave velocity profiles, multichannel analysis of surface waves (MASW) has been proven as an efficient way to analyze shallow-seismic surface waves. By directly inverting the observed waveforms, full-waveform inversion (FWI) provides another feasible way to use surface waves in reconstructing near-surface structures. This paper provides a state of the art on MASW and shallow-seismic FWI, and a comparison of both methods. A two-parameter numerical test is performed to analyze the nonlinearity of MASW and FWI, including the classical, the multiscale, the envelope-based, and the amplitude-spectrum-based FWI approaches. A checkerboard model is used to compare the resolution of MASW and FWI. These numerical examples show that classical FWI has the highest nonlinearity and resolution among these methods, while MASW has the lowest nonlinearity and resolution. The modified FWI approaches have an intermediate nonlinearity and resolution between classical FWI and MASW. These features suggest that a sequential application of MASW and FWI could provide an efficient hierarchical way to delineate near-surface structures. We apply the sequential-inversion strategy to two field data sets acquired in Olathe, Kansas, USA, and Rheinstetten, Germany, respectively. We build a 1D initial model by using MASW and then apply the multiscale FWI to the data. High-resolution 2D S-wave velocity images are obtained in both cases, whose reliabilities are proven by borehole data and a GPR profile, respectively. It demonstrates the effectiveness of combining MASW and FWI for high-resolution imaging of near-surface structures

Flame front propagation velocity measurement and in-cylinder combustion reconstruction using POET

The objective of this thesis is to develop an intelligent diagnostic technique POET (Passive Optical Emission Tomography) for the investigation of in cylinder combustion chemiluminescence. As a non-intrusive optical system, the POET system employs 40 fibre optic cables connected to 40 PMTs (Photo Multiplier Tube) to monitor the combustion process and flame front propagation in a modified commercial OHV (Over Head Valve) Pro 206 IC engine. The POET approach overcomes several limitations of present combustion research methods using a combination of fibre optic detection probes, photomultipliers and a tomographic diagnostics. The fibre optic probes are placed on a specially designed cylinder head gasket for non-invasively inserting cylinder. Each independent probe can measure the turbulent chemiluminescence of combustion flame front at up to 20 kHz. The resultant intensities can then be gathered tomographically using MART (Multiplicative Algebraic Reconstruction Technique) software to reconstruct an image of the complete flame-front. The approach is essentially a lensless imaging technique, which has the advantage of not requiring a specialized engine construction with conventional viewing ports to visualize the combustion image. The fibre optic system, through the use of 40, 2m long thermally isolated fibre optic cables can withstand combustion temperatures and is immune from electronic noise, typically generated by the spark plug. The POET system uses a MART tomographic methodology to reconstruct the turbulent combustion process. The data collected has been reconstructed to produce a temporal and spatial image of the combustion flame front. The variations of lame turbulence are monitored by sequences of reconstructed images. Therefore, the POET diagnostic technique reduces the complications of classic flame front propagation measurement systems and successfully demonstrates the in-cylinder combustion process. In this thesis, a series of calibration exercises have been performed to ensure that the photomultipliers of the POET system have sufficient temporal and spatial resolution to quantitatively map the flow velocity turbulence and chemiluminescence of the flame front. In the results, the flame has been analyzed using UV filters and blue filters to monitor the modified natural gas fuel engine. The flame front propagation speed has been evaluated and it is, on average, 12 m/s at 2280 rpm. Sequences of images have been used to illustrate the combustion explosion process at different rpm

Reconstructing the Hemodynamic Response Function via a Bimodal Transformer

The relationship between blood flow and neuronal activity is widely recognized, with blood flow frequently serving as a surrogate for neuronal activity in fMRI studies. At the microscopic level, neuronal activity has been shown to influence blood flow in nearby blood vessels. This study introduces the first predictive model that addresses this issue directly at the explicit neuronal population level. Using in vivo recordings in awake mice, we employ a novel spatiotemporal bimodal transformer architecture to infer current blood flow based on both historical blood flow and ongoing spontaneous neuronal activity. Our findings indicate that incorporating neuronal activity significantly enhances the model's ability to predict blood flow values. Through analysis of the model's behavior, we propose hypotheses regarding the largely unexplored nature of the hemodynamic response to neuronal activity