Enlarged Field of View in Spatially Modulated Selective Volume Illumination Microscopy.

Three-dimensional fluorescence microscopy is a key technology for inspecting biological samples, ranging from single cells to entire organisms. We recently proposed a novel approach called spatially modulated Selective Volume Illumination Microscopy (smSVIM) to suppress illumination artifacts and to reduce the required number of measurements using an LED source. Here, we discuss a new strategy based on smSVIM for imaging large transparent specimens or voluminous chemically cleared tissues. The strategy permits steady mounting of the sample, achieving uniform resolution over a large field of view thanks to the synchronized motion of the illumination lens and the camera rolling shutter. Aided by a tailored deconvolution method for image reconstruction, we demonstrate significant improvement of the resolution at different magnification using samples of varying sizes and spatial features.

Blind deconvolution in autocorrelation inversion for multiview light-sheet microscopy.

Combining the information coming from multiview acquisitions is a problem of great interest in light-sheet microscopy. Aligning the views and increasing the resolution of their fusion can be challenging, especially if the setup is not fully calibrated. Here, we tackle these issues by proposing a new reconstruction method based on autocorrelation inversion that avoids alignment procedures. On top of this, we add a blind deconvolution step to improve the resolution of the final reconstruction. Our method permits us to achieve inherently aligned, highly resolved reconstructions while, at the same time, estimating the unknown point-spread function of the system. RESEARCH HIGHLIGHTS: We tackle the problem of multiview light-sheet deconvolution with a blind approach of autocorrelation inversion Our method recovers the object and PSF, requires no alignment and calibration, and enhances the reconstruction of the specimen.

Compressed sensing in fluorescence microscopy.

Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from under-sampled data with respect to the Nyquist criterium. CS exploits sparsity constraints based on the knowledge of prior information, relative to the structure of the object in the spatial or other domains. It is commonly used in image and video compression as well as in scientific and medical applications, including computed tomography and magnetic resonance imaging. In the field of fluorescence microscopy, it has been demonstrated to be valuable for fast and high-resolution imaging, from single-molecule localization, super-resolution to light-sheet microscopy. Furthermore, CS has found remarkable applications in the field of mesoscopic imaging, facilitating the study of small animals' organs and entire organisms. This review article illustrates the working principles of CS, its implementations in optical imaging and discusses several relevant uses of CS in the field of fluorescence imaging from super-resolution microscopy to mesoscopy.

Simultaneous imaging of ER and cytosolic Ca2+ dynamics reveals long-distance ER Ca2+ waves in plants.

Calcium ions (Ca2+) play a key role in cell signaling across organisms. In plants, a plethora of environmental and developmental stimuli induce specific Ca2+ increases in the cytosol as well as in different cellular compartments including the endoplasmic reticulum (ER). The ER represents an intracellular Ca2+ store that actively accumulates Ca2+ taken up from the cytosol. By exploiting state-of-the-art genetically encoded Ca2+ indicators, specifically the ER-GCaMP6-210 and R-GECO1, we report the generation and characterization of an Arabidopsis (Arabidopsis thaliana) line that allows for simultaneous imaging of Ca2+ dynamics in both the ER and cytosol at different spatial scales. By performing analyses in single cells, we precisely quantified (1) the time required by the ER to import Ca2+ from the cytosol into the lumen and (2) the time required to observe a cytosolic Ca2+ increase upon the pharmacological inhibition of the ER-localized P-Type IIA Ca2+-ATPases. Furthermore, live imaging of mature, soil-grown plants revealed the existence of a wounding-induced, long-distance ER Ca2+ wave propagating in injured and systemic rosette leaves. This technology enhances high-resolution analyses of intracellular Ca2+ dynamics at the cellular level and in adult organisms and paves the way to develop new methodologies aimed at defining the contribution of subcellular compartments in Ca2+ homeostasis and signaling.

Beyond multi view deconvolution for inherently aligned fluorescence tomography.

In multi-view fluorescence microscopy, each angular acquisition needs to be aligned with care to obtain an optimal volumetric reconstruction. Here, instead, we propose a neat protocol based on auto-correlation inversion, that leads directly to the formation of inherently aligned tomographies. Our method generates sharp reconstructions, with the same accuracy reachable after sub-pixel alignment but with improved point-spread-function. The procedure can be performed simultaneously with deconvolution further increasing the reconstruction resolution.

Spinning pupil aberration measurement for anisoplanatic deconvolution.

The aberrations in an optical microscope are commonly measured and corrected at one location in the field of view, within the so-called isoplanatic patch. Full-field correction is desirable for high-resolution imaging of large specimens. Here we present, to the best of our knowledge, a novel wavefront detector, based on pupil sampling with subapertures, measuring the aberrated wavefront phase at each position of the specimen. Based on this measurement, we propose a region-wise deconvolution that provides an anisoplanatic reconstruction of the sample image. Our results indicate that the measurement and correction of the aberrations can be performed in a wide-field fluorescence microscope over its entire field of view.

Deconvolved Image Restoration From Auto-Correlations.

The recovery of a real signal from its auto-correlation is a wide-spread problem in computational imaging, and it is equivalent to retrieve the phase linked to a given Fourier modulus. Image-deconvolution, on the other hand, is a funda- mental aspect to take into account when we aim at increasing the resolution of blurred signals. These problems are addressed separately in a large number of experimental situations, ranging from adaptive astronomy to optical microscopy. Here, instead, we tackle both at the same time, performing auto-correlation inversion while deconvolving the current object estimation. To this end, we propose a method based on I -divergence optimization, turning our formalism into an iterative scheme inspired by Bayesian-based approaches. We demonstrate the method by recovering sharp signals from blurred auto-correlations, regardless of whether the blurring acts in auto-correlation, object, or Fourier domain.

Reliability of fNIRS for noninvasive monitoring of brain function and emotion in sheep.

The aim of this work was to critically assess if functional near infrared spectroscopy (fNIRS) can be profitably used as a tool for noninvasive recording of brain functions and emotions in sheep. We considered an experimental design including advances in instrumentation (customized wireless multi-distance fNIRS system), more accurate physical modelling (two-layer model for photon diffusion and 3D Monte Carlo simulations), support from neuroanatomical tools (positioning of the fNIRS probe by MRI and DTI data of the very same animals), and rigorous protocols (motor task, startling test) for testing the behavioral response of freely moving sheep. Almost no hemodynamic response was found in the extra-cerebral region in both the motor task and the startling test. In the motor task, as expected we found a canonical hemodynamic response in the cerebral region when sheep were walking. In the startling test, the measured hemodynamic response in the cerebral region was mainly from movement. Overall, these results indicate that with the current setup and probe positioning we are primarily measuring the motor area of the sheep brain, and not probing the too deeply located cortical areas related to processing of emotions.

Hidden phase-retrieved fluorescence tomography.

Fluorescence tomography is a well-established methodology able to provide structural and functional information on the measured object. At optical wavelengths, the unpredictable scattering of light is often considered a problem to overcome, rather than a feature to exploit. Advances in disordered photonics have shed new light on possibilities offered by opaque materials, treating them as autocorrelation lenses able to create images and focus light. In this Letter, we propose tomography through disorder, introducing a modified Fourier-slice theorem, the cornerstone of the computed tomography, aiming to reconstruct a three-dimensional fluorescent sample hidden behind an opaque curtain.

Hyperuniformity in amorphous speckle patterns.

Hyperuniform structures possess the ability to confine and drive light, although their fabrication is extremely challenging. Here we demonstrate that speckle patterns obtained by a superposition of randomly arranged sources of Bessel beams can be used to generate hyperunifrom scalar fields. By exploiting laser light tailored with a spatial filter, we experimentally produce (without requiring any computational power) a speckle pattern possessing maxima at locations corresponding to a hyperuniform distribution. By properly filtering out intensity fluctuation from the same speckle pattern, it is possible to retrieve an intensity profile satisfying the hyperuniformity requirements. Our findings are supported by extensive numerical simulations.

Noninvasive optical estimation of CSF thickness for brain-atrophy monitoring.

Dementia disorders are increasingly becoming sources of a broad range of problems, strongly interfering with the normal daily tasks of a growing number of individuals. Such neurodegenerative diseases are often accompanied with progressive brain atrophy that, at late stages, leads to drastically reduced brain dimensions. Currently, this structural change could be followed with X-ray computed tomography (XCT) or magnetic resonance imaging (MRI), but they share numerous disadvantages in terms of usability, invasiveness and costs. In this work, we aim to retrieve information concerning the brain-atrophy stage and its evolution, proposing a novel approach based on non-invasive time-resolved near infra-red (tr-NIR) measurements. For this purpose, we created a set of virtual human-head atlases in which we eroded the brain as it would happen in a clinical brain-atrophy progression. These realistic meshes were used to simulate a longitudinal tr-NIR study, investigating the effects of an increased amount of cerebral spinal fluid (CSF) in the photon diffusion. The analysis of late photons in the time-resolved reflectance curve-obtained via accurate Monte Carlo simulations-exhibited peculiar slope-changes upon CSF layer increase. The visibility of the effect under several measurement conditions suggested good sensitivity to CSF variation, even in the case of real measurement and under different geometrical models. The robustness of the results might promote the technique as a potential indicator of the dementia progression, relying only on fast and non-invasive optical observations.

Optical projection tomography via phase retrieval algorithms.

We describe a computational method for accurate, quantitative tomographic reconstructions in Optical Projection Tomography, based on phase retrieval algorithms. Our method overcomes limitations imposed by light scattering in opaque tissue samples under the memory effect regime, as well as reduces artifacts due to mechanical movements, misalignments or vibrations. We make use of Gerchberg-Saxton algorithms, calculating first the autocorrelation of the object and then retrieving the associated phase under four numerically simulated measurement conditions. By approaching the task in such a way, we avoid the projection alignment procedure, exploiting the fact that the autocorrelation sinogram is always aligned and centered. We thus propose two new, projection-based, tomographic imaging flowcharts that allow registration-free imaging of opaque biological specimens and unlock three-dimensional tomographic imaging of hidden objects. Two main reconstruction approaches are discussed in the text, focusing on their efficiency in the tomographic retrieval and discussing their applicability under four different numerical experiments.

Phase-Retrieved Tomography enables Mesoscopic imaging of Opaque Tumor Spheroids.

We present a new Phase-Retrieved Tomography (PRT) method to radically improve mesoscopic imaging at regimes beyond one transport mean-free-path and achieve high resolution, uniformly throughout the volume of opaque samples. The method exploits multi-view acquisition in a hybrid Selective Plane Illumination Microscope (SPIM) and Optical Projection Tomography (OPT) setup and a three-dimensional Gerchberg-Saxton phase-retrieval algorithm applied in 3D through the autocorrelation sinogram. We have successfully applied this innovative protocol to image optically dense 3D cell cultures in the form of tumor spheroids, highly versatile models to study cancer behavior and response to chemotherapy. We have thus achieved a significant improvement of resolution in depths not yet accessible with the currently used methods in SPIM/OPT, while overcoming all registration and alignment problems inherent to these techniques.

Fluorescence Diffusion in the Presence of Optically Clear Tissues in a Mouse Head Model.

Diffuse Optical Tomography commonly neglects or assumes as insignificant the presence of optically clear regions in biological tissues, estimating their contribution as a small perturbation to light transport. The inaccuracy introduced by this practice is examined in detail in the context of a complete, based on realistic geometry, virtual fluorescence Diffuse Optical Tomography experiment where a mouse head is imaged in the presence of cerebral spinal fluid. Despite the small thickness of such layer, we point out that an error is introduced when neglecting it from the model with possibly reduction in the accuracy of the reconstruction and localization of the fluorescence distribution within the brain. The results obtained in the extensive study presented here suggest that fluorescence diffuse neuroimaging studies can be improved in terms of quantitative and qualitative reconstruction by accurately taking into account optically transparent regions especially in the cases where the reconstruction is aided by the prior knowledge of the structural geometry of the specimen. Thus, this has only recently become an affordable choice, thanks to novel computation paradigms that allow to run Monte Carlo photon propagation on a simple graphic card, hence speeding up the process a thousand folds compared to CPU-based solutions.

Self-assembly of mesogenic bent-core DNA nanoduplexes.

Short cylinder-like DNA duplexes, comprising 6 to 20 base pairs, self-assemble into semi-flexible chains, due to coaxial stacking interactions between their blunt ends. The mutual alignment of these chains gives rise to macroscopically orientationally ordered liquid crystal phases. Interestingly, experiments show that the isotropic-nematic phase boundary is sequence-dependent. We perform all-atom simulations of several sequences to gain insights into the structural properties of the duplex and correlate the resulting geometric properties with the observed location of the isotropic-nematic phase boundary. We identify in the duplex bending the key parameter for explaining the sequence dependence, suggesting that DNA duplexes can be assimilated to bent-core mesogens. We also develop a coarse-grained model for the different DNA duplexes to evaluate in detail how bending affects the persistence length and excluded volume of the aggregates. This information is fed into a recently developed formalism to predict the isotropic-nematic phase boundary for bent-core mesogens. The theoretical results agree with the experimental observations.