Mesoscale volumetric light-field (MesoLF) imaging of neuroactivity across cortical areas at 18 Hz.

Various implementations of mesoscopes provide optical access for calcium imaging across multi-millimeter fields of view in the mammalian brain; however, capturing the activity of the neuronal population within such fields of view near-simultaneously and in a volumetric fashion has remained challenging as approaches for imaging scattering brain tissues typically are based on sequential acquisition. Here we present a modular, mesoscale light-field (MesoLF) imaging hardware and software solution that allows recording from thousands of neurons within volumes of ⌀ 4 × 0.2 mm, located at up to 350 µm depth in the mouse cortex, at 18 volumes per second and an effective voxel rate of ~40 megavoxels per second. Using our optical design and computational approach we show recording of ~10,000 neurons across multiple cortical areas in mice using workstation-grade computing resources.

Rapid detection of neurons in widefield calcium imaging datasets after training with synthetic data.

Widefield microscopy can provide optical access to multi-millimeter fields of view and thousands of neurons in mammalian brains at video rate. However, tissue scattering and background contamination results in signal deterioration, making the extraction of neuronal activity challenging, laborious and time consuming. Here we present our deep-learning-based widefield neuron finder (DeepWonder), which is trained by simulated functional recordings and effectively works on experimental data to achieve high-fidelity neuronal extraction. Equipped with systematic background contribution priors, DeepWonder conducts neuronal inference with an order-of-magnitude-faster speed and improved accuracy compared with alternative approaches. DeepWonder removes background contaminations and is computationally efficient. Specifically, DeepWonder accomplishes 50-fold signal-to-background ratio enhancement when processing terabytes-scale cortex-wide functional recordings, with over 14,000 neurons extracted in 17 h.

Bio-friendly long-term subcellular dynamic recording by self-supervised image enhancement microscopy.

Fluorescence microscopy has become an indispensable tool for revealing the dynamic regulation of cells and organelles. However, stochastic noise inherently restricts optical interrogation quality and exacerbates observation fidelity when balancing the joint demands of high frame rate, long-term recording and low phototoxicity. Here we propose DeepSeMi, a self-supervised-learning-based denoising framework capable of increasing signal-to-noise ratio by over 12 dB across various conditions. With the introduction of newly designed eccentric blind-spot convolution filters, DeepSeMi effectively denoises images with no loss of spatiotemporal resolution. In combination with confocal microscopy, DeepSeMi allows for recording organelle interactions in four colors at high frame rates across tens of thousands of frames, monitoring migrasomes and retractosomes over a half day, and imaging ultra-phototoxicity-sensitive Dictyostelium cells over thousands of frames. Through comprehensive validations across various samples and instruments, we prove DeepSeMi to be a versatile and biocompatible tool for breaking the shot-noise limit.

Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised denoising.

Calcium imaging has transformed neuroscience research by providing a methodology for monitoring the activity of neural circuits with single-cell resolution. However, calcium imaging is inherently susceptible to detection noise, especially when imaging with high frame rate or under low excitation dosage. Here we developed DeepCAD, a self-supervised deep-learning method for spatiotemporal enhancement of calcium imaging data that does not require any high signal-to-noise ratio (SNR) observations. DeepCAD suppresses detection noise and improves the SNR more than tenfold, which reinforces the accuracy of neuron extraction and spike inference and facilitates the functional analysis of neural circuits.

Conformal convolutional neural network (CCNN) for single-shot sensorless wavefront sensing.

Wavefront sensing technique is essential in deep tissue imaging, which guides spatial light modulator to compensate wavefront distortion for better imaging quality. Recently, convolutional neural network (CNN) based sensorless wavefront sensing methods have achieved remarkable speed advantages via single-shot measurement methodology. However, the low efficiency of convolutional filters dealing with circular point-spread-function (PSF) features makes them less accurate. In this paper, we propose a conformal convolutional neural network (CCNN) that boosts the performance by pre-processing circular features into rectangular ones through conformal mapping. The proposed conformal mapping reduces the number of convolutional filters that need to describe a circular feature, thus enables the neural network to recognize PSF features more efficiently. We demonstrate our CCNN could improve the wavefront sensing accuracy over 15% compared to a traditional CNN through simulations and validate the accuracy improvement in experiments. The improved performances make the proposed method promising in high-speed deep tissue imaging.

Acute myocardial injury following hydrogen sulfide poisoning.

BACKGROUND: Hydrogen sulfide poisoning can cause severe myocardial injury, but the damage is subtle and can be easily misdiagnosed. This report presents the dynamic observation of myocardial injury associated with hydrogen sulfide poisoning. CASE REPORT: Two young men presented with symptoms of "lightning-like" death immediately after entering a tank. They were found and rescued in 20 min at a time when they were already in a coma. Case 1 had no spontaneous breathing and pulse, while case 2 had spontaneous breathing and a pulse. Upon transfer to a local hospital, case 1 received continuous cardiopulmonary resuscitation which led to the recovery of his heart rate 3 min after arriving at the hospital. However, the patient remained in a Glasgow coma scale of 3. He was transferred to our hospital where he, unfortunately, died on the seventh day due to multiple organ failure. Case 2 was also transferred to the intensive care unit in our hospital and on the fourth day of hospitalization, the patient presented ST-segment elevation and dynamic changes in markers of myocardial injury. Changes in electrocardiogram and markers of myocardial injury were monitored and examination improved through conventional echocardiography, coronary artery CT, radionuclide myocardial perfusion imaging, and two-dimensional speckle tracking imaging strain. The treatment gradually improved the patient's myocardial injury and was discharged from the hospital. CONCLUSION: Hydrogen sulfide poisoning can cause damage to myocardial function and the damage can be more insidious in nature and with a delayed onset. Recovery from myocardial damage can be very slow.

Adaptive optimization for axial multi-foci generation in multiphoton microscopy.

To improve imaging speed, multifocal excitation is widely adopted as a parallel strategy in laser-scanning microscopy. Specifically, axial multifocal microscopy is popular in neuroscience as it enables functional imaging of neurons in multiple depths simultaneously. However, previous phase searching algorithms for axial multi-foci generation generally generate foci of uniform intensities, which cannot compensate the scattering-induced power loss in deep tissue and causes inhomogeneous excitation. Here, we propose a novel adaptive optimization-based phase-searching method (AdaPS) to generate axial multi-foci with arbitrary intensity modulations for scattering-induced loss compensation. By adopting Adaptive Moment Estimation (Adam) as the searching algorithm, our method could escape from unsatisfactory local minima and stably converge to the optimal phase pattern with errors at least an order of magnitude lower. We validate AdaPS through both numerical simulations and experiments and demonstrate that AdaPS could provide uniform multi-depth imaging in scattering phantom and enable high-fidelity multi-depth recordings of neural network dynamics in mouse brain in vivo.

Overcoming tissue scattering in wide-field two-photon imaging by extended detection and computational reconstruction.

Compared to point-scanning multiphoton microscopy, line-scanning temporal focusing microscopy (LTFM) is competitive in high imaging speed while maintaining tight axial confinement. However, considering its wide-field detection mode, LTFM suffers from shallow penetration depth as a result of the crosstalk induced by tissue scattering. In contrast to the spatial filtering based on confocal slit detection, here we propose the extended detection LTFM (ED-LTFM), the first wide-field two-photon imaging technique to extract signals from scattered photons and thus effectively extend the imaging depth. By recording a succession of line-shape excited signals in 2D and reconstructing signals under Hessian regularization, we can push the depth limitation of wide-field imaging in scattering tissues. We validate the concept with numerical simulations, and demonstrate the performance of enhanced imaging depth in in vivo imaging of mouse brains.

Schlieren two-photon microscopy for phase-contrast imaging.

While simultaneous phase-contrast and two-photon fluorescence imaging in microscopy can bring abundant biomedical information, it is difficult to retrieve phase information from conventional two-photon microscopes. To realize low-cost, in situ phase-contrast and two-photon fluorescence imaging, we propose Schlieren two-photon microscopy, a method that implements phase-contrast imaging on two-photon microscopes. This method involves spatially modulated fluorescence plates, which are made of two-photon fluorescence dyes or upconversion nanoparticles. We demonstrate that the fluorescence intensity fluctuation reflects the phase gradients of the specimen via theoretical analysis, simulations, and experiments. The proposed method is fully compatible with commercial two-photon microscopes, thus enabling widespread applications in live tissue imaging.

Schlieren two-photon microscopy for phase-contrast imaging: publisher's note.

This publisher's note amends the page range in Appl. Opt.58, A26 (2019)APOPAI0003-693510.1364/AO.58.000A26.

Enhancing axial resolution and background rejection in line-scanning temporal focusing microscopy by focal modulation.

Compared with two-photon point-scanning microscopy, line-scanning temporal focusing microscopy breaks the limitation on imaging rate and maintains the axial resolution, which makes it promising for various biomedical studies. However, for deep tissue imaging, it suffers from reduced axial resolution and increased background noise due to sample induced wavefront distortion. Here, we propose a spatio-spectral focal modulation technique to enhance axial resolution and background rejection by simply subtracting an aberrated image, which is induced by a spatial light modulator, from an unaberrated image. The proposed technique could improve the axial resolution by a factor of 1.3 in our implementation, verified by both simulations and experiments. Besides, we show that compared with spatial modulation alone, spatio-spectral modulation induces less peak intensity loss caused by image subtraction. We further demonstrate the performance of our technique on the enhanced axial resolution and background rejection by deep imaging of cleared mouse brains and in vivo imaging of living mouse brains.

Doubling the pixel count limitation of single-pixel imaging via sinusoidal amplitude modulation.

We demonstrate a single-pixel imaging (SPI) method that can achieve pixel resolution beyond the physical limitation of the spatial light modulator (SLM), by adopting sinusoidal amplitude modulation and frequency filtering. Through light field analysis, we observe that the induced intensity with a squared value of the amplitude contains higher frequency components. By filtering out the zero frequency of the sinusoidal amplitude in the Fourier domain, we can separate out the higher frequency components, which enables SPI with higher resolving ability and thus beyond the limitation of the SLM. Further, to address the speed issue in grayscale spatial light modulation, we propose a fast implementation scheme with tens-of-kilohertz refresh rate. Specifically, we use a digital micromirror device (DMD) working at the full frame rate to conduct binarized sinusoidal patterning in the spatial domain and pinhole filtering eliminating the binarization error in the Fourier domain. For experimental validation, we build a single-pixel microscope to retrieve 1200 × 1200-pixel images via a sub-megapixel DMD, and the setup achieves comparable performance to array sensor microscopy and provides additional sectioning ability.

Single-pixel phase and fluorescence microscope.

Multimodal microscopes either use multiple cameras or a single camera to multiplex different modes spatially. The former needs expertise demanding alignment and the latter suffers from limited spatial resolution. Here, we report an alignment-free full-resolution simultaneous fluorescence and phase imaging approach using single-pixel detectors. By combining reference-free interferometry with single-pixel imaging scheme, we employ structured illumination to encode the phase and fluorescence of the sample into two single-pixel detection arms, and then conduct reconstruction computationally from the illumination patterns and recorded correlated measurements. The recovered fluorescence and phase images are inherently aligned thanks to single-pixel imaging scheme. To validate the proposed method, we built a proof-of-concept setup for first imaging the phase of an etched glass with given etching depth and then imaging the phase and fluorescence of the quantum dot sample. This method holds great potential for multispectral fluorescence microscopy with additional single-pixel detectors or a spectrometer. Besides, this cost-efficient multimodal system might find broad applications in biomedical science and material science.

Snapshot hyperspectral imaging via spectral basis multiplexing in Fourier domain.

Hyperspectral imaging is an important tool having been applied in various fields, but still limited in observation of dynamic scenes. In this paper, we propose a snapshot hyperspectral imaging technique which exploits both spectral and spatial sparsity of natural scenes. Under the computational imaging scheme, we conduct spectral dimension reduction and spatial frequency truncation to the hyperspectral data cube and snapshot it in a low cost manner. Specifically, we modulate the spectral variations by several broadband spectral filters, and then map these modulated images into different regions in the Fourier domain. The encoded image compressed in both spectral and spatial are finally collected by a monochrome detector. Correspondingly, the reconstruction is essentially a Fourier domain extraction and spectral dimensional back projection with low computational load. This Fourier-spectral multiplexing in a 2D sensor simplifies both the encoding and decoding process, and makes hyperspectral data captured in a low cost manner. We demonstrate the high performance of our method by quantitative evaluation on simulation data and build a prototype system experimentally for further validation.

Improving the properties of whey protein isolate-zein nanogels with novel acidifiers: Re-dispersity, stability and quercetin bioavailability.

Low bioavailability of quercetin (Que) reduces its preclinical and clinical benefits. In order to improve Que bioavailability, a novel whey protein isolate (WPI)-zein nanogel was prepared by pH-driven self-assembly and heat-induced gelatinization. The results showed that hydrochloric acid can be substituted by both acetic acid and citric acid during the pH-driven process. After encapsulation, the bioavailability of Que in nanogels (composed of 70 % WPI) induced by different acidifiers increased to 19.89 % (citric acid), 21.65 % (hydrochloric acid) and 24.34 % (acetic acid), respectively. Comparatively, nanogels induced by acetic acid showed higher stability (pH and storage stability), re-dispersibility (75.62 %), Que bioavailability (24.34 %), and antioxidant capacity (36.78 % for DPPH scavenging rates). s improved performance of nanogels. In mechanism, acetic acid significantly balanced different intermolecular forces by weakening "acid-induced denaturation" effect. Moreover, the faster binding of Que and protein as well as higher protein molecular flexibility and randomness (higher ratio of random coil) was also observed in nanogels induced by acetic acid. All of these changes contributed to improve nanogels performances. Overall, WPI-zein nanogels induced by acetic acid might be a safe, efficiency and stable delivery system to improve the bioavailability of hydrophobic active ingredients.

Two-Stage Micropyramids Enhanced Flexible Piezoresistive Sensor for Health Monitoring and Human-Computer Interaction.

High-performance flexible piezoresistive sensors are becoming increasingly essential in various novel applications such as health monitoring, soft robotics, and human-computer interaction. The evolution of the interfacial contact morphology determines the sensing properties of piezoresistive devices. The introduction of microstructures enriches the interfacial contact morphology and effectively boosts the sensitivity; however, the limited compressibility of conventional microstructures leads to rapid saturation of the sensitivity in the low-pressure range, which hinders their application. Herein, we present a flexible piezoresistive sensor featuring a two-stage micropyramid array structure, which effectively enhances the sensitivity while widening the sensing range. Owing to the synergistic enhancement effect resulting from the sequential contact of micropyramids of various heights, the devices demonstrate remarkable performance, including boosting sensitivity (30.8 kPa-1) over a wide sensing range (up to 200 kPa), a fast response/recovery time (75/50 ms), and an ultralong durability of 15,000 loading-unloading cycles. As a proof of concept, the sensor is applied to detect human physiological and motion signals, further demonstrating a real-time spatial pressure distribution sensing system and a game control system, showing great potential for applications in health monitoring and human-computer interaction.

Understanding the mechanism for sodium tripolyphosphate in improving the physicochemical properties of low-moisture extrusion textured protein from rapeseed protein and soybean protein blends.

Our previous experiments found that rapeseed protein (RP) has applicability in low-moisture textured proteins. The amount of RP added is limited to <20 %, but the addition of 20 % RP still brings some negative effects. Therefore, in order to improve the quality of 20%RP textured protein, this experiment added different proportions of sodium tripolyphosphate (STPP) to improve the quality of the product, and studied the physical-chemical properties and molecular structure changes of the product to explore the possible modification mechanism. The STPP not only improved the expansion characteristics of extrudates, but also increased the brightness of the extrudates, the rehydration rate. In addition, STPP increased the specific mechanical energy during extrusion, decreased the material mass flow rate. Furthermore, STPP decreased the starch digestibility, increased the content of slow-digesting starch and resistant starch. STPP increased the degree of denaturation of extrudate proteins, the proportion of ß-sheets in the secondary structure of proteins, as well as the intermolecular hydrogen bonding interactions. The gelatinization degradation degree of starch molecules also decreased with the addition of STPP. STPP also increased the protein-starch interactions and enhanced the thermal stability of the extrudate. All these indicate that STPP can improve the physical-chemical properties of extrudate.

Molecular regulation of rapeseed protein for improving its techno-functional properties.

To improve the techno-functional properties of rapeseed protein (RP), this work tried to regulate the molecular structure of RP via inducing the co-assembly of RP with zein and whey protein (WP). The results showed that WP and zein mainly regulate the folding process of RP through hydrophobic and disulfide bonds, thereby altering the structural conformation and forming stable complex RP (CRP). WP addition not only increased the number of surface charges and hydrophilicity of proteins, but also decreased their sizes, improved the water solubility, as well as the availability of active groups. These changes significantly increased the foaming capacity (from 60 % to 147 %) and in vitro gastric digestion rate (from 10 % to 60 %) of CRP. Besides, WP also contributed to the formation of gels and the regulation of their textural profiles. Comparatively, zein improved the hydrophobicity of CRP and balanced degree of intermolecular forces, which effectively increased the emulsifying activity index of CRP from 22 m2/g to 90 m2/g. Zein decreased the hardness, springiness and water-holding capacity of gel, but increased its gumminess and chewiness. Overall, both WP and zein effectively changed the structural conformation of RP, and improved its techno-functional properties, which provides an effective strategy to modify protein.

A miniaturized mesoscope for the large-scale single-neuron-resolved imaging of neuronal activity in freely behaving mice.

Exploring the relationship between neuronal dynamics and ethologically relevant behaviour involves recording neuronal-population activity using technologies that are compatible with unrestricted animal behaviour. However, head-mounted microscopes that accommodate weight limits to allow for free animal behaviour typically compromise field of view, resolution or depth range, and are susceptible to movement-induced artefacts. Here we report a miniaturized head-mounted fluorescent mesoscope that we systematically optimized for calcium imaging at single-neuron resolution, for increased fields of view and depth of field, and for robustness against motion-generated artefacts. Weighing less than 2.5 g, the mesoscope enabled recordings of neuronal-population activity at up to 16 Hz, with 4 µm resolution over 300 µm depth-of-field across a field of view of 3.6 × 3.6 mm2 in the cortex of freely moving mice. We used the mesoscope to record large-scale neuronal-population activity in socially interacting mice during free exploration and during fear-conditioning experiments, and to investigate neurovascular coupling across multiple cortical regions.