Swept-source Raman spectroscopy of chemical and biological materials

Significance

Raman spectroscopy has been used as a powerful tool for chemical analysis, enabling the noninvasive acquisition of molecular fingerprints from various samples. Raman spectroscopy has proven to be valuable in numerous fields, including pharmaceutical, materials science, and biomedicine. Active research and development efforts are currently underway to bring this analytical instrument into the field, enabling in situ Raman measurements for a wider range of applications. Dispersive Raman spectroscopy using a fixed, narrowband source is a common method for acquiring Raman spectra. However, dispersive Raman spectroscopy requires a bulky spectrometer, which limits its field applicability. Therefore, there has been a tremendous need to develop a portable and sensitive Raman system.

Aim

We developed a compact swept-source Raman (SS-Raman) spectroscopy system and proposed a signal processing method to mitigate hardware limitations. We demonstrated the capabilities of the SS-Raman spectroscopy by acquiring Raman spectra from both chemical and biological samples. These spectra were then compared with Raman spectra obtained using a conventional dispersive Raman spectroscopy system.

Approach

The SS-Raman spectroscopy system used a wavelength-swept source laser (822 to 842 nm), a bandpass filter with a bandwidth of 1.5 nm, and a low-noise silicon photoreceiver. Raman spectra were acquired from various chemical samples, including phenylalanine, hydroxyapatite, glucose, and acetaminophen. A comparative analysis with the conventional dispersive Raman spectroscopy was conducted by calculating the correlation coefficients between the spectra from the SS-Raman spectroscopy and those from the conventional system. Furthermore, Raman mapping was obtained from cross-sections of swine tissue, demonstrating the applicability of the SS-Raman spectroscopy in biological samples.

Results

We developed a compact SS-Raman system and validated its performance by acquiring Raman spectra from both chemical and biological materials. Our straightforward signal processing method enhanced the quality of the Raman spectra without incurring high costs. Raman spectra in the range of 900 to 1200    cm - 1 were observed for phenylalanine, hydroxyapatite, glucose, and acetaminophen. The results were validated with correlation coefficients of 0.88, 0.84, 0.87, and 0.73, respectively, compared with those obtained from dispersive Raman spectroscopy. Furthermore, we performed scans across the cross-section of swine tissue to generate a biological tissue mapping plot, providing information about the composition of swine tissue.

Conclusions

We demonstrate the capabilities of the proposed compact SS-Raman spectroscopy system by obtaining Raman spectra of chemical and biological materials, utilizing straightforward signal processing. We anticipate that the SS-Raman spectroscopy will be utilized in various fields, including biomedical and chemical applications.

QuATON: Quantization Aware Training of Optical Neurons

Optical processors, built with "optical neurons", can efficiently perform high-dimensional linear operations at the speed of light. Thus they are a promising avenue to accelerate large-scale linear computations. With the current advances in micro-fabrication, such optical processors can now be 3D fabricated, but with a limited precision. This limitation translates to quantization of learnable parameters in optical neurons, and should be handled during the design of the optical processor in order to avoid a model mismatch. Specifically, optical neurons should be trained or designed within the physical-constraints at a predefined quantized precision level. To address this critical issues we propose a physics-informed quantization-aware training framework. Our approach accounts for physical constraints during the training process, leading to robust designs. We demonstrate that our approach can design state of the art optical processors using diffractive networks for multiple physics based tasks despite quantized learnable parameters. We thus lay the foundation upon which improved optical processors may be 3D fabricated in the future.

Optical diffraction tomography for assessing single cell models in angular light scattering

Angularly resolved light scattering (ALS) has become a useful tool for assessing the size and refractive index of biological scatterers at cellular and organelle length scales. Sizing organelle populations with ALS relies on Mie scattering theory models, which require significant assumptions about the object, including spherical scatterers and a homogeneous medium. These assumptions may incur greater error at the single cell level, where there are fewer scatterers to be averaged over. We investigate the validity of these assumptions using 3D refractive index (RI) tomograms measured via optical diffraction tomography (ODT). We compute the angular scattering on digitally manipulated tomograms with increasingly strong model assumptions, including RI-matched immersion media, homogeneous cytosol, and spherical organelles. We also compare the tomogram-computed angular scattering to experimental measurements of angular scattering from the same cells to ensure that the ODT-based approach accurately models angular scattering. We show that enforced RI-matching with the immersion medium and a homogeneous cytosol significantly affects the angular scattering intensity shape, suggesting that these assumptions can reduce the accuracy of size distribution estimates.

Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA

Single-cell RNA sequencing and other profiling assays have helped interrogate cells at unprecedented resolution and scale, but are inherently destructive. Raman microscopy reports on the vibrational energy levels of proteins and metabolites in a label-free and nondestructive manner at subcellular spatial resolution, but it lacks genetic and molecular interpretability. Here we present Raman2RNA (R2R), a method to infer single-cell expression profiles in live cells through label-free hyperspectral Raman microscopy images and domain translation. We predict single-cell RNA sequencing profiles nondestructively from Raman images using either anchor-based integration with single molecule fluorescence in situ hybridization, or anchor-free generation with adversarial autoencoders. R2R outperformed inference from brightfield images (cosine similarities: R2R >0.85 and brightfield <0.15). In reprogramming of mouse fibroblasts into induced pluripotent stem cells, R2R inferred the expression profiles of various cell states. With live-cell tracking of mouse embryonic stem cell differentiation, R2R traced the early emergence of lineage divergence and differentiation trajectories, overcoming discontinuities in expression space. R2R lays a foundation for future exploration of live genomic dynamics.

Multiphoton imaging of the monosachharide induced formation of fluorescent advanced glycation end products in tissues

We studied the in vitro rate of fluorescent advanced glycation end products (fAGEs) formation with multiphoton microscopy in different porcine tissues (aorta, cornea, kidney, dermis, and tendon). These tissues were treated with d-glucose, d-galactose, and d-fructose, three primary monosaccharides found in human diets. We found that the use of d-fructose resulted in the highest glycation rate, followed by d-galactose and then d-glucose. Moreover, compared to non-collagen tissue constituents such as elastic fibers and cells, the rate of tissue glycation was consistently higher in collagen, suggesting that collagen is a more sensitive target for fAGE formation. However, we also found that collagen in different tissues exhibits different rates of fAGE formation, with slower rates observed in tightly packed tissues such as cornea and tendon. Our study suggests that for fAGE to be developed into a long-term glycemic biomarker, loosely organized collagen tissues located in the proximity of vasculature may be the best targets.

Optical Diffraction Tomography and Raman Confocal Microscopy for the Investigation of Vacuoles Associated with Cancer Senescent Engulfing Cells

Wild-type p53 cancer therapy-induced senescent cells frequently engulf and degrade neighboring ones inside a massive vacuole in their cytoplasm. After clearance of the internalized cell, the vacuole persists, seemingly empty, for several hours. Despite large vacuoles being associated with cell death, this process is known to confer a survival advantage to cancer engulfing cells, leading to therapy resistance and tumor relapse. Previous attempts to resolve the vacuolar structure and visualize their content using dyes were unsatisfying for lack of known targets and ineffective dye penetration and/or retention. Here, we overcame this problem by applying optical diffraction tomography and Raman spectroscopy to MCF7 doxorubicin-induced engulfing cells. We demonstrated a real ability of cell tomography and Raman to phenotype complex microstructures, such as cell-in-cells and vacuoles, and detect chemical species in extremely low concentrations within live cells in a completely label-free fashion. We show that vacuoles had a density indistinguishable to the medium, but were not empty, instead contained diluted cell-derived macromolecules, and we could discern vacuoles from medium and cells using their Raman fingerprint. Our approach is useful for the noninvasive investigation of senescent engulfing (and other peculiar) cells in unperturbed conditions, crucial for a better understanding of complex biological processes.

DEEP-squared: deep learning powered De-scattering with Excitation Patterning

Limited throughput is a key challenge in in vivo deep tissue imaging using nonlinear optical microscopy. Point scanning multiphoton microscopy, the current gold standard, is slow especially compared to the widefield imaging modalities used for optically cleared or thin specimens. We recently introduced "De-scattering with Excitation Patterning" or "DEEP" as a widefield alternative to point-scanning geometries. Using patterned multiphoton excitation, DEEP encodes spatial information inside tissue before scattering. However, to de-scatter at typical depths, hundreds of such patterned excitations were needed. In this work, we present DEEP2, a deep learning-based model that can de-scatter images from just tens of patterned excitations instead of hundreds. Consequently, we improve DEEP's throughput by almost an order of magnitude. We demonstrate our method in multiple numerical and experimental imaging studies, including in vivo cortical vasculature imaging up to 4 scattering lengths deep in live mice.

Mapping nanoscale topographic features in thick tissues with speckle diffraction tomography

Resolving three-dimensional morphological features in thick specimens remains a significant challenge for label-free imaging. We report a new speckle diffraction tomography (SDT) approach that can image thick biological specimens with ~500 nm lateral resolution and ~1 μm axial resolution in a reflection geometry. In SDT, multiple-scattering background is rejected through spatiotemporal gating provided by dynamic speckle-field interferometry, while depth-resolved refractive index maps are reconstructed by developing a comprehensive inverse-scattering model that also considers specimen-induced aberrations. Benefiting from the high-resolution and full-field quantitative imaging capabilities of SDT, we successfully imaged red blood cells and quantified their membrane fluctuations behind a turbid medium with a thickness of 2.8 scattering mean-free paths. Most importantly, we performed volumetric imaging of cornea inside an ex vivo rat eye and quantified its optical properties, including the mapping of nanoscale topographic features of Dua's and Descemet's membranes that had not been previously visualized.

De-scattering Deep Neural Network Enables Fast Imaging of Spines through Scattering Media by Temporal Focusing Microscopy

Today the gold standard for in vivo imaging through scattering tissue is point-scanning two-photon microscopy (PSTPM). Especially in neuroscience, PSTPM is widely used for deep-tissue imaging in the brain. However, due to sequential scanning, PSTPM is slow. Temporal focusing microscopy (TFM), on the other hand, focuses femtosecond pulsed laser light temporally while keeping wide-field illumination, and is consequently much faster. However, due to the use of a camera detector, TFM suffers from the scattering of emission photons. As a result, TFM produces images of poor quality, obscuring fluorescent signals from small structures such as dendritic spines. In this work, we present a de-scattering deep neural network (DeScatterNet) to improve the quality of TFM images. Using a 3D convolutional neural network (CNN) we build a map from TFM to PSTPM modalities, to enable fast TFM imaging while maintaining high image quality through scattering media. We demonstrate this approach for in vivo imaging of dendritic spines on pyramidal neurons in the mouse visual cortex. We quantitatively show that our trained network rapidly outputs images that recover biologically relevant features previously buried in the scattered fluorescence in the TFM images. In vivo imaging that combines TFM and the proposed neural network is one to two orders of magnitude faster than PSTPM but retains the high quality necessary to analyze small fluorescent structures. The proposed approach could also be beneficial for improving the performance of many speed-demanding deep-tissue imaging applications, such as in vivo voltage imaging.

Stomach tissue classification using autofluorescence spectroscopy and machine learning

BACKGROUND AND OBJECTIVES

Determination of stomach tumor location and invasion depth requires delineation of gastric histological structure, which has hitherto been widely accomplished by histochemical staining. In recent years, alternative histochemical evaluation methods have been pursued to accelerate intraoperative diagnosis, often by bypassing the time-consuming step of dyeing. Owing to strong endogenous signals from coenzymes, metabolites, and proteins, autofluorescence spectroscopy is a favorable candidate technique to achieve this aim.

MATERIALS AND METHODS

We investigated stomach tissue slices and block specimens using a fast fluorescence imaging scanner. To obtain histological information from broad and structureless fluorescence spectra, we analyzed tens of thousands of spectra with multiple machine-learning algorithms and built a tissue classification model trained with dissected gastric tissues.

RESULTS

A machine-learning-based spectro-histological model was built based on the autofluorescence spectra measured from stomach tissue samples with delineated and validated histological structures. The scores from a principal components analysis were employed as input features, and prediction accuracy was confirmed to be 92.0%, 90.1%, and 91.4% for mucosa, submucosa, and muscularis propria, respectively. We investigated the tissue samples in both sliced and block forms using a fast fluorescence imaging scanner.

CONCLUSION

We successfully demonstrated differentiation of multiple tissue layers of well-defined specimens with the guidance of a histologist. Our spectro-histology classification model is applicable to histological prediction for both tissue blocks and slices, even though only sliced samples were trained.

Bendable long graded index lens microendoscopy

Graded index (GRIN) lens endoscopy has broadly benefited biomedical microscopic imaging by enabling accessibility to sites not reachable by traditional benchtop microscopes. It is a long-held notion that GRIN lenses can only be used as rigid probes, which may limit their potential for certain applications. Here, we describe bendable and long-range GRIN microimaging probes for a variety of potential micro-endoscopic biomedical applications. Using a two-photon fluorescence imaging system, we have experimentally demonstrated the feasibility of three-dimensional imaging through a 500-µm-diameter and ∼11 cm long GRIN lens subject to a cantilever beam-like deflection with a minimum bend radius of ∼25 cm. Bend-induced perturbation to the field of view and resolution has also been investigated quantitatively. Our development alters the conventional notion of GRIN lenses and enables a range of innovative applications. For example, the demonstrated flexibility is highly desirable for implementation into current and emerging minimally invasive clinical procedures, including a pioneering microdevice for high-throughput cancer drug selection.

Label-free three-photon imaging of intact human cerebral organoids for tracking early events in brain development and deficits in Rett syndrome

Human cerebral organoids are unique in their development of progenitor-rich zones akin to ventricular zones from which neuronal progenitors differentiate and migrate radially. Analyses of cerebral organoids thus far have been performed in sectioned tissue or in superficial layers due to their high scattering properties. Here, we demonstrate label-free three-photon imaging of whole, uncleared intact organoids (~2 mm depth) to assess early events of early human brain development. Optimizing a custom-made three-photon microscope to image intact cerebral organoids generated from Rett Syndrome patients, we show defects in the ventricular zone volumetric structure of mutant organoids compared to isogenic control organoids. Long-term imaging live organoids reveals that shorter migration distances and slower migration speeds of mutant radially migrating neurons are associated with more tortuous trajectories. Our label-free imaging system constitutes a particularly useful platform for tracking normal and abnormal development in individual organoids, as well as for screening therapeutic molecules via intact organoid imaging.

Label-free discrimination of tumorigenesis stages using in vitro prostate cancer bone metastasis model by Raman imaging

Metastatic prostate cancer colonizes the bone to pave the way for bone metastasis, leading to skeletal complications associated with poor prognosis and morbidity. This study demonstrates the feasibility of Raman imaging to differentiate between cancer cells at different stages of tumorigenesis using a nanoclay-based three-dimensional (3D) bone mimetic in vitro model that mimics prostate cancer bone metastasis. A comprehensive study comparing the classification of as received prostate cancer cells in a two-dimensional (2D) model and cancer cells in a 3D bone mimetic environment was performed over various time intervals using principal component analysis (PCA). Our results showed distinctive spectral differences in Raman imaging between prostate cancer cells and the cells cultured in 3D bone mimetic scaffolds, particularly at 1002, 1261, 1444, and 1654 cm-1, which primarily contain proteins and lipids signals. Raman maps capture sub-cellular responses with the progression of tumor cells into metastasis. Raman feature extraction via cluster analysis allows for the identification of specific cellular constituents in the images. For the first time, this work demonstrates a promising potential of Raman imaging, PCA, and cluster analysis to discriminate between cancer cells at different stages of metastatic tumorigenesis.

Single-Shot Quantitative Polarization Imaging of Complex Birefringent Structure Dynamics

Polarization light microscopes are powerful tools for probing molecular order and orientation in birefringent materials. While a number of polarization microscopy techniques are available to access steady-state properties of birefringent samples, quantitative measurements of the molecular orientation dynamics on the millisecond time scale have remained a challenge. We propose polarized shearing interference microscopy (PSIM), a single-shot quantitative polarization imaging method, for extracting the retardance and orientation angle of the laser beam transmitting through optically anisotropic specimens with complex structures. The measurement accuracy and imaging performance of PSIM are validated by imaging a birefringent resolution target and a bovine tendon specimen. We demonstrate that PSIM can quantify the dynamics of a flowing lyotropic chromonic liquid crystal in a microfluidic channel at an imaging speed of 506 frames per second (only limited by the camera frame rate), with a field-of-view of up to 350 × 350 μm² and a diffraction-limit spatial resolution of ~2 μm. We envision that PSIM will find a broad range of applications in quantitative material characterization under dynamical conditions.

De-scattering with Excitation Patterning enables rapid wide-field imaging through scattering media

Nonlinear optical microscopy has enabled in vivo deep tissue imaging on the millimeter scale. A key unmet challenge is its limited throughput especially compared to rapid wide-field modalities that are used ubiquitously in thin specimens. Wide-field imaging methods in tissue specimens have found successes in optically cleared tissues and at shallower depths, but the scattering of emission photons in thick turbid samples severely degrades image quality at the camera. To address this challenge, we introduce a novel technique called De-scattering with Excitation Patterning or "DEEP," which uses patterned nonlinear excitation followed by computational imaging-assisted wide-field detection. Multiphoton temporal focusing allows high-resolution excitation patterns to be projected deep inside specimen at multiple scattering lengths due to the use of long wavelength light. Computational reconstruction allows high-resolution structural features to be reconstructed from tens to hundreds of DEEP images instead of millions of point-scanning measurements.

Multiphoton imaging of the effect of monosaccharide diffusion and formation of fluorescent advanced end products in porcine aorta

Prolonged exposure of tissues to elevated blood sugar levels lead to the formation of advanced glycation end products (AGEs), thus contributing to diabetic complications. Since the vascular system is in immediate contact with blood, diabetic effects on aorta is a major health concern. However, the relative effect of the diffusion of sugar molecular through the vascular wall and the rate of AGE formation is not known. In this study, we aim to address this issue by incubating excised porcine aorta in D-glucose, D-galactose, and D-fructose solutions for different periods. The tissue specimens were then excised for multiphoton imaging of autofluorescence intensity profiles across the aorta wall. We found that for Days 4 to 48 incubation, autofluorescence is constant along the radial direction of the aorta sections, suggesting that monosaccharide diffusion is rapid in comparison to the rate of formation of fluorescent AGEs (fAGEs). Moreover, we found that in porcine aorta, the rate of fAGE formation of D-fructose and D-glucose are factors 2.08 and 1.14 that of D-galactose. Our results suggest that for prolonged exposure of the cardiovascular system to elevated monosaccharides 4 days or longer, damage to the aorta is uniform throughout the tissues.

Tumor cell nuclei soften during transendothelial migration

During cancer metastasis, tumor cells undergo significant deformation in order to traverse through endothelial cell junctions in the walls of blood vessels. As cells pass through narrow gaps, smaller than the nuclear diameter, the spatial configuration of chromatin must change along with the distribution of nuclear enzymes. Nuclear stiffness is an important determinant of the ability of cells to undergo transendothelial migration, yet no studies have been conducted to assess whether tumor cell cytoskeletal or nuclear stiffness changes during this critical process in order to facilitate passage. To address this question, we employed two non-contact methods, Brillouin confocal microscopy (BCM) and confocal reflectance quantitative phase microscopy (QPM), to track the changes in mechanical properties of live, transmigrating tumor cells in an in vitro collagen gel platform. Using these two imaging modalities to study transmigrating MDA-MB-231, A549, and A375 cells, we found that both the cells and their nuclei soften upon extravasation and that the nuclear membranes remain soft for at least 24 h. These new data suggest that tumor cells adjust their mechanical properties in order to facilitate extravasation.

Spectrochemical Probing of MicroRNA Duplex Using Spontaneous Raman Spectroscopy for Biosensing Applications

MicroRNAs are emerging as both diagnostic and therapeutic targets in different human pathologies. An accurate understanding of the structural dependency of microRNAs for their biological functions is essential for designing synthetic oligos with various base and linkage modifications that can transform into highly sensitive diagnostic devices and therapeutic molecules. In this proof-of-principle study, we have utilized label-free spontaneous Raman spectroscopy to understand the structural differences in sense and antisense microRNA-21 by hybridizing them with complementary RNA and DNA oligos. Overall, the results suggest that the changes in the Raman band at 785 cm^-1 originating from the phosphodiester bond of the nucleic acid backbone, linking 5' phosphate of the nucleic acid with 3' OH of the other nucleotide, can serve as a marker to identify these structural variations. Our results support the application of Raman spectroscopy in discerning intramolecular (ssRNA and ssDNA) and intermolecular (RNA-RNA, RNA-DNA, and DNA-DNA hybrids) interactions of nucleic acids. This is potentially useful for developing biosensors to quantify microRNAs in clinical samples and to design therapeutic microRNAs with robust functionality.

Quantitative third-harmonic generation imaging of mouse visual cortex areas reveals correlations between functional maps and structural substrates

The structure of brain regions is assumed to correlate with their function, but there are very few instances in which the relationship has been demonstrated in the live brain. This is due to the difficulty of simultaneously measuring functional and structural properties of brain areas, particularly at cellular resolution. Here, we performed label-free, third-harmonic generation (THG) microscopy to obtain a key structural signature of cortical areas, their effective attenuation lengths (EAL), in the vertical columns of functionally defined primary visual cortex and five adjacent visual areas in awake mice. EALs measured by THG microscopy in the cortex and white matter showed remarkable correspondence with the functional retinotopic sign map of each area. Structural features such as cytoarchitecture, myeloarchitecture and blood vessel architecture were correlated with areal EAL values, suggesting that EAL is a function of these structural features as an optical property of these areas. These results demonstrate for the first time a strong relationship between structural substrates of visual cortical areas and their functional representation maps in vivo. This study may also help in understanding the coupling between structure and function in other animal models as well as in humans.

Dual modal spectroscopic tissue scanner for colorectal cancer diagnosis

BACKGROUND

Margin status is an important prognostic factor for treating colorectal cancer. This study aimed to investigate the usefulness of a multimodal spectroscopic tissue scanner for real-time cancer diagnosis without tissue staining.

PATIENTS AND METHODS

Diffuse reflectance spectra (DRS) and fluorescence spectra (FS) of < 1-mm-sized paired cancer and normal mucosa tissue were acquired using custom-built spectroscopic tissue scanners. For FS, we analyzed wavelengths and intensities at peaks and highest intensities near (± 1.25 nm) the known fluorescence spectral peaks of collagen (380 nm), reduced nicotinamide adenine dinucleotide (NADH, 460 nm), and flavin adenine dinucleotide (FAD, 550 nm). For DRS, we performed a similar analysis near the peaks of strong absorbers, oxyhemoglobin (oxyHb; 414 nm, 540 nm, and 576 nm) and deoxyhemoglobin (deoxyHb; 432 nm and 556 nm). Logistic regression analysis for these parameters was performed in the testing set.

RESULTS

We acquired 17,735 spectra of cancer tissues and 9438 of normal tissues from 30 patients. Intensity peaks of representative normal spectra for FS and DRS were higher than those of representative cancer spectra. Logistic regression analysis showed wavelength and intensity at peaks, and the intensities of the peak wavelength of NADH, FAD, deoxyHb, and oxyHb had significant coefficients. The area under the receiver operating characteristic curve was 0.927. The scanner had 100%, 64.3%, and 85.3% sensitivity, specificity, and accuracy, respectively.

CONCLUSIONS

The spectroscopic tissue scanner has high sensitivity and accuracy and provides real-time intraoperative resection margin assessments and should be further investigated as an alternative to frozen section.

Analysis of subcutaneous swine fat via deep Raman spectroscopy using a fiber-optic probe

Since the fat content of pork is a deciding factor in meat quality grading, the use of a noninvasive subcutaneous probe for real-time in situ monitoring of the fat components is of importance to vendors and other interested parties. In this work, we developed a spectroscopic method using a fiber-optic probe for subcutaneous fat analysis that utilizes spatially offset Raman spectroscopy (SORS). Here, normalized Raman spectra were acquired as a function of spatial offset, and the relative composition of fat-to-skin was determined. We found that the Raman intensity ratio varied disproportionately depending on the fat content and that the variations of the slope were correlated to the thickness of the fat layer. Furthermore, ordinary least square (OLS) regression using two components indicated that the depth-resolved SORS spectra reflected the relative thickness of the fat layer. We concluded that the local distribution of subcutaneous fat could be measured noninvasively using a pair of fiber-optic probes.

Direct observation of glucose fingerprint using in vivo Raman spectroscopy

Noninvasive blood glucose monitoring has been a long-standing dream in diabetes management. The use of Raman spectroscopy, with its molecular specificity, has been investigated in this regard over the past decade. Previous studies reported on glucose sensing based on indirect evidence such as statistical correlation to the reference glucose concentration. However, these claims fail to demonstrate glucose Raman peaks, which has raised questions regarding the effectiveness of Raman spectroscopy for glucose sensing. Here, we demonstrate the first direct observation of glucose Raman peaks from in vivo skin. The signal intensities varied proportional to the reference glucose concentrations in three live swine glucose clamping experiments. Tracking spectral intensity based on linearity enabled accurate prospective prediction in within-subject and intersubject models. Our direct demonstration of glucose signal may quiet the long debate about whether glucose Raman spectra can be measured in vivo in transcutaneous glucose sensing.

Self-assembling amyloid-like peptides as exogenous second harmonic probes for bioimaging applications

Amyloid-like peptides are an ideal model for the mechanistic study of amyloidosis, which may lead to many human diseases, such as Alzheimer disease. This study reports a strong second harmonic generation (SHG) effect of amyloid-like peptides, having a signal equivalent to or even higher than those of endogenous collagen fibers. Several amyloid-like peptides (both synthetic and natural) were examined under SHG microscopy and shown they are SHG-active. These peptides can also be observed inside cells (in vitro). This interesting property can make these amyloid-like peptides second harmonic probes for bioimaging applications. Furthermore, SHG microscopy can provide a simple and label-free approach to detect amyloidosis. Lattice corneal dystrophy was chosen as a model disease of amyloidosis. Morphological difference between normal and diseased human corneal biopsy samples can be easily recognized, proving that SHG can be a useful tool for disease diagnosis.

Increasing the penetration depth of temporal focusing multiphoton microscopy for neurobiological applications

The first ever demonstration of temporal focusing with short wave infrared (SWIR) excitation and emission is demonstrated, achieving a penetration depth of 500 µm in brain tissue. This is substantially deeper than the highest previously-reported values for temporal focusing imaging in brain tissue, and demonstrates the value of these optimized wavelengths for neurobiological applications.

Scanless volumetric imaging by selective access multifocal multiphoton microscopy

Simultaneous, high-resolution imaging across a large number of synaptic and dendritic sites is critical for understanding how neurons receive and integrate signals. Yet, functional imaging that targets a large number of submicrometer-sized synaptic and dendritic locations poses significant technical challenges. We demonstrate a new parallelized approach to address such questions, increasing the signal-to-noise ratio by an order of magnitude compared to previous approaches. This selective access multifocal multiphoton microscopy uses a spatial light modulator to generate multifocal excitation in three dimensions (3D) and a Gaussian-Laguerre phase plate to simultaneously detect fluorescence from these spots throughout the volume. We test the performance of this system by simultaneously recording Ca2+ dynamics from cultured neurons at 98-118 locations distributed throughout a 3D volume. This is the first demonstration of 3D imaging in a "single shot" and permits synchronized monitoring of signal propagation across multiple different dendrites.

Scattering reduction by structured light illumination in line-scanning temporal focusing microscopy

Line-scanning temporal focusing microscopy (LineTFM) is capable of imaging biological samples more than 10 times faster than two-photon laser point-scanning microscopy (TPLSM), while achieving nearly the same lateral and axial spatial resolution. However, the image contrast taken by LineTFM is lower than that by TPLSM because LineTFM is severely influenced by biological tissue scattering. To reject the scattered photons, we implemented LineTFM using both structured illumination and uniform illumination combined with the HiLo post-processing algorithm, called HiLL microscopy (HiLo-Line-scanning temporal focusing microscopy). HiLL microscopy significantly reduces tissue scattering and improves image contrast. We demonstrate HiLL microscopy with in vivo brain imaging. This approach could potentially find applications in monitoring fast dynamic events and in mapping high resolution structures over a large volume.

Deep learning enables automated scoring of liver fibrosis stages

Current liver fibrosis scoring by computer-assisted image analytics is not fully automated as it requires manual preprocessing (segmentation and feature extraction) typically based on domain knowledge in liver pathology. Deep learning-based algorithms can potentially classify these images without the need for preprocessing through learning from a large dataset of images. We investigated the performance of classification models built using a deep learning-based algorithm pre-trained using multiple sources of images to score liver fibrosis and compared them against conventional non-deep learning-based algorithms - artificial neural networks (ANN), multinomial logistic regression (MLR), support vector machines (SVM) and random forests (RF). Automated feature classification and fibrosis scoring were achieved by using a transfer learning-based deep learning network, AlexNet-Convolutional Neural Networks (CNN), with balanced area under receiver operating characteristic (AUROC) values of up to 0.85–0.95 versus ANN (AUROC of up to 0.87–1.00), MLR (AUROC of up to 0.73–1.00), SVM (AUROC of up to 0.69–0.99) and RF (AUROC of up to 0.94–0.99). Results indicate that a deep learning-based algorithm with transfer learning enables the construction of a fully automated and accurate prediction model for scoring liver fibrosis stages that is comparable to other conventional non-deep learning-based algorithms that are not fully automated.

Reference-free polarization-sensitive quantitative phase imaging using single-point optical phase conjugation

We propose and experimentally demonstrate a method of polarization-sensitive quantitative phase imaging using two photodetectors and a digital micromirror device. Instead of recording wide-field interference patterns, finding the modulation patterns maximizing focused intensities in terms of the polarization states enables polarization-dependent quantitative phase imaging without the need for a reference beam and an image sensor. The feasibility of the present method is experimentally validated by reconstructing Jones matrices of several samples including a polystyrene microsphere, a maize starch granule, and a mouse retinal nerve fiber layer. Since the present method is simple and sufficiently general, we expect that it may offer solutions for quantitative phase imaging of birefringent materials.

In vivo detection of drug-induced apoptosis in tumors using Raman spectroscopy

We describe a label-free approach based on Raman spectroscopy, to study drug-induced apoptosis in vivo. Spectral-shifts at wavenumbers associated with DNA, proteins, lipids, and collagen have been identified on breast and melanoma tumor tissues. These findings may enable a new analytical method for rapid readout of drug-therapy with miniaturized probes.

Quantitative phase microscopy of red blood cells during planar trapping and propulsion

Red blood cells (RBCs) have the ability to undergo morphological deformations during microcirculation, such as changes in surface area, volume and sphericity. Optical waveguide trapping is suitable for trapping, propelling and deforming large cell populations along the length of the waveguide. Bright field microscopy employed with waveguide trapping does not provide quantitative information about structural changes. Here, we have combined quantitative phase microscopy and waveguide trapping techniques to study changes in RBC morphology during planar trapping and transportation. By using interference microscopy, time-lapsed interferometric images of trapped RBCs were recorded in real-time and subsequently utilized to reconstruct optical phase maps. Quantification of the phase differences before and after trapping enabled study of the mechanical effects during planar trapping. During planar trapping, a decrease in the maximum phase values, an increase in the surface area and a decrease in the volume and sphericity of RBCs were observed. QPM was used to analyze the phase values for two specific regions within RBCs: the annular rim and the central donut. The phase value of the annular rim decreases whereas it increases for the central donut during planar trapping. These changes correspond to a redistribution of cytosol inside the RBC during planar trapping and transportation.

Three-dimensional super-resolution high-throughput imaging by structured illumination STED microscopy

Stimulated emission depletion (STED) microscopy is able to image fluorescence labeled samples with nanometer scale resolution. STED microscopy is typically a point-scanning method, limited by the high intensity requirement of the depletion beam. With the development of high peak power lasers, two dimensional parallel STED microscopy has been developed. Here, we develop the theoretical basis for extending STED microscopy to three dimensional imaging in parallel. This method uses structured illumination (SI) to generates a three dimensional depletion pattern. Compared to the two dimensional parallel STED microscopy, the 3D SI-STED microscopy generates intensity modulation along the light propagation direction without requiring higher laser power. This method not only achieves axial super-resolution of STED microscopy but also greatly reduces photobleaching and photodamage for 3D volumetric imaging.

Single-Shot Optical Anisotropy Imaging with Quantitative Polarization Interference Microscopy

Optical anisotropy measurement is essential for material characterization and biological imaging. In order to achieve single-shot mapping of the birefringence parameters of anisotropic samples, a novel polarized light imaging concept is proposed, namely quantitative polarization interference microscopy (QPIM). QPIM can be realized through designing a compact polarization-resolved interference microscopy system that captures interferograms bearing sample's linear birefringence information. To extract the retardance and the orientation angle maps from a single-shot measurement, a mathematical model for QPIM is further developed. The QPIM system is validated by measuring a calibrated quarter-wave plate, whose fast-axis orientation angle and retardance are determined with great accuracies. The single-shot nature of QPIM further allows to measure the transient dynamics of birefringence changes in material containing anisotropic structures. This application is demonstrated by capturing transient retardance changes in a custom-designed parallel-aligned nematic liquid crystal-based device.

Evaluation of accuracy dependence of Raman spectroscopic models on the ratio of calibration and validation points for non-invasive glucose sensing

Optical monitoring of blood glucose levels for non-invasive diagnosis is a growing area of research. Recent efforts in this direction have been inclined towards reducing the requirement of calibration framework. Here, we are presenting a systematic investigation on the influence of variation in the ratio of calibration and validation points on the prospective predictive accuracy of spectral models. A fiber-optic probe coupled Raman system has been employed for transcutaneous measurements. Limit of agreement analysis between serum and partial least square regression predicted spectroscopic glucose values has been performed for accurate comparison. Findings are suggestive of strong predictive accuracy of spectroscopic models without requiring substantive calibration measurements. Graphical abstract.

Regeneration mechanism for skin and peripheral nerves clarified at the organ and molecular scales

This article is a review of current research on the mechanism of regeneration of skin and peripheral nerves based on use of collagen scaffolds, particularly the dermis regeneration template (DRT), which is widely used clinically. DRT modifies the normal wound healing process, converting it from wound closure by contraction and scar formation to closure by regeneration. DRT achieves this modification by blocking wound contraction, which spontaneously leads to cancellation of scar formation, a process secondary to contraction. Contraction blocking by DRT is the result of a dramatic phenotype change in contractile cells (myofibroblasts, MFB) which follows specific binding of integrins α₁β₁ and α₂β₁ onto hexapeptide ligands, probably GFOGER and GLOGER, that are naturally present on the surface of collagen fibers in DRT. The methodology of organ regeneration based on use of DRT has been recently extended from traumatized skin to diseased skin. Successful extension of the method to other organs in which wounds heal by contraction is highly likely though not yet attempted. This regenerative paradigm is much more advanced both in basic mechanistic understanding and clinical use than methods based on tissue culture or stem cells. It is also largely free of risk and has shown decisively lower morbidity and lower cost than organ transplantation.

Eleven quick tips for running an interdisciplinary short course for new graduate students

Quantitative reasoning and techniques are increasingly ubiquitous across the life sciences. However, new graduate researchers with a biology background are often not equipped with the skills that are required to utilize such techniques correctly and efficiently. In parallel, there are increasing numbers of engineers, mathematicians, and physical scientists interested in studying problems in biology with only basic knowledge of this field. Students from such varied backgrounds can struggle to engage proactively together to tackle problems in biology. There is therefore a need to establish bridges between those disciplines. It is our proposal that the beginning of graduate school is the appropriate time to initiate those bridges through an interdisciplinary short course. We have instigated an intensive 10-day course that brought together new graduate students in the life sciences from across departments within the National University of Singapore. The course aimed at introducing biological problems as well as some of the quantitative approaches commonly used when tackling those problems. We have run the course for three years with over 100 students attending. Building on this experience, we share 11 quick tips on how to run such an effective, interdisciplinary short course for new graduate students in the biosciences.

Single-shot dual-wavelength interferometric microscopy

Interferometric microscopy (IM) can provide complex field information of the biological samples with high spatial and temporal resolution with virtually no photodamage. Measuring wavelength-dependent information in particular has a wide range of applications from cell and tissue refractometry to the cellular biophysical measurements. IM measurements at multiple wavelengths are typically associated with a loss in temporal resolution, field of view, stability, sensitivity, and may involve using expensive equipment such as tunable filters or spatial light modulators. Here, we present a novel and simple design for an interferometric microscope that provides single-shot off-axis interferometric measurements at two wavelengths by encoding the two spectral images at two orthogonal spatial frequencies that allows clean separation of information in the Fourier space with no resolution loss. We demonstrated accurate simultaneous quantification of polystyrene bead refractive indices at two wavelengths.

Tomographic phase microscopy: principles and applications in bioimaging [Invited]

Tomographic phase microscopy (TPM) is an emerging optical microscopic technique for bioimaging. TPM uses digital holographic measurements of complex scattered fields to reconstruct three-dimensional refractive index (RI) maps of cells with diffraction-limited resolution by solving inverse scattering problems. In this paper, we review the developments of TPM from the fundamental physics to its applications in bioimaging. We first provide a comprehensive description of the tomographic reconstruction physical models used in TPM. The RI map reconstruction algorithms and various regularization methods are discussed. Selected TPM applications for cellular imaging, particularly in hematology, are reviewed. Finally, we examine the limitations of current TPM systems, propose future solutions, and envision promising directions in biomedical research.

Dynamic spatial filtering using a digital micromirror device for high-speed optical diffraction tomography

Optical diffraction tomography (ODT) is an emerging microscopy technique for three-dimensional (3D) refractive index (RI) mapping of transparent specimens. Recently, the digital micromirror device (DMD) based scheme for angle-controlled plane wave illumination has been proposed to improve the imaging speed and stability of ODT. However, undesired diffraction noise always exists in the reported DMD-based illumination scheme, which leads to a limited contrast ratio of the measurement fringe and hence inaccurate RI mapping. Here we present a novel spatial filtering method, based on a second DMD, to dynamically remove the diffraction noise. The reported results illustrate significantly enhanced image quality of the obtained interferograms and the subsequently derived phase maps. And moreover, with this method, we demonstrate mapping of 3D RI distribution of polystyrene beads as well as biological cells with high accuracy. Importantly, with the proper hardware configuration, our method does not compromise the 3D imaging speed advantage promised by the DMD-based illumination scheme. Specifically, we have been able to successfully obtain interferograms at over 1 kHz speed, which is critical for potential high-throughput label-free 3D image cytometry applications.

Three-dimensional wide-field pump-probe structured illumination microscopy: erratum

We found errors in Eqs. (5), (6), (7), (8), (23), (25), Figs. 2, 3, 4, 5, 10, and Discussion of our article "Three-dimensional wide-field pump-probe structured illumination microscopy." Here we publish the revised equations, figures, and discussion. In general, the corrections do not affect the essential conclusion and image reconstruction quality improves with these corrections.

Development of a classification model for non-alcoholic steatohepatitis (NASH) using confocal Raman micro-spectroscopy

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder in developed countries [1]. A subset of individuals with NAFLD progress to non-alcoholic steatohepatitis (NASH), an advanced form of NAFLD which predisposes individuals to cirrhosis, liver failure and hepatocellular carcinoma. The current gold standard for NASH diagnosis and staging is based on histological evaluation, which is largely semi-quantitative and subjective. To address the need for an automated and objective approach to NASH detection, we combined Raman micro-spectroscopy and machine learning techniques to develop a classification model based on a well-established NASH mouse model, using spectrum pre-processing, biochemical component analysis (BCA) and logistic regression. By employing a selected pool of biochemical components, we identified biochemical changes specific to NASH and show that the classification model is capable of accurately detecting NASH (AUC=0.85-0.87) in mice. The unique biochemical fingerprint generated in this study may serve as a useful criterion to be leveraged for further validation in clinical samples.

Near-common-path interferometer for imaging Fourier-transform spectroscopy in wide-field microscopy

Imaging Fourier-transform spectroscopy (IFTS) is a powerful method for biological hyperspectral analysis based on various imaging modalities, such as fluorescence or Raman. Since the measurements are taken in the Fourier space of the spectrum, it can also take advantage of compressed sensing strategies. IFTS has been readily implemented in high-throughput, high-content microscope systems based on wide-field imaging modalities. However, there are limitations in existing wide-field IFTS designs. Non-common-path approaches are less phase-stable. Alternatively, designs based on the common-path Sagnac interferometer are stable, but incompatible with high-throughput imaging. They require exhaustive sequential scanning over large interferometric path delays, making compressive strategic data acquisition impossible. In this paper, we present a novel phase-stable, near-common-path interferometer enabling high-throughput hyperspectral imaging based on strategic data acquisition. Our results suggest that this approach can improve throughput over those of many other wide-field spectral techniques by more than an order of magnitude without compromising phase stability.

Large population cell characterization using quantitative phase cytometer

A major challenge in cellular analysis is the phenotypic characterization of large cell populations within a short period of time. Among various parameters for cell characterization, the cell dry mass is often used to describe cell size but is difficult to be measured directly with traditional techniques. Here, we propose an interferometric approach based on line-focused beam illumination for high-content precision dry mass measurements of adherent cells in a non-invasive fashion-we call it quantitative phase cytometry (QPC). Besides dry mass, abundant cellular morphological features such as projected area, sphericity, and phase skewness can be readily extracted from the QPC interferometric data. To validate the utility of our technique, we demonstrate characterizing a large population of ∼10⁴ HeLa cells. Our reported QPC system is envisioned as a promising quantitative tool for label-free characterization of a large cell count at single cell resolution. © 2017 International Society for Advancement of Cytometry.

Next-generation in vivo optical imaging with short-wave infrared quantum dots

For in vivo imaging, the short-wavelength infrared region (SWIR; 1000–2000 nm) provides several advantages over the visible and near-infrared regions: general lack of autofluorescence, low light absorption by blood and tissue, and reduced scattering. However, the lack of versatile and functional SWIR emitters has prevented the general adoption of SWIR imaging by the biomedical research community. Here, we introduce a class of high-quality SWIR-emissive indium-arsenide-based quantum dots (QDs) that are readily modifiable for various functional imaging applications, and that exhibit narrow and size-tunable emission and a dramatically higher emission quantum yield than previously described SWIR probes. To demonstrate the unprecedented combination of deep penetration, high spatial resolution, multicolor imaging and fast-acquisition-speed afforded by the SWIR QDs, we quantified, in mice, the metabolic turnover rates of lipoproteins in several organs simultaneously and in real time as well as heartbeat and breathing rates in awake and unrestrained animals, and generated detailed three-dimensional quantitative flow maps of the mouse brain vasculature.

Digital micromirror device-based common-path quantitative phase imaging

We propose a novel common-path quantitative phase imaging (QPI) method based on a digital micromirror device (DMD). The DMD is placed in a plane conjugate to the objective back-aperture plane for the purpose of generating two plane waves that illuminate the sample. A pinhole is used in the detection arm to filter one of the beams after sample to create a reference beam. Additionally, a transmission-type liquid crystal device, placed at the objective back-aperture plane, eliminates the specular reflection noise arising from all the "off" state DMD micromirrors, which is common in all DMD-based illuminations. We have demonstrated high sensitivity QPI, which has a measured spatial and temporal noise of 4.92 nm and 2.16 nm, respectively. Experiments with calibrated polystyrene beads illustrate the desired phase measurement accuracy. In addition, we have measured the dynamic height maps of red blood cell membrane fluctuations, showing the efficacy of the proposed system for live cell imaging. Most importantly, the DMD grants the system convenience in varying the interference fringe period on the camera to easily satisfy the pixel sampling conditions. This feature also alleviates the pinhole alignment complexity. We envision that the proposed DMD-based common-path QPI system will allow for system miniaturization and automation for a broader adaption.

Regeneration of injured skin and peripheral nerves requires control of wound contraction, not scar formation

We review the mounting evidence that regeneration is induced in wounds in skin and peripheral nerves by a simple modification of the wound healing process. Here, the process of induced regeneration is compared to the other two well-known processes by which wounds close, i.e., contraction and scar formation. Direct evidence supports the hypothesis that the mechanical force of contraction (planar in skin wounds, circumferential in nerve wounds) is the driver guiding the orientation of assemblies of myofibroblasts (MFB) and collagen fibers during scar formation in untreated wounds. We conclude that scar formation depends critically on wound contraction and is, therefore, a healing process secondary to contraction. Wound contraction and regeneration did not coincide during healing in a number of experimental models of spontaneous (untreated) regeneration described in the literature. Furthermore, in other studies in which an efficient contraction-blocker, a collagen scaffold named dermis regeneration template (DRT), and variants of it, were grafted on skin wounds or peripheral nerve wounds, regeneration was systematically observed in the absence of contraction. We conclude that contraction and regeneration are mutually antagonistic processes. A dramatic change in the phenotype of MFB was observed when the contraction-blocking scaffold DRT was used to treat wounds in skin and peripheral nerves. The phenotype change was directly observed as drastic reduction in MFB density, dispersion of MFB assemblies and loss of alignment of the long MFB axes. These observations were explained by the evidence of a surface-biological interaction of MFB with the scaffold, specifically involving binding of MFB integrins α1 β1 and α2 β1 to ligands GFOGER and GLOGER naturally present on the surface of the collagen scaffold. In summary, we show that regeneration of wounded skin and peripheral nerves in the adult mammal can be induced simply by appropriate control of wound contraction, rather than of scar formation.

Modeling the depth-sectioning effect in reflection-mode dynamic speckle-field interferometric microscopy

Unlike most optical coherence microscopy (OCM) systems, dynamic speckle-field interferometric microscopy (DSIM) achieves depth sectioning through the spatial-coherence gating effect. Under high numerical aperture (NA) speckle-field illumination, our previous experiments have demonstrated less than 1 μm depth resolution in reflection-mode DSIM, while doubling the diffraction limited resolution as under structured illumination. However, there has not been a physical model to rigorously describe the speckle imaging process, in particular explaining the sectioning effect under high illumination and imaging NA settings in DSIM. In this paper, we develop such a model based on the diffraction tomography theory and the speckle statistics. Using this model, we calculate the system response function, which is used to further obtain the depth resolution limit in reflection-mode DSIM. Theoretically calculated depth resolution limit is in an excellent agreement with experiment results. We envision that our physical model will not only help in understanding the imaging process in DSIM, but also enable better designing such systems for depth-resolved measurements in biological cells and tissues.

Fluorescent probes for nanoscopy: four categories and multiple possibilities

Nanoscopy enables breaking down the light diffraction limit and reveals the nanostructures of objects being studied using light. In 2014, three scientists pioneered the development of nanoscopy and won the Nobel Prize in Chemistry. This recognized the achievement of the past twenty years in the field of nanoscopy. However, fluorescent probes used in the field of nanoscopy are still numbered. Here, we review the currently available four categories of probes and existing methods to improve the performance of probes.

Investigating Effects of Proteasome Inhibitor on Multiple Myeloma Cells Using Confocal Raman Microscopy

Due to its label-free and non-destructive nature, applications of Raman spectroscopic imaging in monitoring therapeutic responses at the cellular level are growing. We have recently developed a high-speed confocal Raman microscopy system to image living biological specimens with high spatial resolution and sensitivity. In the present study, we have applied this system to monitor the effects of Bortezomib, a proteasome inhibitor drug, on multiple myeloma cells. Cluster imaging followed by spectral profiling suggest major differences in the nuclear and cytoplasmic contents of cells due to drug treatment that can be monitored with Raman spectroscopy. Spectra were also acquired from group of cells and feasibility of discrimination among treated and untreated cells using principal component analysis (PCA) was accessed. Findings support the feasibility of Raman technologies as an alternate, novel method for monitoring live cell dynamics with minimal external perturbation.

Superpixel-based segmentation of muscle fibers in multi-channel microscopy

BACKGROUND

Confetti fluorescence and other multi-color genetic labelling strategies are useful for observing stem cell regeneration and for other problems of cell lineage tracing. One difficulty of such strategies is segmenting the cell boundaries, which is a very different problem from segmenting color images from the real world. This paper addresses the difficulties and presents a superpixel-based framework for segmentation of regenerated muscle fibers in mice.

RESULTS

We propose to integrate an edge detector into a superpixel algorithm and customize the method for multi-channel images. The enhanced superpixel method outperforms the original and another advanced superpixel algorithm in terms of both boundary recall and under-segmentation error. Our framework was applied to cross-section and lateral section images of regenerated muscle fibers from confetti-fluorescent mice. Compared with "ground-truth" segmentations, our framework yielded median Dice similarity coefficients of 0.92 and higher.

CONCLUSION

Our segmentation framework is flexible and provides very good segmentations of multi-color muscle fibers. We anticipate our methods will be useful for segmenting a variety of tissues in confetti fluorecent mice and in mice with similar multi-color labels.

Microfluidic device for the formation of optically excitable, three-dimensional, compartmentalized motor units

Motor units are the fundamental elements responsible for muscle movement. They are formed by lower motor neurons and their muscle targets, synapsed via neuromuscular junctions (NMJs). The loss of NMJs in neurodegenerative disorders (such as amyotrophic lateral sclerosis or spinal muscle atrophy) or as a result of traumatic injuries affects millions of lives each year. Developing in vitro assays that closely recapitulate the physiology of neuromuscular tissues is crucial to understand the formation and maturation of NMJs, as well as to help unravel the mechanisms leading to their degeneration and repair. We present a microfluidic platform designed to coculture myoblast-derived muscle strips and motor neurons differentiated from mouse embryonic stem cells (ESCs) within a three-dimensional (3D) hydrogel. The device geometry mimics the spinal cord-limb physical separation by compartmentalizing the two cell types, which also facilitates the observation of 3D neurite outgrowth and remote muscle innervation. Moreover, the use of compliant pillars as anchors for muscle strips provides a quantitative functional readout of force generation. Finally, photosensitizing the ESC provides a pool of source cells that can be differentiated into optically excitable motor neurons, allowing for spatiodynamic, versatile, and noninvasive in vitro control of the motor units.