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.

Mapping the neural dynamics of locomotion across the Drosophila brain.

Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.

Detection of osteoporotic-related bone changes and prediction of distal radius strength using Raman spectra from excised human cadaver finger bones.

While osteoporosis is reliably diagnosed using dual energy X-ray absorptiometry (DXA), screening rates are alarmingly low, contributing to preventable fractures. Raman spectroscopy (RS) can detect biochemical changes that occur in bones transcutaneously and can arguably be more accessible than DXA as a fracture risk assessment. A reasonable approach to translate RS is to interrogate phalangeal bones of human hands, where the soft tissues covering the bone are less likely to hamper transcutaneous measurements. To that end, we set out to first determine whether Raman spectra obtained from phalangeal bones correlate with distal radius fracture strength, which can predict subsequent osteoporotic fractures at the spine and hip. We performed RS upon diaphyseal and epiphyseal regions of exposed proximal phalanges from 12 cadaver forearms classified as healthy (n = 3), osteopenic (n = 4), or osteoporotic (n = 5) based on wrist T-scores measured by DXA. We observed a significant decrease in phosphate to matrix ratio and a significant increase in carbonate substitution in the osteoporotic phalanges relative to healthy and osteopenic phalanges. Multivariate regression models produced wrist T-score estimates with significant correlation to the DXA-measured values (r = 0.79). Furthermore, by accounting for phalangeal RS parameters, body mass index, and age, a multivariate regression significantly predicted distal radius strength measured in a simulated-fall biomechanical test (r = 0.81). These findings demonstrate the feasibility of interrogating the phalanges using RS for bone quality assessment of distant clinical sites of fragility fractures, such as the wrist. Future work will address transcutaneous measurement challenges as another requirement for scale-up and translation.

Three-dimensional angular scattering simulations inform analysis of scattering from single cells.

Significance: Organelle sizes, which are indicative of cellular status, have implications for drug development and immunology research. At the single cell level, such information could be used to study the heterogeneity of cell response to drugs or pathogens. Aim: Angularly resolved elastic light scattering is known to be sensitive to changes in organelle size distribution. We developed a Mie theory-based simulation of angular scattering from single cells to quantify the effects of noise on scattering and size estimates. Approach: We simulated randomly sampled organelle sizes (drawn from a log normal distribution), interference between different organelles' scattering, and detector noise. We quantified each noise source's effect upon the estimated mean and standard deviation of organelle size distributions. Results: The results demonstrate that signal-to-noise ratio in the angular scattering increased with the number of scatterers, cell area, and exposure time and decreased with the size distribution width. The error in estimating the mean of the size distributions remained below 5% for nearly all experimental parameters tested, but the widest size distribution tested (standard deviation of 600 nm) reached 20%. Conclusions: The simulator revealed that sparse sampling of a broad size distribution can dominate the mismatch between actual and predicted size parameters. Alternative estimation strategies could reduce the discrepancy.

BIFROST: a method for registering diverse imaging datasets.

Quantitative comparison of brain-wide neural dynamics across different experimental conditions often requires precise alignment to a common set of anatomical coordinates. While such approaches are routinely applied in functional magnetic resonance imaging (fMRI), registering in vivo fluorescence imaging data to ex vivo-derived reference atlases is challenging, given the many differences in imaging modality, microscope specification, and sample preparation. Moreover, in many systems, animal to animal variation in brain structure limits registration precision. Using the highly stereotyped architecture of the fruit fly brain as a model, we overcome these challenges by building a reference atlas based directly on in vivo multiphoton-imaged brains, called the Functional Drosophila Atlas (FDA). We then develop a novel two-step pipeline, BrIdge For Registering Over Statistical Templates (BIFROST), for transforming neural imaging data into this common space, and for importing ex vivo resources, such as connectomes. Using genetically labeled cell types to provide ground truth, we demonstrate that this method allows voxel registration with micron precision. Thus, this method provides a generalizable pipeline for registering neural activity datasets to one another, allowing quantitative comparisons across experiments, microscopes, genotypes, and anatomical atlases, including connectomes.

Glial control of sphingolipid levels sculpts diurnal remodeling in a circadian circuit.

Structural plasticity in the brain often necessitates dramatic remodeling of neuronal processes, with attendant reorganization of the cytoskeleton and membranes. Although cytoskeletal restructuring has been studied extensively, how lipids might orchestrate structural plasticity remains unclear. We show that specific glial cells in Drosophila produce glucocerebrosidase (GBA) to locally catabolize sphingolipids. Sphingolipid accumulation drives lysosomal dysfunction, causing gba1b mutants to harbor protein aggregates that cycle across circadian time and are regulated by neural activity, the circadian clock, and sleep. Although the vast majority of membrane lipids are stable across the day, a specific subset that is highly enriched in sphingolipids cycles daily in a gba1b-dependent fashion. Remarkably, both sphingolipid biosynthesis and degradation are required for the diurnal remodeling of circadian clock neurites, which grow and shrink across the day. Thus, dynamic sphingolipid regulation by glia enables diurnal circuit remodeling and proper circadian behavior.

Matching an immersion medium's refractive index to a cell's cytosol isolates organelle scattering.

Angularly-resolved light scattering has been proven to be an early detector of subtle changes in organelle size due to its sensitivity to scatterer size and refractive index contrast. However, for cells immersed in media with a refractive index close to 1.33, the cell itself acts as a larger scatterer and contributes its own angular signature. This whole-cell scattering, highly dependent on the cell's shape and size, is challenging to distinguish from the desired organelle scattering signal. This degrades the accuracy with which organelle size information can be extracted from the angular scattering. To mitigate this effect, we manipulate the refractive index of the immersion medium by mixing it with a water-soluble, biocompatible, high-refractive-index liquid. This approach physically reduces the amount of whole-cell scattering by minimizing the refractive index contrast between the cytosol and the modified medium. We demonstrate this technique on live cells adherent on a coverslip, using Fourier transform light scattering to compute the angular scattering from complex field images. We show that scattering from the cell: media refractive index contrast contributes significant scattering at angles up to twenty degrees and that refractive index-matching reduces such low-angle scatter by factors of up to 4.5. This result indicates the potential of refractive index-matching for improving the estimates of organelle size distributions in single cells.

Calibration Technique for Suppressing Residual Etalon Artifacts in Slit-Averaged Raman Spectroscopy.

Back-illuminated charged-coupled device (BI-CCD) arrays increase quantum efficiency but also amplify etaloning, a multiplicative, wavelength-dependent fixed-pattern effect. When spectral data from hundreds of BI-CCD rows are combined, the averaged spectrum will generally appear etalon-free. This can mask substantial etaloning at the row level, even if the BI-CCD has been treated to suppress the effect. This paper compares two methods of etalon correction, one with simple averaging and one with row-by-row calibration using a fluorescence standard. Two BI-CCD arrays, both roughened by the supplier to reduce etaloning, were used to acquire Raman spectra of murine bone specimens. For one array, etaloning was the dominant source of noise under the exposure conditions chosen, even for the averaged spectrum across all rows; near-infrared-excited Raman peaks were noticeably affected. In this case, row-by-row calibration improved the spectral quality of the average spectrum. The other CCD's performance was shot-noise limited and therefore received no benefit from the extra calibration. The different results highlight the importance of checking for and correcting row-level fixed pattern when measuring weak Raman signals in the presence of a large fluorescence background.

Improved prediction of femoral fracture toughness in mice by combining standard medical imaging with Raman spectroscopy.

Bone fragility and fracture risk are assessed by measuring the areal bone mineral density (aBMD) using dual-energy X-ray absorptiometry (DXA). While aBMD correlates with bone strength, it is a poor predictor of fragility fracture risk. Alternatively, fracture toughness assesses the bone's resistance to crack propagation and fracture, making it a suitable bone quality metric. Here, we explored how femoral midshaft measurements from DXA, micro-computed tomography (µCT), and Raman spectroscopy could predict fracture toughness. We hypothesized that ovariectomy (OVX) decreases aBMD and fracture toughness compared to controls and we can optimize a multivariate assessment of bone quality by combining results from X-ray and Raman spectroscopy. Female mice underwent an OVX (n = 5) or sham (n = 5) surgery at 3 months of age. Femurs were excised 3 months after ovariectomy and assessed with Raman spectroscopy, µCT, and DXA. Subsequently, a notch was created on the anterior side of the mid-diaphysis of the femurs. Three-point bending induced a controlled fracture that initiated at the notch. The OVX mice had a significantly lower aBMD, cortical thickness, and fracture toughness when compared to controls (p < 0.05). A leave one out cross-validated (LOOCV) partial least squares regression (PLSR) model based only on the combination of aBMD and cortical thickness showed no significant predictive correlations with fracture toughness, whereas a PLSR model based on principal components derived from the full Raman spectra yielded significant prediction (r2 = 0.71, p < 0.05). Further, the PLSR model was improved by incorporating aBMD, cortical thickness, and principal components from Raman spectra (r2 = 0.92, p < 0.001). This exploratory study demonstrates combining X-ray with Raman spectroscopy leads to a more accurate assessment of bone fracture toughness and could be a useful diagnostic tool for the assessment of fragility fracture risk.

Determination of best Raman spectroscopy spatial offsets for transcutaneous bone quality assessments in human hands.

Spatially offset Raman spectroscopy (SORS) is able to detect bone signal transcutaneously and could assist in predicting bone fracture risk. Criteria for optimal source-detector offsets for transcutaneous human measurements, however, are not well-established. Although larger offsets yield a higher percentage of bone signal, the absolute amount of bone signal decreases. Spectral unmixing into bone, adipose, and non-adipose components was employed to quantify changes in bone signal to noise ratio across a range of offsets, and optimal offsets for phalanx and metacarpal measurements were determined. The bone signal to noise ratio was maximized at offsets ranging from 4-6 mm.

Phase-sensitive, angle-resolved light-scattering microscopy of single cells.

We report what is to our knowledge the first use of Fourier phase microscopy (FPM) to estimate diameters of individual single-micrometer beads and to classify cells based upon changes in scatterer size distribution. FPM, a quantitative phase imaging (QPI) method, combines the planar illumination typically used in off-axis QPI (ideal for Mie theory analysis) with the common-path geometry typically used in on-axis QPI (ideal for optimizing angular scattering range). Low-spatial-frequency imaging artifacts inherent to FPM have negligible impact upon these angular-domain applications. The system is simple to align and stable, and requires no external reference beam. Angular scattering patterns obtained from single 1 µm polystyrene beads in glycerol (Δn=0.11) display unprecedented fidelity to Mie theory, produce diameter estimates consistent with the manufacturer's specifications, and offer precision on the scale of tens of nanometers. Measurements of macrophages at different stages of antibody-dependent cellular phagocytosis demonstrate the ability to detect changes in a cell's scattering caused by the presence of phagocytosed material within.

Purification of Human CD34+CD90+ HSCs Reduces Target Cell Population and Improves Lentiviral Transduction for Gene Therapy.

Hematopoietic stem cell (HSC) gene therapy has the potential to cure many genetic, malignant, and infectious diseases. We have shown in a nonhuman primate gene therapy and transplantation model that the CD34+CD90+ cell fraction was exclusively responsible for multilineage engraftment and hematopoietic reconstitution. In this study, we show the translational potential of this HSC-enriched CD34 subset for lentivirus-mediated gene therapy. Alternative HSC enrichment strategies include the purification of CD133+ cells or CD38low/- subsets of CD34+ cells from human blood products. We directly compared these strategies to the isolation of CD90+ cells using a good manufacturing practice (GMP) grade flow-sorting protocol with clinical applicability. We show that CD90+ cell selection results in about 30-fold fewer target cells in comparison to CD133+ or CD38low/- CD34+ hematopoietic stem and progenitor cell (HSPC) subsets without compromising the engraftment potential in vivo. Single-cell RNA sequencing confirmed nearly complete depletion of lineage-committed progenitor cells in CD90+ fractions compared to alternative selections. Importantly, lentiviral transduction efficiency in purified CD90+ cells resulted in up to 3-fold higher levels of engrafted gene-modified blood cells. These studies should have important implications for the manufacturing of patient-specific HSC gene therapy and gene-engineered cell products.

Soft-tissue spectral subtraction improves transcutaneous Raman estimates of murine bone strength in vivo.

Transcutaneous determination of a bone's Raman spectrum is challenging because the type I collagen in the overlying soft tissue is spectroscopically identical to that in bone. In a previous transcutaneous study of murine tibiae, we developed a library-based model called SOLD to unmix spatially offset Raman measurements into three spectra: a bone estimate, a soft tissue estimate, and a residual. Here, we demonstrate the value of combining the bone estimate and the residual to produce a "top layer subtracted" (tls) spectrum. We report superior prediction of two standard bone metrics (volumetric bone mineralization density and maximum torque) using partial least squares regression models based upon tls spectra rather than SOLD bone estimates, implying that the spectral residuals contain useful information. Simulations reinforce experimental in vivo findings. This chemometric approach, which we denote as SOLD/TLS, could have broad applicability in situations where comprehensive spectral libraries are difficult to acquire.

Silicon Nanomembrane Filtration and Imaging for the Evaluation of Microplastic Entrainment along a Municipal Water Delivery Route.

To better understand the origin of microplastics in municipal drinking water, we evaluated 50 mL water samples from different stages of the City of Rochester's drinking water production and transport route, from Hemlock Lake to the University of Rochester. We directly filtered samples using silicon nitride nanomembrane filters with precisely patterned slit-shaped pores, capturing many of the smallest particulates (<20 µm) that could be absorbed by the human body. We employed machine learning algorithms to quantify the shapes and quantity of debris at different stages of the water transport process, while automatically segregating out fibrous structures from particulate. Particulate concentrations ranged from 13 to 720 particles/mL at different stages of the water transport process and fibrous pollution ranged from 0.4 to 8.3 fibers/mL. A subset of the debris (0.2-8.6%) stained positively with Nile red dye which identifies them as hydrophobic polymers. Further spectroscopic analysis also indicated the presence of many non-plastic particulates, including rust, silicates, and calcium scale. While water leaving the Hemlock Lake facility is mostly devoid of debris, transport through many miles of piping results in the entrainment of a significant amount of debris, including plastics, although in-route reservoirs and end-stage filtration serve to reduce these concentrations.

Angularly resolved, finely sampled elastic scattering measurements of single cells: requirements for robust organelle size extractions.

Angularly resolved elastic light scattering is an established technique for probing the average size of organelles in biological tissue and cellular ensembles. Focusing of the incident light to illuminate no more than one cell at a time restricts the minimum forward-scattering angle θmin that can be detected. Series of simulated single-cell angular-scattering patterns have been generated to explore how size estimates vary as a function of θmin. At a setting of θmin = 20 deg, the size estimates hop unstably between multiple minima in the solution space as simulated noise (mimicking experimentally observed levels) is varied. As θmin is reduced from 20 deg to 10 deg, the instability vanishes, and the variance of estimates near the correct answer also decreases. The simulations thus suggest that robust Mie theory fits to single-cell scattering at 785 nm excitation require measurements down to at least 15 deg. Notably, no such instability was observed at θmin = 20 deg for narrow bead distributions. Accurate sizing of traditional calibration beads is, therefore, insufficient proof that an angular-scattering system is capable of robust analysis of single cells. Experimental support for the simulation results is also presented using measurements on cells fixed with formaldehyde.

In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level.

The mouse embryo has long been central to the study of mammalian development; however, elucidating the cell behaviors governing gastrulation and the formation of tissues and organs remains a fundamental challenge. A major obstacle is the lack of live imaging and image analysis technologies capable of systematically following cellular dynamics across the developing embryo. We developed a light-sheet microscope that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation mouse embryo and captures its development from gastrulation to early organogenesis at the cellular level. We furthermore developed a computational framework for reconstructing long-term cell tracks, cell divisions, dynamic fate maps, and maps of tissue morphogenesis across the entire embryo. By jointly analyzing cellular dynamics in multiple embryos registered in space and time, we built a dynamic atlas of post-implantation mouse development that, together with our microscopy and computational methods, is provided as a resource. VIDEO ABSTRACT.

Spatially offset Raman spectroscopy for in vivo bone strength prediction.

Bone strength is a worldwide health concern. Although multiple techniques have been developed to evaluate bone quality, there are still gaps to be filled. Here we report a non-invasive approach for the prediction of bone strength in vivo using spatially offset Raman spectroscopy. Raman spectra were acquired transcutaneously from the tibiae of mice from 4 to 23 weeks old and subsequently on the exposed bones. Partial least squares regression was applied to generate predictions of the areal bone mineral density (aBMD), volumetric bone mineralization density (vBMD), and maximum torque (MT) of each tibia as quantified by dual-energy X-ray absorptiometry, microCT imaging, and biomechanical tests, respectively. Significant correlations were observed between Raman spectral predictions and the reference values in all three categories. To our knowledge, this is the first demonstration of Raman spectroscopy predicting a biomechanical bone parameter (MT) in vivo with an uncertainty much smaller than the spread in the reference values.

Sensitivity of spatially offset Raman spectroscopy (SORS) to subcortical bone tissue.

The development of spatially offset Raman spectroscopy (SORS) has enabled deep, non-invasive chemical characterization of turbid media. Here, we use SORS to measure subcortical bone tissue and depth-resolved biochemical variability in intact, exposed murine bones. We also apply the technique to study a mouse model of the genetic bone disorder osteogenesis imperfecta. The results suggest that SORS is more sensitive to disease-related biochemical differences in subcortical trabecular bone and marrow than conventional Raman measurements.

Methodology for high-yield acquisition of functional near-infrared spectroscopy data from alert, upright infants.

Functional near-infrared spectroscopy (fNIRS) research to date has tended to publish group-averaged rather than individual infant data due to normative basic research goals. Acquisition of individual infant time courses holds interest, however, both for cognitive science and particularly for clinical applications. Infants are more difficult to study than adults as they cannot be instructed to remain still. In addressing this, upright infants pose several associated complications for the researcher. We identified and optimized the factors that affect the quality of fNIRS data from individual 6- to 9-month-old infants exposed to a visual stimulation paradigm. The fNIRS headpiece was reconfigured to reduce inertia, increase comfort, and improve conformity to the head, while preserving fiber density to avoid missing the visual cortex activation. The visual-stimulation protocol was modified to keep the attention of infants throughout the measurement, thus helping to reduce motion artifacts. Adequate optical contact was verified by checking power levels before each measurement. By revising our experimental process and our data rejection criteria to prioritize good optical contact, we report for the first time usable hemodynamic data from 83% of infants and that two-thirds of infants produced a statistically significant fNIRS response.

Isolating the effects of surface vasculature in infant neuroimaging using short-distance optical channels: a combination of local and global effects.

Functional near-infrared spectroscopy (fNIRS) records hemodynamic changes in the cortex arising from neurovascular coupling. However, (noninvasive) fNIRS recordings also record surface vascular signals arising from noncortical sources (e.g., in the skull, skin, dura, and other tissues located between the sensors and the brain). A current and important focus in the fNIRS community is determining how to remove these noncortical vascular signals to reduce noise and to prevent researchers from erroneously attributing responses to cortical sources. The current study is the first to test a popular method for removing signals from the surface vasculature (removing short, 1 cm, channel recordings from long, 3 cm, channel recordings) in human infants, a population frequently studied using fNIRS. We find evidence that this method does remove surface vasculature signals and indicates the presence of both local and global surface vasculature signals. However, we do not find that the removal of this information changes the statistical inferences drawn from the data. This latter result not only questions the importance of removing surface vasculature responses for empiricists employing this method, but also calls for future research using other tasks (e.g., ones with a weaker initial result) with this population and possibly additional methods for removing signals arising from the surface vasculature in infants.