Organelle-specific phase contrast microscopy (OS-PCM) enables facile correlation study of organelles and proteins

Current methods for studying organelle and protein interactions and correlations depend on multiplex fluorescent labeling, which is experimentally complex and harmful to cells. Here we propose to solve this challenge via OS-PCM, where organelles are imaged and segmented without labels, and combined with standard fluorescence microscopy of protein distributions. In this work, we develop new neural networks to obtain unlabeled organelle, nucleus and membrane predictions from a single 2D image. Automated analysis is also implemented to obtain quantitative information regarding the spatial distribution and co-localization of both protein and organelle, as well as their relationship to the landmark structures of nucleus and membrane. Using mitochondria and DRP1 protein as a proof-of-concept, we conducted a correlation study where only DRP1 is labeled, with results consistent with prior reports utilizing multiplex labeling. Thus our work demonstrates that OS-PCM simplifies the correlation study of organelles and proteins.

Deep learning-based size prediction for optical trapped nanoparticles and extracellular vesicles from limited bandwidth camera detection

Due to its ability to record position, intensity, and intensity distribution information, camera-based monitoring of nanoparticles in optical traps can enable multi-parametric morpho-optical characterization at the single-particle level. However, blurring due to the relatively long (10s of microsecond) integration times and aliasing from the resulting limited temporal bandwidth affect the detected particle position when considering nanoparticles in traps with strong stiffness, leading to inaccurate size predictions. Here, we propose a ResNet-based method for accurate size characterization of trapped nanoparticles, which is trained by considering only simulated time series data of nanoparticles' constrained Brownian motion. Experiments prove the method outperforms state-of-art sizing algorithms such as adjusted Lorentzian fitting or CNN-based networks on both standard nanoparticles and extracellular vesicles (EVs), as well as maintains good accuracy even when measurement times are relatively short (<1s per particle). On samples of clinical EVs, our network demonstrates a well-generalized ability to accurately determine the EV size distribution, as confirmed by comparison with gold-standard nanoparticle tracking analysis (NTA). Furthermore, by combining the sizing network with still frame images from high-speed video, the camera-based optical tweezers have the unique capacity to quantify both the size and refractive index of bio-nanoparticles at the single-particle level. These experiments prove the proposed sizing network as an ideal path for predicting the morphological heterogeneity of bio-nanoparticles in optical potential trapping-related measurements.

Highly Sensitive, Portable Detection System for Multiplex Chemiluminescence Analysis

Chemiluminescence (CL) has emerged as a critical tool for the sensing and quantification of various bioanalytes in virtually all clinical fields. However, the rapid nature of many CL reactions raises challenges for typical low-cost optical sensors such as cameras to achieve accurate and sensitive detection. Meanwhile, classic sensors such as photomultiplier tubes are highly sensitive but lack spatial multiplexing capabilities and are generally not suited for point-of-care applications outside a standard laboratory setting. To address this issue, in this paper, a miniaturized and versatile silicon-photomultiplier-based fiber-integrated CL device (SFCD) was designed for sensitive multiplex CL detection. The SFCD comprises a silicon photomultiplier array coupled to an array of high numerical aperture plastic optical fibers to achieve 16-plex detection. The optical fibers ensure efficient light collection while allowing the fixed detector to be mated with diverse sample geometries (e.g., circular or grid), simply by adjusting the fiber configuration. In a head-to-head comparison with a lens-based camera system featuring a cooled detector, the SFCD achieved a 14-fold improved limit of detection in both direct and enzyme-mediated CL reactions. The SFCD also features improved compactness and lower cost, as well as faster temporal resolution compared with camera-based systems while preserving spatial multiplexing and good environmental robustness. Thus, the SFCD has excellent potential for point-of-care biosensing applications.

Fast Raman imaging through the combination of context-aware matrix completion and low spectral resolution

Raman hyperspectral imaging is an effective method for label-free imaging with chemical specificity, yet the weak signals and correspondingly long integration times have hindered its wide adoption as a routine analytical method. Recently, low resolution Raman imaging has been proposed to improve the spectral signal-to-noise ratio, which significantly improves the speed of Raman imaging. In this paper, low resolution Raman spectroscopy is combined with "context-aware" matrix completion, where regions of the sample that are not of interest are skipped, and the regions that are measured are under-sampled, then reconstructed with a low-rank constraint. Both simulations and experiment show that low-resolution Raman boosts the speed and image quality of the computationally-reconstructed Raman images, allowing deeper sub-sampling, reduced exposure time, and an overall >10-fold improvement in imaging speed, without sacrificing chemical specificity or spatial image quality. As the method utilizes traditional point-scan imaging, it retains full confocality and is "backwards-compatible" with pre-existing traditional Raman instruments, broadening the potential scope of Raman imaging applications.

Rapid Intracellular Detection and Analysis of Lipid Droplets' Morpho-Chemical Composition by Phase-Guided Raman Sampling

Intracellular lipid droplets (LDs) are dynamic, complex organelles involved in nearly all aspects of cellular metabolism. In situ characterization methods are primarily limited to fluorescence imaging, which yields limited chemical information, or Raman spectroscopy, which provides excellent chemical profiling but very low throughput. Here, we propose a new paradigm where locations of both large and small droplets are obtained automatically from high-resolution phase images and fed into a galvomirror-controlled Raman sampling arm to obtain the full spectrum of each LD efficiently. Using this phase-guided Raman sampling, we can characterize hundreds of LDs within a single cell in minutes and easily acquire more than 40,000 high-quality spectra. The data set revealed strong, cell line-dependent, cell-dependent, and individual droplet-dependent composition changes to various culture conditions. In particular, we revealed a strong competitive relationship between mono- and polyunsaturated fatty acids, where supplementation with one led to a relative decrease in the other.

Image reconstruction for low cost spatial light interference microscopy with fixed and arbitrary phase modulation

During the past decade, spatial light interference microscopy (SLIM) has undergone rapid development, evidenced by its broadening applications in biology and medicine. However, the need for an expensive spatial light modulator (SLM) may limit its adoption, and the requirement for multiple images per plane limits its speed in volumetric imaging. Here we propose to address these issues by replacing the SLM with a mask fabricated from a low cost optical density (OD) filter, and recover high contrast images computationally rather than through phase-shifting. This is done using a specially constructed Wiener filter to recover the object scattering potential. A crucial part of the Wiener filter is estimating the arbitrary phase introduced by the OD filter. Our results demonstrate that not only were we able to estimate the OD filter's phase modulation in situ, but also the contrast of the reconstructed images is greatly improved. Comparisons with other related methods are also performed, with the conclusion that the combination of an inexpensive OD mask and modified Wiener filtering leads to results that are closest to the traditional SLIM setup. Thus, we have demonstrated the feasibility of a low cost, high speed SLIM system utilizing computational phase reconstruction, paving the way for wider adoption of high resolution phase microscopy.

A critical evaluation of compressed line-scan Raman imaging

The weak signal strength of Raman imaging leads to long imaging times. To increase the speed of Raman imaging, line scanning and compressed Raman imaging methods have been proposed. Here we combine both line scanning and compressed sensing to further increase the speed. However, the direct combination leads to poor reconstruction results due to the missed coverage of the sample. To avoid this issue, "full-coverage" Compressed Line-scan Raman Imaging (FC-CLRI) is proposed, where line positions are random but constrained to measure each line position of the sample at least once. In proof-of-concept studies of polymer beads and yeast cells, FC-CLRI achieved reasonable image quality while making only 20-40% of the measurements of a fully-sampled line-scan image, achieving 640 μm² FOV imaging in <2 min with 1.5 mW μm^-2 laser power. Furthermore, we critically evaluate the CLRI method through comparison with simple downsampling, and have found that FC-CLRI preserves spatial resolution better while naïve downsampling provides an overall higher image quality for complex samples.

Super-resolved Raman imaging via galvo-painted structured line illumination

Traditional line-scan Raman imaging features a rapid imaging speed while preserving complete spectral information, yet has diffraction-limited resolution. Sinusoidally structured line excitation can yield an improvement in the lateral resolution of the Raman image along the line's direction. However, given the need for the line and spectrometer slit to be aligned, the resolution in the perpendicular direction remains diffraction limited. To overcome this, we present here a galvo-modulated structured line imaging system, where a system of three galvos can arbitrarily orient the structured line on the sample plane, while keeping the beam aligned to the spectrometer slit in the detection plane. Thus, a two-fold isotropic improvement in the lateral resolution fold is possible. We demonstrate the feasibility using mixtures of microspheres as chemical and size standards. The results prove an improvement in the lateral resolution of 1.8-fold (limited by line contrast at higher frequencies), while preserving complete spectral information of the sample.

Hybrid Principal Component Analysis Denoising Enables Rapid, Label-Free Morpho-Chemical Quantification of Individual Nanoliposomes

Laser tweezers Raman spectroscopy enables multiplexed, quantitative chemical and morphological analysis of individual bionanoparticles such as drug-loaded nanoliposomes, yet it requires minutes-scale acquisition times per particle, leading to a lack of statistical power in typical small-sized data sets. The long acquisition times present a bottleneck not only in measurement time but also in the analytical throughput, as particle concentration (and thus throughput) must be kept low enough to avoid swarm measurement. The only effective way to improve this situation is to reduce the exposure time, which comes at the expense of increased noise. Here, we present a hybrid principal component analysis (PCA) denoising method, where a small number (∼30 spectra) of high signal-to-noise ratio (SNR) training data construct an effective principal component subspace into which low SNR test data are projected. Simulations and experiments prove the method outperforms traditional denoising methods such as the wavelet transform or traditional PCA. On experimental liposome samples, denoising accelerated data acquisition from 90 to 3 s, with an overall 4.5-fold improvement in particle throughput. The denoised data retained the ability to accurately determine complex morphochemical parameters such as lamellarity of individual nanoliposomes, as confirmed by comparison with cryo-EM imaging. We therefore show that hybrid PCA denoising is an efficient and effective tool for denoising spectral data sets with limited chemical variability and that the RR-NTA technique offers an ideal path for studying the multidimensional heterogeneity of nanoliposomes and other micro/nanoscale bioparticles.

High-Resolution Low-Power Hyperspectral Line-Scan Imaging of Fast Cellular Dynamics Using Azo-Enhanced Raman Scattering Probes

Small-molecule Raman probes for cellular imaging have attracted great attention owing to their sharp peaks that are sensitive to environmental changes. The small cross section of molecular Raman scattering limits dynamic cellular Raman imaging to expensive and complex coherent approaches that acquire single-channel images and lose hyperspectral Raman information. We introduce a new method, dynamic azo-enhanced Raman imaging (DAERI), to couple the new class of azo-enhanced Raman probes with a high-speed line-scan Raman imaging system. DAERI achieved high-resolution low-power imaging of fast cellular dynamics resolved at ∼270 nm along the confocal direction, 75 μW/μm² and 3.5 s/frame. Based on the azo-enhanced Raman probes with characteristic signals 10²-10⁴ stronger than classic Raman labels, DAERI was not restricted to the cellular Raman-silent region as in prior work and enabled multiplex visualization of organelle motions and interactions. We anticipate DAERI to be a powerful tool for future studies in biophysics and cell biology.

A Drop-in, Focus-Extending Phase Mask Simplifies Microscopic and Microfluidic Imaging Systems for Cost-Effective Point-of-Care Diagnostics

Microscopic imaging and imaging flow cytometry have wide potential in point-of-care assays; however, their narrow depth of focus necessitates precise mechanical or fluidic focus control of a sample in order to acquire high-quality images that can be used for downstream analysis, increasing the cost and complexity of the imaging system. This complexity represents a barrier to miniaturization and translation of point-of-care assays based on microscopic imaging or imaging flow cytometry. To address this challenge, we present a simple drop-in phase mask with a physics-informed, circularly symmetric asphere phase profile that extends the depth of focus by >5-fold while largely preserving the image quality compared to other depth extending methods. We show that such a focus-extended system overcomes manufacturing tolerances in low-cost sample chambers, enlarges the useable field-of-view of low-cost objectives, and permits increased throughput and precision in flow imaging systems without the need for complex flow-focusing. As the image quality is preserved without the need for postacquisition image restoration, our solution is also highly appropriate for on-line applications such as cell sorting.

Microfluidic Paper-Based Preconcentration and Retrieval for Rapid Ribonucleic Acid Biomarker Detection and Visualization

Microfluidic paper-based analytical devices (μPADs) have attracted significant attention in the field of point-of-care (POC) diagnostics. However, the heterogeneous structure of the paper often impairs the limit of detection (LOD) for low-abundance targets when those targets are directly analyzed. One viable solution to bypass this limitation is to elevate the target concentration above the LOD on-site to reach a valid readout. Here, we developed a 3D μPADs preconcentrator (3D-μP²) to increase sample concentration by electrokinetic trapping and demonstrated its application in increasing the LOD of a downstream colorimetric assay. The three-dimensional (3D) structure of this device was composed of a loading pad, a vertical fluid path formed by stacked absorbent pads, and an ion-selective membrane of PEDOT:PSS. This novel design facilitates fast preconcentration, high capacity in sample processing, and easy target retrieval. The concentration of an exemplary target, a single-stranded DNA sequence, was increased up to 170-fold within 80 s. The LOD of the colorimetric assay to verify the DNA target was increased 3 orders of magnitude with a preconcentrated sample compared to the control. The device and its analysis equipment used in this study were all cheap and portable. Thus, the 3D-μP² can be a powerful POC tool for sample pretreatment in resource-limited areas.

Label-free imaging of intracellular organelle dynamics using flat-fielding quantitative phase contrast microscopy (FF-QPCM)

Panoramic and long-term observation of nanosized organelle dynamics and interactions with high spatiotemporal resolution still hold great challenge for current imaging platforms. In this study, we propose a live-organelle imaging platform, where a flat-fielding quantitative phase contrast microscope (FF-QPCM) visualizes all the membrane-bound subcellular organelles, and an intermittent fluorescence channel assists in specific organelle identification. FF-QPCM features a high spatiotemporal resolution of 245 nm and 250 Hz and strong immunity against external disturbance. Thus, we could investigate several important dynamic processes of intracellular organelles from direct perspectives, including chromosome duplication in mitosis, mitochondrial fusion and fission, filaments, and vesicles' morphologies in apoptosis. Of note, we have captured, for the first time, a new type of mitochondrial fission (entitled mitochondrial disintegration), the generation and fusion process of vesicle-like organelles, as well as the mitochondrial vacuolization during necrosis. All these results bring us new insights into spatiotemporal dynamics and interactions among organelles, and hence aid us in understanding the real behaviors and functional implications of the organelles in cellular activities.

Simultaneous 3D deconvolution and halo removal for spatial light interference microscopy through a two-edge apodized Wiener filter

As one of the most sensitive quantitative phase microscopy techniques, spatial light interference microscopy (SLIM) has undergone rapid development in the past decade and has seen wide application in both basic science and clinical studies. However, as with any other traditional microscope, the axial resolution is the worst among the three dimensions. This leads to lower contrast in the thicker regions of cell samples. Another common foe in the phase contrast image is the halo artifact, which can block underlying structures, in particular when high resolution is desired. Current solutions focus on either halo removal or contrast enhancement alone, and thus need two processing steps to create both high contrast and halo-free phase images. Further, raw images often suffer from artifacts that are both bright and slowly varying, dubbed here as cloud-like artifacts. After deconvolution, these cloud-like artifacts often dominate the image and obscure high-frequency information, which is typically of greatest interest. In this paper, we first analyzed the unique characteristics of the phase transfer function associated with SLIM to find the root of the cloud-like artifacts and halo artifacts. Then we designed a two-edge apodized deconvolution scheme as a counter measure. We show that even with a simple Wiener filter, the two-edge apodization (TEA) can effectively improve the contrast while suppressing the halo and cloud-like artifacts. Our algorithm, named TEA-Weiner, is non-iterative and thus can be implemented in real time. For low-contrast structures inside the cell such as the endoplasmic reticulum (ER), where ringing artifacts are more likely, we show that two-edge apodization can be combined with additional constraints such as total variation so that their contrast can be enhanced simultaneously with other bright structures inside the cell. Comparing our method with other state-of-the-art algorithms, our method has two advantages: First, deconvolution and halo removal are accomplished simultaneously; second, the image quality is highest using TEA-Weiner filtering.

Multicomponent Raman spectral regression using complete and incomplete models and convolutional neural networks

A critical study of CNN networks for Raman regression problems is presented. In evaluating performance on models where spectral information is missing, CNN performs as well as state-of-the-art methods, without the need for spectral pre-processing.

Epi-illumination dark-field microscopy enables direct visualization of unlabeled small organisms with high spatial and temporal resolution

Dark-field microscopy is known to offer both high resolution and direct visualization of thin samples. However, its performance and optimization on thick samples is under-explored and so far, only meso-scale information from whole organisms has been demonstrated. In this work, we carefully investigate the difference between trans- and epi-illumination configurations. Our findings suggest that the epi-illumination configuration is superior in both contrast and fidelity compared to trans-illumination, while having the added advantage of experimental simplicity and an "open top" for experimental intervention. Guided by the theoretical analysis, we constructed an epi-illumination dark-field microscope with measured lateral and axial resolutions of 260 nm and 520 nm, respectively. Subcellular structures in whole organisms were directly visualized without the need for image reconstruction, and further confirmed via simultaneous fluorescence imaging. With an imaging speed of 20 to 50 fps, we visualize fast dynamic processes such as cell division and pharyngeal pumping in Caenorhabditis elegans.

Vibrational Fingerprint Analysis of an Azo-based Resonance Raman Scattering Probe for Imaging Proton Distribution in Cellular Lysosomes

Due to the fundamental mechanism of vibrational state transitions for chemical bonds, the spectra of Raman scattering are narrow-banded and photostable signals capable of probing specific reactions. In the case of protonation/deprotonation reactions, certain chemical bonds are broken and new bonds are formed. Based on the changes of the vibrational modes for the corresponding bonds, fingerprint analysis of multiple Raman bands may allow for the in situ visualization of proton distribution in live cells. However, Raman scattering faces the well-known challenge of low sensitivity. To perform the vibrational fingerprint analysis of Raman scattering by overcoming this challenge, we developed an azo-based resonance Raman pH probe. It was an azobenzene-featured small molecule responsive to protons with the inherent Raman signal ∼10⁴-fold more intense than that of the conventional alkyne-type Raman reporter 5-ethynyl-2'-deoxyuridine. Through the substitution of the electron-donating and -withdrawing entities to the azobenzene group, the effect of resonance Raman scattering and fluorescence quenching was obtained. This effect resulted in a significant Raman enhancement factor of ∼10³ compared to the counterpart molecules without the molecular design. Based on the enhanced Raman sensitivity of the azo-based resonance Raman pH probe, the identification of vibrational fingerprint changes at the azo group was achieved during the protonation/deprotonation reactions, and the vibrational fingerprint analysis resolved a pH difference of less than 0.2 unit. The method enabled sensitive hyperspectral cell imaging that clearly visualized the change of proton distribution in autophagic cells.

Organelle-specific phase contrast microscopy enables gentle monitoring and analysis of mitochondrial network dynamics

Mitochondria are delicate organelles that play a key role in cell fate. Current research methods rely on fluorescence labeling that introduces stress due to photobleaching and phototoxicity. Here we propose a new, gentle method to study mitochondrial dynamics, where organelle-specific three-dimensional information is obtained in a label-free manner at high resolution, high specificity, and without detrimental effects associated with staining. A mitochondria cleavage experiment demonstrates that not only do the label-free mitochondria-specific images have the required resolution and precision, but also fairly include all cells and mitochondria in downstream morphological analysis, while fluorescence images omit dim cells and mitochondria. The robustness of the method was tested on samples of different cell lines and on data collected from multiple systems. Thus, we have demonstrated that our method is an attractive alternative to study mitochondrial dynamics, connecting behavior and function in a simpler and more robust way than traditional fluorescence imaging.

A sample-preparation-free, automated, sample-to-answer system for cell counting in human body fluids

While many clinical laboratory tests are now highly automated, body fluid cell counting, particularly in low-cellularity samples such as cerebral spinal fluid (CSF), is often performed manually. Here, we report a simple, cost-effective method to obtain white and red blood cell counts from human body fluids such as CSF. The method consists of a compact, automated, and low-cost fluorescence microscope system, coupled to a sample chamber containing all of the necessary reagents in dry form to stain and prepare the sample. Sample focus and scanning are handled automatically, and the acquired multimodal images are automatically analyzed to extract cell counts. Comparison with manual counting on over 200 clinical samples shows excellent agreement. As the system counts a substantially larger image region than a standard manual cell count, we find our sensitivity to extremely low cellularity samples to potentially be higher than the manual gold standard, evidenced by our system recording images of cells in samples whose cell count was registered as "0" by a trained user. Thus, our system holds promise for routine, automated, and sensitive analysis of body fluids whose cellularity extends across a wide dynamic range.

Azo-Enhanced Raman Scattering for Enhancing the Sensitivity and Tuning the Frequency of Molecular Vibrations

Raman scattering provides stable narrow-banded signals that potentially allow for multicolor microscopic imaging. The major obstacle for the applications of Raman spectroscopy and microscopy is the small cross section of Raman scattering that results in low sensitivity. Here, we report a new concept of azo-enhanced Raman scattering (AERS) by designing the intrinsic molecular structures using resonance Raman and concomitant fluorescence quenching strategies. Based on the selection of vibrational modes and the enhancing unit of azobenzenes, we obtained a library of AERS molecules with specific Raman signals in the fingerprint and silent frequency regions. The spectral characterization and molecular simulation revealed that the azobenzene unit conjugated to the vibrational modes significantly enhanced Raman signals due to the mechanism of extending the conjugation system, coupling the electronic-vibrational transitions, and improving the symmetry of vibrational modes. The nonradiative decay of azobenzene from the excited state quenched the commitment fluorescence, thus providing a clean background for identifying Raman scattering. The most sensitive AERS molecules produced Raman signals of more than 4 orders of magnitude compared to 5-ethynyl-2'-deoxyuridine (EdU). In addition, a frequency tunability of 10 distinct Raman bands was achieved by selecting different types of vibrational modes. This methodology of AERS allows for designing small-molecule Raman probes to visualize various entities in complex systems by multicolor spontaneous Raman imaging. It will open new prospects to explore innovative applications of AERS in interdisciplinary research fields.

Fast confocal Raman imaging via context-aware compressive sensing

Raman hyperspectral imaging is a powerful method to obtain detailed chemical information about a wide variety of organic and inorganic samples noninvasively and without labels. However, due to the weak, nonresonant nature of spontaneous Raman scattering, acquiring a Raman imaging dataset is time-consuming and inefficient. In this paper we utilize a compressive imaging strategy coupled with a context-aware image prior to improve Raman imaging speed by 5- to 10-fold compared to classic point-scanning Raman imaging, while maintaining the traditional benefits of point scanning imaging, such as isotropic resolution and confocality. With faster data acquisition, large datasets can be acquired in reasonable timescales, leading to more reliable downstream analysis. On standard samples, context-aware Raman compressive imaging (CARCI) was able to reduce the number of measurements by ∼85% while maintaining high image quality (SSIM >0.85). Using CARCI, we obtained a large dataset of chemical images of fission yeast cells, showing that by collecting 5-fold more cells in a given experiment time, we were able to get more accurate chemical images, identification of rare cells, and improved biochemical modeling. For example, applying VCA to nearly 100 cells' data together, cellular organelles were resolved that were not faithfully reconstructed by a single cell's dataset.

Applying limiting entropy to quantify the alignment of collagen fibers by polarized light imaging

Collagen alignment has shown clinical significance in a variety of diseases. For instance, vulvar lichen sclerosus (VLS) is characterized by homogenization of collagen fibers with increasing risk of malignant transformation. To date, a variety of imaging techniques have been developed to visualize collagen fibers. However, few works focused on quantifying the alignment quality of collagen fiber. To assess the level of disorder of local fiber orientation, the homogeneity index (HI) based on limiting entropy is proposed as an indicator of disorder. Our proposed methods are validated by verification experiments on Poly Lactic Acid (PLA) filament phantoms with controlled alignment quality of fibers. A case study on 20 VLS tissue biopsies and 14 normal tissue biopsies shows that HI can effectively characterize VLS tissue from normal tissue (P < 0.01). The classification results are very promising with a sensitivity of 93% and a specificity of 95%, which indicated that our method can provide quantitative assessment for the alignment quality of collagen fibers in VLS tissue and aid in improving histopathological examination of VLS.

Nanometer precise red blood cell sizing using a cost-effective quantitative dark field imaging system

Because of the bulk, complexity, calibration requirements, and need for operator training, most current flow-based blood counting devices are not appropriate for field use. Standard imaging methods could be much more compact, inexpensive, and with minimal calibration requirements. However, due to the diffraction limit, imaging lacks the nanometer precision required to measure red blood cell volumes. To address this challenge, we utilize Mie scattering, which can measure nanometer-scale morphological information from cells, in a dark-field imaging geometry. The approach consists of a custom-built dark-field scattering microscope with symmetrically oblique illumination at a precisely defined angle to record wide-field images of diluted and sphered blood samples. Scattering intensities of each cell under three wavelengths are obtained by segmenting images via digital image processing. These scattering intensities are then used to determine size and hemoglobin information via Mie theory and machine learning. Validation on 90 clinical blood samples confirmed the ability to obtain mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), and red cell distribution width (RDW) with high accuracy. Simulations based on historical data suggest that an instrument with the accuracy achieved in this study could be used for widespread anemia screening.

Low resolution Raman: the impact of spectral resolution on limit of detection and imaging speed in hyperspectral imaging

The majority of problems in analytical Raman spectroscopy are mathematically over-determined, where many more spectral variables are measured than analytic outputs (such as chemical concentrations) are calculated. Thus, to improve spectral throughput and simplify system design, some researchers have explored the use of low resolution Raman systems for cell or tissue classification, achieving accuracy independent of spectral resolution. However, the tradeoffs inherent in this approach have not been systematically studied. Here, we theoretically and experimentally explore the relationship between spectral resolution and analytical error. We show that decreased spectral resolution leads to spectral signal-to-noise ratio and therefore more reliable results and lower limits of detection for equivalent integration times in blind unmixing of hyperspectral images. Our theoretical analysis demonstrates that the primary benefit of low resolution Raman spectroscopy is in overcoming detector noise (such as thermal or electronic noise). Therefore, the benefits are most pronounced when utilizing lower-grade, uncooled detectors. Therefore, using a low-cost CMOS camera we experimentally demonstrate the ability of low resolution Raman spectroscopy to achieve substantially improved imaging performance compared to fully-resolved Raman spectral imaging, paving the way for cost-effective, pervasive Raman spectroscopy.

Optical volumetric projection with large NA objectives for fast high-resolution 3D imaging of neural signals

One critical challenge in studying neural circuits of freely behaving model organisms is to record neural signals distributed within the whole brain, yet simultaneously maintaining cellular resolution. However, due to the dense packing of neuron cells in animal brains, high numerical aperture (NA) objectives are often required to differentiate neighboring neurons with the consequent need for axial scanning for whole brain imaging. Extending the depth of focus (EDoF) will be beneficial for fast 3D imaging of those neurons. However, current EDoF-enabled microscopes are primarily based on objectives with small NAs (≤0.3 ) such that the paraxial approximation can be applied. In this paper, we started from a nonparaxial approximation of the defocus aberration and derived a new phase mask that was appropriate for large NA microscopic systems. We validated the performance experimentally with a spatial light modulator (SLM) to create the designed phase mask. The performance was tested on different samples such as multilayered fluorescence beads and thick brain tissues, as well as with different objectives. Results confirmed that our design has extended the depth of focus about 10 fold and the image quality is much higher than those based on the most common EDoF method, the cubic phase method, popularly used to generate Airy beams. Meanwhile, our phase mask is rotationally symmetric and easy to fabricate. We fabricated one such phase plate and tested it on the pan-neuronal labeled Caenorhabditis elegans (C.elegans). The imaging performance demonstrated that we can capture all neurons in the whole brain with one snapshot and with cellular resolution, while the imaging speed is increased about 3 fold compared to the system using SLM. Thus we have shown that our method can not only provide the required imaging speed and resolution for studying neural activities in model animals, but also can be implemented as a low-cost, add-on module that can immediately augment existing fluorescence microscopes with only minor system modifications, and yielding substantially higher photon efficiency than SLM-based methods.

Additive Scoring Rules for Discrete Sample Spaces

In this paper, we develop strictly proper scoring rules that may be used to evaluate the accuracy of a sequence of probabilistic forecasts. In practice, when forecasts are submitted for multiple uncertainties, competing forecasts are ranked by their cumulative or average score. Alternatively, one could score the implied joint distributions. We demonstrate that these measures of forecast accuracy disagree under some commonly used rules. Furthermore, and most importantly, we show that forecast rankings can depend on the selected scoring procedure. In other words, under some scoring rules, the relative ranking of probabilistic forecasts does not depend solely on the information content of those forecasts and the observed outcome. Instead, the relative ranking of forecasts is a function of the process by which those forecasts are evaluated. As an alternative, we describe additive and strongly additive strictly proper scoring rules, which have the property that the score for the joint distribution is equal to a sum of scores for the associated marginal and conditional distributions. We give methods for constructing additive rules and demonstrate that the logarithmic score is the only strongly additive rule. Finally, we connect the additive properties of scoring rules with analogous properties for a general class of entropy measures.

Combined Morpho-Chemical Profiling of Individual Extracellular Vesicles and Functional Nanoparticles without Labels

Biological nanoparticles are important targets of study, yet their small size and tendency to aggregate makes their heterogeneity difficult to profile on a truly single-particle basis. Here we present a label-free system called 'Raman-enabled nanoparticle trapping analysis' (R-NTA) that optically traps individual nanoparticles, records Raman spectra and tracks particle motion to identify chemical composition, size, and refractive index. R-NTA has the unique capacity to characterize aggregation status and absolute chemical concentration at the single-particle level. We validate the method on NIST standards and liposomes, demonstrating that R-NTA can accurately characterize size and chemical heterogeneity, including determining combined morpho-chemical properties such as the number of lamellae in individual liposomes. Applied to extracellular vesicles (EVs), we find distinct differences between EVs from cancerous and noncancerous cells, and that knockdown of the TRPP2 ion channel, which is pathologically highly expressed in laryngeal cancer cells, leads the EVs to more closely resemble EVs from normal epithelial cells. Intriguingly, the differences in EV content are found in small subpopulations of EVs, highlighting the importance of single-particle measurements. These experiments demonstrate the power of the R-NTA system to measure and characterize the morpho-chemical heterogeneity of bionanoparticles.

Innovation in resuscitation: A novel clinical decision display system for advanced cardiac life support

INTRODUCTION

The Advanced Cardiac Life Support (ACLS) Clinical Decision Display System (CDDS) is a novel application designed to optimize team organization and facilitate decision-making during ACLS resuscitations. We hypothesized that resuscitation teams would more consistently adhere to ACLS guideline time intervals in simulated resuscitation scenarios with the CDDS compared to without.

METHODS

We conducted a simulation-based, non-blinded, randomized, crossover-design study with resuscitation teams comprised of Emergency Medicine physicians, registered nurses, critical care technicians, and paramedics. Each team performed 4 ACLS scenarios in randomized sequences, half with the CDDS and half without. We analyzed the resuscitations and recorded the times of interventions that have defined intervals by ACLS: rhythm checks, epinephrine administration, and shock delivery. In addition, we surveyed each resuscitation team regarding their experience using the CDDS.

RESULTS

On average, teams performed rhythm checks 4.9 s closer to ACLS guidelines with the CDDS (p = 0.0358). Teams were also more consistent; on average, teams reduced the variation of time between consecutive doses of epinephrine by 45% (p = 0.0001) and defibrillation by 47% (p < 0.0001). Ninety-eight percent of participants indicated they would use the CDDS if available in real cardiac arrests.

CONCLUSIONS

This study demonstrates that the CDDS improves the accuracy and precision of timed ACLS interventions in a simulated setting. Resuscitation teams were strongly in favor of utilizing the CDDS in clinical practice. Further investigations of the introduction of the platform into real time clinical environments will be needed to assess true efficacy and patient outcomes.

Improving the limit of detection in portable luminescent assay readers through smart optical design

Critical biomarkers of disease are increasingly being detected by point-of-care assays. Chemiluminescence (CL) and electrochemiluminescence (ECL) are often used in such assays due to their convenience and that they do not require light sources or other components that could complicate or add cost to the system. Reports of these assays often include readers built on a cellphone platform or constructed from low-cost components. However, the impact the optical design has on the limit of detection (LOD) in these systems remains unexamined. Here, we report a theoretical rubric to evaluate different optical designs in terms of maximizing the use of photons emitted from a CL or ECL assay to improve the LOD. We demonstrate that the majority of cellphone designs reported in the literature are not optimized, in part due to misunderstandings of the optical tradeoffs in collection systems, and in part due to limitations imposed on the designs arising from the use of a mobile phone with a very small lens aperture. Based on the theoretical rubric, we design a new portable reader built using off-the-shelf condenser optics, and demonstrate a nearly 10× performance enhancement compared to prior reports on an ECL assays running on a portable chip.

Quantitative phase microscopy with enhanced contrast and improved resolution through ultra-oblique illumination (UO-QPM)

Recent developments in phase contrast microscopy have enabled the label-free visualization of certain organelles due to their distinct morphological features, making this method an attractive alternative in the study of cellular dynamics. However tubular structures such as endoplasmic reticulum (ER) networks and complex dynamics such as the fusion and fission of mitochondria, due to their low phase contrast, still need fluorescent labeling to be adequately imaged. In this article, we report a quantitative phase microscope with ultra-oblique illumination that enables us to see those structures and their dynamics with high contrast for the first time without labeling. The imaging capability was validated through comparison to the fluorescence images with the same field-of-view. The high image resolution (~270 nm) was validated using both beads and cellular structures. Furthermore, we were able to record the vibration of ER networks at a frame rate of 250 Hz. We additionally show complex cellular processes such as remodeling of the mitochondria networks through fusion and fission and vesicle transportation along the ER without labels. Our high spatial and temporal resolution allowed us to observe mitochondria "spinning", which has not been reported before, further demonstrating the advantages of the proposed method.

Simple adaptive mobile phone screen illumination for dual phone differential phase contrast (DPDPC) microscopy

Phase contrast imaging is widely employed in the physical, biological, and medical sciences. However, typical implementations involve complex imaging systems that amount to in-line interferometers. We adapt differential phase contrast (DPC) to a dual-phone illumination-imaging system to obtain phase contrast images on a portable mobile phone platform. In this dual phone differential phase contrast (dpDPC) microscope, semicircles are projected sequentially on the display of one phone, and images are captured using a low-cost, short focal length lens attached to the second phone. By numerically combining images obtained using these semicircle patterns, high quality DPC images with ≈ 2 micrometer resolution can be easily acquired with no specialized hardware, circuitry, or instrument control programs.

A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning

Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, automated parasite diagnostic system that does not require special sample preparation or a trained user was developed. It is composed of an inexpensive (~US$350), portable, robotic microscope that can scan over the size of an entire McMaster chamber (100 mm² ) and capture high-resolution (~1 μm lateral resolution) bright field images without need for user intervention. Fecal samples prepared using the McMaster flotation method were imaged, with the imaging region comprising the entire McMaster chamber. These images are then automatically segmented and analyzed using a trained convolution neural network (CNN) to robustly separate eggs from background debris. Simple postprocessing of the CNN output yields both egg species and egg counts. The system was validated by comparing accuracy with hand-counts by a trained operator, with excellent performance. As a further demonstration of utility, the system was used to conveniently quantify drug response over time in a single animal, showing residual disease due to Anthelmintic resistance after 2 weeks.

Lin28 enhances de novo fatty acid synthesis to promote cancer progression via SREBP-1

Lin28 plays an important role in promoting tumor development, whereas its exact functions and underlying mechanisms are largely unknown. Here, we show that both human homologs of Lin28 accelerate de novo fatty acid synthesis and promote the conversion from saturated to unsaturated fatty acids via the regulation of SREBP-1. By directly binding to the mRNAs of both SREBP-1 and SCAP, Lin28A/B enhance the translation and maturation of SREBP-1, and protect cancer cells from lipotoxicity. Lin28A/B-stimulated tumor growth is abrogated by SREBP-1 inhibition and by the impairment of the RNA binding properties of Lin28A/B, respectively. Collectively, our findings uncover that post-transcriptional regulation by Lin28A/B enhances de novo fatty acid synthesis and metabolic conversion of saturated and unsaturated fatty acids via SREBP-1, which is critical for cancer progression.

Simultaneous recovery of both bright and dim structures from noisy fluorescence microscopy images using a modified TV constraint

The quality and information content of biological images can be significantly enhanced by postacquisition processing using deconvolution and denoising. However, when imaging complex biological samples, such as neurons, stained with fluorescence labels, the signal level of different structures can differ by several orders of magnitude. This poses a challenge as current image reconstruction algorithms are focused on recovering low signals and generally have sample-dependent performance, requiring tedious manual tuning. This is one of the main hurdles for their wide adoption by nonspecialists. In this work, we modify the general constrained reconstruction method (in our case utilizing a total variation constraint) so that both bright and dim structures can drive the deconvolution with equal force. In this way, we can simultaneously obtain high-quality reconstruction across a wide range of signals within a single image or image sequence. The algorithm is tested on both simulated and experimental data. When compared with current state-of-art algorithms, our algorithm outperforms others in terms of maintaining the resolution in the high-signal areas and reducing artefacts in the low-signal areas. The algorithm was also tested on image sequences where one set of parameters are used to reconstruct all images, with blind evaluation by a group of biologists demonstrating a marked preference for the images produced by our method. This means that our method is suitable for batch processing of image sequences obtained from either spatial or temporal scanning. LAY DESCRIPTION: Fluorescence microscopy images of complex biological samples contain a wide range of signal levels. This signal variation leads current reconstruction algorithms, which aim to enhance the quality of the raw images, to have sample-dependent performance. In this work, we design a new optimization that allows the reconstruction to "pay equal eqattention to" both bright and dim structures. In this way, we can simultaneously recover both bright and dim structures within a single image or image sequence, as validated when the algorithm was quantitatively tested on both simulated and experimental data. When our method was evaluated alongside current state of art algorithms by a group of biologists, our algorithm was considered qualitatively superior.

Automated morphometry toolbox for analysis of microscopic model organisms using simple bright-field imaging

Model organisms with compact genomes, such as yeast and C aenorhabditis elegans, are particularly useful for understanding organism growth and life/cell cycle. Organism morphology is a critical parameter to measure in monitoring growth and stage in the life cycle. However, manual measurements are both time consuming and potentially inaccurate, due to variations among users and user fatigue. In this paper we present an automated method to segment bright-field images of fission yeast, budding yeast, and C. elegans roundworm, reporting a wide range of morphometric parameters, such as length, width, eccentricity, and others. Comparisons between automated and manual methods on fission yeast reveal good correlation in size values, with the 95% confidence interval lying between -0.8 and +0.6 μm in cell length, similar to the 95% confidence interval between two manual users. In a head-to-head comparison with other published algorithms on multiple datasets, our method achieves more accurate and robust results with substantially less computation time. We demonstrate the method's versatility on several model organisms, and demonstrate its utility through automated analysis of changes in fission yeast growth due to single kinase deletions. The algorithm has additionally been implemented as a stand-alone executable program to aid dissemination to other researchers.

Dual-phone illumination-imaging system for high resolution and large field of view multi-modal microscopy

In this paper we present for the first time a system comprised of two mobile phones, one for illumination and the other for microscopy, as a portable, user-friendly, and cost-effective microscopy platform for a wide range of applications. Versatile and adaptive illumination is made with a Retina display of an Apple mobile phone device. The phone screen is used to project various illumination patterns onto the specimen being imaged, each corresponding to a different illumination mode, such as bright-field, dark-field, point illumination, Rheinberg illumination, and fluorescence microscopy. The second phone (a Nokia phone) is modified to record microscopic images about the sample. This imaging platform provides a high spatial resolution of at least 2 μm, a large field-of-view of 3.6 × 2.7 mm, and a working distance of 0.6 mm. We demonstrate the performance of this platform for the visualization of microorganisms within microfluidic devices to gather qualitative and quantitative information regarding microorganism morphology, dimension, count, and velocity/trajectories in the x-y plane.

Screening of nutritional and genetic anemias using elastic light scattering

Anemia affects more than ¼ of the world's population, mostly concentrated in low-resource areas, and carries serious health risks. Yet current screening methods are inadequate due to their inability to separate iron deficiency anemia (IDA) from genetic anemias such as thalassemia trait (TT), thus preventing targeted supplementation of oral iron. Here we present an accurate approach to diagnose anemia and anemia type using measures of pediatric red cell morphology determined through machine learning applied to optical light scattering measurements. A partial least squares model shows that our system can accurately extract mean cell volume, red cell size heterogeneity, and mean cell hemoglobin concentration with high accuracy. These clinical parameters (or the raw data itself) can be submitted to machine learning algorithms such as quadratic discriminants or support vector machines to classify a patient into healthy, IDA, or TT. A clinical trial conducted on 268 Chinese children, of which 49 had IDA and 24 had TT, shows >98% sensitivity and specificity for diagnosing anemia, with 81% sensitivity and 86% specificity for discriminating IDA and TT. The majority of the misdiagnoses are IDA patients with particularly severe anemia, possibly requiring hospital care. Therefore, in a screening paradigm where anyone testing positive for TT is sent to the hospital for gold-standard diagnosis and care, we maximize patient benefit while minimizing use of scarce resources.

Performance of a cost-effective and automated blood counting system for resource-limited settings operated by trained and untrained users

Current flow-based blood counting devices require expensive and centralized medical infrastructure and are not appropriate for field use. In this article we report a streamlined, easy-to-use method to count red blood cells (RBC), white blood cells (WBC), platelets (PLT) and 3-part WBC differential through a cost-effective and automated image-based blood counting system. The approach consists of using a compact, custom-built microscope with large field-of-view to record bright-field and fluorescence images of samples that are diluted with a single, stable reagent mixture and counted using automatic algorithms. Sample collection utilizes volume-controlled capillary tubes, which are then dropped into a premixed, shelf-stable solution to stain and dilute in a single step. Sample measurement and analysis are fully automated, requiring no input from the user. Cost of the system is minimized through the use of custom-designed motorized components. We compare the performance of our system, as operated by trained and untrained users, to the clinical gold standard on 120 adult blood samples, demonstrating agreement within Clinical Laboratory Improvement Amendments guidelines, with no statistical difference in performance among different operator groups. The system's cost-effectiveness, automation and performance indicate that it can be successfully translated for use in low-resource settings where central hematology laboratories are not accessible.

Benchtop and animal validation of a portable fluorescence microscopic imaging system for potential use in cholecystectomy

We propose a portable fluorescence microscopic imaging system (PFMS) for intraoperative display of biliary structure and prevention of iatrogenic injuries during cholecystectomy. The system consists of a light source module, a camera module, and a Raspberry Pi computer with an LCD. Indocyanine green (ICG) is used as a fluorescent contrast agent for experimental validation of the system. Fluorescence intensities of the ICG aqueous solution at different concentration levels are acquired by our PFMS and compared with those of a commercial Xenogen IVIS system. We study the fluorescence detection depth by superposing different thicknesses of chicken breast on an ICG-loaded agar phantom. We verify the technical feasibility for identifying potential iatrogenic injury in cholecystectomy using a rat model in vivo. The proposed PFMS system is portable, inexpensive, and suitable for deployment in resource-limited settings.

Structured illumination microscopy with interleaved reconstruction (SIMILR)

Structured illumination microscopy (SIM) is the commonly used super-resolution (SR) technique for imaging subcellular dynamics. However, due to its need for multiple illumination patterns, the frame rate is just a fraction of that of conventional microscopy and is thus too slow for fast dynamic studies. A new SR image reconstruction method that maximizes the use of each subframe of the acquisition series is proposed for improving the super-resolved frame rate by N times for N illumination directions. The method requires no changes in raw data and is appropriate for many versions of SIM setup, including those implementing fast illumination pattern generation mechanism based on spatial light modulator or digital micromirror device. The performance of the proposed method is demonstrated through imaging the highly dynamic endoplasmic reticulum where continuous rapid growths or shape changes of tiny structures are observed.

Optical volumetric projection for fast 3D imaging through circularly symmetric pupil engineering

Monitoring and manipulating neuronal activities with optical microscopy desires a method where light can be focused or projected over a long axial range so that large brain tissues (>100 [Formula: see text] thick) can be simultaneously imaged, and specific brain regions can be optogenetically stimulated without the need for slow optical refocusing. However, the micron-scale resolution required in neuronal imaging yields a depth of field of less than 10 [Formula: see text] in conventional imaging systems. We propose to use a circularly symmetric phase mask to extend the depth of field. A numerical study shows that our method maintains both the peak and the shape of the point spread function vs the axial position better than current methods. Imaging of a 3D bead suspension and sparsely labelled thick brain tissue confirms the feasibility of the system for fast volumetric imaging.

Subnanometer-resolved chemical imaging via multivariate analysis of tip-enhanced Raman maps

Tip-enhanced Raman spectroscopy (TERS) is a powerful surface analysis technique that can provide subnanometer-resolved images of nanostructures with site-specific chemical fingerprints. However, due to the limitation of weak Raman signals and the resultant difficulty in achieving TERS imaging with good signal-to-noise ratios (SNRs), the conventional single-peak analysis is unsuitable for distinguishing complex molecular architectures at the subnanometer scale. Here we demonstrate that the combination of subnanometer-resolved TERS imaging and advanced multivariate analysis can provide an unbiased panoramic view of the chemical identity and spatial distribution of different molecules on surfaces, yielding high-quality chemical images despite limited SNRs in individual pixel-level spectra. This methodology allows us to exploit the full power of TERS imaging and unambiguously distinguish between adjacent molecules with a resolution of ~0.4 nm, as well as to resolve submolecular features and the differences in molecular adsorption configurations. Our results provide a promising methodology that promotes TERS imaging as a routine analytical technique for the analysis of complex nanostructures on surfaces.

Fs-laser ablation of teeth is temperature limited and provides information about the ablated components

The goal of this work is to investigate the thermal effects of femtosecond laser (fs-laser) ablation for the removal of carious dental tissue. Additional studies identify different tooth tissues through femtosecond laser induced breakdown spectroscopy (fsLIBS) for the development of a feedback loop that could be utilized during ablation in a clinical setting. Scanning Election Microscope (SEM) images reveal that minimal morphological damages are incurred at repetition rates below the carbonization threshold of each tooth tissue. Thermal studies measure the temperature distribution and temperature decay during laser ablation and after laser cessation, and demonstrate that repetition rates at or below 10kHz with a laser fluence of 40 J/cm² would inflict minimal thermal damage on the surrounding nerve tissues and provide acceptable clinical removal rates. Spectral analysis of the different tooth tissues is also conducted and differences between the visible wavelength fsLIBS spectra are evident, though more robust classification studies are needed for clinical translation. These results have initiated a set of precautionary recommendations that would enable the clinician to utilize femtosecond laser ablation for the removal of carious lesions while ensuring that the solidity and utility of the tooth remain intact.

Multispectral Optical Tweezers for Biochemical Fingerprinting of CD9-Positive Exosome Subpopulations

Extracellular vesicles (EVs), including exosomes, are circulating nanoscale particles heavily implicated in cell signaling and can be isolated in vast numbers from human biofluids. Study of their molecular profiling and materials properties is currently underway for purposes of describing a variety of biological functions and diseases. However, the large, and as yet largely unquantified, variety of EV subpopulations differing in composition, size, and likely function necessitates characterization schemes capable of measuring single vesicles. Here we describe the first application of multispectral optical tweezers (MS-OTs) to single vesicles for molecular fingerprinting of EV subpopulations. This versatile imaging platform allows for sensitive measurement of Raman chemical composition (e.g., variation in protein, lipid, cholesterol, nucleic acids), coupled with discrimination by fluorescence markers. For exosomes isolated by ultracentrifugation, we use MS-OTs to interrogate the CD9-positive subpopulations via antibody fluorescence labeling and Raman spectra measurement. We report that the CD9-positive exosome subset exhibits reduced component concentration per vesicle and reduced chemical heterogeneity compared to the total purified EV population. We observed that specific vesicle subpopulations are present across exosomes isolated from cell culture supernatant of several clonal varieties of mesenchymal stromal cells and also from plasma and ascites isolated from human ovarian cancer patients.

Single particle analysis: Methods for detection of platelet extracellular vesicles in suspension (excluding flow cytometry)

Extracellular vesicles (EVs) are small, membrane-bound particles released by all cell types, including abundant release by platelets. EVs are a topic of increasing interest in the academic and clinical community due to their increasingly recognised and diverse role in normal biology as well as in disease. However, typical analysis methods to characterise EVs released by cultured cells or isolated from whole blood or other body fluids are restricted to bulk analysis of all EVs in a sample. In this review, we discuss the motivation for analysis of individual EVs, as well as discuss three emerging methods for physical and chemical characterisation of individual EVs: nanoparticle tracking analysis, tunable resistive pulse sensing and Raman spectroscopy. We give brief descriptions of the working principles of each technique, along with a review noting the benefits and limitations of each method as applied to detection of single EVs.

A mus-51 RIP allele for transformation of Neurospora crassa

This report describes the construction and characterization of mus-51^RIP70 , an allele for high-efficiency targeted integration of transgenes into the genome of the model eukaryote Neurospora crassa. Two of the mus-51^RIP70 strains investigated in this work (RZS27.10 and RZS27.18) can be obtained from the Fungal Genetics Stock Center. The two deposited strains are, to our knowledge, genetically identical and neither one is preferred over the other for use in Neurospora research.

The effects of laser repetition rate on femtosecond laser ablation of dry bone: a thermal and LIBS study

The aim of this study is to understand the effect of varying laser repetition rate on thermal energy accumulation and dissipation as well as femtosecond Laser Induced Breakdown Spectroscopy (fsLIBS) signals, which may help create the framework for clinical translation of femtosecond lasers for surgical procedures. We study the effect of repetition rates on ablation widths, sample temperature, and LIBS signal of bone. SEM images were acquired to quantify the morphology of the ablated volume and fsLIBS was performed to characterize changes in signal intensity and background. We also report for the first time experimentally measured temperature distributions of bone irradiated with femtosecond lasers at repetition rates below and above carbonization conditions. While high repetition rates would allow for faster cutting, heat accumulation exceeds heat dissipation and results in carbonization of the sample. At repetition rates where carbonization occurs, the sample temperature increases to a level that is well above the threshold for irreversible cellular damage. These results highlight the importance of the need for careful selection of the repetition rate for a femtosecond laser surgery procedure to minimize the extent of thermal damage to surrounding tissues and prevent misclassification of tissue by fsLIBS analysis.

Single exosome study reveals subpopulations distributed among cell lines with variability related to membrane content

Current analysis of exosomes focuses primarily on bulk analysis, where exosome-to-exosome variability cannot be assessed. In this study, we used Raman spectroscopy to study the chemical composition of single exosomes. We measured spectra of individual exosomes from 8 cell lines. Cell-line-averaged spectra varied considerably, reflecting the variation in total exosomal protein, lipid, genetic, and cytosolic content. Unexpectedly, single exosomes isolated from the same cell type also exhibited high spectral variability. Subsequent spectral analysis revealed clustering of single exosomes into 4 distinct groups that were not cell-line specific. Each group contained exosomes from multiple cell lines, and most cell lines had exosomes in multiple groups. The differences between these groups are related to chemical differences primarily due to differing membrane composition. Through a principal components analysis, we identified that the major sources of spectral variation among the exosomes were in cholesterol content, relative expression of phospholipids to cholesterol, and surface protein expression. For example, exosomes derived from cancerous versus non-cancerous cell lines can be largely separated based on their relative expression of cholesterol and phospholipids. We are the first to indicate that exosome subpopulations are shared among cell types, suggesting distributed exosome functionality. The origins of these differences are likely related to the specific role of extracellular vesicle subpopulations in both normal cell function and carcinogenesis, and they may provide diagnostic potential at the single exosome level.