Search

Feral Mallards (Anas platyrhynchos) habitat use patterns and behavior are little documented. We quantified activities and habitat use by feral Mallards around urban ponds in Tampa Florida. We recorded 201 activity budgets of 20 min, sampled at 15-sec intervals, during daytime hours in 2019-2021. Male and female feral Mallards spent most time in grass (39.5%), followed by shoreline (27.1%), water (23.7%), tree-shrub (8.2%), and urban (1.4%). A use-availability analysis indicated that feral Mallards selected for water and tree cover but against urban land. The findings have implications for the conservation and management of both nuisance and native waterfowl in urban areas. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We present a mathematical modeling framework for roster construction of a Major League Soccer (MLS) expansion team. The model seeks to construct the best squad feasible under league salary rules, while balancing present value, potential value, and future cap flexibility. Player acquisition decisions, as well as allocation of salary, targeted allocation money (TAM), general allocation money (GAM), and designated player slots, are determined simultaneously by a mixed-integer programming model. We demonstrate the model's functionality in constructing a hypothetical expansion roster and propose a number of extensions. [ABSTRACT FROM AUTHOR]

In Weighted Scoring Rules and Convex Risk Measures, Dr. Zachary J. Smith and Prof. J. Eric Bickel (both at the University of Texas at Austin) present a general connection between weighted proper scoring rules and investment decisions involving the minimization of a convex risk measure. Weighted scoring rules are quantitative tools for evaluating the accuracy of probabilistic forecasts relative to a baseline distribution. In their paper, the authors demonstrate that the relationship between convex risk measures and weighted scoring rules relates closely with previous economic characterizations of weighted scores based on expected utility maximization. As illustrative examples, the authors study two families of weighted scoring rules based on phi-divergences (generalizations of the Weighted Power and Weighted Pseudospherical Scoring rules) along with their corresponding risk measures. The paper will be of particular interest to the decision analysis and mathematical finance communities as well as those interested in the elicitation and evaluation of subjective probabilistic forecasts. This paper establishes a new relationship between proper scoring rules and convex risk measures. Specifically, we demonstrate that the entropy function associated with any weighted scoring rule is equal to the maximum value of an optimization problem where an investor maximizes a concave certainty equivalent (the negation of a convex risk measure). Using this connection, we construct two classes of proper weighted scoring rules with associated entropy functions based on ϕ-divergences. These rules are generalizations of the weighted power and weighted pseudospherical rules. [ABSTRACT FROM AUTHOR]

A microscopy system has been constructed that is capable of simultaneously acquiring both Raman spectra and angle-resolved elastic-scattering patterns in either epi- or transillumination modes with a 7 [micro]m spot size. The benefits and drawbacks of the epi- and transillumination modalities are discussed. Validation studies have been performed on single beads of a few micrometers in size, as well as on ensembles of submicrometer particles. In addition, transilluminated Raman and elastic-scattering spectra were obtained from single granulocytes and peripheral blood monocytes. Both the Raman- and the elastic-scattering channels show clear differences between the two types of immune cells. OCIS codes: 170.5660, 290.4020.

With the advent of hyperspectral Raman imaging technology, especially the rapid and high-resolution imaging schemes, datasets with thousands to millions of spectra are now commonplace. Standard preprocessing and regression methods such as least squares approaches are time consuming and require input from highly trained operators. Here we propose a solution to this analytic bottleneck through a convolutional neural network trained fully on synthetic data and then applied to experimental measurements, including cases where complete spectral information is missing (i.e. an underdetermined model). An advantage of the model is that it combines background correction and regression into a single step, and does not require user-selected parameters. We compare our results with traditional least squares methods, including the popular asymmetric least squares (AsLS) approach. Our results demonstrate that the proposed CNN model boasts less sensitivity to parameter selection, and with a rapid processing speed, with performance equal to or better than comparison methods. The performance is validated on synthetic spectral mixtures, as well as experimentally measured single-vesicle liposome data. [ABSTRACT FROM AUTHOR]

The article argues that artificial intelligence (AI) techniques violate the pretext doctrine in administrative law, applying the U.S. Supreme Court's rationale to AI techniques and articulation of the pretext doctrine in the case Department of Commerce v. New York.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Feral Mallards (Anas platyrhynchos) and invasive Muscovy Ducks (Cairina moschata) are common waterfowl in urban areas in many parts of the world, though relatively little is known about their habits and movements. This study quantified the fine-scale movements and habitat-use patterns of feral Mallards and Muscovy Ducks in an urban area of Tampa, Florida, from hour-long observational and tracking data. Mallards spent more time in water than Muscovy Ducks (41.0% vs. 9.1%), less time in grass (2.8% vs. 21.5%), and less time in urban areas (0.5% vs. 8.0%). Times spent by Mallards and Muscovy Ducks in tree-shrub (37.0% and 48.9%) and shoreline landscapes (18% and 12.5%) were statistically similar. Hourly distances traveled were similar between Mallards and Muscovy Ducks, averaging 250 m and 300 m, respectively. Mean hourly home ranges for Mallards were approximately 1,540 m2, whereas those for Muscovy Ducks averaged about 900 m2. The results suggest that feral Mallards and invasive Muscovy Ducks use similar wetlands and tree cover but differ in their use of other upland cover types. This work has implications for the management of native waterfowl, such as the Florida Mottled Duck (Anas fulvigula fulvigula), which also occupies urban areas and is threatened by interbreeding with feral Mallards. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Nanogap plasmonic structures, which can strongly enhance electromagnetic fields, enable widespread applications in surface‐enhanced Raman spectroscopy (SERS) sensing. Although the directed self‐assembly strategy has been adopted for the fabrication of micro/nanostructures on open surfaces, fabrication of nanogap plasmonic structures on complex substrates or at designated locations still remains a grand challenge. Here, a switchable self‐assembly method is developed to manufacture 3D nanogap plasmonic structures by combining supercritical drying and capillary‐force driven self‐assembly (CFSA) of micropillars fabricated by laser printing. The polymer pillars can stay upright during solvent development via supercritical drying, and then can form the nanogap after metal coating and subsequent CFSA. Due to the excellent flexibility of this method, diverse patterned plasmonic nanogap structures can be fabricated on planar or nonplanar substrates for SERS. The measured SERS signals of different patterned nanogaps in fluidic environment show a maximum enhancement factor ≈8 × 107. Such nanostructures in microchannels also allow localized sensing for anticancer drugs (doxorubicin). Resulting from the marriage of top‐down and self‐assembly techniques, this method provides a facile, effective, and controllable approach for creating nanogap enabled SERS devices in fluidic channels, and hence can advance applications in precision medicine. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper we report the development of a cost-effective, modular, open source, and fully automated slide-scanning microscope, composed entirely of easily available off-the-shelf parts, and capable of bright field and fluorescence modes. The automated X-Y stage is composed of two low-cost micrometer stages coupled to stepper motors operated in open-loop mode. The microscope is composed of a low-cost CMOS sensor and low-cost board lenses placed in a 4f configuration. The system has approximately 1 micron resolution, limited by the f/# of available board lenses. The microscope is compact, measuring just 25×25×30 cm, and has an absolute positioning accuracy of ±1 μm in the X and Y directions. A Z-stage enables autofocusing and imaging over large fields of view even on non-planar samples, and custom software enables automatic determination of sample boundaries and image mosaicking. We demonstrate the utility of our device through imaging of fluorescent- and transmission-dye stained blood and fecal smears containing human and animal parasites, as well as several prepared tissue samples. These results demonstrate image quality comparable to high-end commercial microscopes at a cost of less than US$400 for a bright-field system, with an extra US$100 needed for the fluorescence module. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Raman spectroscopy is a label-free method of obtaining detailed chemical information about samples. Its compatibility with living tissue makes it an attractive choice for biomedical analysis, yet its translation from a research tool to a clinical tool has been slow, hampered by fundamental Raman scattering issues such as long integration times and limited penetration depth. In this review we detail the how combining Raman spectroscopy with other techniques yields multimodal instruments that can help to surmount the translational barriers faced by Raman alone. We review Raman combined with several optical and non-optical methods, including fluorescence, elastic scattering, OCT, phase imaging, and mass spectrometry. In each section we highlight the power of each combination along with a brief history and presentation of representative results. Finally, we conclude with a perspective detailing both benefits and challenges for multimodal Raman measurements, and give thoughts on future directions in the field. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We report an accurate method to count red blood a cells, platelets, and white blood cells, as well as to determine hemoglobin in the blood of humans, horses, dogs, cats, and cows. Red and white blood cell counts can also be performed on human body fluids such as cerebrospinal fluid, synovial fluid, and peritoneal fluid. The approach consists of using a compact, custom-built microscope to record large field-of-view, bright-field, and fluorescence images of samples that are stained with a single dye and using automatic algorithms to count blood cells and detect hemoglobin. The total process takes about 15 min, including 5 min for sample preparation, and 10 min for data collection and analysis. The minimum volume of blood needed for the test is 0.5 µL, which allows for minimally invasive sample collection such as using a finger prick rather than a venous draw. Blood counts were compared to gold-standard automated clinical instruments, with excellent agreement between the two methods as determined by a Bland-Altman analysis. Accuracy of counts on body fluids was consistent with hand counting by a trained clinical lab scientist, where our instrument demonstrated an approximately 100-fold lower limit of detection compared to current automated methods. The combination of a compact, custom-built instrument, simple sample collection and preparation, and automated analysis demonstrates that this approach could benefit global health through use in low-resource settings where central hematology laboratories are not accessible. [ABSTRACT FROM AUTHOR]

Clinical applications in the developing world, such as malaria and anemia diagnosis, demand a change in the medical paradigm of expensive care given in central locations by highly trained professionals. There has been a recent explosion in optical technologies entering the consumer market through the widespread adoption of smartphones and LEDs. This technology commoditization has enabled the development of small, portable optical imaging systems at an unprecedentedly low cost. Here, we review the state-of-the-field of the application of these systems for low-cost blood imaging with an emphasis on cellular imaging systems. In addition to some promising results addressing specific clinical issues, an overview of the technology landscape is provided. We also discuss several key issues that need to be addressed before these technologies can be commercialized. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Current flow-based blood counting devices require significant medical infrastructure and are not appropriate for field use. In this article we report on the development of a sample preparation, measurement, and analysis method that permits automated and accurate counting of red blood cells (RBCs), white blood cells (WBCs), and platelets, as well as allowing a 3-part differential of the WBCs to be performed on extremely small volumes of whole blood. This method is compatible with portable instrumentation that can be deployed in the field. The method consists of serially diluting blood samples first with sodium dodecyl sulfate dissolved in phosphate buffered saline, then in acridine orange dissolved in phosphate buffered saline, followed by fluorescence and dark field imaging with low magnification objectives. Image analysis is performed to extract cell counts and differentials. We performed a paired analysis of 20 volunteers with complete blood count values both within and beyond the normal reference range using a commercial automated hematology analyzer and the image-based method, with the new method achieving accuracies comparable to that of the commercial system. Because the sample preparation and imaging are simple and inexpensive to implement, this method has applications for pediatrics, clinician offices, and global health in regions that do not have access to central hematology laboratories. [ABSTRACT FROM AUTHOR]