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.