A blockchain-based healthcare data marketplace: prototype and demonstration.

Objectives: This study aimed to develop healthcare data marketplace using blockchain-based B2C model that ensures the transaction of healthcare data among individuals, companies, and marketplaces. Materials and methods: We designed an architecture for the healthcare data marketplace using blockchain. A healthcare data marketplace was developed using Panacea, MySQL 8.0, JavaScript library, and Node.js. We evaluated the performance of the data marketplace system in 3 scenarios. Results: We developed mobile and web applications for healthcare data marketplace. The transaction data queries were executed fully within about 1-2 s, and approximately 9.5 healthcare data queries were processed per minute in each demonstration scenario. Discussion: Blockchain-based healthcare data marketplaces have shown compliance performance in the process of data collection and will provide a meaningful role in analyzing healthcare data. Conclusion: The healthcare data marketplace developed in this project can iron out time and place limitations and create a framework for gathering and analyzing fragmented healthcare data.

Automated, high-throughput quantification of EGFP-expressing neutrophils in zebrafish by machine learning and a highly-parallelized microscope.

Normal development of the immune system is essential for overall health and disease resistance. Bony fish, such as the zebrafish (Danio rerio), possess all the major immune cell lineages as mammals and can be employed to model human host response to immune challenge. Zebrafish neutrophils, for example, are present in the transparent larvae as early as 48 hours post fertilization and have been examined in numerous infection and immunotoxicology reports. One significant advantage of the zebrafish model is the ability to affordably generate high numbers of individual larvae that can be arrayed in multi-well plates for high throughput genetic and chemical exposure screens. However, traditional workflows for imaging individual larvae have been limited to low-throughput studies using traditional microscopes and manual analyses. Using a newly developed, parallelized microscope, the Multi-Camera Array Microscope (MCAM™), we have optimized a rapid, high-resolution algorithmic method to count fluorescently labeled cells in zebrafish larvae in vivo. Using transgenic zebrafish larvae, in which neutrophils express EGFP, we captured 18 gigapixels of images across a full 96-well plate, in 75 seconds, and processed the resulting datastream, counting individual fluorescent neutrophils in all individual larvae in 5 minutes. This automation is facilitated by a machine learning segmentation algorithm that defines the most in-focus view of each larva in each well after which pixel intensity thresholding and blob detection are employed to locate and count fluorescent cells. We validated this method by comparing algorithmic neutrophil counts to manual counts in larvae subjected to changes in neutrophil numbers, demonstrating the utility of this approach for high-throughput genetic and chemical screens where a change in neutrophil number is an endpoint metric. Using the MCAM™ we have been able to, within minutes, acquire both enough data to create an automated algorithm and execute a biological experiment with statistical significance. Finally, we present this open-source software package which allows the user to train and evaluate a custom machine learning segmentation model and use it to localize zebrafish and analyze cell counts within the segmented region of interest. This software can be modified as needed for studies involving other zebrafish cell lineages using different transgenic reporter lines and can also be adapted for studies using other amenable model species.

Microheater with copper nanofiber network via electrospinning and electroless deposition.

In this report, we present the development of a copper nanofiber network-based microheater, designed for applications in electron microscopes, gas sensing, and cell culture platforms. The seed layer, essential for electroless deposition, was fabricated through the electrospinning of a palladium-contained polyvinylpyrrolidone solution followed by a heat treatment. This process minimized the contact resistance between nanofibers. We successfully fabricated a microheater with evenly distributed temperature by controlling the electrospinning time, heat treatment conditions, and electroless deposition time. We assessed the electrical and thermal characteristics of the microheater by examining the nanofiber density, sheet resistance, and transmittance. The microheater's performance was evaluated by applying current, and we verified its capacity to heat up to a maximum of 350 °C. We further observed the microheater's temperature distribution at varying current levels through an infrared camera. The entire manufacturing procedure takes place under normal pressure, eliminating the need for masking or etching processes. This renders the method easily adaptable to the mass production of microdevices. The method is expected to be applicable to various materials and sizes and is cost-effective compared to commercially produced microheaters developed through microelectromechanical system processes, which demand complex facilities and high cost.

Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second.

Wide field of view microscopy that can resolve 3D information at high speed and spatial resolution is highly desirable for studying the behaviour of freely moving model organisms. However, it is challenging to design an optical instrument that optimises all these properties simultaneously. Existing techniques typically require the acquisition of sequential image snapshots to observe large areas or measure 3D information, thus compromising on speed and throughput. Here, we present 3D-RAPID, a computational microscope based on a synchronized array of 54 cameras that can capture high-speed 3D topographic videos over an area of 135 cm2, achieving up to 230 frames per second at spatiotemporal throughputs exceeding 5 gigapixels per second. 3D-RAPID employs a 3D reconstruction algorithm that, for each synchronized snapshot, fuses all 54 images into a composite that includes a co-registered 3D height map. The self-supervised 3D reconstruction algorithm trains a neural network to map raw photometric images to 3D topography using stereo overlap redundancy and ray-propagation physics as the only supervision mechanism. The resulting reconstruction process is thus robust to generalization errors and scales to arbitrarily long videos from arbitrarily sized camera arrays. We demonstrate the broad applicability of 3D-RAPID with collections of several freely behaving organisms, including ants, fruit flies, and zebrafish larvae.

Recyclable Superhydrophobic Surface Prepared via Electrospinning and Electrospraying Using Waste Polyethylene Terephthalate for Self-Cleaning Applications.

Superhydrophobic surfaces, i.e., surfaces with a water contact angle (WCA) ≥ 150°, have gained much attention as they are multifunctional surfaces with features such as self-cleaning, which can be useful in various applications such as those requiring waterproof and/or protective films. In this study, we prepared a solution from recycled polyethylene terephthalate (PET) and fabricated a superhydrophobic surface using electrospinning and electrospraying processes. We observed that the fabricated geometry varies depending on the solution conditions, and based on this, we fabricated a hierarchical structure. From the results, the optimized structure exhibited a very high WCA (>156.6°). Additionally, our investigation into the self-cleaning functionality and solar panel efficiency of the fabricated surface revealed promising prospects for the production of superhydrophobic surfaces utilizing recycled PET, with potential applications as protective films for solar panels. Consequently, this research contributes significantly to the advancement of environmentally friendly processes and the progress of recycling technology.

Automated, high-throughput quantification of EGFP-expressing neutrophils in zebrafish by machine learning and a highly-parallelized microscope.

Normal development of the immune system is essential for overall health and disease resistance. Bony fish, such as the zebrafish (Danio rerio), possess all the major immune cell lineages as mammals and can be employed to model human host response to immune challenge. Zebrafish neutrophils, for example, are present in the transparent larvae as early as 48 hours post fertilization and have been examined in numerous infection and immunotoxicology reports. One significant advantage of the zebrafish model is the ability to affordably generate high numbers of individual larvae that can be arrayed in multi-well plates for high throughput genetic and chemical exposure screens. However, traditional workflows for imaging individual larvae have been limited to low-throughput studies using traditional microscopes and manual analyses. Using a newly developed, parallelized microscope, the Multi-Camera Array Microscope (MCAM™), we have optimized a rapid, high-resolution algorithmic method to count fluorescently labeled cells in zebrafish larvae in vivo. Using transgenic zebrafish larvae, in which neutrophils express EGFP, we captured 18 gigapixels of images across a full 96-well plate, in 75 seconds, and processed the resulting datastream, counting individual fluorescent neutrophils in all individual larvae in 5 minutes. This automation is facilitated by a machine learning segmentation algorithm that defines the most in-focus view of each larva in each well after which pixel intensity thresholding and blob detection are employed to locate and count fluorescent cells. We validated this method by comparing algorithmic neutrophil counts to manual counts in larvae subjected to changes in neutrophil numbers, demonstrating the utility of this approach for high-throughput genetic and chemical screens where a change in neutrophil number is an endpoint metric. Using the MCAM™ we have been able to, within minutes, acquire both enough data to create an automated algorithm and execute a biological experiment with statistical significance. Finally, we present this open-source software package which allows the user to train and evaluate a custom machine learning segmentation model and use it to localize zebrafish and analyze cell counts within the segmented region of interest. This software can be modified as needed for studies involving other zebrafish cell lineages using different transgenic reporter lines and can also be adapted for studies using other amenable model species.

Intranasal trigeminal sensitivity to mechanical stimuli is associated with the perception of nasal patency.

PURPOSE: The aim of this prospective study was to examine the characteristics of a clinical test for the assessment of nasal trigeminal sensitivity to mechanical stimuli and its association with the perception of nasal patency. METHODS: Thirty-two normosmic healthy subjects participated (17 women and 15 men; age = 26 ± 3 years). Precisely defined air puffs were used with a flow rate of 2L/min for mechanical stimulation. They were presented to the nasal vestibule, nasal septum, and inferior turbinate with various stimulus durations. Thresholds were measured by single-staircase stimuli with changes in stimulus duration in steps of 10 ms. Trigeminal suprathreshold intensity was rated by subjects for stimulus durations of 200, 300, 400, and 500 ms. Test-retest reliability was examined by intraclass correlations (ICCs) and Bland-Altman plot with limits of agreement. Pearson's correlations were calculated between self-rated nasal patency and nasal trigeminal sensitivity. RESULTS: As indicated by trigeminal threshold and suprathreshold intensities, the nasal vestibule is the most sensitive area among the three locations, followed by the nasal septum and the inferior turbinate (p < 0.001). Coefficients of correlations between test and retest were 0.76 for thresholds, and 0.56 suprathreshold intensities (p < 0.001). The Bland-Altman analysis showed a good agreement between test-retest values. In addition, significant positive associations between trigeminal suprathreshold intensities and self-rated nasal obstruction were found at the inferior turbinate (r = 0.4, p < 0.05). CONCLUSION: Reliable assessment of nasal trigeminal sensitivity for air puffs appears to be possible. Nasal trigeminal suprathreshold sensitivity to mechanical stimuli is associated with the perception of nasal patency at the inferior turbinate. This opens a window into the assessment of the perception of nasal airflow in various clinical purposes, especially for patients with sinonasal diseases.

Multi-modal imaging using a cascaded microscope design.

We present a multi-modal fiber array snapshot technique (M-FAST) based on an array of 96 compact cameras placed behind a primary objective lens and a fiber bundle array. Our technique is capable of large-area, high-resolution, multi-channel video acquisition. The proposed design provides two key improvements to prior cascaded imaging system approaches: a novel optical arrangement that accommodates the use of planar camera arrays, and a new ability to acquire multi-modal image data acquisition. M-FAST is a multi-modal, scalable imaging system that can acquire snapshot dual-channel fluorescence images as well as differential phase contrast measurements over a large 6.59 mm × 9.74 mm field-of-view at 2.2-µm center full-pitch resolution.

Extreme UV Resist Exhibiting Synergism between Chemical and Physical Crosslinking Mechanisms.

Carbon-fluorine bonds in fluorinated molecules can undergo homolytic cleavage reactions when electrons are injected, and the resulting radicals combine to form network structures characterized by reduced solubility. This crosslinking chemistry suggests a new category of patterning materials that function under electron beam (e-beam) and extreme ultraviolet (EUV) lithographic conditions. Although this chemistry enables the production of 50 nm or smaller-sized features of simple fluoroalkylated polymers, it is limited by the need for relatively large amounts of irradiation energy to achieve required solubility changes. Therefore, this study was undertaken to devise a sensitivity-enhancing strategy based on a synergistic combination of radical crosslinking and hydrogen-bonding interactions between highly fluoroalkylated copolymers. An alternating copolymer was synthesized using tert-butoxystyrene and a fluoroalkylated maleimide, the former of which produces active hydrogens through catalytic acidolysis reactions. When the polymer was blended with a catalytic amount of a photoacid generator and subjected to lithographic patterning tests under e-beam and EUV irradiation, the deprotection reactions of tert-butoxy moieties proceeded at room temperature and led to a solubility decrease. We presume the small number of hydroxyl moieties produced formed an intermolecular hydrogen-bonding network, which acted synergistically with the covalent crosslinks generated by C-F bonds. When 30 nm features of copolymer thin films were fabricated by EUV lithography, sensitivity was improved by 25-34% without significant deterioration of pattern quality, especially line-edge roughness. These results demonstrate that EUV resists with improved patterning capabilities can be achieved by combining catalytic acidolysis reactions and noncatalytic crosslinking chemistry.

Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second.

To study the behavior of freely moving model organisms such as zebrafish (Danio rerio) and fruit flies (Drosophila) across multiple spatial scales, it would be ideal to use a light microscope that can resolve 3D information over a wide field of view (FOV) at high speed and high spatial resolution. However, it is challenging to design an optical instrument to achieve all of these properties simultaneously. Existing techniques for large-FOV microscopic imaging and for 3D image measurement typically require many sequential image snapshots, thus compromising speed and throughput. Here, we present 3D-RAPID, a computational microscope based on a synchronized array of 54 cameras that can capture high-speed 3D topographic videos over a 135-cm^2 area, achieving up to 230 frames per second at throughputs exceeding 5 gigapixels (GPs) per second. 3D-RAPID features a 3D reconstruction algorithm that, for each synchronized temporal snapshot, simultaneously fuses all 54 images seamlessly into a globally-consistent composite that includes a coregistered 3D height map. The self-supervised 3D reconstruction algorithm itself trains a spatiotemporally-compressed convolutional neural network (CNN) that maps raw photometric images to 3D topography, using stereo overlap redundancy and ray-propagation physics as the only supervision mechanism. As a result, our end-to-end 3D reconstruction algorithm is robust to generalization errors and scales to arbitrarily long videos from arbitrarily sized camera arrays. The scalable hardware and software design of 3D-RAPID addresses a longstanding problem in the field of behavioral imaging, enabling parallelized 3D observation of large collections of freely moving organisms at high spatiotemporal throughputs, which we demonstrate in ants (Pogonomyrmex barbatus), fruit flies, and zebrafish larvae.

3D Printing as a Planning Tool to Optimize Sinonasal Irrigation.

BACKGROUND: Topical sinus irrigation plays a critical role in the management of sinonasal diseases. Yet, the penetration of irrigant to targeted sinuses may be highly variable and difficult to predict. Here, we investigate the use of 3D printing as a planning tool to optimize outcomes. METHODS: Eight post-operative models were 3D printed with a FormLabs Form3 printer based on individual CT scans. Irrigations were performed and video recorded with a squeeze bottle attached via silicon water-tight seal, in 4 head positions: 45° to-the-side, 90° to-the-side, 45° forward and 45° to-the-side, and 90° forward, with irrigation fluid entering the upper (conventional) or lower (backfill) nostrils. RESULTS: Significant individual variations were observed in sinus penetration as a function of head position. In general, the maxillary sinus was the easiest to irrigate in most head positions (P < .05), followed by frontal and ethmoid, with sphenoid being the most difficult. Both the 90°-to-the-side and the 90°-forward positions were significantly more effective than the others (P < .05), with 90°-forward better for frontal sinuses and 90°-to-the-side superior for all other sinuses. The backfill was significantly superior to conventional technique in head positions involving a side tilt (P < .05). CONCLUSION: Variations in technique and position significantly impacted irrigation outcome. Backfill irrigation that pushes fluid against gravity to pool around the ostium, seems to provide overall better outcomes. This study demonstrates the advantage of 3D printing as a rapid planning tool to guide irrigation strategies.

Gigapixel imaging with a novel multi-camera array microscope.

The dynamics of living organisms are organized across many spatial scales. However, current cost-effective imaging systems can measure only a subset of these scales at once. We have created a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution recording from multiple spatial scales simultaneously, ranging from structures that approach the cellular scale to large-group behavioral dynamics. By collecting data from up to 96 cameras, we computationally generate gigapixel-scale images and movies with a field of view over hundreds of square centimeters at an optical resolution of 18 µm. This allows us to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales, including larval zebrafish, fruit flies, nematodes, carpenter ants, and slime mold. Further, the MCAM architecture allows stereoscopic tracking of the z-position of organisms using the overlapping field of view from adjacent cameras. Overall, by removing the bottlenecks imposed by single-camera image acquisition systems, the MCAM provides a powerful platform for investigating detailed biological features and behavioral processes of small model organisms across a wide range of spatial scales.

Transient Motion Classification Through Turbid Volumes via Parallelized Single-Photon Detection and Deep Contrastive Embedding.

Fast noninvasive probing of spatially varying decorrelating events, such as cerebral blood flow beneath the human skull, is an essential task in various scientific and clinical settings. One of the primary optical techniques used is diffuse correlation spectroscopy (DCS), whose classical implementation uses a single or few single-photon detectors, resulting in poor spatial localization accuracy and relatively low temporal resolution. Here, we propose a technique termed C lassifying R apid decorrelation E vents via P arallelized single photon d E tection (CREPE), a new form of DCS that can probe and classify different decorrelating movements hidden underneath turbid volume with high sensitivity using parallelized speckle detection from a 32 × 32 pixel SPAD array. We evaluate our setup by classifying different spatiotemporal-decorrelating patterns hidden beneath a 5 mm tissue-like phantom made with rapidly decorrelating dynamic scattering media. Twelve multi-mode fibers are used to collect scattered light from different positions on the surface of the tissue phantom. To validate our setup, we generate perturbed decorrelation patterns by both a digital micromirror device (DMD) modulated at multi-kilo-hertz rates, as well as a vessel phantom containing flowing fluid. Along with a deep contrastive learning algorithm that outperforms classic unsupervised learning methods, we demonstrate our approach can accurately detect and classify different transient decorrelation events (happening in 0.1-0.4 s) underneath turbid scattering media, without any data labeling. This has the potential to be applied to non-invasively monitor deep tissue motion patterns, for example identifying normal or abnormal cerebral blood flow events, at multi-Hertz rates within a compact and static detection probe.

Investigation of correlative parameters to evaluate EUV lithographic performance of PMMA.

Investigations to evaluate the extreme ultraviolet (EUV) lithographic performance of 160 nm thick poly(methyl methacrylate) with 13.5 nm wavelength EUV light were performed using a synchrotron radiation source at Pohang Light Source-II (PLS-II). The single system enabled the determination of the sensitivity, contrast, linear absorption coefficient, critical dimension, and line edge roughness of polymer thin films through tests and measurements. The experimental findings were also compared to theoretical results and those of previously reported studies. According to the results of the dose-to-clear test and transmission measurements, the critical dimension of a line and space pattern (>50 nm) via interference lithography with 250 nm pitch grating agreed well with the results calculated using the lumped parameter model. The experimental results demonstrated that the equipment and test protocol can be used for EUV material infrastructure evaluation in academia and in industry.

Maternal disease factors associated with neonatal jaundice: a case-control study.

BACKGROUND: Neonatal jaundice is common, and despite the considerable medical costs associated with it, there are still few studies on the maternal factors associated with it. Identification of maternal factors associated with neonatal jaundice is very important in terms of prevention, screening and management of neonatal jaundice. The current study aimed to identify maternal disease factors associated with neonatal jaundice. METHODS: We compared the maternal disease diagnostic codes during pregnancy (study A) and 1 year before conception (study B) in mothers whose insurance claims data included newborns treated for neonatal jaundice before birth registration via the National Health Insurance Service-National Sample Cohort (control group). To decrease the effect of confounding variables, the neonatal jaundice and control groups were matched at a ratio of 1:10 via propensity score matching using covariates including age and income. RESULTS: The matched samples for studies A and B included 4,026 and 3,278 (jaundice group: 366 and 298) delivery cases, respectively. In both studies, the jaundice group had a higher proportion of patients who underwent cesarean section than the control group. In study A, other diseases of the digestive system had the highest odds ratio (OR) (K92; adjusted OR: 14.12, 95% confidence interval [CI]: 2.70-82.26). Meanwhile, gastritis and duodenitis had the lowest OR (K29; adjusted OR: 0.39, 95% CI: 0.22-0.69). In study B, salpingitis and oophoritis had the highest OR (N70; adjusted OR: 3.33, 95% CI: 1.59-6.94). Heartburn had the lowest OR (R12; adjusted OR: 0.29, 95% CI:0.12-0.71). CONCLUSIONS: This study identified maternal disease factors correlated with neonatal jaundice during pregnancy and 1 year before conception. Maternal risk factors for neonatal jaundice included syphilis and leiomyoma during pregnancy, and salpingo-oophoritis before pregnancy. The protective factors included infection, inflammatory diseases, and dyspepsia.

Increasing a microscope's effective field of view via overlapped imaging and machine learning.

This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various morphological features of interest is now a crucial component of both biomedical research and disease diagnosis. While convolutional neural networks (CNNs) have dramatically improved the accuracy of counting cells and sub-cellular features from acquired digital image data, the overall throughput is still typically hindered by the limited space-bandwidth product (SBP) of conventional microscopes. Here, we show both in simulation and experiment that overlapped imaging and co-designed analysis software can achieve accurate detection of diagnostically-relevant features for several applications, including counting of white blood cells and the malaria parasite, leading to multi-fold increase in detection and processing throughput with minimal reduction in accuracy.

Radiation-induced C-reactive protein triggers apoptosis of vascular smooth muscle cells through ROS interfering with the STAT3/Ref-1 complex.

Damage to normal tissue can occur over a long period after cancer radiotherapy. Free radical by radiation can initiate or accelerate chronic inflammation, which can lead to atherosclerosis. However, the underlying mechanisms remain unclear. Vascular smooth muscle cells (VSMCs) proliferate in response to JAK/STAT3 signalling. C-reactive protein (CRP) can induce VSMCs apoptosis via triggering NADPH oxidase (NOX). Apoptotic VSMCs promote instability and inflammation of atherosclerotic lesions. Herein, we identified a VSMCs that switched from proliferation to apoptosis through was enhanced by radiation-induced CRP. NOX inhibition using lentiviral sh-p22phox prevented apoptosis upon radiation-induced CRP. CRP overexpression reduced the amount of STAT3/Ref-1 complex, decreased JAK/STAT phosphorylation and formed a new complex of Ref-1/CRP in VSMC. Apoptosis of VSMCs was further increased by CRP co-overexpressed with Ref-1. Functional inhibition of NOX or p53 also prevented apoptotic activity of the CRP-Ref-1 complex. Immunofluorescence showed co-localization of CRP, Ref-1 and p53 with α-actin-positive VSMC in human atherosclerotic plaques. In conclusion, radiation-induced CRP increased the VSMCs apoptosis through Ref-1, which dissociated the STAT3/Ref-1 complex, interfered with JAK/STAT3 activity, and interacted with CRP-Ref-1, thus resulting in transcription-independent cell death via p53. Targeting CRP as a vascular side effect of radiotherapy could be exploited to improve curability.

3D printed transwell-integrated nose-on-chip model to evaluate effects of air flow-induced mechanical stresses on mucous secretion.

While there are many chip models that simulate the air-tissue interface of the respiratory system, only a few represent the upper respiratory system. These chips are restricted to unidirectional flow patterns that are not comparable to the highly dynamic and variable flow patterns found in the native nasal cavity. Here we describe the development of a tunable nose-on-chip device that mimics the air-mucosa interface and is coupled to an air delivery system that simulates natural breathing patterns through the generation of bi-directional air flow. Additionally, we employ computational modeling to demonstrate how the device design can be tuned to replicate desired mechanical characteristics within specific regions of the human nasal cavity. We also demonstrate how to culture human nasal epithelial cell line RPMI 2650 within the lab-on-chip (LOC) device. Lastly, Alcian Blue histological staining was performed to label mucin proteins, which play important roles in mucous secretion. Our results revealed that dynamic flow conditions can increase mucous secretion for RPMI 2650 cells, when compared to no flow, or stationary, conditions.

A Nasal Aerodynamics Perspective of Retronasal Olfaction: Rodents vs. Humans.

Introduction: Odor perception can be achieved through ortho or retronasal routes, with the latter being an important component of flavor perception. There are significant olfactory differences that exist between rats and humans and by understanding the role of structural differences, further insight can be gained into the mechanism of odorant perception via ortho or retronasal routes. Methods: 3D human and rat (Sprague Dawley) computational models were used to investigate nasal anatomy impact on ortho vs. retronasal odorant transport to the olfactory epithelium. The nasal pharynx region was modified for human and rat models to probe nasal structure impact on ortho vs retro olfaction. 65 odorant absorption rates to the olfactory epithelium were extracted from each model. Results: For human, the retronasal route provided higher peak odorant absorption compared to orthonasal route (left: 90% higher, right: 45% higher), but substantially lowered peak absorption for rat (medial: 97% lower, lateral: 75% lower). For both models, anatomical modification had minimal impact to orthonasal routes, but substantially modulated the retronasal route: decrease (left: -41.4%, right: -44.2%) for human, and increase to the medial (29.5%) but not to lateral (-14.3%) for rat. Conclusions: There exist key differences between humans and rats regarding retro/orthonasal odorant transport routes, which matched well with experimental olfactory bulb activity data in literature. Implications: While humans have equivalent odorant delivery between routes, the difference in retro and orthonasal routes in rodents is substantial and changes to the transverse lamina above the nasopharynx can substantially modulate the retronasal route, but not enough to bridge the gap between the two routes.

A multiple instance learning approach for detecting COVID-19 in peripheral blood smears.

A wide variety of diseases are commonly diagnosed via the visual examination of cell morphology within a peripheral blood smear. For certain diseases, such as COVID-19, morphological impact across the multitude of blood cell types is still poorly understood. In this paper, we present a multiple instance learning-based approach to aggregate high-resolution morphological information across many blood cells and cell types to automatically diagnose disease at a per-patient level. We integrated image and diagnostic information from across 236 patients to demonstrate not only that there is a significant link between blood and a patient's COVID-19 infection status, but also that novel machine learning approaches offer a powerful and scalable means to analyze peripheral blood smears. Our results both backup and enhance hematological findings relating blood cell morphology to COVID-19, and offer a high diagnostic efficacy; with a 79% accuracy and a ROC-AUC of 0.90.