Motionless volumetric structured light sheet microscopy.

To meet the increasing need for low-cost, compact imaging technology with cellular resolution, we have developed a microLED-based structured light sheet microscope for three-dimensional ex vivo and in vivo imaging of biological tissue in multiple modalities. All the illumination structure is generated directly at the microLED panel-which serves as the source-so light sheet scanning and modulation is completely digital, yielding a system that is simpler and less prone to error than previously reported methods. Volumetric images with optical sectioning are thus achieved in an inexpensive, compact form factor without any moving parts. We demonstrate the unique properties and general applicability of our technique by ex vivo imaging of porcine and murine tissue from the gastrointestinal tract, kidney, and brain.

Exploring uncertainty measures in convolutional neural network for semantic segmentation of oral cancer images.

Significance: Oral cancer is one of the most prevalent cancers, especially in middle- and low-income countries such as India. Automatic segmentation of oral cancer images can improve the diagnostic workflow, which is a significant task in oral cancer image analysis. Despite the remarkable success of deep-learning networks in medical segmentation, they rarely provide uncertainty quantification for their output. Aim: We aim to estimate uncertainty in a deep-learning approach to semantic segmentation of oral cancer images and to improve the accuracy and reliability of predictions. Approach: This work introduced a UNet-based Bayesian deep-learning (BDL) model to segment potentially malignant and malignant lesion areas in the oral cavity. The model can quantify uncertainty in predictions. We also developed an efficient model that increased the inference speed, which is almost six times smaller and two times faster (inference speed) than the original UNet. The dataset in this study was collected using our customized screening platform and was annotated by oral oncology specialists. Results: The proposed approach achieved good segmentation performance as well as good uncertainty estimation performance. In the experiments, we observed an improvement in pixel accuracy and mean intersection over union by removing uncertain pixels. This result reflects that the model provided less accurate predictions in uncertain areas that may need more attention and further inspection. The experiments also showed that with some performance compromises, the efficient model reduced computation time and model size, which expands the potential for implementation on portable devices used in resource-limited settings. Conclusions: Our study demonstrates the UNet-based BDL model not only can perform potentially malignant and malignant oral lesion segmentation, but also can provide informative pixel-level uncertainty estimation. With this extra uncertainty information, the accuracy and reliability of the model's prediction can be improved.

Bayesian deep learning for reliable oral cancer image classification.

In medical imaging, deep learning-based solutions have achieved state-of-the-art performance. However, reliability restricts the integration of deep learning into practical medical workflows since conventional deep learning frameworks cannot quantitatively assess model uncertainty. In this work, we propose to address this shortcoming by utilizing a Bayesian deep network capable of estimating uncertainty to assess oral cancer image classification reliability. We evaluate the model using a large intraoral cheek mucosa image dataset captured using our customized device from high-risk population to show that meaningful uncertainty information can be produced. In addition, our experiments show improved accuracy by uncertainty-informed referral. The accuracy of retained data reaches roughly 90% when referring either 10% of all cases or referring cases whose uncertainty value is greater than 0.3. The performance can be further improved by referring more patients. The experiments show the model is capable of identifying difficult cases needing further inspection.

Classification of imbalanced oral cancer image data from high-risk population.

SIGNIFICANCE: Early detection of oral cancer is vital for high-risk patients, and machine learning-based automatic classification is ideal for disease screening. However, current datasets collected from high-risk populations are unbalanced and often have detrimental effects on the performance of classification. AIM: To reduce the class bias caused by data imbalance. APPROACH: We collected 3851 polarized white light cheek mucosa images using our customized oral cancer screening device. We use weight balancing, data augmentation, undersampling, focal loss, and ensemble methods to improve the neural network performance of oral cancer image classification with the imbalanced multi-class datasets captured from high-risk populations during oral cancer screening in low-resource settings. RESULTS: By applying both data-level and algorithm-level approaches to the deep learning training process, the performance of the minority classes, which were difficult to distinguish at the beginning, has been improved. The accuracy of "premalignancy" class is also increased, which is ideal for screening applications. CONCLUSIONS: Experimental results show that the class bias induced by imbalanced oral cancer image datasets could be reduced using both data- and algorithm-level methods. Our study may provide an important basis for helping understand the influence of unbalanced datasets on oral cancer deep learning classifiers and how to mitigate.

MicroLED chromatic confocal microscope.

In this Letter, a microLED-based chromatic confocal microscope with a virtual confocal slit is proposed and demonstrated for three-dimensional (3D) profiling without any mechanical scanning or external light source. In the proposed method, a micro-scale light-emitting diode (microLED) panel works as a point source array to achieve lateral scanning. Axial scanning is realized through the chromatic aberration of an aspherical objective. A virtual pinhole technique is utilized to improve the contrast and precision of depth reconstruction. The system performance has been demonstrated with a diamond-turned copper sample and onion epidermis. The experimental results show that the microLED panel could be a potential solution for portable 3D confocal microscopy. Several considerations and prospects are proposed for future microLED requirements in confocal imaging.

Toward Sequencing the Human Milk Glycome: High-Resolution Cyclic Ion Mobility Separations of Core Human Milk Oligosaccharide Building Blocks.

Human milk oligosaccharides (HMOs) are an unconjugated class of glycans that have been implicated for their role in promoting the healthy development of the brain-gut axes of infants. Production of HMOs is ever-changing and specifically tailored for each infant in response to various biological factors (e.g., cognitive development, diseases, or allergies). While every HMO consists of up to only five monosaccharides, their structures can be composed of many possible glycosidic linkage positions and corresponding α/ß anomericities, linear or branched chains, and potential fucosylation/sialylation modifications, thus leading to a tremendous degree of isomeric heterogeneity. With limited availability of authentic standards for every putative HMO structure (estimated to be >200 total), new analytical methods are needed for their accurate characterization. Complete sequencing of the human milk glycome would enable a better understanding of their infant-specific biological roles and potentially lead to their widespread incorporation into infant formula. Herein, we explore the use of our high-resolution cyclic ion mobility spectrometry-mass spectrometry (cIMS-MS)-based platform for the separation of core disaccharide and trisaccharide isomer building blocks as a first step toward the sequencing of larger HMOs. By utilizing the flexible capabilities of the cIMS array, separation pathlengths were extended up to 40 m, thus enabling the resolution of all seven sets of sialylated, fucosylated galactosyllactose and lactosamine HMO building block isomers. Additionally, we assessed the utility of pre-/post-cIMS tandem mass spectrometry (MS/MS) and tandem cIMS (cIMS/cIMS) for the characterization of HMOs based on their diagnostic fragmentation patterns and mobility fingerprints. We anticipate that our presented cIMS-MS-based methodology will enable the better characterization of larger, unknown HMOs when incorporated into an overall workflow that also includes online liquid chromatography and enzymatic hydrolyses.

Reevaluating America's Latest Pharmaceutical Trend: The Cardiovascular Risk of Cannabis.

For the first time in the history of the modern era smoking tobacco is not the most popular inhaled product. After a flurry of legislature, cannabis has come to the forefront of both medicinal and recreational drug use. A confluence of evidence suggests, however, that marijuana consumption may confer a particularly worrisome cardiovascular risk profile. While combustible forms still contain many of the same harmful chemicals found in tobacco such as aromatic amines, polycyclic aromatic hydrocarbons (PAHs), and nitric oxide, some in even greater concentrations than tobacco, edible preparations have been evidenced to cause more cardiovascular-related emergency department visits. Importantly, this body of evidence suggests that cannabis use may be placing a younger, healthier population at risk of suffering major cardiovascular accidents particularly in the moments immediately following consumption. With males in their 30's apparently bearing the brunt of this burden, cannabis consumption has been associated with an increase in ischemic stroke-a blockage in the cerebral or cerebellar vasculature-and almost a fivefold increase in myocardial infarction. THC containing compounds have also been linked to vascular complications ranging from mild plaques to total arterial occlusion resulting in claudication, rest pain, ischemic ulceration and gangrene-recently termed cannabis arteritis. While this research remains in a nascent stage, marijuana consumption seems to be predisposing a youthful, traditionally low health risk cohort to a variety of major adverse cardiovascular events.

Rapid cyclic ion mobility separations of monosaccharide building blocks as a first step toward a high-throughput reaction screening platform for carbohydrate syntheses.

Herein we present a new high-throughput screening method for carbohydrate syntheses based on cyclic ion mobility spectrometry-mass spectrometry (cIMS-MS)-based separations. We rapidly resolved the α/ß anomers for carbohydrates with varying protecting groups after only 5 m of cIMS-MS separation and also detected their respective unwanted anomeric impurities at levels lower than 2%. All experiments were performed in 1 minute of total acquisition time demonstrating our method's high-throughput nature. Our methodology was also extended to the separation of an isomeric mixtures of two protected disaccharides illustrating its utility beyond only monosaccharides. We envision our presented workflow as a first step toward the development of a high-throughput screening platform for the rapid and sensitive detection of α/ß anomeric selectivities and for trace isomeric/isobaric impurities.

Mirativity as Surprise: Evidentiality, Information, and Deixis.

The goal of this paper is to investigate the linguistic, psychological and cognitive properties of utterances that express the surprise of the speaker, with a focus on how grammatical evidentials are used for this purpose. This is often labeled in the linguistics literature as mirativity. While there has been a flurry of recent interest in mirativity, we still lack an understanding of how and why evidentials are used this way, and an explanation of this effect. In this paper I take steps to filling this gap by showing how the mirativity associated with grammatical evidentials is one of the many linguistic reflexes of the more general cognitive process of surprise. I approach this by analyzing mirativity, and the language of surprise more generally, in a schema-theoretic framework enriched with the notion of new environmental information. I elaborate on the field methodological issues involved with testing the mirative use of an evidential and why they are used this way by connecting mirative evidentials to the broader phenomenon of deixis.

Low yield of stress imaging in a population-based study of asymptomatic patients after percutaneous coronary intervention.

BACKGROUND: Little is known about the clinical value of stress imaging studies in asymptomatic patients after percutaneous coronary intervention (PCI). METHODS AND RESULTS: Residents of Olmsted County, MN, who underwent PCI were followed up for the occurrence of stress imaging (stress nuclear or stress echocardiography), coronary angiography, or coronary artery bypass grafting (without angiography) as initial procedures after PCI. Patients whose first follow-up procedure was a stress imaging test were evaluated for their symptom status at the time of the study and whether they underwent angiography or revascularization (PCI or coronary artery bypass grafting) within 90 days. Of 1848 patients who underwent PCI during the study period, 710 (38%) had stress imaging as their initial procedure after PCI, and 241 (13% of the entire cohort) were asymptomatic at the time of testing. The majority (86%) of these 241 patients underwent PCI for acute myocardial infarction or unstable angina. Within 90 days of stress imaging, 16 of the 241 asymptomatic patients underwent angiography, and 2 patients were revascularized. Stratified by timing after PCI, none of 138 asymptomatic patients tested within 2 years of PCI underwent revascularization. Two of 103 asymptomatic patients tested after 2 years from PCI underwent revascularization. Compared with patients who were asymptomatic at the time of stress imaging, patients who did not undergo any follow-up procedures (stress imaging, angiography, or coronary artery bypass grafting) after the index PCI were older, were more likely to have comorbidities, and had significantly greater all-cause mortality (P<0.001). CONCLUSIONS: In a population-based sample of patients undergoing PCI primarily for acute coronary syndromes, 1 in 8 had subsequent stress imaging when they were asymptomatic. These stress imaging tests resulted in further revascularization in <1% of patients. The low rate of downstream revascularization suggests that stress imaging in asymptomatic patients after PCI has low value.

Unveiling nonischemic cardiomyopathies with cardiac magnetic resonance.

Cardiomyopathy is defined as a heterogeneous group of myocardial disorders with mechanical or electrical dysfunction. Identification of the etiology is important for accurate diagnosis, treatment and prognosis, but continues to be challenging. The ability of cardiac MRI to non-invasively obtain 3D-images of unparalleled resolution without radiation exposure and to provide tissue characterization gives it a distinct advantage over any other diagnostic tool used for evaluation of cardiomyopathies. Cardiac MRI can accurately visualize cardiac morphology and function and also help identify myocardial edema, infiltration and fibrosis. It has emerged as an important diagnostic and prognostic tool in tertiary care centers for work up of patients with non-ischemic cardiomyopathies. This review covers the role of cardiac MRI in evaluation of nonischemic cardiomyopathies, particularly in the context of other diagnostic and prognostic imaging modalities.

Characteristics and outcome after hospitalization for acute right heart failure in patients with pulmonary arterial hypertension.

BACKGROUND: Although much is known about the risk factors for poor outcome in patients hospitalized with acute heart failure and left ventricular dysfunction, much less is known about the syndrome of acute heart failure primarily affecting the right ventricle (acute right heart failure). METHODS AND RESULTS: By using Stanford Hospital's pulmonary hypertension database, we identified consecutive acute right heart failure hospitalizations in patients with PAH. We used longitudinal regression analysis with the generalized estimating equations method to identify factors associated with an increased likelihood of 90-day mortality or urgent transplantation. From June 1999 to September 2009, 119 patients with PAH were hospitalized for acute right heart failure (207 episodes). Death or urgent transplantation occurred in 34 patients by 90 days of admission. Multivariable analysis identified a higher respiratory rate on admission (>20 breaths per minute; OR, 3.4; 95% CI, 1.5-7.8), renal dysfunction on admission (glomerular filtration rate <45 mL/min per 1.73 m2; OR, 2.7; 95% CI, 1.2-6.3), hyponatremia (serum sodium ≤136 mEq/L; OR, 3.6; 95% CI, 1.7-7.9), and tricuspid regurgitation severity (OR, 2.5 per grade; 95% CI, 1.2-5.5) as independent factors associated with an increased likelihood of death or urgent transplantation. CONCLUSIONS: These results highlight the high mortality after hospitalizations for acute right heart failure in patients with PAH. Factors identifiable within hours of hospitalization may help predict the likelihood of death or the need for urgent transplantation in patients with PAH.

Incidence, correlates, and consequences of acute kidney injury in patients with pulmonary arterial hypertension hospitalized with acute right-side heart failure.

BACKGROUND: Though much is known about the prognostic influence of acute kidney injury (AKI) in left-side heart failure, much less is known about AKI in patients with pulmonary arterial hypertension (PAH). METHODS AND RESULTS: We identified consecutive patients with PAH who were hospitalized at Stanford Hospital for acute right-side heart failure. AKI was diagnosed according to the criteria of the Acute Kidney Injury Network. From June 1999 to June 2009, 105 patients with PAH were hospitalized for acute right-side heart failure (184 hospitalizations). AKI occurred in 43 hospitalizations (23%) in 34 patients (32%). The odds of developing AKI were higher among patients with chronic kidney disease (odds ratio [OR] 3.9, 95% confidence interval [CI] 1.8-8.5), high central venous pressure (OR 1.8, 95% CI 1.1-2.4, per 5 mm Hg), and tachycardia on admission (OR 4.3, 95% CI 2.1-8.8). AKI was strongly associated with 30-day mortality after acute right-side heart failure hospitalization (OR 5.3, 95% CI 2.2-13.2). CONCLUSIONS: AKI is relatively common in patients with PAH and associated with a short-term risk of death.

A novel non-invasive method of estimating pulmonary vascular resistance in patients with pulmonary arterial hypertension.

BACKGROUND: The assessment of pulmonary vascular resistance (PVR) plays an important role in the diagnosis and management of pulmonary arterial hypertension (PAH). The main objective of this study was to determine whether the noninvasive index of systolic pulmonary arterial pressure (SPAP) to heart rate (HR) times the right ventricular outflow tract time-velocity integral (TVI(RVOT)) (SPAP/[HR x TVI(RVOT)]) provides clinically useful estimations of PVR in PAH. METHODS: Doppler echocardiography and right-heart catheterization were performed in 51 consecutive patients with established PAH. The ratio of SPAP/(HR x TVI(RVOT)) was then correlated with invasive indexed PVR (PVRI) using regression and Bland-Altman analysis. Using receiver operating characteristic curve analysis, a cutoff value for the Doppler equation was generated to identify patients with PVRI > or = 15 Wood units (WU)/m2. RESULTS: The mean pulmonary arterial pressure was 52 +/- 15 mm Hg, the mean cardiac index was 2.2 +/- 0.6 L/min/m2, and the mean PVRI was 20.5 +/- 9.6 WU/m2. The ratio of SPAP/(HR x TVI(RVOT)) correlated very well with invasive PVRI measurements (r = 0.860; 95% confidence interval, 0.759-0.920). A cutoff value of 0.076 provided well-balanced sensitivity (86%) and specificity (82%) to determine PVRI > 15 WU/m2. A cutoff value of 0.057 increased sensitivity to 97% and decreased specificity to 65%. CONCLUSION: The novel index of SPAP/(HR x TVI(RVOT)) provides useful estimations of PVRI in patients with PAH.