Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy.

Fluorescence intravital microscopy captures large data sets of dynamic multicellular interactions within various organs such as the lungs, liver, and brain of living subjects. In medical imaging, edge detection is used to accurately identify and delineate important structures and boundaries inside the images. To improve edge sharpness, edge detection frequently requires the inclusion of low-level features. Herein, a machine learning approach is needed to automate the edge detection of multicellular aggregates of distinctly labeled blood cells within the microcirculation. In this work, the Structured Adaptive Boosting Trees algorithm (AdaBoost.S) is proposed as a contribution to overcome some of the edge detection challenges related to medical images. Algorithm design is based on the observation that edges over an image mask often exhibit special structures and are interdependent. Such structures can be predicted using the features extracted from a bigger image patch that covers the image edge mask. The proposed AdaBoost.S is applied to detect multicellular aggregates within blood vessels from the fluorescence lung intravital images of mice exposed to e-cigarette vapor. The predictive capabilities of this approach for detecting platelet-neutrophil aggregates within the lung blood vessels are evaluated against three conventional machine learning algorithms: Random Forest, XGBoost and Decision Tree. AdaBoost.S exhibits a mean recall, F-score, and precision of 0.81, 0.79, and 0.78, respectively. Compared to all three existing algorithms, AdaBoost.S has statistically better performance for recall and F-score. Although AdaBoost.S does not outperform Random Forest in precision, it remains superior to the XGBoost and Decision Tree algorithms. The proposed AdaBoost.S is widely applicable to analysis of other fluorescence intravital microscopy applications including cancer, infection, and cardiovascular disease.

Short-term exposure of female BALB/cJ mice to e-cigarette aerosol promotes neutrophil recruitment and enhances neutrophil-platelet aggregation in pulmonary microvasculature.

Despite the perception that e-cigarettes are safer than conventional cigarettes, numerous findings demonstrated that e-cigarette aerosol (EC) exposure induced compromised immune functionality, vascular changes even after acute exposure, and lung injury. Notably, altered neutrophil functionality and platelet hemodynamics have been observed post-EC exposure. It was hypothesized that EC exposure initiates an inflammatory response resulting in altered neutrophil behavior and increased neutrophil-platelet interaction in the pulmonary microvasculature. Neutrophil and platelet responses were examined up to 48 hrs following whole-body, short-term EC exposure without flavorants or nicotine in a murine model, which most closely modeled secondhand exposure. This study is the first to investigate the impact of EC exposure through lung intravital imaging. Compared to room air-exposed mice, EC-exposed mice displayed significantly increased 1.7‒1.9-fold number of neutrophils in the pulmonary microvasculature associated with no marked change in neutrophils within whole blood or bronchoalveolar lavage fluid (BALF). Neutrophil-platelet interactions were also significantly elevated 1.9‒2.5-fold in exposed mice. Plasma concentration of myeloperoxidase was markedly reduced 1.5-fold 48 hr following exposure cessation, suggesting suppressed neutrophil antimicrobial activity. Cytokine expression exhibited changes indicating vascular damage. Effects persisted for 48 hr post-EC exposure. Data demonstrated that EC exposure repeated for 3 consecutive days in 2.5 hr intervals in the absence of flavorants or nicotine resulted in modified pulmonary vasculature hemodynamics, altered immune functionality, and a pro-inflammatory state in female BALB/cJ mice.

Platelet Extracellular Vesicles Drive Inflammasome-IL-1ß-Dependent Lung Injury in Sickle Cell Disease.

Rationale: Intraerythrocytic polymerization of Hb S promotes hemolysis and vasoocclusive events in the microvasculature of patients with sickle cell disease (SCD). Although platelet-neutrophil aggregate-dependent vasoocclusion is known to occur in the lung and contribute to acute chest syndrome, the etiological mechanisms that trigger acute chest syndrome are largely unknown.Objectives: To identify the innate immune mechanism that promotes platelet-neutrophil aggregate-dependent lung vasoocclusion and injury in SCD.Methods:In vivo imaging of the lung in transgenic humanized SCD mice and in vitro imaging of SCD patient blood flowing through a microfluidic system was performed. SCD mice were systemically challenged with nanogram quantities of LPS to trigger lung vasoocclusion.Measurements and Main Results: Platelet-inflammasome activation led to generation of IL-1ß and caspase-1-carrying platelet extracellular vesicles (EVs) that bind to neutrophils and promote platelet-neutrophil aggregation in lung arterioles of SCD mice in vivo and SCD human blood in microfluidics in vitro. The inflammasome activation, platelet EV generation, and platelet-neutrophil aggregation were enhanced by the presence of LPS at a nanogram dose in SCD but not control human blood. Inhibition of the inflammasome effector caspase-1 or IL-1ß pathway attenuated platelet EV generation, prevented platelet-neutrophil aggregation, and restored microvascular blood flow in lung arterioles of SCD mice in vivo and SCD human blood in microfluidics in vitro.Conclusions: These results are the first to identify that platelet-inflammasome-dependent shedding of IL-1ß and caspase-1-carrying platelet EVs promote lung vasoocclusion in SCD. The current findings also highlight the therapeutic potential of targeting the platelet-inflammasome-dependent innate immune pathway to prevent acute chest syndrome.

E-Cigarette Use: Device Market, Study Design, and Emerging Evidence of Biological Consequences.

Electronic cigarettes are frequently viewed as a safer alternative to conventional cigarettes; however, evidence to support this perspective has not materialized. Indeed, the current literature reports that electronic cigarette use is associated with both acute lung injury and subclinical dysfunction to the lung and vasculature that may result in pathology following chronic use. E-cigarettes can alter vascular dynamics, polarize innate immune populations towards a proinflammatory state, compromise barrier function in the pulmonary endothelium and epithelium, and promote pre-oncogenic phenomena. This review will summarize the variety of e-cigarette products available to users, discuss current challenges in e-cigarette study design, outline the range of pathologies occurring in cases of e-cigarette associated acute lung injury, highlight disease supporting tissue- and cellular-level changes resulting from e-cigarette exposure, and briefly examine how these changes may promote tumorigenesis. Continued research of the mechanisms by which e-cigarettes induce pathology benefit users and clinicians by resulting in increased regulation of vaping devices, informing treatments for emerging diseases e-cigarettes produce, and increasing public awareness to reduce e-cigarette use and the onset of preventable disease.

Neutrophil extracellular traps in breast cancer and beyond: current perspectives on NET stimuli, thrombosis and metastasis, and clinical utility for diagnosis and treatment.

The formation of neutrophil extracellular traps (NETs), known as NETosis, was first observed as a novel immune response to bacterial infection, but has since been found to occur abnormally in a variety of other inflammatory disease states including cancer. Breast cancer is the most commonly diagnosed malignancy in women. In breast cancer, NETosis has been linked to increased disease progression, metastasis, and complications such as venous thromboembolism. NET-targeted therapies have shown success in preclinical cancer models and may prove valuable clinical targets in slowing or halting tumor progression in breast cancer patients. We will briefly outline the mechanisms by which NETs may form in the tumor microenvironment and circulation, including the crosstalk between neutrophils, tumor cells, endothelial cells, and platelets as well as the role of cancer-associated extracellular vesicles in modulating neutrophil behavior and NET extrusion. The prognostic implications of cancer-associated NETosis will be explored in addition to development of novel therapeutics aimed at targeting NET interactions to improve outcomes in patients with breast cancer.

Intelligent and automatic in vivo detection and quantification of transplanted cells in MRI.

PURPOSE: Magnetic resonance imaging (MRI)-based cell tracking has emerged as a useful tool for identifying the location of transplanted cells, and even their migration. Magnetically labeled cells appear as dark contrast in T2*-weighted MRI, with sensitivities of individual cells. One key hurdle to the widespread use of MRI-based cell tracking is the inability to determine the number of transplanted cells based on this contrast feature. In the case of single cell detection, manual enumeration of spots in three-dimensional (3D) MRI in principle is possible; however, it is a tedious and time-consuming task that is prone to subjectivity and inaccuracy on a large scale. This research presents the first comprehensive study on how a computer-based intelligent, automatic, and accurate cell quantification approach can be designed for spot detection in MRI scans. METHODS: Magnetically labeled mesenchymal stem cells (MSCs) were transplanted into rats using an intracardiac injection, accomplishing single cell seeding in the brain. T2*-weighted MRI of these rat brains were performed where labeled MSCs appeared as spots. Using machine learning and computer vision paradigms, approaches were designed to systematically explore the possibility of automatic detection of these spots in MRI. Experiments were validated against known in vitro scenarios. RESULTS: Using the proposed deep convolutional neural network (CNN) architecture, an in vivo accuracy up to 97.3% and in vitro accuracy of up to 99.8% was achieved for automated spot detection in MRI data. CONCLUSION: The proposed approach for automatic quantification of MRI-based cell tracking will facilitate the use of MRI in large-scale cell therapy studies. Magn Reson Med 78:1991-2002, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Clinically viable magnetic poly(lactide-co-glycolide) particles for MRI-based cell tracking.

PURPOSE: To design, fabricate, characterize, and in vivo assay clinically viable magnetic particles for MRI-based cell tracking. METHODS: Poly(lactide-co-glycolide) (PLGA) encapsulated magnetic nano and microparticles were fabricated. Multiple biologically relevant experiments were performed to assess cell viability, cellular performance, and stem cell differentiation. In vivo MRI experiments were performed to separately test cell transplantation and cell migration paradigms, as well as in vivo biodegradation. RESULTS: Highly magnetic nano (∼100 nm) and microparticles (∼1-2 µm) were fabricated. Magnetic cell labeling in culture occurred rapidly achieving 3-50 pg Fe/cell at 3 h for different particles types, and >100 pg Fe/cell after 10 h, without the requirement of a transfection agent, and with no effect on cell viability. The capability of magnetically labeled mesenchymal or neural stem cells to differentiate down multiple lineages, or for magnetically labeled immune cells to release cytokines following stimulation, was uncompromised. An in vivo biodegradation study revealed that NPs degraded ∼80% over the course of 12 weeks. MRI detected as few as 10 magnetically labeled cells, transplanted into the brains of rats. Also, these particles enabled the in vivo monitoring of endogenous neural progenitor cell migration in rat brains over 2 weeks. CONCLUSION: The robust MRI properties and benign safety profile of these particles make them promising candidates for clinical translation for MRI-based cell tracking.

Poly(lactic-co-glycolic acid) encapsulated gadolinium oxide nanoparticles for MRI-based cell tracking.

Superparamagnetic iron oxide particles have proven useful for cell tracking applications by monitoring cell transplantation and migration in living organisms. However, one perceived drawback is that these particles cause dark contrast in MRI, sometimes yielding confusion with other biological phenomena, which also yield dark contrast. To that end, researchers have investigated the use of gadolinium oxide (Gd2O3) based contrast agents for MRI-based cell tracking, as Gd2O3 has favorable r1 molar relaxivity. We synthesized Gd2O3 nanocrystals and encapsulated them within PLGA matrices to form approximatley to 150 nm nanoparticles. r1 was 1.9 mM(-1) sec(-1) and r2 was 8.4 mM(-1) sec(-1). Cell labeling with particles was well tolerated by cells except at very high doses. MRI of labeled cells showed that labeled cells could achieve both R1 and R2 enhancements due to the internalized particles. R2 enhancements were approximately to twice that of R1 enhancements suggesting the use of very short echo times when using Gd2O3 based contrast agents for MRI-based cell tracking.

Caveat Emptor: Commercialized Manganese Oxide Nanoparticles Exhibit Unintended Properties.

Nano-encapsulated manganese oxide (NEMO) particles are noteworthy contrast agents for magnetic resonance imaging (MRI) due to their bright, pH-switchable signal ("OFF" to "ON" at low pH), high metal loading, and targeting capability for increased specificity. For the first time, we performed a head-to-head comparison of NEMO particles from In-house and commercialized sources (US Nano vs Nanoshel) to assess their potential as bright T1 MRI contrast agents. Manganese oxide nanocrystals (MnO, Mn2O3, and Mn3O4) were systematically evaluated for size, chemistry, release of manganese ions, and MRI signal pre- and post-encapsulation within poly(lactic-co-glycolic acid) (PLGA). Suprisingly, a majority of the commercialized formulations were not as advertised by displaying unintended sizes, morphologies, chemistry, dissolution profiles, and/or MRI signal that precludes in vivo use. US Nano's Mn3O4 and Mn2O3 nanocrystals contained impurities that impacted Mn ion release as well as micron-sized rodlike structures. Nanoshel's MnO and Mn2O3 nanoparticles had very large hydrodynamic sizes (>600 nm). In-house MnO and Nanoshel's Mn3O4 nanoparticles demonstrated the best characteristics with brighter T1 MRI signals, small hydrodynamic sizes, and high encapsulation efficiencies. Our findings highlight that researchers must confirm the properties of purchased nanomaterials before utilizing them in desired applications, as their experimental success may be impacted.