AngioMT: A MATLAB based 2D image-to-physics tool to predict oxygen transport in vascularized microphysiological systems.

Microphysiological models (MPS) are increasingly getting recognized as in vitro preclinical systems of pathophysiology and drug discovery. However, there is also a growing need to adapt and advance MPS to include the physiological contributions of the capillary vascular dynamics, because they undergo angiogenesis or vasculogenesis to deliver soluble oxygen and nutrients to its organs. Currently, the process of formation of microvessels in MPS is measured arbitrarily, and vascularized MPS do not include oxygen measurements in their analysis. Sensing and measuring tissue oxygen delivery is extremely difficult because it requires access to opaque and deep tissue, and/or requires extensive integration of biosensors that makes such systems impractical to use in the real world. Here, a finite element method-based oxygen transport program, called AngioMT, is built in MATLAB. AngioMT processes the routinely acquired 2D confocal images of microvascular networks in vitro and solves physical equations of diffusion-reaction dominated oxygen transport phenomena. This user-friendly image-to-physics transition in AngioMT is an enabling tool of MPS analysis because unlike the averaged morphological measures of vessels, it provides information of the spatial transport of oxygen both within the microvessels and the surrounding tissue regions. Further, it solves the more complex higher order reaction mechanisms which also improve the physiological relevance of this tool when compared directly against in vivo measurements. Finally, the program is applied in a multicellular vascularized MPS by including the ability to define additional organ/tissue subtypes in complex co-cultured systems. Therefore, AngioMT serves as an analytical tool to enhance the predictive power and performance of MPS that incorporate microcirculation.

Angiogenesis-Enabled Human Ovarian Tumor Microenvironment-Chip Evaluates Pathophysiology of Platelets in Microcirculation.

The tumor microenvironment (TME) promotes angiogenesis for its growth through the recruitment of multiple cells and signaling mechanisms. For example, TME actively recruits and activates platelets from the microcirculation to facilitate metastasis, but platelets may simultaneously also support tumor angiogenesis. Here, to model this complex pathophysiology within the TME that involves a signaling triad of cancer cells, sprouting endothelial cells, and platelets, an angiogenesis-enabled tumor microenvironment chip (aTME-Chip) is presented. This platform recapitulates the convergence of physiology of angiogenesis and platelet function within the ovarian TME and describes the contribution of platelets in promoting angiogenesis within an ovarian TME. By including three distinct human ovarian cancer cell-types, the aTME-Chip quantitatively reveals the following outcomes-first, introduction of platelets significantly increases angiogenesis; second, the temporal dynamics of angiogenic signaling is dependent on cancer cell type; and finally, tumor-educated platelets either activated exogenously by cancer cells or derived clinically from a cancer patient accelerate tumor angiogenesis. Further, analysis of effluents available from aTME-Chip validate functional outcomes by revealing changes in cytokine expression and several angiogenic and metastatic signaling pathways due to platelets. Collectively, this tumor microphysiological system may be deployed to derive antiangiogenic targets combined with antiplatelet treatments to arrest cancer metastasis.

AngioMT: An in silico platform for digital sensing of oxygen transport through heterogenous microvascular networks.

Measuring the capacity of microvascular networks in delivering soluble oxygen and nutrients to its organs is essential in health, disease, and surgical interventions. Here, a finite element method-based oxygen transport program, AngioMT, is designed and validated to predict spatial oxygen distribution and other physiologically relevant transport metrics within both the vascular network and the surrounding tissue. The software processes acquired images of microvascular networks and produces a digital mesh which is used to predict vessel and tissue oxygenation. The image-to-physics translation by AngioMT correlated with results from commercial software, however only AngioMT could provide predictions within the solid tissue in addition to vessel oxygenation. AngioMT predictions were sensitive and positively correlated to spatial heterogeneity and extent of vascularization of 500 different vascular networks formed with variable vasculogenic conditions. The predictions of AngioMT cross-correlate with experimentally-measured oxygen distributions in vivo. The computational power of the software is increased by including calculations of higher order reaction mechanisms, and the program includes defining additional organ and tissue structures for a more physiologically relevant analysis of tissue oxygenation in complex co-cultured systems, or in vivo. AngioMT may serve as a digital performance measuring tool of vascular networks in microcirculation, experimental models of vascularized tissues and organs, and in clinical applications, such as organ transplants.

Machine learning chained neural network analysis of oxygen transport amplifies the physiological relevance of vascularized microphysiological systems.

Since every biological system requires capillaries to support its oxygenation, design of engineered preclinical models of such systems, for example, vascularized microphysiological systems (vMPS) have gained attention enhancing the physiological relevance of human biology and therapies. But the physiology and function of formed vessels in the vMPS is currently assessed by non-standardized, user-dependent, and simple morphological metrics that poorly relate to the fundamental function of oxygenation of organs. Here, a chained neural network is engineered and trained using morphological metrics derived from a diverse set of vMPS representing random combinations of factors that influence the vascular network architecture of a tissue. This machine-learned algorithm outputs a singular measure, termed as vascular network quality index (VNQI). Cross-correlation of morphological metrics and VNQI against measured oxygen levels within vMPS revealed that VNQI correlated the most with oxygen measurements. VNQI is sensitive to the determinants of vascular networks and it consistently correlates better to the measured oxygen than morphological metrics alone. Finally, the VNQI is positively associated with the functional outcomes of cell transplantation therapies, shown in the vascularized islet-chip challenged with hypoxia. Therefore, adoption of this tool will amplify the predictions and enable standardization of organ-chips, transplant models, and other cell biosystems.

Evaluation of the morphological and biological functions of vascularized microphysiological systems with supervised machine learning.

Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease. While vascularization is emerging as a necessary physiological organ-level feature required in most such systems, there is no standard tool or morphological metric to measure the performance or biological function of vascularized networks within these models. Further, the commonly reported morphological metrics may not correlate to the network's biological function - oxygen transport. Here, a large library of vascular network images was analyzed by the measure of each sample's morphology and oxygen transport potential. The oxygen transport quantification is computationally expensive and user-dependent, so machine learning techniques were examined to generate regression models relating morphology to function. Principal component and factor analyses were applied to reduce dimensionality of the multivariate dataset, followed by multiple linear regression and tree-based regression analyses. These examinations reveal that while several morphological data relate poorly to the biological function, some machine learning models possess a relatively improved, but still moderate predictive potential. Overall, random forest regression model correlates to the biological function of vascular networks with relatively higher accuracy than other regression models.

Evaluation of the Morphological and Biological Functions of Vascularized Microphysiological Systems with Supervised Machine Learning.

Vascularized microphysiological systems and organoids are contemporary preclinical experimental platforms representing human tissue or organ function in health and disease. While vascularization is emerging as a necessary physiological organ-level feature required in most such systems, there is no standard tool or morphological metric to measure the performance or biological function of vascularized networks within these models. Further, the commonly reported morphological metrics may not correlate to the network's biological function-oxygen transport. Here, a large library of vascular network images was analyzed by the measure of each sample's morphology and oxygen transport potential. The oxygen transport quantification is computationally expensive and user-dependent, so machine learning techniques were examined to generate regression models relating morphology to function. Principal component and factor analyses were applied to reduce dimensionality of the multivariate dataset, followed by multiple linear regression and tree-based regression analyses. These examinations reveal that while several morphological data relate poorly to the biological function, some machine learning models possess a relatively improved, but still moderate predictive potential. Overall, random forest regression model correlates to the biological function of vascular networks with relatively higher accuracy than other regression models.

Vascular Transcriptomics: Investigating Endothelial Activation and Vascular Dysfunction Using Blood Outgrowth Endothelial Cells, Organ-Chips, and RNA Sequencing.

Vascular organ-chip or vessel-chip technology has significantly impacted our ability to model microphysiological vasculature. These biomimetic platforms have garnered significant interest from scientists and pharmaceutical companies as drug screening models. However, these models still lack the inclusion of patient-specific vasculature in the form of patient-derived endothelial cells. Blood outgrowth endothelial cells are patient blood-derived endothelial progenitors that have gained interest from the vascular biology community as an autologous endothelial cell alternative and have also been incorporated with the vessel-chip model. Next-generation sequencing techniques like RNA sequencing can further unlock the potential of personalized vessel-chips in discerning patient-specific hallmarks of endothelial dysfunction. Here we present a detailed protocol for (1) isolating blood outgrowth endothelial cells from patient blood samples, (2) culturing them in microfluidic vessel-chips, (3) isolating and preparing RNA from individual vessel-chips for sequencing, and (4) performing differential gene expression and bioinformatics analyses of vascular dysfunction and endothelial activation pathways. This method focuses specifically on identification of pathways and genes involved in vascular homeostasis and pathology, but can easily be adapted for the requirements of other systems. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Isolation of blood outgrowth endothelial cells from patient blood Basic Protocol 2: Culture of blood outgrowth endothelial cells in microfluidic vessel-chips Basic Protocol 3: Isolation of RNA from autologous vessel-chips Basic Protocol 4: Differential gene expression and bioinformatics analyses of endothelial activation pathways.

Physicochemical Properties of a Bi-aromatic Heterocyclic-Azo/BSA Hybrid System at the Air-Water Interface.

The interaction of a heterocyclic azo compound with itself and with bovine serum albumin (BSA) is realized by probing the structural modifications in Langmuir (L) monolayers and Langmuir-Blodgett (LB) films. It was found from the pressure-area/molecule isotherms that the elastic, thermodynamic, and hysteretic properties of the pure azo L monolayer were strongly altered due to the variation of temperature and pH of subphase water. In addition to that, the modification of such properties of the azo L monolayer due to mixing with BSA was also studied. The incorporation of BSA within the azo molecular assembly reduced the elasticity of that assembly. Such reduction of in-plane elasticity of the pure azo monolayer can also be achieved by reducing the temperature and pH of subphase water without adding BSA. A reduction in area per molecule of the azo assembly at the air-water interface associated with the conformational change from horizontal to vertical orientation facilitating π-π interaction was observed with increase in temperature and pH of the subphase. Such parameters also affected the interactions between azo and BSA molecules within the azo/BSA binary system. The structures of pure azo and binary films can be determined after they are transferred to hydrophilic and hydrophobic Si surfaces using the LB technique. Their out-of-plane and in-plane structures, as extracted from two complementary surface sensitive techniques, X-ray reflectivity and atomic force microscopy, were found to be strongly dependent on mixing with BSA, subphase pH, temperature, and substrate nature.

Airway management, procedural data, and in-hospital mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19).

PURPOSE: Although unexpected airway difficulties are reported in patients with mucormycosis, the literature on airway management in patients with mucormycosis associated with Coronavirus disease is sparse. METHODS: In this retrospective case record review of 57 patients who underwent surgery for mucormycosis associated with coronavirus disease, we aimed to evaluate the demographics, airway management, procedural data, and in-hospital mortality records. RESULTS: Forty-one (71.9%) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) patients had a diagnosis of rhino-orbital mucormycosis, and 2 (3.5%) patients had a diagnosis of palatal mucormycosis. A total of 44 (77.2%) patients had co-morbidities. The most common co-morbidities were diabetes mellitus in 42 (73.6%) patients, followed by hypertension in 21 (36.8%) patients, and acute kidney injury in 14 (28.1%) patients. We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 (92.9%) patients. In our study, mortality occurred in 7 (12.3%) patients. The median (range) mortality time was 60 (27-74) days. The median (range) time to hospital discharge was 53.5 (10-85) days. The median [interquartile range] age of discharged versus expired patients was 47.5 [41,57.5] versus 64 [47,70] years (P = 0.04), and median (interquartile range) D-dimer levels in discharged versus expired patients was 364 [213, 638] versus 2448 [408,3301] ng/mL (P = 0.03). CONCLUSION: In patients undergoing surgery for mucormycosis associated with the coronavirus disease, airway management was easy to slightly difficult in most patients. Perioperative complications can be minimized by taking timely and precautionary measures.

Tripartite collaboration of blood-derived endothelial cells, next generation RNA sequencing and bioengineered vessel-chip may distinguish vasculopathy and thrombosis among sickle cell disease patients.

Sickle cell disease (SCD) is the most prevalent inherited blood disorder in the world. But the clinical manifestations of the disease are highly variable. In particular, it is currently difficult to predict the adverse outcomes within patients with SCD, such as, vasculopathy, thrombosis, and stroke. Therefore, for most effective and timely interventions, a predictive analytic strategy is desirable. In this study, we evaluate the endothelial and prothrombotic characteristics of blood outgrowth endothelial cells (BOECs) generated from blood samples of SCD patients with known differences in clinical severity of the disease. We present a method to evaluate patient-specific vaso-occlusive risk by combining novel RNA-seq and organ-on-chip approaches. Through differential gene expression (DGE) and pathway analysis we find that BOECs from SCD patients exhibit an activated state through cell adhesion molecule (CAM) and cytokine signaling pathways among many others. In agreement with clinical symptoms of patients, DGE analyses reveal that patient with severe SCD had a greater extent of endothelial activation compared to patient with milder symptoms. This difference is confirmed by performing qRT-PCR of endothelial adhesion markers like E-selectin, P-selectin, tissue factor, and Von Willebrand factor. Finally, the differential regulation of the proinflammatory phenotype is confirmed through platelet adhesion readouts in our BOEC vessel-chip. Taken together, we hypothesize that these easily blood-derived endothelial cells evaluated through RNA-seq and organ-on-chips may serve as a biotechnique to predict vaso-occlusive episodes in SCD patients and will ultimately allow better therapeutic interventions.

Comparative Analysis of Blood-Derived Endothelial Cells for Designing Next-Generation Personalized Organ-on-Chips.

Background Organ-on-chip technology has accelerated in vitro preclinical research of the vascular system, and a key strength of this platform is its promise to impact personalized medicine by providing a primary human cell-culture environment where endothelial cells are directly biopsied from individual tissue or differentiated through stem cell biotechniques. However, these methods are difficult to adopt in laboratories, and often result in impurity and heterogeneity of cells. This limits the power of organ-chips in making accurate physiological predictions. In this study, we report the use of blood-derived endothelial cells as alternatives to primary and induced pluripotent stem cell-derived endothelial cells. Methods and Results Here, the genotype, phenotype, and organ-chip functional characteristics of blood-derived outgrowth endothelial cells were compared against commercially available and most used primary endothelial cells and induced pluripotent stem cell-derived endothelial cells. The methods include RNA-sequencing, as well as criterion standard assays of cell marker expression, growth kinetics, migration potential, and vasculogenesis. Finally, thromboinflammatory responses under shear using vessel-chips engineered with blood-derived endothelial cells were assessed. Blood-derived endothelial cells exhibit the criterion standard hallmarks of typical endothelial cells. There are differences in gene expression profiles between different sources of endothelial cells, but blood-derived cells are relatively closer to primary cells than induced pluripotent stem cell-derived. Furthermore, blood-derived endothelial cells are much easier to obtain from individuals and yet, they serve as an equally effective cell source for functional studies and organ-chips compared with primary cells or induced pluripotent stem cell-derived cells. Conclusions Blood-derived endothelial cells may be used in preclinical research for developing more robust and personalized next-generation disease models using organ-on-chips.

Human tumor microenvironment chip evaluates the consequences of platelet extravasation and combinatorial antitumor-antiplatelet therapy in ovarian cancer.

Platelets extravasate from the circulation into tumor microenvironment, enable metastasis, and confer resistance to chemotherapy in several cancers. Therefore, arresting tumor-platelet cross-talk with effective and atoxic antiplatelet agents in combination with anticancer drugs may serve as an effective cancer treatment strategy. To test this concept, we create an ovarian tumor microenvironment chip (OTME-Chip) that consists of a platelet-perfused tumor microenvironment and which recapitulates platelet extravasation and its consequences. By including gene-edited tumors and RNA sequencing, this organ-on-chip revealed that platelets and tumors interact through glycoprotein VI (GPVI) and tumor galectin-3 under shear. Last, as proof of principle of a clinical trial, we showed that a GPVI inhibitor, Revacept, impairs metastatic potential and improves chemotherapy. Since GPVI is an antithrombotic target that does not impair hemostasis, it represents a safe cancer therapeutic. We propose that OTME-Chip could be deployed to study other vascular and hematological targets in cancer.

OvCa-Chip microsystem recreates vascular endothelium-mediated platelet extravasation in ovarian cancer.

In ovarian cancer, platelet extravasation into the tumor and resulting metastasis is thought to be regulated mostly by the vascular endothelium. Because it is difficult to dissect complex underlying events in murine models, organ-on-a-chip methodology is applied to model vascular and platelet functions in ovarian cancer. This system (OvCa-Chip) consists of microfluidic chambers that are lined by human ovarian tumor cells interfaced with a 3-dimensional endothelialized lumen. Subsequent perfusion with human platelets within the device's vascular endothelial compartment under microvascular shear conditions for 5 days uncovered organ-to-molecular-level contributions of the endothelium to triggering platelet extravasation into tumors. Further, analysis of effluents available from the device's individual tumor and endothelial chambers revealed temporal dynamics of vascular disintegration caused by cancer cells, a differential increase in cytokine expression, and an alteration of barrier maintenance genes in endothelial cells. These events, when analyzed within the device over time, made the vascular tissue leaky and promoted platelet extravasation. Atorvastatin treatment of the endothelial cells within the OvCa-Chip revealed improved endothelial barrier function, reduction in inflammatory cytokines and, eventually, arrest of platelet extravasation. These data were validated through corresponding observations in patient-derived tumor samples. The OvCa-Chip provides a novel in vitro dissectible platform to model the mechanisms of the cancer-vascular-hematology nexus and the analyses of potential therapeutics.

Structure and Elastic Properties of an Unsymmetrical Bi-Heterocyclic Azo Compound in the Langmuir Monolayer and Langmuir-Blodgett Film.

We study the structure and elastic properties of the bi-heterocyclic azo compound at the air-water interface through surface pressure (π)-area (A) isotherm recording followed by transferring them on hydrophilic and hydrophobic Si surfaces by the Langmuir-Blodgett (LB) deposition method. A substantial change in the area/molecule is observed as a function of subphase pH and temperature. Such parameters strongly influence intramolecular interactions within azo molecules and the interactions between azo molecules and water that manifested in higher surface activity at low temperature and high pH, which in turn modifies the elasticity of azo assembly at the air-water interface. A large pH-dependent hysteresis with negative change in entropy, indicating molecular rearrangements, is observed. Molecular assembly formed at the air-water interface is then transferred onto hydrophilic and hydrophobic Si surfaces at two different surface pressures (5 and 30 mN/m) by the LB technique. The structural analysis performed by X-ray reflectivity and atomic force microscopy techniques suggests that the LB films exhibit an abrupt layered structure on hydrophilic Si, whereas an overall rough film is formed on hydrophobic Si. The coverage and compactness of individual layers are found to increase with the deposition pressure (5 to 30 mN/m).

Tortuosity-powered microfluidic device for assessment of thrombosis and antithrombotic therapy in whole blood.

Accurate assessment of blood thrombosis and antithrombotic therapy is essential for the management of patients in a variety of clinical conditions, including surgery and on extracorporeal life support. However, current monitoring devices do not measure the effects of hemodynamic forces that contribute significantly to coagulation, platelet function and fibrin formation. This limits the extent to which current assays can predict clotting status in patients. Here, we demonstrate that a biomimetic microfluidic device consisting stenosed and tortuous arteriolar vessels would analyze blood clotting under flow, while requiring a small blood volume. When the device is connected to an inline pressure sensor a clotting time analysis is applied, allowing for the accurate measurement of coagulation, platelets and fibrin content. Furthermore, this device detects a prolonged clotting time in clinical blood samples drawn from pediatric patients on extracorporeal membrane oxygenation receiving anticoagulant therapy. Thus, this tortuosity activated microfluidic device could lead to a more quantitative and rapid assessment of clotting disorders and their treatment.

Organ-on-chips made of blood: endothelial progenitor cells from blood reconstitute vascular thromboinflammation in vessel-chips.

Development of therapeutic approaches to treat vascular dysfunction and thrombosis at disease- and patient-specific levels is an exciting proposed direction in biomedical research. However, this cannot be achieved with animal preclinical models alone, and new in vitro techniques, like human organ-on-chips, currently lack inclusion of easily obtainable and phenotypically-similar human cell sources. Therefore, there is an unmet need to identify sources of patient primary cells and apply them in organ-on-chips to increase personalized mechanistic understanding of diseases and to assess drugs. In this study, we provide a proof-of-feasibility of utilizing blood outgrowth endothelial cells (BOECs) as a disease-specific primary cell source to analyze vascular inflammation and thrombosis in vascular organ-chips or "vessel-chips". These blood-derived BOECs express several factors that confirm their endothelial identity. The vessel-chips are cultured with BOECs from healthy or diabetic patients and form an intact 3D endothelial lumen. Inflammation of the BOEC endothelium with exogenous cytokines reveals vascular dysfunction and thrombosis in vitro similar to in vivo observations. Interestingly, our study with vessel-chips also reveals that unstimulated BOECs of type 1 diabetic pigs show phenotypic behavior of the disease - high vascular dysfunction and thrombogenicity - when compared to control BOECs or normal primary endothelial cells. These results demonstrate the potential of organ-on-chips made from autologous endothelial cells obtained from blood in modeling vascular pathologies and therapeutic outcomes at a disease and patient-specific level.