Laminin and hyaluronan supplementation of collagen hydrogels enhances endothelial function and tight junction expression on three-dimensional cylindrical microvessel-on-a-chip.

Vasculature-on-chip (VoC) models have become a prominent tool in the study of microvasculature functions because of their cost-effective and ethical production process. These models typically use a hydrogel in which the three-dimensional (3D) microvascular structure is embedded. Thus, VoCs are directly impacted by the physical and chemical cues of the supporting hydrogel. Endothelial cell (EC) response in VoCs is critical, especially in organ-specific vasculature models, in which ECs exhibit specific traits and behaviors that vary between organs. Many studies customize the stimuli ECs perceive in different ways; however, customizing the hydrogel composition accordingly to the target organ's extracellular matrix (ECM), which we believe has great potential, has been rarely investigated. We explored this approach to organ-specific VoCs by fabricating microvessels (MVs) with either human umbilical vein ECs or human brain microvascular ECs in a 3D cylindrical VoC using a collagen hydrogel alone or one supplemented with laminin and hyaluronan, components found in the brain ECM. We characterized the physical properties of these hydrogels and analyzed the barrier properties of the MVs. Barrier function and tight junction (ZO-1) expression improved with the addition of laminin and hyaluronan in the composite hydrogel.

Protocol for fabricating and characterizing microvessel-on-a-chip for human umbilical vein endothelial cells.

Organ-on-a-chip technologies enable the fabrication of endothelial tissues, so-called microvessels (MVs), which emulate the endothelial barrier function in healthy or disease conditions. In this protocol, we describe the fabrication of perfusable open-chamber style MVs embedded in collagen gels. We then report a simple technology to characterize the MV barrier properties in static or under pressure based on fluorescence confocal imaging. Finally, we provide quantification techniques that enable us to infer the structure of MV paracellular pores. For complete details on the use and execution of this protocol, please refer to Cacheux et al.1.

CD40 is expressed in the subsets of endothelial cells undergoing partial endothelial-mesenchymal transition in tumor microenvironment.

Tumor progression and metastasis are regulated by endothelial cells undergoing endothelial-mesenchymal transition (EndoMT), a cellular differentiation process in which endothelial cells lose their properties and differentiate into mesenchymal cells. The cells undergoing EndoMT differentiate through a spectrum of intermediate phases, suggesting that some cells remain in a partial EndoMT state and exhibit an endothelial/mesenchymal phenotype. However, detailed analysis of partial EndoMT has been hampered by the lack of specific markers. Transforming growth factor-ß (TGF-ß) plays a central role in the induction of EndoMT. Here, we showed that inhibition of TGF-ß signaling suppressed EndoMT in a human oral cancer cell xenograft mouse model. By using genetic labeling of endothelial cell lineage, we also established a novel EndoMT reporter cell system, the EndoMT reporter endothelial cells (EMRECs), which allow visualization of sequential changes during TGF-ß-induced EndoMT. Using EMRECs, we characterized the gene profiles of multiple EndoMT stages and identified CD40 as a novel partial EndoMT-specific marker. CD40 expression was upregulated in the cells undergoing partial EndoMT, but decreased in the full EndoMT cells. Furthermore, single-cell RNA sequencing analysis of human tumors revealed that CD40 expression was enriched in the population of cells expressing both endothelial and mesenchymal cell markers. Moreover, decreased expression of CD40 in EMRECs enhanced TGF-ß-induced EndoMT, suggesting that CD40 expressed during partial EndoMT inhibits transition to full EndoMT. The present findings provide a better understanding of the mechanisms underlying TGF-ß-induced EndoMT and will facilitate the development of novel therapeutic strategies targeting EndoMT-driven cancer progression and metastasis.

Asymmetry of tensile versus compressive elasticity and permeability contributes to the regulation of exchanges in collagen gels.

The Starling principle describes exchanges between blood and tissues based on the balance of hydrostatic and osmotic flows. However, the permeation properties of the main constituent of tissues, namely, collagen, in response to the stress exerted by blood pressure remain poorly characterized. Here, we develop an instrument to determine the elasticity and permeability of collagen gels under tensile and compressive stress based on measuring the temporal change in pressure in an air cavity sealed at the outlet of a collagen slab. Data analysis with an analytical model reveals a drop in the permeability and enhanced strain stiffening of native collagen gels under compression versus tension, both effects being essentially lost after chemical cross-linking. Furthermore, we report the control of the permeability of native collagen gels using sinusoidal fluid injection, an effect explained by the asymmetric response in tension and compression. We lastly suggest that blood-associated pulsations could contribute to exchanges within tissues.

Endothelial tissue remodeling induced by intraluminal pressure enhances paracellular solute transport.

The endothelial layers of the microvasculature regulate the transport of solutes to the surrounding tissues. It remains unclear how this barrier function is affected by blood flow-induced intraluminal pressure. Using a 3D microvessel model, we compare the transport of macromolecules through endothelial tissues at mechanical rest or with intraluminal pressure, and correlate these data with electron microscopy of endothelial junctions. On application of an intraluminal pressure of 100 Pa, we demonstrate that the flow through the tissue increases by 2.35 times. This increase is associated with a 25% expansion of microvessel diameter, which leads to tissue remodeling and thinning of the paracellular junctions. We recapitulate these data with the deformable monopore model, in which the increase in paracellular transport is explained by the augmentation of the diffusion rate across thinned junctions under mechanical stress. We therefore suggest that the deformation of microvasculatures contributes to regulate their barrier function.

Solute transport in the brain tissue: what are the key biophysical parameters tying in vivo and in vitro studies together?

The mechanisms of solute transport in brain tissues are still under debate. The medical relevance of this topic has put the blood-brain barrier and the mechanisms of solute transport through the brain parenchyma in the spotlight, notably in the context of brain clearance. In the last decade, the classical view of pure diffusive flow across the brain parenchyma was tested against the recent proposal of an active, convectional fluid flow model known as the glymphatic model. Experimental studies of brain transport on living humans and animals have temporal and spatial limitations to validate any of these models. Therefore, detailed microscopic observations, mostly ex vivo tissue and simplified in vitro brain models with the support from computational models, are necessary to understand transport mechanisms in brain tissues. However, standardization is lacking between these experimental approaches, which tends to limit the generality of conclusions. In this review, we provide an overview of the output and limitations of modern brain solute transport studies to search for key parameters comparable across experimental setups. We emphasize that in vitro models relying on physiological material and reproducing the biophysical setting of the brain, as well as computational/mathematical models constitute powerful solutions to understand the solute transport phenomena inside of the brain tissue. Finally, we suggest the blood-brain barrier permeability and the apparent diffusion coefficient through the brain parenchyma to be robust biophysical parameters for the extraction of cross-model conclusion.

A visual analytic approach for the identification of ICU patient subpopulations using ICD diagnostic codes.

A large number of clinical concepts are categorized under standardized formats that ease the manipulation, understanding, analysis, and exchange of information. One of the most extended codifications is the International Classification of Diseases (ICD) used for characterizing diagnoses and clinical procedures. With formatted ICD concepts, a patient profile can be described through a set of standardized and sorted attributes according to the relevance or chronology of events. This structured data is fundamental to quantify the similarity between patients and detect relevant clinical characteristics. Data visualization tools allow the representation and comprehension of data patterns, usually of a high dimensional nature, where only a partial picture can be projected. In this paper, we provide a visual analytics approach for the identification of homogeneous patient cohorts by combining custom distance metrics with a flexible dimensionality reduction technique. First we define a new metric to measure the similarity between diagnosis profiles through the concordance and relevance of events. Second we describe a variation of the Simplified Topological Abstraction of Data (STAD) dimensionality reduction technique to enhance the projection of signals preserving the global structure of data. The MIMIC-III clinical database is used for implementing the analysis into an interactive dashboard, providing a highly expressive environment for the exploration and comparison of patients groups with at least one identical diagnostic ICD code. The combination of the distance metric and STAD not only allows the identification of patterns but also provides a new layer of information to establish additional relationships between patient cohorts. The method and tool presented here add a valuable new approach for exploring heterogeneous patient populations. In addition, the distance metric described can be applied in other domains that employ ordered lists of categorical data.

Spanning Trees as Approximation of Data Structures.

The connections in a graph generate a structure that is independent of a coordinate system. This visual metaphor allows creating a more flexible representation of data than a two-dimensional scatterplot. In this article, we present STAD (Simplified Topological Abstraction of Data), a parameter-free dimensionality reduction method that projects high-dimensional data into a graph. STAD generates an abstract representation of high-dimensional data by giving each data point a location in a graph which preserves the approximate distances in the original high-dimensional space. The STAD graph is built upon the Minimum Spanning Tree (MST) to which new edges are added until the correlation between the distances from the graph and the original dataset is maximized. Additionally, STAD supports the inclusion of additional functions to focus the exploration and allow the analysis of data from new perspectives, emphasizing traits in data which otherwise would remain hidden. We demonstrate the effectiveness of our method by applying it to two real-world datasets: traffic density in Barcelona and temporal measurements of air quality in Castile and León in Spain.

Effect of aspirin on the diagnostic accuracy of the faecal immunochemical test for colorectal advanced neoplasia.

BACKGROUND: Aspirin (ASA) is a drug that can cause gastrointestinal lesions and symptoms. Colorectal cancer (CRC) is the most prevalent type of cancer in Western countries. We assessed the effect of aspirin on the diagnostic accuracy of the faecal immunochemical test (FIT) for CRC and/or advanced neoplasia (AN) in patients undergoing colonoscopy for gastrointestinal symptoms. METHODS: We conducted a prospective multicentre observational study of diagnostic tests that included patients with gastrointestinal symptoms undergoing colonoscopy between March 2012 and 2014 (the COLONPREDICT study). Symptoms were assessed and a FIT and blood tests assessing haemoglobin and carcinoembryonic antigen (CEA) levels were performed. RESULTS: The study included 3052 patients: A total of 2567 did not take aspirin (non-user group) and 485 (16%) took aspirin (user group). Continuous treatment with ASA did not change the AUC (0.88, 0.82; p = 0.06), sensitivity (92%, 88%; p = 0.5) or specificity (71%, 67%; p = 0.2) of the FIT for CRC detection. Similarly, we found no differences in the AUC (0.81, 0.79; p = 0.6), sensitivity (74%, 75.5%; p = 0.3) or specificity (76%, 73.6%; p = 0.3) for AN detection. Patients with an aspirin use of ≥ 300 mg/day had a lower prevalence of AN and the sensitivity, specificity and AUC for AN for these patients were 54%, 68% and 0.66, significantly lower than for the non-user group (p = 0.03). CONCLUSIONS: Aspirin does not modify the diagnostic accuracy of FIT for CRC and/or AN in patients with gastrointestinal symptoms. Aspirin use of ≥ 300 mg/day decreases the accuracy of the test.

MCLEAN: Multilevel Clustering Exploration As Network.

Finding useful patterns in datasets has attracted considerable interest in the field of visual analytics. One of the most common tasks is the identification and representation of clusters. However, this is non-trivial in heterogeneous datasets since the data needs to be analyzed from different perspectives. Indeed, highly variable patterns may mask underlying trends in the dataset. Dendrograms are graphical representations resulting from agglomerative hierarchical clustering and provide a framework for viewing the clustering at different levels of detail. However, dendrograms become cluttered when the dataset gets large, and the single cut of the dendrogram to demarcate different clusters can be insufficient in heterogeneous datasets. In this work, we propose a visual analytics methodology called MCLEAN that offers a general approach for guiding the user through the exploration and detection of clusters. Powered by a graph-based transformation of the relational data, it supports a scalable environment for representation of heterogeneous datasets by changing the spatialization. We thereby combine multilevel representations of the clustered dataset with community finding algorithms. Our approach entails displaying the results of the heuristics to users, providing a setting from which to start the exploration and data analysis. To evaluate our proposed approach, we conduct a qualitative user study, where participants are asked to explore a heterogeneous dataset, comparing the results obtained by MCLEAN with the dendrogram. These qualitative results reveal that MCLEAN is an effective way of aiding users in the detection of clusters in heterogeneous datasets. The proposed methodology is implemented in an R package available at https://bitbucket.org/vda-lab/mclean.

Candidate gene prioritization with Endeavour.

Genomic studies and high-throughput experiments often produce large lists of candidate genes among which only a small fraction are truly relevant to the disease, phenotype or biological process of interest. Gene prioritization tackles this problem by ranking candidate genes by profiling candidates across multiple genomic data sources and integrating this heterogeneous information into a global ranking. We describe an extended version of our gene prioritization method, Endeavour, now available for six species and integrating 75 data sources. The performance (Area Under the Curve) of Endeavour on cross-validation benchmarks using 'gold standard' gene sets varies from 88% (for human phenotypes) to 95% (for worm gene function). In addition, we have also validated our approach using a time-stamped benchmark derived from the Human Phenotype Ontology, which provides a setting close to prospective validation. With this benchmark, using 3854 novel gene-phenotype associations, we observe a performance of 82%. Altogether, our results indicate that this extended version of Endeavour efficiently prioritizes candidate genes. The Endeavour web server is freely available at https://endeavour.esat.kuleuven.be/.

Consumer's risk in the EMA and FDA regulatory approaches for bioequivalence in highly variable drugs.

The 2010 US Food and Drug Administration and European Medicines Agency regulatory approaches to establish bioequivalence in highly variable drugs are both based on linearly scaling the bioequivalence limits, both take a 'scaled average bioequivalence' approach. The present paper corroborates previous work suggesting that none of them adequately controls type I error or consumer's risk, so they result in invalid test procedures in the neighbourhood of a within-subject coefficient of variation osf 30% for the reference (R) formulation. The problem is particularly serious in the US Food and Drug Administration regulation, but it is also appreciable in the European Medicines Agency one. For the partially replicated TRR/RTR/RRT and the replicated TRTR/RTRT crossover designs, we quantify these type I error problems by means of a simulation study, discuss their possible causes and propose straightforward improvements on both regulatory procedures that improve their type I error control while maintaining an adequate power. Copyright © 2015 John Wiley & Sons, Ltd.

Overall and Cardiovascular Safety of Aclidinium Bromide in Patients With COPD: A Pooled Analysis of Six Phase III, Placebo-Controlled, Randomized Studies.

Background: Aclidinium bromide, an M3-receptor-selective, twice-daily (BID), long-acting muscarinic antagonist, is rapidly hydrolyzed in human plasma, resulting in low systemic exposure and urinary excretion. We evaluated the overall and cardiovascular (CV) safety of aclidinium in patients with moderate to severe chronic obstructive pulmonary disease (COPD) by pooling data from 6 randomized, double-blind, placebo-controlled, parallel-group studies of ≥1 month's duration. METHODS: Patients were current/former smokers aged ≥40 years with no history of clinically significant CV conditions. Treatment was administered (morning and evening) via GenuairTM/Pressair.®a Adverse events (AEs), major adverse CV events (MACE), cardiac and cerebrovascular AEs, and serious AEs (SAEs) were analyzed. Results: The pooled population included 2781 patients (aclidinium: n=1529; placebo: n=1252). The incidence of AEs was similar with aclidinium (53.5%) and placebo (55.4%), as was the incidence of cardiac (aclidinium: 5.0%; placebo: 4.4%) and cerebrovascular (aclidinium: 0.4%; placebo: 0.5%) events. The incidence of MACE was low (AEs: 0.7%; SAEs: 0.5%) and comparable between groups. The incidence of cardiac and cerebrovascular events was similar for patients with CV risk factors with aclidinium and placebo (rate ratio [RR] [95 %confidence interval (CI)]=1.01[.074, 1.39]). In patients with mild to severe renal impairment, the incidence of cardiac events was similar between groups (RR [95% CI]=0.87 [0.56, 1.36]). Conclusion: Aclidinium 400µg BID has a good safety profile and this pooled analysis found no evidence of increased CV or cerebrovascular risk compared with placebo in patients with moderate to severe COPD. Further studies are needed in high-risk patients.