Dataset Information

Screening for potential targets to reduce stenosis in bioprosthetic heart valves.

ABSTRACT: Progressive stenosis is one of the main factors that limit the lifetime of bioprosthetic valved conduits. To improve long-term performance we aimed to identify targets that inhibit pannus formation on conduit walls. From 11 explanted, obstructed, RNAlater presevered pulmonary valved conduits, we dissected the thickened conduit wall and the thin leaflet to determine gene expression-profiles using ultra deep sequencing. Differential gene expression between pannus and leaflet provided the dataset that was screened for potential targets. Promising target candidates were immunohistologically stained to see protein abundance and the expressing cell type(s). While immunostainings for DDR2 and FGFR2 remained inconclusive, EGFR, ErbB4 and FLT4 were specifically expressed in a subset of tissue macrophages, a cell type known to regulate the initiation, maintenance, and resolution of tissue repair. Taken toghether, our data suggest EGFR, ErbB4 and FLT4 as potential target candidates to limit pannus formation in bioprosthestic replacement valves.

SUBMITTER: Foth R

PROVIDER: S-EPMC7843970 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Screening for potential targets to reduce stenosis in bioprosthetic heart valves.

Foth Rudi R Shomroni Orr O Sigler Matthias M Hörer Jürgen J Cleuziou Julie J Paul Thomas T Eildermann Katja K

Scientific reports 20210128 1

Progressive stenosis is one of the main factors that limit the lifetime of bioprosthetic valved conduits. To improve long-term performance we aimed to identify targets that inhibit pannus formation on conduit walls. From 11 explanted, obstructed, RNAlater presevered pulmonary valved conduits, we dissected the thickened conduit wall and the thin leaflet to determine gene expression-profiles using ultra deep sequencing. Differential gene expression between pannus and leaflet provided the dataset t ...[more]

PMID: 33510256

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Project description:In this paper, we develop a geometrically flexible technique for computational fluid-structure interaction (FSI). The motivating application is the simulation of tri-leaflet bioprosthetic heart valve function over the complete cardiac cycle. Due to the complex motion of the heart valve leaflets, the fluid domain undergoes large deformations, including changes of topology. The proposed method directly analyzes a spline-based surface representation of the structure by immersing it into a non-boundary-fitted discretization of the surrounding fluid domain. This places our method within an emerging class of computational techniques that aim to capture geometry on non-boundary-fitted analysis meshes. We introduce the term "immersogeometric analysis" to identify this paradigm. The framework starts with an augmented Lagrangian formulation for FSI that enforces kinematic constraints with a combination of Lagrange multipliers and penalty forces. For immersed volumetric objects, we formally eliminate the multiplier field by substituting a fluid-structure interface traction, arriving at Nitsche's method for enforcing Dirichlet boundary conditions on object surfaces. For immersed thin shell structures modeled geometrically as surfaces, the tractions from opposite sides cancel due to the continuity of the background fluid solution space, leaving a penalty method. Application to a bioprosthetic heart valve, where there is a large pressure jump across the leaflets, reveals shortcomings of the penalty approach. To counteract steep pressure gradients through the structure without the conditioning problems that accompany strong penalty forces, we resurrect the Lagrange multiplier field. Further, since the fluid discretization is not tailored to the structure geometry, there is a significant error in the approximation of pressure discontinuities across the shell. This error becomes especially troublesome in residual-based stabilized methods for incompressible flow, leading to problematic compressibility at practical levels of refinement. We modify existing stabilized methods to improve performance. To evaluate the accuracy of the proposed methods, we test them on benchmark problems and compare the results with those of established boundary-fitted techniques. Finally, we simulate the coupling of the bioprosthetic heart valve and the surrounding blood flow under physiological conditions, demonstrating the effectiveness of the proposed techniques in practical computations.

Dataset Information

Screening for potential targets to reduce stenosis in bioprosthetic heart valves.

Publications

Screening for potential targets to reduce stenosis in bioprosthetic heart valves.

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