An extracellular matrix scaffold for regenerating small diameter blood vessels - fabrication parameters, microstructure and mechanotransduction in small intestinal submucosa vascular grafts

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Doctoral Dissertation

Diana M. Sánchez Palencia

An Extracellular Matrix

Scaffold for Regenerating

Small Diameter

Blood Vessels

Fabrication Parameters, Microstructure and Mechanotransduction

in Small Intestinal Submucosa Vascular Grafts

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Cover image: Scanning Electron Microscopy of a small intestinal

submucosa scaffold fabricated by preserving the stratum compactum

layer of the intestine and keeping in a hydrated state until fixation

for imaging (PH scaffold). 3000x. Taken by the author at the Center

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An Extracellular Matrix Scaffold for Regenerating Small

Diameter Blood Vessels

Fabrication Parameters, Microstructure and Mechanotransduction in Small

Intestinal Submucosa Vascular Grafts

A dissertation presented by

Diana M. S´

anchez Palencia

to the School of Engineering,

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

in the subject of

Engineering

Universidad de los Andes

Bogota, Colombia

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Approved by:

Dr. Juan Carlos Brice˜no, Advisor

Dr. Ajit Yoganathan, Coadvisor

Georgia Institute of Technology

Dr. William Wagner

University of Pittsburgh

Dr. Andr´es Gonzalez-Mancera

Dr. Juan Cordovez

Dr. Jose Luis Roa

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Acknowledgements

I would like to extend my gratitude to my advisor, Dr. Juan Carlos Brice˜no, for his

guidance and support during the development of these studies. I also thank my

coadvisor, Dr. Ajit Yoganathan, for the support and resources at the Cardiovascular

Fluid Mechanics Laboratory at the Georgia Institute of Technology. Many thanks as

well to Dr. William Wagner for the research done at the Wagner Cardiovascular

Engineering Laboratory at the McGowan Institute for Regenerative Medicine. I also

wish to express my gratitude to Dr. Nestor Sandoval and Dr. Roc´ıo L´opez for the

extensive hours they dedicated to contribute to this research. My thanks also to the

members of my committee, Dr. Andr´es Gonzalez, Dr. Juan Manuel Cordovez, Dr. Jos´e

Luis Roa, Dr. William Wagner, Dr. Ajit Yoganathan and Dr. Juan Carlos Brice˜no, for

their valuable comments and suggestions for improving this dissertation.

I also wish to acknowledge the very special and valuable support of Dr. Antonio

D’Amore, Swetha Rathan, Javier Navarro and Lina Quijano, as well as members of Dr.

Juan Carlos Brice˜no’s laboratory at the Universidad de los Andes and the Fundaci´on

Cardioinfantil Juan Camilo Araque MD, undergraduate students Juan Bernardo Uma˜na

and Alvaro Felipe Guerrero and Sergio Galvis DVM, members of Dr. Ajit Yoganathan’s,

Dr. William Wagner’s, Dr. Stephen Badylak’s, Dr. Hanjoong Jo’s and Dr. Robert

Nerem’s laboratories (Dr. Casey Ankeny and Dr. Randy Ankeny). I also thank

Professor Rigoberto G´omez for his kind assistance on the synthesis of peracetic acid for

the preparation of samples.

Last but not least, I thank my parents, family and friends for the unconditional support

that allowed me to achieve this accomplishment.

Funding to these studies was provided by Colciencias Projects 459-2008 and 464-2012,

CIFI-Universidad de los Andes Project 49-2009, CEIBA Complex Systems Research

Center - Tissue Engineering Program, the Research Department of Fundaci´on

Cardioinfantil, the American Heart Association under the Pre-doctoral Research Award

12PRE11750044 awarded to Swetha Rathan and Georgia Tech discretionary chair funds

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Chapter 1 Introduction

1.1 Cardiovascular disease

Cardiovascular disease (CVD) is the main cause of mortality in the Western World,

ac-counting for 1 out of every 3 deaths in the USA and claiming more lives each year than

cancer, chronic lower respiratory disease and accidents combined [1]. Vascular grafts are

often used in the treatment of CVD related to the lack of a functional blood vessel, such

as atherosclerosis, aneurysms and congenital heart defects, and in the construction of

vascular accesses for hemodialysis treatment in patients with renal failure.

Current options for treating vascular disease comprise the use of biological or synthetic

grafts. In the small diameter range (<5 mm), the gold standard is an autograft, primarily

the autologous internal mammary artery, and as a secondary choice the saphenous vein.

This produces a kind response from the host and often exhibits long term patency [2,3].

However, autologous grafts are scarce due to previous use in coronary artery bypass

grafting or peripheral revascularization, mismatch of the mechanical properties desired for

the final location or previous harm caused by the CVD being treated on such autologous

vessels [4,5]. Autografts also demand additional surgical harvesting procedures and do

not report high enough patency rates in applications such as vascular access (20% patency

at 2 years) [4].

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di-ameter application. Synthetic grafts made of expanded polytetrafluoroethylene (ePTFE)

or polyethylene teraphtalate fiber (commercially known as Dacron_r), have low and non

reliable patency rates in small diameter applications (patency rates between 12 to 85%

at different time periods [4,6]). Moreover, even in the large diameters, they have

lim-ited durability due to the occurrence of early or late thrombosis and increased risk of

infection [4]. Synthetic grafts also lack an ability of growing with a pediatric patient.

Nonetheless, ePTFE has been used in small vessel applications since the late 1970’s,

despite of the high incidence of occlusion and infection [4]. The use of homografts and

al-lografts has also been explored and has been found to provide better results than ePTFE,

however, they have not yet achieved the desired results [4], probably in part due to the

adverse host response to cross-linking procedures performed to preserve these materials

from degradation [7].

Hence, tissue engineering principles have been used over the last two decades in the

development of a vascular graft that features the mechanical and biological properties

necessary for successful replacement of ill blood vessels, with a similar or better outcome

than the one obtained with autografts . Within this approach, scaffolds mimicking the

functions of the extracellular matrix (ECM) have been evaluated as suitable supports for

vascular tissue remodelling, with promising but still not satisfactory results, particularly

in the small diameter range [5,8–15].

1.2 Current state of tissue engineered vascular grafts

Approaches for treating CVD with tissue engineered vascular grafts (TEVGs) include the

construction of grafts using endothelialized ePTFE, cell-culture tissue engineered, natural

extracellular matrix and biodegradable polymer materials [5,16]. Promising results have

been obtained, but there are still difficulties to face in terms of consistently satisfactory

patency rate (success rates are not high enough yet), and commercial viability when

expensive or cumbersome technologies are used [8].

Challenges in designing tissue engineered vascular grafts comprise providing: 1) a

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withstand physiological pressures, 2) anti-thrombotic properties [5], and 3) appropriate

humoral and mechanical signals [11]. In more detail, the ideal TEVG should exhibit

biomechanical properties that mimic those of native blood vessels [11], to avoid a

me-chanical mismatch that can be associated to restenosis and graft failure [3]. It should also

facilitate a rapid development of an endothelium, as this layer provides a non-thrombotic

surface and resistance to the development of pseudointimal anastomotic hyperplasia [11].

A rapid vascularization should also be achieved to provide oxygen and nutrients to the

regenerating tissue. Finally, another key attribute explored recently is the triggering of an

inflammatory response of the host in a reconstructive pathway, either than in a scarring,

foreign body response pathway, where the first stimulates cellular proliferation,

angiogen-esis, ECM remodeling and cellular regeneration, and the latter triggers inflammation and

fibrosis [10,17].

1.3 Small intestinal submucosa vascular grafts

Within tissue engineering, the use of an extracellular matrix (ECM) scaffold material has

been identified as an advantageous approach, in which the ECM provides a cell-adhesive

substrate, controls the three-dimensional (3-D) tissue structure and presents growth

fac-tors, cell-adhesion signals and mechanical signals [18]. Small intestinal submucosa (SIS)

is a natural ECM scaffold obtained from the processing (washing and disinfecting [19])

of mammal small intestine. The anatomy of the intestine comprises several distinct

tis-sue layers: from the abluminal to the luminal surface, mesenteric tistis-sues, tunica serosa,

tunica muscularis, tunica submucosa and tunica mucosa, the latter being composed of

lamina muscularis mucosa, stratum compactum, lamina propria and lamina epithelialis

mucosa [20]. For tissue remodelling applications, canine, feline and porcine sources have

shown favourable patency rates and mechanical properties, however porcine SIS is

gen-erally preferred as donor species given the ready availability of porcine intestine and the

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1.3.1 Composition of SIS

SIS composition has been extensively studied and is reported to be collagen in more

than 90%, primarily collagen type I, which is the major structural protein present in

tissues and is ubiquitous within the animal kingdom [21]. Minor amounts of collagen

types III, IV, V and VI are also present [7]. Second in content of SIS is the adhesion

molecule fibronectin, which possesses ligands for adhesion of many cell types and has

been found critical for the development of vascular structures in developing embryos

[22]. Other components of SIS are the adhesive protein laminin, glycosaminoglycans

(GAGs) including heparin, heparan sulfate, chondroitin sulfate and hyaluronic acid and

growth factors such as transforming growth factor-β(TGF-β), the fibroblast growth factor

(FGF) family and vascular endothelial growth factor (VEGF) [7]. The diverse composition

of SIS provides a complex of molecules organized in their native 3-D structure that is

advantageously suited for stimulating remodelling processes.

1.3.2 Previous results with SIS TEVGs

Badylak et al. studied in several small-diameter, arterial, canine models SIS vascular

grafts constructed with membranes that comprised the tunica submucosa, the lamina

muscularis mucosa and the stratum compactum, having the latter as the luminal surface.

The SIS source was initially autogenous and was later switched to porcine. Patency rates

up to 75% after 48 weeks were obtained in an autogenous SIS, canine left carotid and right

femoral artery (4.3 mean diameter) model [23]. In succeeding studies of this group using

porcine SIS and a canine carotid artery model (3.5-5.0 mm diameter range), patency rates

of 83% [24] and of 88% [6] up to 180 days were obtained. Huynh et al. [14] studied grafts

made of porcine SIS, where the intestine was mechanically cleaned using a commercial gut

cleaning machine and chemically processed for removing residual cells or cellular debris,

rendering as a result the acellular tunica submucosa. Two layer, 4-mm diameter grafts

studied as a canine ex vivo shunt or as an aortic graft in rabbits, produced a thrombogenic

response and 0% patency. A following modification, in which a thin (<100 µm) layer of

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a leporid carotid artery model. In summary, previous results suggest that SIS vascular

grafts are a promising option for replacing or providing new small diameter blood vessels,

but still need improvement in the variability of patency rates obtained in different studies.

1.3.3 Regeneration process

Follow-ups of the cellular and biological structures appearing during a successful

regen-eration process with SIS were reported in detail by Badylak et al. [6,24] and Hunyh et

al. [14]. The first month was characterized by being the most eventful period of time. At

2 days, findings consisted on a smooth and reddish brown lumen, a luminal compact mesh

layer of fibrin and red blood cells (RBCs) that was approximately 20 µm thick and had

numerous orifices, capillaries in the abluminal half portion, a mononuclear cell infiltrate

with neutrophils and a few non-activated platelets attached. At 4 days, fibroblasts were

identified. At day 7, there were numerous capillaries and some endothelial cells. Between

days 7 and 14, the lumen was a glistening, red-tinged smooth surface, with a lighter cream

color near the anastomoses, the cellular infiltrate was less intense, there was a moderately

dense and irregular collagenous connective tissue, a partially organized fibrin mesh with

trapped leukocytes and blood-filled spaces of 15-20 µm internal diameter, and a marked

fibroplasia in the adventitia. At day 14 it was possible to identify an endothelium and

arrangements of fibroblast sheets parallel to the lumen. Day 21 was characterized by

showing very few mononuclear cells and a lumen with fibrocytes, and by SIS being

undis-tinguishable from neocollagenous tissue. The initial fibrin mesh was no longer discernible

at day 28, when the presence of a new intima with endothelial cells parallel to blood flow

was observed and smooth muscle cells (SMCs) were found to be forming a new media.

At this point there was also a dense fibrosis in the adventitia.

Between the second and the third month, a white, glistening surface on 50-70% of

the lumen was observed, where the remaining surface was light red but smooth. Reddish

areas had less organized collagen bundles and were RBC rich. An endothelium, a

promi-nent SMCs-media and a fibrotic adventitia were present. There was also an organized

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was around 600µm.

At the fourth month more than 90% of the lumen was white and glistening, and

indis-tinguishable from the adjacent vessel. There was an organized arrangement of collagen

fibers. At months 6 to 7 regeneration was practically complete, with a rich capillary

and arteriolar network found especially in the adventitial half, and no increase in intimal

thickness. At month 10, more than 98% of the lumen was white and glistening.

1.4 Regeneration pathway or scarring pathway

The type of host response triggered by a biomaterial can consist of processes that lead

either to the regeneration of the tissue or, on the contrary, to the isolation of the

ma-terial with scarring tissue. A methodology to characterize and quantify this has been

designed and validated by Badylak and colleagues [17], where each group is classified

into one of four possible scores. A lower score indicates a response that leans towards a

scarring pathway, while a higher score indicates a response leaning towards a regenerative

pathway. Scoring criteria comprise cellular infiltration, the presence of multinucleated

giant cells, vascularity, connective tissue organization, encapsulation, test article

degra-dation and muscle tissue ingrowth. Another recent criterion used for characterizing the

host response pathway consists on the determination of the macrophage differentiation

phenotype during the early response to the biomaterial. It has been found that grafts

involve a monocyte migration to the material immediately after implantation, followed

by a differentiation into macrophages of either the M-1 or the M-2 phenotype [10]. M-1

phenotype macrophages have been associated to the inflammatory pathway that leads to

inflammation and fibrosis, while M-2 macrophages have been identified to be of an

anti-inflammatory phenotype that triggers regenerative processes [10,17,25]. Thus, the ratios

between M-0 (undifferentiated), M-2 and M-1 phenotype macrophages are currently been

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1.5 Mechanotransduction, micromechanical

environ-ment and phenotype control

An approach for exploring the impact of the specific characteristics of a biomaterial on

patency outcome and tissue regeneration, is understanding the relationship between

scaf-fold structure and function in terms of mechanotransduction. Mechanotransduction is the

process by which mechanical signals are transduced into changes in cellular biochemistry

and gene expression [26]. As such, interest is on unrevealing the role of micromechanical

forces in guiding cell and tissue development [26], and finding a way of controlling them to

provide appropriate physical cues. In the case of ECM scaffolds for tissue engineering, the

possibility of achieving such control would lie on understanding the final microstructural

organization of collagen fibers obtained after fabrication of the scaffold, and finding a way

of inducing an organization that is favorable for the regeneration of the tissue of interest.

Several groups have worked on understanding the effects of the different types of

mechanical forces in play at the microstructural scale. Forces can be transmitted from

the ECM to cells, between adjacent cells, from cells to the ECM and from blood flow to

cells. Forces from the ECM to cells are caused, in the case of blood vessels, by blood

pressure, which generates circumferential stresses and strains on the vessel wall [27] and

can be cyclic due to blood pulsatility. Forces between adjacent cells are transduced in the

form of interactions in their membrane junctions [28]. Forces applied by cells to the ECM

originate as they accomodate their geometry and cytoskeleton (CSK) to the substrate to

which they are attached to. Finally, blood flow applies drag (or shear) forces on the inner

surface of blood vessels. It has been well documented that forces between ECM and cells

are applied at adhesion sites such as focal adhesions, complexes in cell-ECM adhesions

that include integrins, among other molecules [29–31]. Focal adhesions are formed from

focal complexes, integrin-containing structures of around 100 nm diameter [29]. Integrins

are transmembrane receptors that bind actin-associated proteins inside the cell and often

mediate mechanotransduction [29,32,33]. The magnitude of these forces, applied at

cell-ECM adhesions or intercellular junctions, ranges in the nN to the pN scale [33–35].

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been found to affect cellular behavior in terms of gene and protein expression [27,36].

There are numerous studies that have explored these alterations, and only some will be

mentioned here to exemplify the characteristics of these responses.

Studies exploring the impact of exercise on endothelial cell phenotype, related to

behavior and gene expression, have provided information about the impact of mechanical

forces on ECs [37]. Investigators have reported that cyclic strain caused by blood pressure

alters EC gene expression patterns, where this can be in an anti-atherogenic or a

pro-atherogenic way. They have also reported that the major effect of rhythmic circumferential

strain on ECs apppears to cause pro-atherogenic effects (such as an increase in reactive

oxygen species an monocyte adhesion) to override anti-atherogenic effects (such as increase

in endothelial nitric oxyde synthase and other vasodilators) [37].

Other phenotypic responses have been observed as a consequence of mechanical

mis-match in vascular grafting. When the graft is more compliant than the native vessel,

consequent geometry mismatches due to difference in stretching might originate disturbed

and potentially atherogenic flow, triggering the development of neointimal hyperplasia in

the anastomosis [38]. The disturbed atherogenic flow is also related to an observed

polyg-onal morphology of ECs, instead of an elongated morphology in the direction of blood

flow as seen in nonatherogenic areas.

Some other studies have explored how stem cell differentiation for tissue engineering

therapies is influenced by the 3D stem cell niche [36]. It has been observed that cells

detect the composition, stiffness and geometry of the scaffold, which overall dictates the

phenotype in which stem cells become differentiated. Yang and colleagues [33] studied

how the elasticity of the substrate influenced stem cell differentiation. They observed

that mechanical properties of adhesion substrates modulate stem cell fate in terms of

activities, growth and elongation of focal adhesion proteins, which can undergo

tension-dependent conformational changes. Their work explored how cells sense ECM elasticity,

and indicated that integrin-ligand complexes were more easily ruptured on soft substrates

than in stiff substrates (rupture forces were calculated to be 37 pN in soft substrates and

95 pN in stiff substrates). Integrins also became more internalized where stem cells were

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neural lineage differentiation. As a conclusion, they observed that expression of genes and

phosphorylation of proteins depended on the stiffness of the substrate.

An extensive review from Engler and colleagues [39] also describes multiple studies

showing how mesenchymal stem cells specify lineage and commit to phenotypes with

extreme sensitivity to tissue-level elasticity, where soft substrates that mimic brain induce

a neurogenic phenotype, stiffer substrates that mimic muscle induce a myogenic phenotype

and rigid substrates that mimic bone induce a osteogenic phenotype. A similar review by

DuFort et al. [28] collects further evidence on how perturbations in mechanotransduction,

from the nanoscale-level to the tissue-level, cause conformational changes on proteins

within focal adhesions in response to pN forces (e.g., the protein talin undergoes

force-dependent unfolding). Other strain-based mechanisms change intermolecular distances

that ultimately lead to altered cellular function. These perturbations also compromise

tensional homeostasis of cells to promote pathologies such as cardiovascular disease or

cancer.

Impact of substrate elasticity was also studied on growth and apoptosis on NIH 3T3

cells by Wang and colleagues [40], who found more apoptosis and decreased DNA synthesis

rate in cells seeded on more flexible substrates. They were also able to measure the

traction counterforces applied by cells on to the substrate, which were in the range of

10-15 kdyn/cm2_{, by measuring the deformation of the substrate due to cell-generated stresses}

and using the Young’s modulus of the substrate. A similar study by Hur and colleagues

[35] also explored cell-cell junctions and intracellular tensions (defined therein as force

per unit length), which were found to be around 3,000 pN/µm and 100-1500 pN/µm,

respectively. These tensions were found to be dependant on shear stress direction and

magnitude, and were associated to a possible modulation of translation and transcription

of ECs under different flow patterns, having a final effect on susceptibility to atherogenesis.

Regarding forces from blood flow, which are originated in the shear stress caused by

flow at the vascular wall, Chien and colleagues have produced extensive studies,

particu-larly on the response of endothelial cells (ECs) to mechanotransduction and shear. They

have found that ECs respond to forces by altering their geometry to minimize alterations

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the perpendicular direction of applied uniaxial stretch, probably in an effort to decrease

intracellular stress or, in other words, to reduce the stretch-induced increase in

intracel-lular mechanical energy generated by uniaxial stretch [27]. This orientation of the CSK

was not observed in biaxial stretch. These researchers also observed in this study that

cyclic stretch without a clear direction could cause a higher frequency of apoptosis.

1.6 Fabrication

In section 1.3.2, a description of the large variability observed in previous studies with SIS

vascular grafts was made. Bearing in mind the concept of mechanotransduction described

above, it becomes clear that one possible explanation for such a large variability in patency

could be the use of different scaffold fabrication techniques among independent studies.

Apparently, ECM scaffolds do not always provide the same beneficial microenvironment

if the fabrication technique is changed. Between the mentioned studies, parameters such

as luminal surface modification treatments [14], hydration state of the scaffold [6,7],

decellularization method [15,19], number of layers of the material used in the construction

of the graft [6] and source species (i.e. autograft or xenograft) [6,14] greatly vary. Out

of these parameters, the results strongly indicate that luminal surface modifications and

hydration state could correlate to patency outcome. In terms of surface modifications,

there were differences in patency rates when the grafts had a dense collagen luminal

layer such as the stratum compactum (which could be preserved or removed) [15,23] or

a deposited thin luminal layer of dense bovine collagen [14]. Those grafts with a dense

collagen luminal layer exhibited patency up to 88-100%, opposed to a 0-13% range in its

absence [14,15,23]. On the other side, a study on hydration state with human dermal

microvascular endothelial cells adhesionin vitro, reported that hydrated scaffolds showed a 3-fold increase in adhesion [41] when compared to the dehydrated counterparts, which

could lead to a better patency rate if there is an increased adhesion of endothelial cells.

Thus, it would seem that exploration of these two fabrication parameters could provide

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1.7 Hypothesis

In view of the previous ideas, the hypothesis tested in this study stated thatfabrication

parameters, particularly 1) the preservation or removal of the dense collagen layer

nat-urally present in SIS, and 2) hydration state, have an effect on:

1. Microstructural organization of collagen fibers, measured quantitatively in terms of

anisotropy in the alignment of collagen fibers and void area, and compared using two-way

ANOVA.

2. Mechanical properties, measured quantitatively in terms of anisotropy in

compli-ance, and compared using two-way ANOVA.

3. Micromechanical environment, calculated theoretically using a multi-layer

consti-tutive model that integrates microstructural and mechanical anisotropy.

4. Mechanotransduction, measured quantitatively with the expression of two

mechanosen-sory genes, and compared using two-way ANOVA.

5. Patency outcome, observed macroscopically as complete occlusion or presence of

flow, and compared as percentage success rate.

6. Regeneration outcome, measured quantitatively in terms of thrombogenicity,

in-flammatory response, vascularization, scaffold population and macrophage phenotype,

and compared using a classification into four possible scores.

Effects which cause the differently fabricated SIS scaffolds to have statistically

signif-icant - or biologically relevant - differences between them.

1.8 Experimental design

To test this hypothesis, four differently fabricated SIS scaffolds were obtained according

to a two-factor, two-level factorial experimental design, as shown in Table 1.1, where the

first factor is the preservation or removal of the dense collagen layer naturally present in

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of the scaffold. In this design, a sample size of n=4 provided a statistical power of 0.738,

a sample size of n=5 a power of 0.8432 and a sample size of n=6 a power of 0.9088.

These sample sizes were chosen depending on the test performed and in view of ethical

considerations (for example, larger sample size for mechanical testing and smaller sample

size for in vivo testing).

Table 1.1: Fabrication parameters used to obtain four differently fabricated SIS scaffolds.

Scaffold Fabrication parameters

PD Preserved dense collagen luminal layer and dehydrated RD Removed dense collagen luminal layer and dehydrated PH Preserved dense collagen luminal layer and hydrated RH Removed dense collagen luminal layer and hydrated

1.9 Specific aims

1.9.1 SA1: Effects of fabrication parameters on the

microme-chanical environment

To explore if fabrication parameters alter the micromechanical environment

of four differently fabricated SIS scaffolds.

SA1 was to explore the first three statements of the hypothesis, regarding the impact

of fabrication parameters on: microstructural alignment of collagen fibers, mechanical

properties and mechanotransduction.

To analyze the microstructural organization of collagen fibers, quantitative

measure-ments of the anisotropy in the alignment of collagen fibers and void area were performed

using scanning electron microscopy (SEM) and digital image analysis. SEM images at

3000 magnifications were obtained along the thickness of the material, in fifteen en face

sections of each of the SIS samples. A detection of the collagen fibers in each section was

performed by using an image analysis algorythm previously developed and validated by

D’Amore et. al [42]. The detection of the fibers allowed the measurement of their angles

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was measured by thresholding and converting to black and white the same images, and

quantifying the percentage area in these images without fibers.

Mechanical properties were measured quantitatively in terms of anisotropy in

com-pliance by using biaxial mechanical testing. Five protocols of biaxial stress states in

the preferential and cross-preferential directions were used to explore a wide range of

the material strain space. The mechanical anisotropy of the scaffolds was calculated by

using an anisotropy ratio, AR, defined as the ratio of the maximum stretches in the

cross-preferential direction over those in the preferential direction.

Mechanotransduction was explored theoretically for a scaffold subject to an

equib-iaxial load, using a multi-layer constitutive model that integrated microstructural and

mechanical anisotropy using the mathematical correlation between OI and AR. Using

this correlation, the mechanical anisotropy of each of the fifteen layers analyzed in their

microstructure was estimated. The loads applied in each of the layers, onto the area

that a cell would occupy, were calculated afterwards. This final result was a theoretical

estimation of the micromechanical environment provided by these scaffolds to cells, and

constituted the basis of the discussion on mechanotransduction in SIS grafts.

1.9.2 SA2: Effects of fabrication parameters on

mechanotrans-duction in an

in vitro

model

To explore if fabrication parameters that might have altered the

microical environment of four differently fabricated SIS scaffolds also alter

mechan-otransduction.

SA2 was to explore the fourth statement of the hypothesis, regarding the impact of

fabrication parameters on mechanotransduction, measured quantitatively with the

ex-pression of two mechanosensory genes.

To induce the expression of mechanosensory genes by cells populating the SIS

scaf-folds, human umbilical vein ECs (HUVECs) were seeded on the scaffolds and exposed

to a mechanical stimulus (a pulsatile shear stress) in a cone-and-plate flow system. The

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im-munofluorescence and qPCR.

1.9.3 SA3: Effects of fabrication parameters on patency and

regeneration outcome in an early response

in vivo

model

To perform animal studies with four differently manufactured SIS vascular

grafts and determine which fabrication parameters are best in terms of the

ini-tial response of the host to the graft, classified either in the anti-inflammatory

and constructive regenerative pathway or in the inflammatory and scarring

pathway.

SA3 was to explore the fifth and sixth statements of the hypothesis, regarding patency

outcome and regeneration outcome in an in vivo model.

A short-term, porcine carotid artery model was used in order to explore the differences

in the early response of an in vivo environemnt to the SIS materials. The four scaffolds

were randomly implanted for seven days as an interpositional graft in the left or right

external carotid artery of 25 kg Yorkshire swine1_{. Criteria for classifying the response of}

the host in the constructive regenerative pathway or the inflammatory and scarring

path-way comprised qualifying, with a four-score classification methodology, thrombogenicity,

inflammatory reaction, vascularization, population of the scaffold and macrophage

phe-notype.

1_{For simplicity of the model, an interpositional graft with an end-to-end anastomosis was selected;}

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Chapter 2 Specimen preparation

All specimens were prepared from the jejunum portion of small intestines harvested from

market weight pigs within 10 minutes of euthanasia. The tissues were immediately placed

in 0.9% saline solution and kept at 4. Fabrication of SIS in which the dense collagen

luminal layer was preserved (P scaffolds) was performed according to the methods

de-scribed previously by Badylak and colleagues [41,45]. Briefly, intestinal contents were

rinsed and the intestine was split open longitudinally to form a rectangular membrane,

with its longitudinal axis parallel to the longitudinal direction of the intestine. The tunica

mucosa, muscularis externa and tunica serosa layers were removed by mechanical

scrap-ing. The remaining tissue was comprised of the stratum compactum, muscularis mucosa

and submucosa layers. The tissue was then desinfected with a 0.1% peracetic acid solution

(Sigma Aldrich, St. Louis, MO) and rinsed thoroughly in phosphate buffered saline (PBS,

pH=7.0) and type I water. SIS in which the dense collagen luminal layer was removed

(R scaffolds) was also fabricated by rinsing the intestinal contents and removing the

tu-nica mucosa, muscularis externa and tutu-nica serosa layers mechatu-nically, but by disinfecting

with a proprietary sodium hypochlorite and hydrogen peroxide solution (both from Sigma

Aldrich) that removes the stratum compactum, followed by washes with PBS and

dis-tilled water. It should be noted that both disinfection procedures had a sterilization effect

on the samples. After disinfection and rinsing procedures, SIS materials were stored in

autoclaved type I water at 4until use. Samples that were used in a hydrated state (H

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obtained by air drying the hydrated SIS material at least for one hour in a laminar flow

hood, and re-sterilizing with ethylene oxide. The face of the SIS membranes that was

closest to the previous luminal surface of the intestine (i.e. the face closest to the tunica

mucosa) was designated and marked as the luminal surface.

Differences in luminal collagen density were verified with H&E staining of cross

sec-tions at a 10x magnification, and consisted in a well-defined, dense collagen layer lining

in P scaffolds (preserved dense collagen luminal layer, Fig. 2.1A), whereas R scaffolds

(removed dense collagen luminal layer) had loose collagen fibers on the surface (Fig.

2.1B). Microscopical differences between hydrated (H) and dehydrated (D) scaffolds were

observed using scanning electron microscopy and are shown in Figure 2.1C and D,

re-spectively. H scaffolds were observed to have fiber bundles with empty spaces between

the bundles, while D scaffolds were composed of densely compacted fibers without empty

spaces between them. The average thickness in each group was: PD, 42±6µm; RD, 33±3

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Figure 2.1: A. H&E staining representative image of small intestinal submucosa (SIS) where the stratum compactum was preserved (10x). B. H&E of SIS after removal of the stratum compactum (10x). C. Hydrated SIS. D. Dehydrated SIS.

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Chapter 3 SA1: Effects of fabrication

parameters on the micromechanical

environment

3.1 Overall experimental design

Four differently fabricated SIS scaffolds were obtained according to a factor,

two-level factorial experimental design, as indicated in the introduction and recalled here in

Table 3.1. Scanning electron microscopy (SEM) and digital image analysis were used to

obtain images at 3000 magnifications along the thickness of the material, and to evaluate

the microstructural anisotropy of 15 layers of the SIS samples as well as void areas.

Microstructural anisotropy was quantified by using an orientation index, OI, defined as

the average of the square cosines of the angles of orientation of the fibers [42–44]. Then,

biaxial mechanical testing was used to evaluate mechanical anisotropy using an anisotropy

ratio, AR, defined as the ratio between the maximum stretches in the cross-preferential

and preferential directions. Finally, the correlation between OI and AR was used to

predict variations in the loading states to which a cell would be subject in each of the 15

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Table 3.1: Groups.

Scaffold Fabrication parameters

PD Preserved dense collagen luminal layer and dehydrated RD Removed dense collagen luminal layer and dehydrated PH Preserved dense collagen luminal layer and hydrated RH Removed dense collagen luminal layer and hydrated

3.2 Methods

3.2.1 Microstructural analysis

For imaging, SIS membranes (n=4) were cut into 1.0 x 0.5 cm portions, fixed in 10%

formalin, dehydrated through graded alcohols (70%-100%), cleared in xylene, infiltrated

with paraffin and embedded in paraffin blocks. En fauce slices were cut continuously from the blocks with a microtome, starting on the luminal surface and moving towards

the abluminal surface. To compare the microstructure of the four SIS scaffolds, 15 slices

were obtained from each sample, assuming that the scaffolds were composed of 15 layers

that were either far apart in the hydrated samples or close together in the dehydrated

samples. This specific number of layers was chosen in consideration of microtome cutting

resolution and the thickness of the dehydrated samples (which were the thinnest). A

preliminary observation with SEM also showed that SIS is a material naturally arranged

in layers (Fig. 3.1), which validated our assumption of a material composed by layers.

The slices were then mounted on glass slides and deparaffinized by melting 1 hour at

60°C, exposing for 10 minutes to xylene, then rinsing in graded alcohols (100%-95%) and

ending in water. For imaging, the slides were sputter coated with a Pd/Au 3.5 nm layer,

attached with double sided copper tape and silver paste to a metallic sample holder,

and imaged with an scanning electron microscope (SEM) (JEOL JSM6330F) at a 3000x

magnification.

The anisotropy of the microstructure was evaluated by analysing at least six SEM

images per group and layer, with a custom image analysis algorithm previously developed

and described by D’Amore et al. [42]. Briefly, the algorythm performed a series of

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Figure 3.1: Scanning electron microscopy of a small intestinal submucosa scaffold showing the natural arrangement in layers. A) Side view (3000x), B) Top view (3000x).

identify fibers. Automatic local thresholding was used to separate the outer fiber network

from the background on sub-images with an image length equal to 10 times a

represen-tative fiber diameter (RFD) that was manually identified by the operator. A sequence

of morphological operations consisting of erosion, elimination of pixel areas smaller than

200xRFD, dilation and an additional erosion served to refine the image, highlighting fiber

edges and eliminating isolated pixel areas. These procedures allowed identifying the main

direction of alignment of the fibers that composed the scaffold. Comparison between the

groups was performed by using a known fiber orientation index [42–44], the average over

all fiber segments ofcos2_θ _{(OI), where}_θ _{represents the angle between a fiber segment and}

the main direction of alignment. Notice that an OI equal to 0.5 indicated that the fibers

had an isotropic distribution whereas an OI equal to 1.0 indicated anisotropy (i.e. all the

fibers oriented in the same direction).

In order to calculate void spaces in each of the materials, a second image analysis was

performed in Matlab (The Mathworks, Inc., Natick, MA) using the “im2bw” function, in

which all the images of each group were manually thresholded and converted to black and

white. In the thresholded images, collagen fibers were white and void spaces were black.

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area.

3.2.2 Biaxial mechanical testing

Biaxial mechanical testing was performed on a biaxial testing device described

else-where [46]. Briefly, square 10x10 mm samples (n=6) were mounted to pivoting carriages

using hooks attached to 3-0 suture lines set up in loops that encircled two small pulleys.

The pulleys and the pivoting carriages assured that forces were evenly distributed in the

lines and along the sides. The sides of the samples were aligned to the longitudinal and

circumferential directions of the intestine, which are known to be the preferential and

cross-preferential directions of SIS, respectively [46–48]. These same directions were used

for labelling the results in the analysis. The samples, hooks and pulleys were immersed

in a water bath to rehydrate the dehydrated samples [41] and maintain hydration of all

samples during testing. Tests were stress-controlled adopting a 500 kPa maximum stress

level, which was determined by using the thin-wall theory for stresses on a cylindrical

pressurized vessel [46]:

σC =

P r t

whereP is a pressure equal to 200 mmHg (chosen as the highest physiological pressure that a vascular graft would be subject to),r is a 2.5 mm radius andt is a 130µm average thickness. Five stress ratio protocols were performed continuously on each sample with

longitudinal to circumferential stress ratios (σL:σC) of 250:500, 375:500, 500:500, 500:375

and 500:250 kPa, to characterize the mechanical behavior of the materials in a wide range

of the strain space. Loads were monitored with two load cells (1mN/0.1 g resolution) and

stretches λ (λ=(final length)/(initial length)) were determined by digitally calculating

the centroid of four black markers affixed to the surface of the sample. Measurements of

the marker positions were taken first with the specimen floating free in the bath with the

hooks attached to the sample, in order to zero the loads applied by the hooks. Next, a 0.5

g tare load was applied and the position of the markers was recorded again. A

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accommodate the sample in the testing device and take a final measurement of the initial

position of the markers, to be used in the subsequent mechanical testing and analyses.

Analysis of biaxial testing results was done by calculating an anisotropy ratio (AR)

previously used in the field to compare biomaterials [49,50], defined as the ratio of the

maximum circumferential stretch to the maximum longitudinal stretch (λC/λL).

3.2.3 Multi-layer constitutive model

The microstructural and mechanical characterizations were integrated to formulate

con-stitutive models of the scaffolds, with the purpose of estimating the loading states in

each of the analyzed layers. These loading states served as the basis for the discussion on

possible differences in the micromechanical environment between the layers, expected as a

consequence of the variations in OI. Such differences in the micromechanical environment

were of interest as they could potentially affect the mechanotransduction of physiological

loads to cells attached to the scaffold in the in vivo setting.

The procedure to calculate these loads is illustrated in Figure 3.2, and comprised a

series of steps as follows. First, the ARs were calculated as a function of the OIs found for

each layer in the microstructural analysis, using a correlation of AR vs. OI based on the

mean experimental data obtained of these two indexes (first step in Fig. 3.2, see results

for details on this correlation). Next, based on the general behavior observed

experimen-tally (see biaxial mechanical testing results), an assumption that the mechanical behavior

of the preferential (i.e. the longitudinal) direction stays constant, and that mechanical

anisotropy changes are due to variations in the behavior of the cross-preferential (i.e. the

circumferential) direction was made. With this assumption, the variating circumferential

stretches of each of the n layers were estimated by supposing a situation in which the

stresses were equal in all the anisotropically different layers (second step in Fig. 3.2). This

estimation produced different stretch values for each layer in view of their anisotropy or,

in other words, as an effect of applying the same strain energy to a stiffer or a more

compliant material. The stretches were calculated by using the estimated ARs, the m

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Equa-Figure 3.2: Flow chart of the main steps followed to calculate the loads applied onto the area of attachment of a cell, in each of the layers comprising an SIS scaffold (see text for an explanation of each step).

tions 3.1 and 3.2. In Eq. 3.1,λCji is the calculated stretch value of the ith layer at the jth

experimental point, experienced by the layer when it is supposed to be subject to the jth

experimental stress value, andλCj is the experimentally measured jth stretch value of the

entire scaffold. In Eq. 3.2,ARi is the calculated AR value of the ith layer and ARaverage

is the experimental mean AR value of the entire scaffold. Note that Eq. 3.1 adjusts the

experimental strain values at the m experimental stress values for each layer, using the

”normalizing”βi factor, and thus estimates a stress-stretch curve for each of the n layers

of the scaffold.

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βi =ARi/ARaverage (3.2)

Next, the estimated stress-stretch curves of each of the layers were used to calculate

the material constants in the Yeoh constitutive model, a model that was found to closely

represent the behavior of SIS [51] (third step in Fig. 3.2, see results). The Yeoh model

(Eq. 3.3) is a hyperelastic constitutive model that calculates the strain energy in terms

of the first invariant (Eq. 3.4) and three material constants C10, C20 and C30 [52,53].

The equibiaxial stresses for this model were calculated using Eq. 3.5 [53], where B is the

direction of interest1 or 2,1 for the longitudinal direction and 2 for the circumferential direction. Calculating the partial derivative∂W/∂I1 and substituting forI1, a least mean

squares fitting algorithm was used to solve them equations of the n layers, to find the n

sets of material constants, using Eq. 3.6.

W =C10(I1−3) +C20(I1−3)2+C30(I1−3)3 (3.3)

I1 =λ21+λ 2

2 (3.4)

σB = 2(λB−λ−5B )

∂W ∂I1

+λ2_B∂W ∂I2

(3.5)

σBji = 2(λBj −λ−5Bj)

C10i + 2C20i(λ21j+λ22j −3) +C30i(λ21j +λ22j−3)2

(3.6)

Once the material constants were obtained for all the layers, a calculation of stresses

on the layers was performed using the correspondent set of material constants and the

experimental stretches. This time, the formulation was based on the experimental setting,

in which all the layers were subject to the same stretch (all the layers were attached to the

same hook in the biaxial testing machine, and thus subject to the same stretch) and so,

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(fourth step in Fig. 3.2).

Finally, the loads on the area of attachment of a cell were calculated, in order to

contextualize the importance of the differences in the stress states in each layer with

mechanotransduction and the characterization of the microenvironment. Assuming that

the entire surface of the cell in contact with the scaffold would be attached to it, and

assuming that the depth of this contact was the diameter of focal complexes (the early

structures from where focal adhesions are formed, and that provide attachment of the cells

to ECM), the area of attachment used for this calculation was 10µm wide (the diameter

of the cell) and 100 nm thick (the diameter of a focal complex [29–31]) (fifth step in

Fig. 3.2, focal complexes are illustrated here as yellow rectangles). These calculations

corresponded to the different circumferential forces that were to be applied to the cells

attached to anisotropically different layers within the scaffold (last step of Fig. 3.2).

All the calculations described in this section were performed in a custom-made

algo-rithm implemented in Matlab that is included in the Appendix. The inputs provided to

the algorithm are listed next.

Inputs:

1. Experimental equibiaxial stresses and correspondent stretches

2. OI values of each layer

3. ARaverage value

4. The equation for AR as a function of OI

5. Width and thickness of the area of interest (e.g. cell diameter and focal complex

diameter)

Outputs:

1. ARi and βi for each layer

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3. r2 _and _{RM S} _{values of the fitting results (RMS between calculated stresses and}

experimental mean stresses, which should be equal, see second step of Fig. 3.2)

4. Stress-stretch curves for each layer used for fitting to the Yeoh Model

5. Material constants C10i, C20i and C30i for each layer

6. Stress-stretch curves for each layer calculated with the experimental stretches and

the material constants

7. Forces in the layers

8. Differences in forces between layers at a stress state of 500 kPa

3.2.4 Statistical analysis

All data is reported as mean±standard error of the mean. One-way analysis of variance

(ANOVA) was used to determine differences between the groups, with p<0.05 considered

to be significant.

3.3 Results

3.3.1 Microstructural evaluation

En fauce sections sliced along the thickness of the material and imaged with SEM al-lowed a clear detection of collagen fibers with our image analysis algorithm. Examples

of the scanned samples are shown in Figure 3.3 with results of the image analysis. OIs

calculated along the thickness of the material are shown in Figure 3.4. Values of OI were

spread in a broader range in the dehydrated scaffolds, suggesting that the process of

de-hydration provided freedom to the fibers in each layer to re-accommodate into a wider

variety of anisotropy arrangements. This meant that the layers in D scaffolds were more

heterogeneous than in H scaffolds, although D scaffolds ranged around a higher OI. There

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Figure 3.3: Representative scanning electron microscopy (SEM) images (A, C, 3000x) and corresponding fiber detection (B, D). A) and B) show a hydrated scaffold, C) and D) show a dehydrated scaffold.

As mentioned in Chapter 2, SEM imaging also showed strong differences in fiber

organization between hydrated and dehydrated scaffolds, in terms of the arrangement

into bundles in H grafts. The quantification of the void space area indicated that PD

scaffolds had a 12.31 ± 1.07% void area (n=106), RD 10.82 ± 0.85% (n=86), PH 38.47 ± 1.15% (n=154) and RH 17.29 ± 0.86% (n=131) (Fig. 3.6). All the percentage void

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Figure 3.4: Orientation index in the four scaffolds, for the 15 layers sectioned along the thickness of the material, starting from the luminal surface and moving towards the abluminal surface (as illustrated in the left panel). Mean and SE for each layer, the red dashed line represents the mean of all the layers.

PD RD PH RH

0.5 0.6 0.7 0.8 0.9

Scaffold

O

ri

en

ta

ti

o

n

In

d

ex

*

#

Figure 3.5: Mean orientation index (OI) in the four scaffolds. PD was significantly dif-ferent from PH (*p<0.05) and RH (#p<0.01).

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Figure 3.6: Percentage void space area of the four scaffolds. All the percentage void areas were significantly different from each other except for PD from RD. ***p<0.0001 for PD vs. PH, RD vs. PH and PH vs. RH. #p<0.01 for PD vs. RH. †p<0.001 for RD vs. RH.

3.3.2 Biaxial mechanical testing

AR values indicated that SIS had a more compliant behavior in the circumferential

di-rection than in the longitudinal didi-rection in all protocols (except for PH in 500:250 kPa).

This confirmed that the longitudinal direction is the macroscopic preferential direction

of SIS, as found previously by others [46–48]. The stretch response in the longitudinal

direction was similar between groups, while the response in the circumferential direction

changed more drastically. This finding was the basis of the assumption for stretch

cal-culations in the constitutive model mentioned previously. Also, a more linear response

and a stiffer behavior was seen in the dehydrated samples, as shown in Figure 3.7 for the

equibiaxial protocol.

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Figure 3.7: Equibiaxial testing protocol for (A) PD scaffolds, (B) RD scaffolds, (C) PH scaffolds and (D) RH scaffolds. H scaffolds exhibited a more compliant behavior in the circumferential direction compared to D scaffolds, where the latter also had a more linear behavior.

the groups exhibited a different anisotropical response depending on the loading protocol,

with the AR varying between 0.95 and 1.30. PD and RD grafts had similar AR values

in all the protocols, while PH and RH were very different when compared to the other

scaffolds. The strongest dependency on the loading protocol was seen for PH scaffolds,

which had an AR of 1.3 in the 250:500 kPa protocol and an AR of 0.95 in the inverse

500:250 kPa protocol. At 500:250 kPa PD, RD and RH had an AR around 1.02 and PH

a value of 0.95. At 500:500 kPa, the equibiaxial protocol, PH and RH showed a similar

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AR was significantly different in the equibiaxial protocol between PD and PH (p=0.001),

PD and RH (p=0.007), RD and PH (p=0.0003) and RD and RH (p=0.002), which means

that at a 500:500 kPa stress state the AR was significantly different between hydrated

and dehydrated samples (Fig.3.9).

Figure 3.8: Anisotropy ratio in the five loading protocols used for evaluating the four scaffolds. All the groups exhibited different anisotropical responses depending on the loading stress ratio.

PD RD PH RH

0.9 1.0 1.1 1.2 1.3

Scaffold

A

n

is

o

tr

o

p

y

R

at

io

**

#

Figure 3.9: Anisotropy ratio (AR) of the four scaffolds when subject to the equibiaxial stress protocol. AR was significantly different between hydrated and deydrated scaffolds. **p<0.001 for PD vs. PH and RD vs. PH, #p<0.01 for PD vs. RH and RD vs. RH.

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Figure 3.10: Correlations between AR and OI, where the scaffolds were separated in two populations, one population of hydrated scaffolds and another population of dehydrated scaffolds.

3.3.3 Constitutive model

The finding that the AR at an equibiaxial stress state was significantly different between

hydrated and dehydrated samples, suggested that the hydration state fabrication

param-eter separated the SIS groups into two different populations of anisotropy, where the AR

was higher in the hydrated group and lower in the dehydrated group. In order to relate

the findings of the microstructural characterization with the mechanical characterization,

two separate correlations were performed to estimate ARs in function of OIs. In these

correlations, a higher OI corresponded to a higher AR. The dehydrated scaffolds were

characterized by one relationship AR=f(OI), and the hydrated scaffolds were

character-ized by a different relationship AR=g(OI). The two correlations are shown in Figure 3.10.

When a linear regression of all the AR vs. OI data (without separating into two

populations) was made, surprisingly, an inversely proportional relationship between the

two variables was found, where a higher OI corresponded to a lower AR (r2 = 0.65, Fig.

3.11). This inverse behavior was probably related to the loading state in which the two

indexes were measured and is analyzed in more detail in the Discussion.

The material constants in the constitutive model estimated for each of the layers are

shown in Table 3.2, with r2 and RMS values of the fits. Material constants C10 were

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0.5 0.6 0.7 0.8 0.9 0.9

1.0 1.1 1.2 1.3

Orientation Index

A

n

is

o

tr

o

p

y

R

at

io

PD RD

PH RH

Figure 3.11: Correlation between AR and OI with the data of the four scaffolds (r2 = 0.65), that showed an unexpected inversely proportional relation between the two indexes.

magnitude, C10 was generally higher in R grafts than in P grafts, indicating a stiffer

behavior in the layers of R grafts.

Stretch values estimated for the second step of Fig. 3.2 are shown in the left panels

of Fig. 3.12 for the dehydrated scaffolds and of Fig. 3.13 for the hydrated scaffolds.

Stress values calculated with the constitutive models are shown in the right panels of Fig.

3.12 for the dehydrated scaffolds and of Fig. 3.13 for the hydrated scaffolds. Stresses in

the layers were distributed over a wider range in H scaffolds, probably since the slope

of AR=f(OI) for this population was greater and hence a variation in OI affected more

strongly the estimated AR. Stresses varied between 170-910 kPa in H scaffolds, while the

range was only 420-550 kPa in D scaffolds.

Circumferential loads in the area of attachment of a cell to a layer of the scaffold, and

differences of these forces with the mean force applied to an area of the same size using

a mean stress of 500 kPa, are shown in Fig. 3.14 for the dehydrated scaffolds and in

Fig. 3.15 for the hydrated scaffolds. Loads in the layers varied from the mean in a range

of -25 to 30 pN in the dehydrated scaffolds, whereas in the hydrated scaffolds variations

were one order of magnitude higher, between -340 and 400 pN. Again, the wide range of

variation in H scaffolds obeyed to a stronger change in fiber alignment (characterized by

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measured) to the loaded state (at which AR was measured).

3.4 Discussion

An exploration of the micromechanical environment of four SIS scaffolds obtained by

varying two fabrication parameters was performed, and indicated that both parameters

had an influence on the microstructure and mechanics of the scaffolds. It seems that

orientation of fibers and void spaces have a strong influence on the mechanical response,

and a discussion of the results integrating the three characterizations is included next.

First, in the characterization of microstructure, OI values were spread in a broader

range in D scaffolds, suggesting that the process of dehydration could have allowed the

fibers to move into a wider range of positions set free by the evaporation of water.

Nonetheless, D scaffolds ranged around a higher AR, probably due to the residual stresses

originated in the loading (and preferential) direction of the intestinal source, which could

have dominated the “free movement” and finally oriented the fibers in a more anisotropic

configuration. Apparently, void areas had a high impact on the behavior in a loaded state,

which was characterized by the AR. When compared to results in OI, void areas did not

seem to be related with fiber alignment, in other words, more (or less) voids did not

re-late to more (or less) alignment. However, AR measurements in the five stress protocols

showed a strong dependency of AR on the loading protocol for PH scaffolds, which had

the highest void area (38%). RD scaffolds (17% void area) also exhibited dependency,

but not as strong as with PH. PD and RD grafts, on the other side, had a much slighter

dependency on the loading protocol. It seems that the hydration state allowed a much

wider range of anisotropical behaviors of the fibers in H scaffolds, and furthermore, that

a higher void area increased the range of these behaviors.

Differences in void area could be related to the disinfection solution used to fabricate

the scaffolds, which was the parameter varied between P and R grafts. The disinfection

solution could have caused either a swelling effect on the tissues that made the fibers

spread over a wider area in PH grafts, compress against each other in PD scaffolds or lose

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T able 3.2: Material constan ts and qualit y of fit to the Y eoh mo del for the la y ers in the scaffolds (material consta n ts and RMS are in kP a). L ayer 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 PD C10 1.23E+5 1.24E+5 1.33E+5 1.28E+5 1.34E+5 1.28E+5 1.18E+5 1.16E+5 1.22E+5 1.24E+5 1.19E+5 1.14E+5 1.20E+5 1.16E+5 1.10E+5 C20 1.22E+5 1.23E+5 1.31E+5 1.27E+5 1.33E+5 1.26E+5 1.17E+5 1.15E+5 1.21E+5 1.23E+5 1.18E+5 1.13E+5 1.19E+5 1.15E+5 1.08E+5 C30 4.07E+4 4.09E+4 4.38E+4 4.23E+4 4.44E+4 4.21E+4 3.89E+4 3.83E+4 4.03E+4 4.09E+4 3.93E+4 3.77E+4 3.96E+4 3.83E+4 3.61E+4 r 2 0.99792 0. 99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 0.99792 RMS 7.30 7.43 11. 84 9.04 13.01 8.82 7.85 8.77 7.15 7.40 7.48 9.81 7.31 8.80 13.24 RD C10 4.23E+5 3.96E+5 4.13E+5 4.49E+5 4.32E+5 4.16E+5 4.29E+5 4.11E+5 3.90E+5 4.17E+5 4.21E+5 4.08E+5 3.94E+5 3.97E+5 3.75E+5 C20 4.34E+5 4.06E+5 4.23E+5 4.60E+5 4.43E+5 4.26E+5 4.40E+5 4.22E+5 4.00E+5 4.28E+5 4.32E+5 4.18E+5 4.04E+5 4.07E+5 3.84E+5 C30 1.49E+5 1.39E+5 1.45E+5 1.58E+5 1.52E+5 1.46E+5 1.51E+5 1.44E+5 1.37E+5 1.46E+5 1.48E+5 1.43E+5 1.39E+5 1.39E+5 1.32E+5 r 2 0.99836 0. 99837 0.99836 0.99836 0.99836 0.99836 0.99836 0.99836 0.99837 0.99836 0.99836 0.99837 0.99837 0.99837 0.99837 RMS 6.86 7.14 6.24 10.73 7.89 6.32 7.51 6.23 7.92 6.40 6. 68 6.27 7.34 7.04 10.68 PH C10 8.36E+3 1.08E+4 8.99E+3 9.11E+3 1.12E+4 6.66E+3 1.47E+4 8.93E+3 9.22E+3 1.07E+4 8.20E+3 8.35E+3 1.06E+4 1.08E+4 1.80E+4 C20 8.51E+3 1.10E+4 9.14E+3 9.26E+3 1.13E+4 6.78E+3 1.49E+4 9.08E+3 9.37E+3 1.08E+4 8.34E+3 8.49E+3 1.08E+4 1.10E+4 1.83E+4 C30 2.91E+3 3.74E+3 3.12E+3 3.17E+3 3.87E+3 2.32E+3 5.09E+3 3.10E+3 3.20E+3 3.70E+3 2.85E+3 2.90E+3 3.67E+3 3.75E+3 6.24E+3 r 2 0.99996 0. 99997 0.99996 0.99996 0.99997 0.99996 0.99997 0.99996 0.99996 0.99997 0.99996 0.99996 0.99996 0.99997 0.99997 RMS 15.87 7.60 9.48 8.31 10.95 34.77 39. 90 10.11 7. 23 6.56 17.55 16.00 5.77 7.95 63.92 RH C10 1.35E+4 1.31E+4 1.55E+4 1.07E+4 1.26E+4 5.40E+3 1.91E+4 1.66E+4 1.28E+4 1.29E+4 1.34E+4 1.36E+4 1.60E+4 1.83E+4 1.65E+4 C20 1.49E+4 1.45E+4 1.70E+4 1.20E+4 1.39E+4 6.17E+3 2.09E+4 1.82E+4 1.41E+4 1.43E+4 1.48E+4 1.50E+4 1.76E+4 2.00E+4 1.81E+4 C30 5.53E+3 5.37E+3 6.28E+3 4.48E+3 5.17E+3 2.38E+3 7.65E+3 6.70E+3 5.25E+3 5.32E+3 5.48E+3 5.58E+3 6.50E+3 7.35E+3 6.67E+3 r 2 0.99982 0. 99982 0.99982 0.99982 0.99982 0.99980 0.99983 0.99983 0.99982 0.99982 0.99982 0.99982 0.99982 0.99983 0.99983 RMS 2.34 2.69 13. 03 17.39 5. 43 63.11 32. 53 19.15 4. 23 3.32 2.15 2.77 16.24 28.46 18.71

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of the present study and thus it is not clear, further exploration on the control of this

property would be worth, as it could provide an interesting tool in tissue engineering with

SIS (or similar fibrous scaffolds) to obtain a desired anisotropical response under loading,

by manipulating the void areas in fibrous scaffolds.

The correlation of the data of AR vs. OI of the four scaffolds altogether also showed

the influence of hydration and void spaces in the dynamic response of the scaffolds,

rep-resented by the changes in fiber alignment under loading characterized by the relation

AR vs. OI. OI was a measurement of fiber alignment at an unloaded state, while AR

was measured at an equibixially loaded state. Analyzed separately, the hydrated and

the dehydrated populations had directly proportional relationships in which a higher OI

meant a higher AR, in agreement with the definition of both indexes. However, when the

four scaffolds were used to formulate the correlation, the relation was inversely

propor-tional. This phenomenon indicated that fibers are organized into a dynamic arrangement

that changes when the scaffolds are loaded (in other words, alignment is not fixed, but a

rather dynamic property that depends on the loading configuration). Void area probably

plays an important role in the dynamics of anisotropy. In the case of H scaffolds, voids

could have provided space enough to have the fibers align with the preferential

direc-tion dictated by the intestine’s residual stresses. In contrast, D scaffolds, in view of the

dense organization of fibers, could have had not changed their alignment as strongly as

H scaffolds and kept a lower AR under equibiaxial loading.

Analysis of the layers using the constitutive model showed that C10 was generally

higher in R grafts than in P grafts. However, this effect did not translate in a clear manner

on loads applied to cells, which were very similar between P and R grafts (compared in

the same hydration state). In terms of the hydration parameter, the correlation between

AR and OI showed a marked influence on the spread of stress values. These variations

indicate that the stresses necessary to stretch the anisotropically different layers depend

on the initial arrangement of the collagen fibers, and will have a wider variation on a

scaffold with a larger void area. The dynamics of anisotropy in these scaffolds make their

layers greatly different in their mechanical response to loading. Those variations in stress,

An extracellular matrix scaffold for regenerating small diameter blood vessels - fabrication parameters, microstructure and mechanotransduction in small intestinal submucosa vascular grafts

Doctoral Dissertation

Diana M. Sánchez Palencia

An Extracellular Matrix

Scaffold for Regenerating

Small Diameter

Blood Vessels

Fabrication Parameters, Microstructure and Mechanotransduction

in Small Intestinal Submucosa Vascular Grafts

Cover image: Scanning Electron Microscopy of a small intestinal

submucosa scaffold fabricated by preserving the stratum compactum

layer of the intestine and keeping in a hydrated state until fixation

for imaging (PH scaffold). 3000x. Taken by the author at the Center

An Extracellular Matrix Scaffold for Regenerating Small

Diameter Blood Vessels

Diana M. S´

anchez Palencia

Acknowledgements

Contents

Chapter 1

Introduction

1.1

Cardiovascular disease

1.2

Current state of tissue engineered vascular grafts

1.3

Small intestinal submucosa vascular grafts

1.3.1

Composition of SIS

1.3.2

Previous results with SIS TEVGs

1.3.3

Regeneration process

1.4

Regeneration pathway or scarring pathway

1.5

Mechanotransduction, micromechanical

environ-ment and phenotype control

1.6

Fabrication

1.7

Hypothesis

1.8

Experimental design

1.9

Specific aims

1.9.1

SA1: Effects of fabrication parameters on the

microme-chanical environment

1.9.2

SA2: Effects of fabrication parameters on

mechanotrans-duction in an

in vitro

model

1.9.3

SA3: Effects of fabrication parameters on patency and

regeneration outcome in an early response

in vivo

model

Chapter 2

Specimen preparation

Chapter 3

SA1: Effects of fabrication

parameters on the micromechanical

environment

3.1

Overall experimental design

3.2

Methods

3.2.1

Microstructural analysis

3.2.2

Biaxial mechanical testing

3.2.3

Multi-layer constitutive model

3.2.4

Statistical analysis

3.3

Results

3.3.1