In Vivo Studies of the Foreign Body Reaction to Biomedical

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IN VIVO STUDIES OF THE FOREIGN BODY REACTION

TO BIOMEDICAL POLYMERS

Junghoon Yang

Submitted in partial fulfillment of the requirements

For the degree of Master of Science

Thesis Adviser: Dr. James M. Anderson

Department of Biomedical Engineering

CASE WESTERN RESERVE UNIVERSITY

May, 2013

CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the thesis/dissertation of

Junghoon Yang

candidate for the Master of Science in Biomedical Engineering.

Chair of the Committee

Dr. James M. Anderson

Members of the Committee

Dr. Horst von Recum

Dr. Roger Marchant

Date of Defense: March 7th, 2013

Table of Contents

List of Tables………………………………………………………………………..ii

List of Figures……………………………………………………………………….iv

Abstract……………………………………………………………………………..vii

Chapter I: Introduction………………………………………………………………1

Chapter II: Quantitative Versus Qualitative Assessment of the Extent of Foreign Body Reaction (Percent Fusion, Cell Density, and Nuclei Density)……...7 Materials and Methods……………………………………………………….11 Results………………………………………………………………………...31 Discussion……………………………………………………………………..65 References…………………………………………………………………….70

Chapter III: Controlling Fibrous Capsule Formation through Long-Term Down-Regulation of Collagen Type 1 (COL1A1) Expression by Nanofiber- Mediated siRNA Gene Silencing……………………………………………………….73 Materials and Methods…………………………………………………………75 Results…………………………………………………………………………..79 Discussion……………………………………………………………………….84

List of Tables

Chapter II

Table 1. Animal Phenotype Table Indicating Strain, General Information, Specific Traits, and References………………………………………………………….9 Table 2. Quantitative Percent Fusion for PEU with Timepoints 14, 21, and 28 Days…..37 Table 3. Average Cell Density for PEU with Timepoints 14, 21, and 28 Days…………39 Table 4. Average Nuclei Density for PEU with Timepoints 14, 21, and 28 Days………41 Table 5. Qualitative Normalized Average Grading for PEU with Timepoints 14, 21, and 28 Days…………………………………………………………43 Table 6. Quantitative Percent Fusion for PET with Timepoints 14, 21, 28 Days ………45 Table 7. Average Cell Density for PET with Timepoints 14, 21, and 28 Days………….47 Table 8. Average Nuclei Density for PET with Timepoints 14, 21, and 28 Days……….49 Table 9. Qualitative Normalized Average Grading for PET with Timepoints 14, 21, and 28 Days…………………………………………………………51 Table 10. One-way ANOVA Testing for Percent Fusion P Values between Two Different Strains for Material PEU…………………………………………………53 Table 11. One-way ANOVA Testing for Percent Fusion P Values between Two Different Strains for Material PET…………………………………………………54 Table 12. One-way ANOVA Testing P Values between the Percent Fusion for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB/cJ Control…………………………………………………………………...55 Table 13. One-way ANOVA Testing P Values between the Percent Fusion for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control…………………………………………………………………………55 Table 14. One-way ANOVA Testing P Values between the Cell Density for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB/cJ Control…………………………………………………………………...55 Table 15. One-way ANOVA Testing P Values between the Cell Density for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control…………………………………………………………………………55 Table 16. One-way ANOVA Testing P Values between the Nuclei Density for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB/cJ Control…………………………………………………………………...56

Table 17. One-way ANOVA Testing P Values between the Nuclei Density for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control…………………………………………………………………………56 Table 18. One-way ANOVA Testing P Values between the Normalized Grading for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB Control………………………………………………………56 Table 19. One-way ANOVA Testing P Values between the Normalized Grading for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control………………………………………………………….56 Table 20. One-way ANOVA Testing P Values between the Percent Fusion for the Two Time Points with Material PEU…………………………………………….57 Table 21. One-way ANOVA Testing P Values between the Percent Fusion for the Two Time Points with Material PET…………………………………………….58 Table 22. One-way ANOVA Testing P Values between the Cell Density for the Two Time Points with Material PEU……………………………………………59 Table 23. One-way ANOVA Testing P Values between the Cell Density for the Two Time Points with Material PET…………………………………………….60

Table 24. One-way ANOVA Testing P Values between the Nuclei Density for the Two Time Points with Material PEU……………………………………………61 Table 25. One-way ANOVA Testing P Values between the Nuclei Density for the Two Time Points with Material PET…………………………………………….62 Table 26. One-way ANOVA Testing P Values between the Normalized Grading for the Two Time Points with Material PEU…………………………………..63 Table 27. One-way ANOVA Testing P Values between the Normalized Grading for the Two Time Points with Material PET…………………………………...64

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List of Figures

Chapter I

Figure 1. Macrophage adherent cell density at Days 7 (A), 14 (B), and 21 (C) postimplantation in BALB/c and nude BALB/c mice……………………….2 Figure 2. Percent fusion at Days 14 (A) and 21 (B) post-implantation in BALB/c and nude BALB/c mice……………………………………………………...4

Chapter II

Figure 1. Foreign body giant cell formation for BALB/c control on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days…………………………17 Figure 2. Foreign body giant cell formation for NKT deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days…………………………18 Figure 3. Foreign body giant cell formation for IL-4 receptor alpha deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days…………19 Figure 4. Foreign body giant cell formation for c57 control on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days…………………………20 Figure 5. Foreign body giant cell formation for NK deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days…………………………21 Figure 6. Foreign body giant cell formation for mast cell deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days…………………………22 Figure 7. Foreign body giant cell formation for SCID mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days…………………………23 Figure 8. Foreign body giant cell formation for BALB/c control on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days………………………….24 Figure 9. Foreign body giant cell formation for NKT deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days………………………….25 Figure 10. Foreign body giant cell formation for IL-4 receptor alpha deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days………….26 Figure 11. Foreign body giant cell formation for c57 control on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days………………………….27 Figure 12. Foreign body giant cell formation for NK deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days………………………….28

Figure 13. Foreign body giant cell formation for mast cell deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days……………………29 Figure 14. Foreign body giant cell formation for SCID mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days………………………….30 Figure 15: Average Quantitative Percent Fusion for PEU with Control and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient…..38

Figure 16: Average Cell Density for PEU with Control and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient………………40

Figure 17: Average Nuclei Density for PEU with Control and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient………………42

Figure 18: Average Normalized Qualitative Grading for PEU with Experimental and Control Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient………………………………………………………………………44

Figure 19: Average Quantitative Percent Fusion for PET with Control and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient. ……………………………………………………………………..46

Figure 20: Average Cell Density for PET with Control and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient………………48

Figure 21: Average Nuclei Density for PET with Controls and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient………………50

Figure 22: Average Normalized Qualitative Grading for PET with Experimental and Control Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient………………………………………………………………….52

Chapter III

Figure 1. Histological images showing fibrous capsule formation and cell infiltration on aligned nanofibers supported on film at (a–h) week 2 and (i–p) week 4 with hematoxylin & eosin staining (left) and Masson’s Trichrome staining (right)………………………………………………………………..84

Figure 2 Histological images showing the fibrous capsule formation and cell infiltration on aligned nanofibers scaffolds that were supported on films at week 4 with hematoxylin & eosin staining (left) and Masson’s Trichrome staining (right). (a and b) siCOL1A1/CADY and (c and d) PCLEEP samples………………………………………………………….86

Figure 3 Quantitative analysis of (a) fibrous capsule thickness and (b) cell infiltration...87

IN VIVO STUDIES OF THE FOREIGN BODY REACTION

TO BIOMEDICAL POLYMERS

ABSTRACT

JUNGHOON YANG

ABSTRACT

The in vivo foreign body reaction on biomaterials regarding development of foreign body giant cells and formation of fibrous capsules was studied. The first study

(chapter II) discusses the development of foreign body reaction with specific lymphocytic immunodeficient mice mainly targeting IL-4 (interleukin-4) cytokine. The experiment consisted of in vivo subcutaneous implants of polyether urethane (PEU) and polyethylene terephthalate (PET) in immunodeficient mice strains. Analysis on polymer surfaces using quantitative calculations such as percent fusion, cell density, and nuclei density described the development of foreign body reaction on biomaterial surface. In addition qualitative assessment was implemented to also describe the development of foreign body reaction that provided similar characterization to the quantitative calculations. The second study (chapter III) focuses on the fibrous capsule formation around biomaterials.

Electrospun nanofibers poly(ε-caprolactone-co-ethylethylene phosphate) coupled with collagen type I siRNA were subcutaneously implanted. A significant decrease in fibrous capsule thickness at weeks 2 and 4 were shown compared to the control nanofibers.

vii

Chapter I - Introduction

Lymphocytes are present during the chronic inflammatory stage [1]. In addition,

previous in vitro studies have shown that lymphocytes promote macrophage adhesion and

fusion on material surfaces [2]. IL-4 and IL-13 cytokines revealed increased macrophage

fusion and altered foreign body giant cell formation on biomaterial surfaces [2 - 8].

Furthermore, T lymphocytes have been hypothesized to be a source of both IL-4 and IL-

13 (Interleukin-13) [1].

An in vivo study done by Rodriguez et al. investigated the role of T-cells on

formation of foreign body giant cells on synthetic biomaterials [3]. T-cell deficient

BALB/c nude mice model was used to compare with BALB/c background strain as control. 3 materials, PEU, PET (Mylar), and silicate resin-filled crosslinked polydimethylsiloxane (SR) were used for subcutaneous cage implant. Macrophage fusion and adherent cell density were calculated for time points 7, 14, and 21 days for all material surfaces using May Grünwold Giemsa (MGG) stain.

Results show that at day 7, BALB/c control strain showed higher cell density

compared to nude BALB/c strain with PET (Figure 1). In addition, cell density for PET

surfaces showed higher cell density compared to SR surfaces at day 7. However, no

apparent adherent cell density was found for any time point [3].

Figure 1. Macrophage adherent cell density at Days 7 (A), 14 (B), and 21 (C) postimplantation in BALB/c and nude BALB/c mice. Data represent mean and standard deviation for five animals. *Statistical significant difference p <0.05 [3].

At 7 days, foreign body giant cells were not seen on biomaterial surfaces, and

values for percent fusion for 14 days and 21 days were recorded. Percent fusion data

shown in Figure 2 indicate that no alterations in macrophage fusion were observed

between materials. In addition, no differences were noted between BALB/c and nude

BALB/c mice.

Results from Rodriguez et al. indicated that T-cells did not influence foreign body giant cell formation on synthetic biomaterials in vivo. T-cells did not participate in the development of foreign body giant cells, but IL-4 cytokines have different sources that induce macrophage fusion. Past studies have shown that IL-4 sources are: NK cells,

NKT cells and mast cells [3, 9 - 11].

Current study for chapter II in this thesis is a continuation of Rodriguez’s study in which in vivo sources of IL-4 cytokine was investigated. Direct subcutaneous implants of biomaterials, PEU and PET, were used instead of the subcutaneous cage system to directly assess the surfaces of the biomaterials for development of foreign body reaction.

7 day time points were omitted due to the lack of foreign body giant cells present on the material surfaces in Rodriguez’s study [3], and 28 day time point were added for long term observation on the development of the foreign body reaction. NKT deficient, NK deficient, IL-4 receptor alpha deficient, mast cell deficient, and SCID mice strains were compared with appropriate control background strains. Quantitative assessment such as percent fusion, cell density, and nuclei density on PEU or PET surface was calculated to note alterations to the formation of foreign body giant cells. In addition, qualitative grading was done for PEU or PET surfaces to provide similar statements on the development of foreign body reaction comparable to the quantitative calculations.

Figure 2. Percent fusion at Days 14 (A) and 21 (B) post-implantation in BALB/c and nude BALB/c mice Data represent the mean and standard deviation. [3]

References

1. Anderson JM, Rodriguez A, Chang DT. 2008 Foreign body reaction to biomaterials.

Sem in Immunol 30(2): 86-100.

2. Brodbeck WG, MacEwan M, Colton E, Meyerson H, Anderson JM. 2005

Lymphocytes and the foreign body response: lymphocyte enhancement of

macrophage adhesion and fusion. J Biomed Mater Res 74A:222-229.

3. Rodriguez A, MacEwan SR, Meyerson H, Kirk JT, Anderson JM. 2009b. The foreign

body reaction in T-cell deficient mice. J Biomed Mater Res 90A: 106-113.

4. McNally AK, Anderson JM 1995. Interleukin-4 induces foreign body giant cells from

human monocytes/macrophages. Differential lymphokine regulation of macrophage

fusion leads to morphological variants of multinucleated giant cells. Am J Pathol

147:1487-1499.

5. Kao WJ, McNally AK, Hiltner A, Anderson JM. 1995. Role of interleukin-4 in

foreign-body giant cell formation on a poly(etherurethane urea) in vivo. J Biomed

Mater Res 29:1267-1275.

6. DeFife KM, Jenney CR, McNally AK, Colton E, Anderson JM. 1997. Interleukin-13

induces human monocyte/macrophage fusion and macrophage mannose receptor

expression. J Immunol 158:3385-3390.

7. MacEwan MR, Brodbweck WG, Matsuda T, Anderson JM. 2005.

Monocyte/lymphocyte interactions and foreign body response: in vitro effects of

biomaterial surface chemistry. J Biomed Mater Res 74A:285-293.

8. McNally, A.K., Anderson, J.M., 2011. Foreign body-type multinucleated giant cells

induced by interleukin-4 express select lymphocyte co-stimulatory molecules and are

phenotypically distinct from osteoclasts and dendritic cells. Exp and Mole Path 91:

673-681.

9. Paul WE. 1991. Interleukin-4: A prototypic immunoregulatory lymphokine. Blood 77:

1859-1870.

10. Gessner A., Mohrs K., Mohrs M. 2005. Mast cells, basophils, and eosinophils acquire

constitutive IL-4 and IL-13 transcripts during lineage differentiation that are

sufficient for rapid cytokine production. J Immunol 174: 1063-1072.

11. Metwali A, de Andres B, Blum A, Elliott D, Li J, Qadir K, Sandor M, Weinstock J.

2002. Th2-type granuloma development in acute murine schistosomiasis is only

partly dependent on CD4+ T cells as the source of IL-4. Eur J Immunol 32: 1242 –

1252.

Chapter II – Quantitative Versus Qualitative Assessment of the Extent of the Foreign

Body Reaction (Percent Fusion, Cell Density, and Nuclei Density)

Introduction

A clear understanding of the development and function of the foreign body

reaction is needed for successful development of novel biomaterials, tissue-engineered

constructs, and prostheses. The temporal series of events following the implantation of a

biomaterial are characterized by: acute inflammation (polymorphonuclear leukocytes or

PMNs) and chronic inflammation (monocytes, lymphocytes), monocyte/macrophage

adhesion to the biomaterial surface, macrophage fusion to create foreign body giant cells

(FBGCs), and fibrosis (fibrous capsule formation) [1]. These responses promote the production of bioreactive molecules and inflammatory mediators such that activated macrophages/FBGCs release reactive oxygen species at the cell/biomaterial interface and the production of cytokines and growth factors that promote wound healing cells toward a fibrogenic phenotype. These activities can lead to biomaterial degradation, fibrous

encapsulation, and device failure [2-4]. As a result, the foreign body reaction defined as the monocyte/macrophage adhesion, FBGC formation, and fibrous capsule formation may be undesirable and therefore is an appropriate target for intervention.

In order to further understand the foreign body reaction, additional host

mechanisms must be characterized. Even though no apparent relationship may be seen

between the synthetic polymer materials and the immune response, previous studies

suggested that lymphocytes may play a role in the inflammatory and foreign body

responses to implanted biomaterials [2 -11]. Lymphocyte activation occurs through an

interaction with antigen-presenting cells such as macrophages and dendritic cells.

Investigations have shown that alternative macrophage activation cytokines interleukin-4

(IL-4) and IL-13 promote in vitro macrophage fusion, [4, 6] and IL-4 plays an important role in FBGC formation in vivo [5]. It is well known that IL-4 cytokines are recognized as Th2 lymphocyte products, but natural killer (NK) and natural killer T (NKT) lymphocytes produce IL-4, and mast cells are alternate sources of IL-4 [10].

Although IL-4 has been known to induce FBGC formation, the specific source/sources of IL-4 cytokine production is still unclear [5]. Past in vivo studies have compared Th1 and Th2 lymphocyte-deficient mice with the normal mice for differences in FBGC formation regarding morphology and extent of formation (percent fusion) [3].

However, this investigation showed that the Th2 lymphocyte was either not the source or not the only source of macrophage fusion inducing IL-4. As a result, other possible sources such as NK or NKT lymphocytes are appropriate target sources for further identification of fusion inducing IL-4.

In order to focus on various sources of macrophage fusion inducing IL-4, different mouse strains with appropriate deficiencies (Table 1) [17 - 38] were implanted with clinically relevant biomedical polymers, i.e. Elasthane 80-A (PEU) and polyethylene terephtalate (PET). NKT deficient, NK deficient, mast cell deficient, and SCID mouse strains were compared with appropriate background mice to provide quantitative calculations alongside qualitative measurements to provide comparisons of the extent of macrophage fusion. Findings support the previous study that materials reveal similar levels of FBGC formation [3]. In addition, the strains show statistically insignificant differences and the timepoints show similar formation of foreign body giant cells.

Table 1. Animal Phenotype Table Indicating Strain, General Information, Specific Traits, and References

General Strain Specific Traits Reference Information -Lack NK activity NK Deficient -Reduced production of IL-2 by C57BL/6J -[17] B6.129S4- stimulated T cells (~40%) Background -[18] Il2rgtm1Wjl/J -Reduced production of IL-4 by stimulated T cells (~40%) NKT Deficient -Lack NKT cells Balb/cJ -[19] C.129S2- -Reduced CD-4 positive T cell number Background -[20] CD1tm1Gru/J -Reduced IL-4 secretion

-Reduced Immunoglobulin E IL-4 Receptor alpha Balb/cJ -Reduced Immunoglobulin G1 Deficient -[21] Background -Reduced IL-10, IL-4, and IL-5 secretion BALB/c-IL4ratm1Sz/J -Increased Immunoglobulin G2a

-[22] -[23] -Reduced mast cell degranulation Mast Cell Deficient -[24] C57BL/6J -Decreased release of Histamine STOCK Kitw- -[25] Background -Decreased level of Immunoglobulin E sh/HNihrJaeBsmJ -[26] -Decreased mast cell number -[27] -[28] -[29]

-[30] -[31] -Increased number of NK cells Severe combined -[32] -Decreased number of B cells immune deficiency -[33] C57BL/6J -Decreased number of T cells (SCID) -[34] Background -Increased number of macrophage B6.CB17- -[35] -Increased number of monocyte Prkdcscid/SzJ -[36] -Increased number of granulocyte -[37] -[38]

The hypothesis of this study is to determine if specific types of lymphocytes

participate in the development of the foreign body reaction to biomaterials. Results show

that the specific types of lymphocytes chosen for the study did not participate in the

development of the foreign body reaction to PEU and PET. Also, the quantitative

findings were validated by comparing previous study’s patterns for foreign body formation related to material and timepoints [3]. Then, the quantitative assessments were compared with the qualitative findings to reflect similar patterns. Comparisons show that qualitative assessments reveal similar development of the foreign body reaction comparable to the quantitative assessments. Ultimately, the qualitative assessment displayed the ability to answer the hypothesis just like the quantitative measurements.

Methods and MATERIALS

Polymer Material

Additive free Elasthane 80A (PEU) and polyethylene teraphalate (PET, Mylar®)

were obtained from Medtronic (Minneapolis, MN), and were cut into 0.8 cm by 0.8 cm

squares. Each polymer square was sonicated for 15 minutes with 100% ethanol, rinsed

off with Millipore water 3 times, and then air dried. Once the polymers were dry, the polymer squares were placed inside sterilization packets and were sent to University

Hospital’s services for ethylene oxide sterilization. Upon receiving the sterilized material, the packets were placed inside an air vacuum for 24 hours prior to implantation.

Experimental and Control Group for Animal Study

The in vivo procedure required 5 different mice phenotype experimental groups and 2 different background mice for controls; all acquired from Jackson Lab (Bar Harbor,

ME) (Table 1). The two background mice for controls were Balb/cJ and C57Bl/6J.

Three Phenotype strains with C57Bl/6J background strain were: Natural Killer (NK)

Deficient, Mast Cell Deficient, and Severe combined immune deficiency (SCID). Two

Balb/cJ background strains were interleukin-4 receptor α (IL-4Rα) deficient strain and

Natural Killer T (NKT) deficient strain. Each strain group contained 5 mice (n=5), which were placed in the same cage. For each group (n=5), PET and PEU were implanted. In addition there are 4 time groups: 14 days, 21 days, 28 days, and an extra time group, used

as replacement for mice that had discarded data. As a result, the total number of mice

used were 7 strains * 5 mice per strain group * 2 material groups * 4 time groups = 280

mice. All mice were age matched to be 6 weeks old, fed ad libitum on standard pellets

and water were used. (Animal Resource Center, Case Western Reserve University). NIH

guidelines for the care and use of laboratory animals were observed. All protocols were

approved by the Institutional Animal Care and Use Committee (IACUC) of Case Western

Reserve University.

In vivo Surgical Procedure

All surgery was done under sterile conditions in the Ultrabarrier of the Animal

Resource Center at Case Western Reserve University. First, mice were injected

peritoneally with 0.1cc of rodent cocktail consisting of 0.1 ml xylazine (100mg/ml), 1.0

ml ketamine, and 4.6 ml sterile water. The back was shaved and alcohol and betadiene

were applied for preparation. An incision along the midline of 1 cm was made and 0.5%

Marcaine was applied to the incision. Next, using a pair of blunt scissors, subcutaneous

pockets were created on the left and right side, respectively. Using forceps, a sterilized

polymer square, PET or PEU, was placed inside the pocket, so that the polymer would

not move once the surgical procedure was over. The incision site was stapled using a 0.7

mm stapler and Marcaine solution was added once again. Lastly, when the effect of the

rodent cocktail slowly started to disappear, 0.1cc of diluted buprenex (1:10 of 0.3mg/ml)

was intraperitoneally injected for analgesia.

Histological Slide Preparation for Qualitative and Quantitative Analysis

Once the mice were sacrificed on the appropriate timepoint, the materials on left

and right sides were retrieved. The materials were gently taken out of the fibrous

capsules while minimizing contact to reduce cell detachment for May-Grünwald Giemsa

(MGG) staining. The other material was fixed using 10% buffered formalin for 24 hours and then sectioned for hematoxylin and Eosin (H&E) staining.

Qualitative Grading Using Light Microscopy

Each sample surface, stained with May–Grünwald–Giemsa (MGG) stain, was observed through light microscopy at 10x magnification covering an area of 0.80 mm x

1.06 mm for a representative field that reflects the overall foreign body reaction (FBR).

In order to assess qualitative evaluation of the extent of FBR, a grading system was implemented. For each sample, four representative fields were picked; one field was photographed and evaluated with a grade that described the foreign body reaction in relation to size of the foreign body giant cells (FBGCs), number of macrophages, and number of nuclei within the FBGCs. The range of the grading system was from 0 to 4: 0, none; +1 minimal; +2 mild; +3 moderate; and +4 extensive. To further confirm the accuracy of grading, grading was done independently taking different sample images by two observers to provide an average grading with standard deviation for each sample.

Data was normalized to produce scores ranging from 0 to +1 for easy comparison to the quantitative percent fusion data.

Quantitative Counting and Parameter Calculation

Three 10x magnification (0.80 mm x 1.06 mm) representative images for each strain and timepoint were chosen for quantitative counting and parameter calculation.

Two equal areas were divided to provide two counts for one image, and for a specific timepoint, strain, and material, 6 measurements (n=6) were taken, and a total of n= 252 (6 measurements*7 strains* 3 timepoints * 2 materials) for total number of counting

13 measurements. ImageJ provided by the NIH was used to measure three parameters: total number of macrophages and FBGCs, total number of nuclei, and number of FBGCs. The number of macrophages was indicated by counting cells with only one nucleus, and the number of FBGC was determined by counting cells in which more than 3 nuclei were present. Using the measured parameters, the percent fusion of macrophages, average number of nuclei per FBGC, and percent of FBGC were quantified.

Percent of FBGCs measures the percent ratio of FBGCs and total number of cells within the field. The equation for percent fusion is given as:

Number of FBGCs Percent of FBGCs = (1) Total number of cells

Average number of nuclei per FBGCs measures the ratio of number of nuclei within FBGCs to the number of FBGCs. The equation for Average number of nuclei per

FBGC is:

Number of nuclei in FBGCs Average number of nuclei per FBGC = (2) Number of FBGCs

With the measured parameters, the number of nuclei in FBGCs from equation 2 can be related to the total number of nuclei, total number of cells, and number of FBGCs:

Number of nuclei in FBGCs

= Total number of nuclei (Total number of cells Number of FBGCs) (3)

− − Using equations 2 and 3, a new equation for average number of nuclei per FBGC is:

( ) Average number of nuclei per FBGC = (4) Total number of nuclei− Total number of cells−Number of FBGCs Number of FBGCs

The percent fusion of FBGCs describes the extent of macrophage fusion to form

FBGCs. Quantitatively, percent fusion is the ratio between the number of nuclei in

FBGCs and the total number of nuclei.

Percent Fusion = (5) Number of nuclei in FBGCs Total number of nuclei

Using equation 3 the numerator, number of nuclei in FBGCs, can be substituted into terms that depend on the counted parameters for data collection:

( ) Percent Fusion = (6) Total number of nuclei− Total number of cells−Number of FBGCs Total number of nuclei Using the 3 quantitative values, graphical representation of quantitative mean values and mean qualitative grading was done to validate the accuracy and determine the correlation between the qualitative and quantitative grading (Figure 15 ,Figure 18 , Figure

19 , and Figure 22 )

Quantitative Cell Density and Nuclei Density Calculation

The area of the 10x magnification images was determined by using a calibration slide (0.80 mm x 1.06 mm). Then the area was divided by 2 to account for using half of the area for each parameter calculation. The cell density was calculated by using the ratio of total number of cells to the half area. Nuclei density was calculated by using the dividing the total number of nuclei by the half area. For each respective timepoints, strain, and material, the mean and standard deviation were calculated in order to create graphical representation of quantitative cell density and nuclei density. See Figure 16 to

Figure 17 for PEU, Figure 20 to Figure 21 for PET. Figure 1 to Figure 7 show

representative May–Grünwald–Giemsa stained image on PEU surfaces for each mice strains at 10X magnification. Figure 8 to Figure 14 show representative May–Grünwald–

Giemsa stained image on PET surfaces for each mice strains at 10X magnification.

Statistical Analysis

One way ANOVA analysis (Origin® 8.5) was used to compare average percent

fusion, cell density, nuclei density, or normalized grading score for each respective

material at each time point in each knockout model compared to control. See Table 3 to

Table 4 for PEU and Table 7 to Table 8 for PET.

Figure 1. Foreign body giant cell formation for BALB/c control on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 2. Foreign body giant cell formation for NKT deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 3. Foreign body giant cell formation for IL-4 receptor alpha deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 4. Foreign body giant cell formation for c57 control on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 5. Foreign body giant cell formation for NK deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 6. Foreign body giant cell formation for mast cell deficient mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 7. Foreign body giant cell formation for SCID mice on PEU surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 8. Foreign body giant cell formation for BALB/c control on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 9. Foreign body giant cell formation for NKT deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 10. Foreign body giant cell formation for IL-4 receptor alpha deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 11. Foreign body giant cell formation for c57 control on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 12. Foreign body giant cell formation for NK deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 13. Foreign body giant cell formation for mast cell deficient mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

Figure 14. Foreign body giant cell formation for SCID mice on PET surfaces at (A) 14 days, (B) 21 days, and (C) 28 Days. Polymer surfaces were MGG stained and images were taken at 10X magnification.

RESULTS

Percent fusion for PEU is compared between experimental immunodeficient

strains and their respective control background strains. Figure 15 shows a graph

showing average percent fusion for PEU for all strains. Average percent fusion values

and p values in Table 2 show comparison between the experimental strains and control

background strains. At 21 days percent fusion, IL-4 receptor alpha deficient and SCID

strains show statistically significant differences compared to their respective control strain. At 28 days percent fusion, NKT deficient and NK deficient mice indicated statistically significant differences compared to their respective control strain. However, no specific trends are present to determine that immunodeficient strains participated in development of percent fusion on PEU surfaces.

The Cell density on PEU is compared between experimental immunodeficient strains and their respective control background strains. A bar graph of average cell density is shown in Figure 16 , and average cell density values and p values are shown in

Table 3. ANOVA comparison indicates that NK deficient, SCID, and mast cell deficient mice at 28 days have statistically significant differences to their c57 control mice.

ANOVA comparison indicates no trends and patterns are present. This shows that on

PEU surfaces specific lymphocyte subset deficiency had no effect on cell density compared to the background strain.

Nuclei density for PEU is compared between experimental immunodeficient strains and their respective control background strains (Figure 17 ). Average nuclei density, standard deviation, and one-way ANOVA p values are given in Table 4. For 21

31 days mast cell deficient showed statistically significant differences compared to their c57 control mice. All experimental strains compared to their respective control indicated statistically significantly different. Only one time point out of three showed statistically significant difference, which is not enough to show effect on nuclei density. Overall, no trends or patterns were noted for effect, and no specific immunodeficiency had corollary with nuclei density on PEU surfaces.

Representation of qualitative normalized grading with PEU data in shown in

Figure 18 and Table 5. P values show that SCID strains at 28 days showed statistically significant differences, and the others showed no statistically significant differences.

Normalized grading indicates that lymphocytic immunodeficient strains did not affect the extent of the foreign body reaction on PEU surfaces.

Percent fusion on PET surface was calculated, and one-way ANOVA p values were calculated for comparison between immunodeficient experimental strains and their respective control background strains (Table 6 and Figure 19 ). IL-4 receptor alpha deficient strain at 14 days had statistically significant differences between BALB/c control mice. At 28 days, NKT deficient, NK deficient, and SCID mice showed statistically significant differences to their respective control background strains.

Although some statistical differences are noted at 28 and 14 days, no clear trends and patterns are distinguished. Overall, on PET surfaces, experimental immunodeficient strains did not alter macrophage fusion compared to the control strains.

Figure 20 and Table 7 present data regarding cell density on PET surfaces. At 14 days, IL-4 receptor alpha deficient and SCID mice strains have statistically significant

differences between BALB/c control and c57 control, respectively. Also, IL-4 receptor alpha deficient mice show statistically significant differences with BALB/c control strain at 21 days. At 28 days, NKT deficient, NK deficient, and SCID mice have statistically significant differences between their respective control strains. IL-4 receptor alpha deficient and SCID mice show significant differences for two time points, but no patterns are shown since only two out of three timepoints present significant difference. The other strains that have statistically significant differences occur for one time point. Since no strains present significant differences for all three time points, immunodeficient strains did not make any alterations for cell density on PET surfaces.

Average nuclei density on PET surfaces was recorded and presented in Table 8 and Figure 21 . At 14 days, SCID mice showed statistically significant differences compared to the c57 control. IL-4 receptor alpha deficient, SCID, and mast cell deficient mice were statistically significantly different with their respective background control strain. At 28 days, the NK deficient strain was statistically significantly different compared to the c57 control strain. No patterns or trends were noticeable, and therefore immunodeficient strains did not affect the density of nuclei on PET surfaces.

Qualitative normalized average grading for PET was represented in Figure 22 and

Table 9. No strains showed statistically significant difference with their respective control background. The observation can be made that no alterations in the extent of the foreign body reaction were seen on PET surfaces.

One-way ANOVA testing was done to create p values between two different strains for materials PEU or PET at all time points (Table 10 and Table 11). Some strains

show statistically significant differences, but no definite patterns and trends are seen

between time point and strains.

Percent fusion for PEU compared to PET through ANOVA analysis of data from the different strains compared to the respective controls showed that only the day 21 values for percent fusion were statistically significant different (Table 12 and Table 13).

Analysis of day 14 and day 28 data showed no statistically significant difference when

PEU was compared to PET. This shows that macrophage fusion to form foreign body

giant cells, while comparable for PEU and PET at 14 days, continued for the PEU

polymer through 21 days. The 28 day analysis demonstrated that the fusion of

macrophages had modulated to become comparable for the PEU and PET polymers.

ANOVA analysis using cell density for PEU compared to PET indicated that at

28 days, the strains with the c57 control group showed statistically significant differences

(Table 14 and Table 15). However, 14 days and 21 days cell density data showed some statistically significant differences. Even though one c57 background control and experimental strains were statistically significantly different, no patterns and trends were determined to indicate that PEU and PET surfaces had comparable cell density.

Nuclei density for PEU compared to PET through ANOVA analysis of data from the different strains showed that at 28 days the c57 background experimental and control groups were statistically significantly different (Table 16 and Table 17). Other time points such as 14 days and 21 days indicate some statistically significant differences, but no definite patterns are shown to indicate a difference in nuclei density between PEU and

PET. Statistically significant differences at 28 days for strains with c57 background

control and did not indicate a trend or pattern that determines that PEU and PET surfaces

showed a difference in nuclei density.

One-way ANOVA analysis for normalized grading between materials, PEU and

PET, showed that statistically significant differences were present at 21 and 28 days

(Table 18 and Table 19). In addition, 14 days normalized grading did not show

statistically significant differences. Although two time points were significantly different,

one time point did not show a significant difference. Therefore, no clear pattern or trend was present to determine that PEU and PET altered the extent of foreign body reaction.

Table 21 - Table 27 show ANOVA p value analysis of percent fusion, cell density,

nuclei density, and normalized grading between two timepoints for all strains with PEU

and PET. ANOVA analysis for percent fusion with PEU shows that BALB/c control and

mast cell deficient mice strains were statistically significant different for all three time

points (Table 20). On the other hand ANOVA analysis for percent fusion with PET

showed no statistically significant differences for experimental and control strains at 3

different time point comparisons (Table 21). For cell density ANOVA analysis (Table 22

and Table 23), only SCID mice with PEU and NKT deficient mice with PET were

statistically significantly different for three time points. Only the mast cell deficient

strain with PET was statistically significantly different at a three time point comparison

for ANOVA analysis of nuclei density for materials PET and PEU (Table 24 and Table

25). No trends and patterns were found that indicated that increased time points provided

changes in percent fusion, cell density, and nuclei density. Overall, lymphocytic

immunodeficient strains did not alter the development of the foreign body reaction

35 because no specific strains showed statistically significant differences for percent fusion, cell density, and nuclei density with PEU and PET.

Normalized grading ANOVA analysis indicated that no strains were statistically significantly different for all time points. Overall, the extent of foreign body reaction is not altered at different time points for all immunodeficient mice when compared to their respective background controls.

Table 2. Quantitative Percent Fusion for PEU with Timepoints 14, 21, and 28 Days

14 Days PEU Percent Fusion NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 72.5 75.3 74.6 72.1 68.3 70.1 69.4 Standard Deviation 10.9 9.91 4.20 4.93 5.63 10.9 10.5 n 6 6 8 6 6 6 6 P value* 0.65 0.87 N/A 0.63 0.85 0.91 N/A

21 Days PEU Percent Fusion NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 87.6 81.2 90.2 81.1 91.2 85.9 67.8 Standard Deviation 2.99 3.55 3.33 5.84 3.65 11.2 14.9 n 6 6 8 6 6 6 6 P value* 0.21 0.002 N/A 0.09 0.007 0.055 N/A

28 Days PEU Percent Fusion NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 70.1 79.0 82.4 74.1 95.5 97.8 96.5 Standard Deviation 10.3 13.2 4.15 7.55 2.71 1.59 0.91 n 6 6 8 6 6 6 6 P value* 0.03 0.59 N/A 6.14*10-5 0.44 0.15 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Figure 15: Average Quantitative Percent Fusion for PEU with Control and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient. Data is presented with mean ± standard deviation, n=6.

Table 3. Average Cell Density for PEU with Timepoints 14, 21, and 28 Days

14 Days PEU Cell Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (cells/mm2) 408 483 366 565 794 656 617 Standard Deviation (cells/mm2) 151 204 125 196 164 208 358 n 6 6 8 6 6 6 6 P value* 0.61 0.25 N/A 0.78 0.34 0.84 N/A

21 Days PEU Cell Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (cells/mm2) 340 376 312 433 288 625 695 Standard Deviation (cells/mm2) 70.8 108 150 83.9 71.1 209 478 n 6 6 6 6 6 6 6 P value* 0.71 0.45 N/A 0.25 0.09 0.77 N/A

28 Days PEU Cell Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (cells/mm2) 284 412 259 390 152 135 295 Standard Deviation (cells/mm2) 109 225 58.0 84.8 43.3 33.7 38.5 n 6 6 6 6 6 6 6 -5 P value* 0.66 0.17 N/A 0.046 2.52 *10-4 3.64*10 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Table 4. Average Nuclei Density for PEU with Timepoints 14, 21, and 28 Days.

14 Days PEU Nuclei Density Mast NKT IL4-ra Balb/cJ NK Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (Nuclei/mm2) 1237 1547 1154 1756 2220 1845 1400 Standard Deviation (Nuclei/mm2) 434.5 220.0 499.4 607.6 748.8 457.1 636.2 n 6 6 8 6 6 6 6 P value* 0.61 0.25 N/A 0.78 0.34 0.84 N/A

21 Days PEU Nuclei Density Mast NKT IL4-ra Balb/cJ NK Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (Nuclei/mm2) 1836 1367 1611 1686 1746 3757 1672 Standard Deviation (Nuclei/mm2) 499.3 337.4 681.1 96.92 718.4 1357.7 605.2 n 6 6 6 6 6 6 6 P value* 0.57 0.49 N/A 0.96 0.86 0.01 N/A

28 Days PEU Nuclei Density Mast NKT IL4-ra Balb/cJ NK Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (Nuclei/mm2) 741.2 1418 1047 1202 1238 1611 2545 Standard Deviation (Nuclei/mm2) 144.0 266.8 116.6 235.5 321.8 228.0 187.6 n 6 6 6 6 6 6 6 -6 -6 P value* 0.004 0.02 N/A 1.62*10 1.39*10 3.66*10-5 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Table 5. Qualitative Normalized Average Grading for PEU with Timepoints 14, 21, and 28 Days

PEU 14 Days Normalized Grading NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 0.70 0.76 0.77 0.80 0.65 0.88 0.79 Standard Deviation 0.19 0.17 0.14 0.09 0.16 0.16 0.15 n 8 10 16 10 11 6 6 P value* 0.37 0.96 N/A 0.89 0.09 0.37 N/A

PEU 21 Days Normalized Grading NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 0.78 0.89 0.81 0.90 0.73 0.84 0.82 Standard Deviation 0.16 0.11 0.17 0.10 0.11 0.14 0.15 n 10 10 22 10 10 10 14 P value* 0.62 0.17 N/A 0.17 0.11 0.80 N/A

PEU 28 Days Normalized Grading NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 0.84 0.89 0.76 0.92 0.83 0.94 0.96 Standard Deviation 0.12 0.13 0.17 0.09 0.12 0.16 0.06 n 12 9 20 8 12 10 10 P value* 0.15 0.06 N/A 0.28 0.007 0.65 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Figure 18: Average Normalized Qualitative Grading for PEU with Experimental and Control Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient. Data is presented with mean ± standard deviation.

Table 6. Quantitative Percent Fusion for PET with Timepoints 14, 21, 28 Days

14 Days PET Percent Fusion NKT IL4-ra Balb/cJ Mast Cell c57 Deficient Deficient Control NK Deficient SCID Deficient Control Average 68.8 78.4 65.6 61.1 69.8 70.1 64.8 Standard Deviation 7.65 7.70 9.18 11.4 12.4 8.95 4.95 n 6 6 8 6 6 6 6 P value* 0.56 0.04 N/A 0.52 0.42 0.273 N/A

21 Days PET Percent Fusion NKT IL4-ra Balb/cJ Mast Cell c57 Deficient Deficient Control NK Deficient SCID Deficient Control Average 71.0 54.8 68.7 57.6 64.4 58.5 65.0 Standard Deviation 13.0 13.2 5.90 5.99 7.38 14.6 11.7 n 6 6 8 6 6 6 6 P value* 0.73 0.06 N/A 0.24 0.92 0.45 N/A

28 Days PET Percent Fusion NKT IL4-ra Balb/cJ Mast Cell c57 Deficient Deficient Control NK Deficient SCID Deficient Control Average 89.6 65.6 76.1 75.9 56.4 82.1 94.5 Standard Deviation 7.72 15.8 5.50 3.77 11.0 16.1 3.10 n 6 6 8 6 6 6 6 P value* 0.01 0.19 N/A 6.73*10-6 2.11*10-5 0.12 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Figure 19: Average Quantitative Percent Fusion for PET with Control and Experimental Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient. Data is presented with mean ± standard deviation, n=6.

Table 7. Average Cell Density for PET with Timepoints 14, 21, and 28 Days

14 Days PET Cell Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (cells/mm2) 847 452 735 514 312 746 838 Standard Deviation (cells/mm2) 221 137 214 137 171 209 305 n 6 6 8 6 6 6 6 P value* 0.43 0.03 N/A 0.06 0.007 0.59 N/A

21 Days PET Cell Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (cells/mm2) 300 160 468 704 368 329 820 Standard Deviation (cells/mm2) 154 26.8 152 272 111 148 530 n 6 6 6 6 6 6 6 P value* 0.113 0.001 N/A 0.675 0.092 0.074 N/A

28 Days PET Cell Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (cells/mm2) 110 525 447 596 1001 380 176 Standard Deviation (cells/mm2) 27.6 287 233 118 379 319 35.7 n 6 6 6 6 6 6 6 P value* 0.01 0.65 N/A 1.74*10-5 6.70*10-4 0.19 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Table 8. Average Nuclei Density for PET with Timepoints 14, 21, and 28 Days

14 Days PET Nuclei Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (Nuclei/mm2) 2428 1804 1907 1291 882.8 2145 2122 Standard Deviation (Nuclei/mm2) 839.2 765.7 436.1 417.8 335.5 394.1 834.0 n 6 6 8 6 6 6 6 P value* 0.25 0.80 N/A 0.07 0.01 0.96 N/A

21 Days PET Nuclei Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (Nuclei/mm2) 1109 323.1 1278 1577 911.2 645.3 2084 Standard Deviation (Nuclei/mm2) 856.5 61.93 427.4 750.8 272.4 186.8 946.5 n 6 6 6 6 6 6 6 P value* 0.701 5.84*10-4 N/A 0.370 0.024 0.008 N/A

28 Days PET Nuclei Density NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average (Nuclei/mm2) 787.4 1346 1447 1977 1960 1311 1307 Standard Deviation (Nuclei/mm2) 269.5 599.0 627.3 481.7 620.3 352.8 325.2 n 6 6 6 6 6 6 6 P value* 0.056 0.800 N/A 0.027 0.064 0.986 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Table 9. Qualitative Normalized Average Grading for PET with Timepoints 14, 21, and 28 Days

PET 14 Days NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 0.542 0.638 0.535 0.653 0.722 0.700 0.734 Standard Deviation 0.207 0.239 0.176 0.163 0.150 0.105 0.194 n 9 10 18 9 9 10 8 P value* 0.93 0.20 N/A 0.36 0.89 0.64 N/A PET 21 Days NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 0.700 0.600 0.612 0.594 0.568 0.722 0.609 Standard Deviation 0.169 0.154 0.166 0.111 0.171 0.205 0.245 n 10 10 19 8 11 9 8 P value* 0.19 0.85 N/A 0.87 0.67 0.32 N/A PET 28 Days NKT IL4-ra Balb/cJ NK Mast Cell c57 Deficient Deficient Control Deficient SCID Deficient Control Average 0.725 0.597 0.644 0.648 0.613 0.693 0.615 Standard Deviation 0.142 0.150 0.257 0.215 0.161 0.188 0.180 n 10 9 20 11 10 11 12 P value* 0.36 0.62 N/A 0.69 0.98 0.32 N/A Balb/cJ control for NKT Deficient and IL4-ra Deficient c57 control for NK Deficient, SCID, and Mast Cell Deficient *p values are from one-way ANOVA analyses for immunodeficient data compared to background control

Figure 22: Average Normalized Qualitative Grading for PET with Experimental and Control Groups. Balb/cJ control for NKT Deficient and IL4-ra Deficient. c57 control for NK Deficient, SCID, and Mast Cell Deficient. Data is presented with mean ± standard deviation.

Table 10. One-way ANOVA Testing for Percent Fusion P Values between Two Different Strains for Material PEU.

Group 1 Group 2 P Value Balb/c NKT 0.65 Balb/c IL4 0.87 NKT IL4 0.68

c57 NK 0.64 PEU 14 Day c57 SCID 0.85 c57 Mast Cell 0.91 NK SCID 0.28 NK Mast Cell 0.72 SCID Mast Cell 0.74

Balb/c NKT 0.21 Balb/c IL4 0.002 NKT IL4 0.01 c57 NK 0.09 PEU 21 Days c57 SCID 0.007 c57 Mast Cell 0.06 NK SCID 0.008 NK Mast Cell 0.42 SCID Mast Cell 0.34

Balb/c NKT 0.03 Balb/c IL4 0.59 NKT IL4 0.26 c57 NK 6.14*10-5 PEU 28 Days c57 SCID 0.44 c57 Mast Cell 0.15 NK SCID 1.39*10-4 NK Mast Cell 4.34*10-5 SCID Mast Cell 0.13

Table 11. One-way ANOVA Testing for Percent Fusion P Values between Two Different Strains for Material PET.

Group 1 Group 2 P Value Balb/c NKT 0.558 Balb/c IL4 0.037 NKT IL4 0.076 c57 NK 0.519 PET c57 SCID 0.422 14 Days c57 Mast Cell 0.273 NK SCID 0.275 NK Mast Cell 0.194 SCID Mast Cell 0.965

Balb/c NKT 0.727 Balb/c IL4 0.057 NKT IL4 0.079 c57 NK 0.236 PET c57 SCID 0.918 21 Days c57 Mast Cell 0.453 NK SCID 0.142 NK Mast Cell 0.902 SCID Mast Cell 0.439

Balb/c NKT 0.010 Balb/c IL4 0.192 NKT IL4 0.012 c57 NK 6.73*10-6 PET -5 28 Days c57 SCID 2.11*10 c57 Mast Cell 0.123 NK SCID 3.73*10-3 NK Mast Cell 0.42 SCID Mast Cell 0.015

Table 12. One-way ANOVA Testing P Values between the Percent Fusion for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB/cJ Control.

P Value for 14 Days P Value for 21 Days P Value for 28 Days NKT Deficient 0.55 0.02 0.007 IL4-ra Deficient 0.59 0.001 0.18 Balb/cJ Control 0.04 3.30*10-5 0.07

Table 13. One-way ANOVA Testing P Values between the Percent Fusion for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control.

P Value for 14 Days P Value for 21 Days P Value for 28 Days NK Deficient 0.08 9.01*10-5 0.64 SCID 0.81 2.62*10-5 1.57*10-5 Mast Cell Deficient 0.99 0.008 0.06 c57 Control 0.40 0.75 0.20

Table 14. One-way ANOVA Testing P Values between the Cell Density for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB/cJ Control.

P Value for 14 Days P Value for 21 Days P Value for 28 Days NKT Deficient 0.004 0.61 0.006 IL4-ra Deficient 0.78 0.001 0.50 Balb/cJ Control 0.003 0.13 0.11

Table 15. One-way ANOVA Testing P Values between the Cell Density for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control.

P Value for 14 Days P Value for 21 Days P Value 28 Days NK Deficient 0.65 0.59 0.01 SCID 0.001 0.21 5.53*10-4 Mast Cell Deficient 0.51 0.03 0.12 c57 Control 0.32 0.71 4.70*10-4

Table 16. One-way ANOVA Testing P Values between the Nuclei Density for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB/cJ Control.

P Value for 14 Days P Value for 21 Days P Value for 28 Days NKT Deficient 0.02 0.13 0.74 IL4-ra Deficient 0.49 4.72*10-5 0.81 Balb/cJ Control 0.02 0.38 0.19

Table 17. One-way ANOVA Testing P Values between the Nuclei Density for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control.

P Value for 14 Days P Value for 21 Days P Value for 28 Days NK Deficient 0.19 0.75 0.009 SCID 0.005 3.54*10-2 0.04 Mast Cell Deficient 0.29 4.80*10-4 0.14 c57 Control 0.16 0.43 2.39*10-5

Table 18. One-way ANOVA Testing P Values between the Normalized Grading for the Two Materials, PEU and PET, for Experimental Strain Groups with BALB Control.

P Value for 14 Days P Value for 21 Days P Value for 28 Days NKT Deficient 0.11 0.33 0.046 IL4-ra Deficient 0.20 1.38*10-4 4.67*10-4 Balb/cJ Control 2.21*10-4 5.95*10-4 0.09

Table 19. One-way ANOVA Testing P Values between the Normalized Grading for the Two Materials, PEU and PET, for Experimental Strain Groups with c57 Control.

P Value for 14 Days P Value for 21 Days P Value for 28 Days NK Deficient 0.02 1.27*10-5 0.004 SCID 0.29 0.0247 0.002 Mast Cell Deficient 0.02 0.17 0.005 c57 Control 0.56 0.02 1.10*10-05

Table 20. One-way ANOVA Testing P Values between the Percent Fusion for the Two Time Points with Material PEU.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.01 NKT Deficient 21 28 0.005 NKT Deficient 14 28 0.74

IL4-ra Deficient 14 21 0.24

IL4-ra Deficient 21 28 0.73

IL4-ra Deficient 14 28 0.62 Balb/cJ Control 14 21 1.48*10-5 Balb/cJ Control 21 28 0.008 Balb/cJ Control 14 28 0.007 NK Deficient 14 21 0.02 NK Deficient 21 28 0.13 NK Deficient 14 28 0.63 SCID 14 21 1.75*10-5 SCID 21 28 0.06 SCID 14 28 2.03*10-6

Mast Cell Deficient 14 21 0.048

Mast Cell Deficient 21 28 0.04

Mast Cell Deficient 14 28 2.17*10-4 c57 Control 14 21 0.85 c57 Control 21 28 0.002 c57 Control 14 28 1.85*10-4

Table 21. One-way ANOVA Testing P Values between the Percent Fusion for the Two Time Points with Material PET.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.75 NKT Deficient 21 28 0.02 NKT Deficient 14 28 0.002 IL4-ra Deficient 14 21 0.006 IL4-ra Deficient 21 28 0.27 IL4-ra Deficient 14 28 0.13 Balb/cJ Control 14 21 0.53 Balb/cJ Control 21 28 0.07 Balb/cJ Control 14 28 0.05 NK Deficient 14 21 0.56 NK Deficient 21 28 1.75*10-4 NK Deficient 14 28 0.02 SCID 14 21 0.42 SCID 21 28 0.21 SCID 14 28 0.10 Mast Cell Deficient 14 21 0.16 Mast Cell Deficient 21 28 0.04 Mast Cell Deficient 14 28 0.18 c57 Control 14 21 0.97 c57 Control 21 28 2.87*10-4 c57 Control 14 28 4.83*10-7

Table 22. One-way ANOVA Testing P Values between the Cell Density for the Two Time Points with Material PEU.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.38 NKT Deficient 21 28 0.36 NKT Deficient 14 28 0.17 IL4-ra Deficient 14 21 0.33 IL4-ra Deficient 21 28 0.75 IL4-ra Deficient 14 28 0.61 Balb/cJ Control 14 21 0.51 Balb/cJ Control 21 28 0.48 Balb/cJ Control 14 28 0.10 NK Deficient 14 21 0.20 NK Deficient 21 28 0.44 NK Deficient 14 28 0.10 SCID 14 21 8.58*10-5 SCID 21 28 0.004 SCID 14 28 7.15*10-6 Mast Cell Deficient 14 21 0.82 Mast Cell Deficient 21 28 4.13*10-4 Mast Cell Deficient 14 28 2.52*10-4 c57 Control 14 21 0.77 c57 Control 21 28 0.09 c57 Control 14 28 0.07

Table 23. One-way ANOVA Testing P Values between the Cell Density for the Two Time Points with Material PET.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.001 NKT Deficient 21 28 0.02 NKT Deficient 14 28 2.28*10-5 IL4-ra Deficient 14 21 8.59*10-4 IL4-ra Deficient 21 28 0.02 IL4-ra Deficient 14 28 0.62 Balb/cJ Control 14 21 0.046 Balb/cJ Control 21 28 0.87 Balb/cJ Control 14 28 0.07 NK Deficient 14 21 0.19 NK Deficient 21 28 0.43 NK Deficient 14 28 0.34 SCID 14 21 0.56 SCID 21 28 0.005 SCID 14 28 0.004 Mast Cell Deficient 14 21 0.005 Mast Cell Deficient 21 28 0.75 Mast Cell Deficient 14 28 0.06 c57 Control 14 21 0.95 c57 Control 21 28 0.02 c57 Control 14 28 6.95*10-4

Table 24. One-way ANOVA Testing P Values between the Nuclei Density for the Two Time Points with Material PEU.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.07 NKT Deficient 21 28 8.28*10-4 NKT Deficient 14 28 0.04 IL4-ra Deficient 14 21 0.34 IL4-ra Deficient 21 28 0.80 IL4-ra Deficient 14 28 0.42 Balb/cJ Control 14 21 0.20 Balb/cJ Control 21 28 0.10 Balb/cJ Control 14 28 0.64 NK Deficient 14 21 0.81 NK Deficient 21 28 0.002 NK Deficient 14 28 0.09 SCID 14 21 0.33 SCID 21 28 0.18 SCID 14 28 0.02 Mast Cell Deficient 14 21 0.01 Mast Cell Deficient 21 28 0.006 Mast Cell Deficient 14 28 0.33 c57 Control 14 21 0.51 c57 Control 21 28 0.01 c57 Control 14 28 0.003

Table 25. One-way ANOVA Testing P Values between the Nuclei Density for the Two Time Points with Material PET.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.03 NKT Deficient 21 28 0.44 NKT Deficient 14 28 0.002 IL4-ra Deficient 14 21 0.002 IL4-ra Deficient 21 28 0.003 IL4-ra Deficient 14 28 0.32 Balb/cJ Control 14 21 0.04 Balb/cJ Control 21 28 0.63 Balb/cJ Control 14 28 0.21 NK Deficient 14 21 0.47 NK Deficient 21 28 0.34 NK Deficient 14 28 0.04 SCID 14 21 0.89 SCID 21 28 0.006 SCID 14 28 0.007 Mast Cell Deficient 14 21 1.67*10-5 Mast Cell Deficient 21 28 0.004 Mast Cell Deficient 14 28 0.006 c57 Control 14 21 0.95 c57 Control 21 28 0.11 c57 Control 14 28 0.07

Table 26. One-way ANOVA Testing P Values between the Normalized Grading for the Two Time Points with Material PEU.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.40 NKT Deficient 21 28 0.27 NKT Deficient 14 28 0.06 IL4-ra Deficient 14 21 0.07 IL4-ra Deficient 21 28 0.98 IL4-ra Deficient 14 28 0.09 Balb/cJ Control 14 21 0.43 Balb/cJ Control 21 28 0.40 Balb/cJ Control 14 28 0.95 NK Deficient 14 21 0.03 NK Deficient 21 28 0.64 NK Deficient 14 28 0.01 SCID 14 21 0.22 SCID 21 28 0.047 SCID 14 28 0.005 Mast Cell Deficient 14 21 0.64 Mast Cell Deficient 21 28 0.16 Mast Cell Deficient 14 28 0.46 c57 Control 14 21 0.69 c57 Control 21 28 0.01 c57 Control 14 28 0.006

Table 27. One-way ANOVA Testing P Values between the Normalized Grading for the Two Time Points with Material PET.

Strain Timpoint 1 Timepoint 2 P Value NKT Deficient 14 21 0.08 NKT Deficient 21 28 0.72 NKT Deficient 14 28 0.04 IL4-ra Deficient 14 21 0.68 IL4-ra Deficient 21 28 0.97 IL4-ra Deficient 14 28 0.67 Balb/cJ Control 14 21 0.18 Balb/cJ Control 21 28 0.65 Balb/cJ Control 14 28 0.14 NK Deficient 14 21 0.40 NK Deficient 21 28 0.53 NK Deficient 14 28 0.95 SCID 14 21 0.049 SCID 21 28 0.55 SCID 14 28 0.14 Mast Cell Deficient 14 21 0.77 Mast Cell Deficient 21 28 0.75 Mast Cell Deficient 14 28 0.92 c57 Control 14 21 0.28 c57 Control 21 28 0.96 c57 Control 14 28 0.17

DISCUSSION

In this study, two specific aims were addressed. First, quantitative parameters were measured to evaluate the in vivo development of the foreign body reaction for specific types of lymphocytes. The second aim was to validate qualitative measurements with the quantitative parameters for the foreign body reaction. The first aim was achieved by determining the percent fusion, cell density, and nuclei density. (Figure 15 to Figure 17 and Table 2 to Table 4 for PEU surfaces; Figure 19 to Figure 21 and Table 6 to Table 8 for PET surfaces). Only a few immunodeficient strains showed statistically significant differences by having a p value of less than 0.05 when compared to controls, this was not indicative of participation by the respective specific lymphocyte subset in the in vivo development of the foreign body reaction. In this study, 3 timepoints, 14 days, 21 days, and 28 days, were used for each mice group and material. If the lymphocyte subset participation in the development of foreign body reaction was to occur, all 3 timepoints for the respective knockout strains should show statistically significant differences for percent fusion, cell density, and nuclei density compared to their respective control groups. However, the data from Table 2 to Table 4 for PEU surfaces and Table 6 to

Table 8 for PET surfaces suggest that no strains have statistically significant differences for all three timepoints for percent fusion, cell density, and nuclei density in comparison with the controls for PEU and PET. As a result, the quantitative values show that no specific type of lymphocyte participated in the in vivo development of the foreign body reaction in comparison to their respective background strains.

To validate the quantitative values, parameter comparison for timepoints and materials were made. P values from ANOVA testing for percent fusion at 21 days show

statistically significant differences between PEU and PET (Table 12 to Table 13).

However, only one out of three timepoints showed statistically significant differences,

meaning that PEU and PET did not show clear patterns and trends for differences in

percent fusion. In addition, cell density and nuclei density had few p values that showed

statistically significant differences, but no definite patterns or trends were shown to

determine that PEU and PET had differences in cell density and nuclei density for all

strains and timepoints. The majority of the knock-out systems with their comparable

controls did not clearly identify a lymphocyte subset that played a significant role in the

parameters for foreign body giant cell formation with PEU and PET (Table 14 to Table

17).

The finding of no difference in the development of foreign body giant cell

formation with PEU and PET in this study agrees with a previous study. A study done by

Rodriguez et al. explored the in vivo foreign body giant cell formation for different

materials using the subcutaneous cage implant system for BALB/c and T-cell deficient

nude BALB/c mice [3]. Two parameters, adherent cell density and percent fusion, did

not show differences between PEU and PET for both BALB/c control and nude BABL/c

mice, which shows that PEU and PET demonstrate similar foreign body giant cell

formation for all timepoints. Consequently, both the current study and the previous study

show an identical pattern with foreign body giant cell formation for PEU and PET.

Time point is the final parameter for validation of the quantitative data. P values

from Table 20 to Table 25 show few statistically significant differences for various strains to note. For mast cell deficient, PEU percent fusion and PET nuclei density showed statistically significant difference for the respective time point comparisons.

BALB/c control for PEU material showed statistical significant difference in time points

for percent fusion. SCID mice showed statistically significant differences for 3 time

points for cell density with PEU. NKT deficient mice for cell density with PET showed

statistically significant differences with 3 time points. Although some strains showed

statistically significant differences, no strains for PEU or PET material had statistically

significant differences for all three quantitative parameters: percent fusion, cell density,

and nuclei density. Therefore, trends determined that there are no differences in foreign

body giant cell development for different timepoints ranging from 14 days to 28 days.

For a previous study, adherent cell density between timepoints did not show any apparent trend which is similar to the current cell density p value data [3]. However, higher percent fusion was shown for increasing timepoints with PEU and PET, which the pattern differs from the current percent fusion data [3]. The previous study showed an increase in percent fusion whereas this current study showed no difference in percent fusion.

However, the same statement is given that with increment of time, no specific lymphocyte subset played a significant role in the parameters for foreign body giant cell formation with PEU and PET since immunodeficiency did not alter formation of foreign body giant cells. Ultimately, the current study reflects identical development of foreign body giant cell in regards to time point and material compared to the previous study, which shows that the quantitative parameters are valid.

The second aim focuses the comparison between the qualitative and quantitative data. Similar to the percent fusion, nuclei density, and cell density, no statistically significant difference was determined for the normalized grading when the immunodeficient strains were compared with their respective control background strains

(Table 5 and Table 9). Therefore, the first specific aim within the context of qualitative

data was fulfilled by showing that no specific type of lymphocytes played a factor in the

extent of foreign body reaction. For material, the p value comparison between

normalized grading for the majority of the strain showed a statistically significant

difference for the majority of the strains at timepoints 21 and 28 (Table 18 and Table 19).

However, majority of the strains at 14 days for both PEU and PET did not show a

statistically significant difference. Since only two out of the three time points showed

statistically significant difference, no difference in development of the foreign body

reaction was shown between PEU and PET; the qualitative parameter has similar

assessment of the extent of the foreign body reaction between PEU and PET with the

quantitative parameters. Lastly, the time point comparison for the p values using the normalized grading was similar to the quantitative parameters (Table 26 and Table 27).

Normalized grading showed that no differences were determined during increments of

timepoints. Qualitative assessment patterns in strain, timepoints, and materials indicate

that no lymphocyte subset played a significant role in the extent of the foreign body

reaction. Therefore, the qualitative assessment revealed similar conclusion to the

quantitative calculations. Ultimately, the second specific aim was achieved by showing

that both quantitative and qualitative assessments indicated similar development of the

foreign body giant cell formation.

Although the specific aims were fulfilled for this study, two main issues must be

addressed. In the past in vivo study, the timepoints used were 7, 14, and 21 days [3].

However, for this study the timepoints used were 14, 21, and 28 days. From this study, a

conclusion can be made that the foreign body reaction development is similar at 14, 21,

and 28 days, respectively. Also, no assessment was made for the timepoints earlier than

14 days. A previous study showed similar cell densities for all timepoints, but for foreign

body giant cell formation, no foreign body giant cells at day 7 were seen on nearly all surfaces [3]. However, a previous study by Rodriguez used the cage implant system, while this current study used direct subcutaneous implant of material. The kinetics of the foreign body giant cell formation before 14 days should be determined in future works combined with the 14, 21, and 28 days to generate a quantitative kinetic assessment of the formation of the foreign body reaction. A thorough calculation of the kinetics from day 0 to day 28 will provide more accurate evaluation on the development of the foreign body giant cells.

In this study, the lymphocyte subsets do not participate in the development of the foreign body reaction. The redundant sources of IL-4 are NK cells, NKT cells, and mast cells [10, 16, 40, 41], but all these strains in this study have shown no participation in the extent of foreign body reaction. Previous in vitro studies have shown that IL-4 and IL-13 are two main cytokines that induce formation of foreign body giant cells that are from human derived monocytes [2, 7, 4 - 5, 3 , 41]. In addition, in vivo blockade of IL-4 alters the formation of the foreign body giant cells [5]. Lymphocyte subset sources of IL-4 did not contribute to change in the development of the foreign body reaction. In future studies, IL-13 should be explored to determine changes in the formation of foreign body giant cells. In addition, a study should consist of total IL-4 deficiency coupled with IL-

13 deficiency to determine if both cytokines participate in the in vivo development of the foreign body reaction.

References

1. Anderson JM, Rodriguez A, Chang DT. 2008 Foreign body reaction to biomaterials.

Sem in Immunol 30(2): 86-100.

2. Anderson JM. 2013. Chapter II.2.2. Inflammation, Wound Healing, and the Foreign

Body Response. In: Biomaterials Science: An Introduction to Materials in Medicine,

Eds: BD Ratner, AS Hoffman, FJ Schoen and JE Lemons, Elsevier, New York, 3rd

Edition pp 503-512.

3. Anderson JM, Schoen FJ, Brown SA, Merritt K. 2013. Chapter III.1.5. Implant

retrieval and evaluation. In Biomaterials Science: An introduction to materials in

medicine, Eds: BD Ratner, AS Hoffman, FJ Schoen and JE Lemons, Elsevier, New

York, 3rd Edition pp 1368-1383.

4. Wiggins MJ, Wilkoff B, Anderson JM, Hiltner A. 2001. Biodegradation of polyether

polyurethane inner insulation in bipolar pacemaker leads. J Biomed Mater Res (Appl

Biomater) (58: 302-307).

5. Brodbeck WG, MacEwan M, Colton E, Meyerson H, Anderson JM. 2005

Lymphocytes and the foreign body response: lymphocyte enhancement of

macrophage adhesion and fusion. J Biomed Mater Res 74A:222-229.

6. MacEwan MR, Brodbweck WG, Matsuda T, Anderson JM. 2005.

Monocyte/lymphocyte interactions and foreign body response: in vitro effects of

biomaterial surface chemistry. J Biomed Mater Res 74A:285-293.

7. Chang DT, Jones JA, Meyerson H, Colton E, Kwon IK, Matsuda T, Anderson JM.

2008. Lymphocyte/macrophage interactions: Biomaterial surface-dependent cytokine,

chemokine, and matrix protein production. J Biomed Mater Res 87A:676-687.

8. Chang DT, Colton E, Anderson JM. 2009. Paracrine and juxtacrine lymphocyte

enhancement of adherent macrophage and foreign body giant cell activation. J

Biomed Mater Res 89 A:290-298.

9. Chang DT, Colton E, Matsuda T, Anderson JM. 2009. Lymphocyte adhesion and

interactions with biomaterial adherent macrophages and foreign body giant cells. J

Biomed Mater Res 91 A: 1210-1220.

10. Rodriguez A, Voskerician G, Meyerson H, MacEwan S., Andersno JM. 2007. T cell

subset distributions following primary and secondary implantation at subcutaneous

biomaterial implant sites. J Biomed Mater Res 85A:556-565.

11. Rodriguez A, Meyerson H, Anderson JM. 2009. Quantitative in vivo cytokine

analysis at synthetic biomaterial implant sites. J Biomed Mater Res 89A: 152-159.

12. McNally AK, Anderson JM 1995. Interleukin-4 induces foreign body giant cells from

human monocytes/macrophages. Differential lymphokine regulation of macrophage

fusion leads to morphological variants of multinucleated giant cells. Am J Pathol

147:1487-1499.

13. DeFife KM, Jenney CR, McNally AK, Colton E, Anderson JM. 1997. Interleukin-13

induces human monocyte/macrophage fusion and macrophage mannose receptor

expression. J Immunol 158:3385-3390.

14. Kao WJ, McNally AK, Hiltner A, Anderson JM. 1995. Role of interleukin-4 in

foreign-body giant cell formation on a poly(etherurethane urea) in vivo. J Biomed

Mater Res 29:1267-1275.

15. Gessner A., Mohrs K., Mohrs M. 2005. Mast cells, basophils, and eosinophils acquire

constitutive IL-4 and IL-13 transcripts during lineage differentiation that are

sufficient for rapid cytokine production. J Immunol 174: 1063-1072.

16. Rodriguez A, MacEwan SR, Meyerson H, Kirk JT, Anderson JM. 2009b. The foreign

body reaction in T-cell deficient mice. J Biomed Mater Res 90A: 106-113.

17. Cao X, Shores EW, Hu-Li J, ANver MR, Kelsall BL, Russell SM, Drago J, Noguchi

M, Grinber A, Bloom ET, Paul WE, Katz SI, Love PE, Leonard WJ. 1995. Defective

lyphoid development in mice lacking expression of the common cytokine receptor γ

chain. Immunity 2: 23-238.

18. Yamaoka K, Min Bb, Zhou YJ, Paul WE, and O’Shea JJ. 2005. Jak3 negatively

regulates dendritic-cell cytokine production and survival. Blood 106: 3227-3233.

19. Smiley ST, Kaplan MH, and Grusby MJ. 1997. Immunoglobulin E production in the

absence of interleukin-4-secreting CD1-dependent cells. Science 275: 977-979.

20. Huber S, Sartini D, and Exley M. 2003. Role of CD1d in coxsackievirus B3-induced

myocarditis. J Immunol 170: 3147 – 3153.

21. Noben-Trauth N, Shultz LD, Brombacher F, Urban JF, Gu H, and Paul WE. 1997.

An interleukin 4 (IL-4) independent pathway for CD4+ T cell IL-4 production is

revealed in IL-4 receptor – deficient mice. Immunol 94: 10838-10843.

22. Tono T, Tsujimura T, Koshimizu U, Kasugai T, Adachi S, Isozaki K, Nishikawa S,

Morimoto M, Nishimune Y, and Nomura S. 1992. C-kit Gene was not transcribed in

cultured mast cells of mast cell-deficient Wsh/Wsh mice that have a normal number

of erythrocytes and a normal c-kit coding region. Blood 80: 1448-1453.

23. Duttlinger R, Manova K, Berrozpe G, Chu TY, DeLeon V, Timokhina I, Chaganti

RSK, Zelenetz AD, Bachvarova RF, and Besmer P. 1995. The Wsh and Ph mutations

affect the c-kit expression profile: c-kit misexpression in embryogenesis impairs

melanogenesis in Wshand Ph mutant mice. Genetics 95: 3754-3758.

24. Duttlinger R, Manova K, Chu TY, Gyssler C, Zelenetz AD, Bachvarova F, and

Besmer P. 1993. W-sash affects positive and negative elements controlling c-kit

expression: ectopic c-kit expression at sites of kit-ligand expression affects

melanogenesis. Development 118: 705-717.

25. Liu Q, Tang Z, Surdenikova L, Kim S, Patel KN, Kim A, Ru F, Guan Y, Weng HJ,

Geng Y, Undem BJ, Kollarik M, Chen ZF, Anderson DJ, Dong X. 2009. Sensory

neuron-specific GPCR Mrgprs are itch receptors mediating chloroquine-induced

pruritus. Cell 139: 1353-1365.

26. Allen JD, Jeffer ZM, Park SJ, Burgin S, Hoffmann C, Sells MA, Chen S, Derr-Yellin

E, Michels EG, McDaniel A, Bessler WK, Ingram DA, Atkinson SJ, Travers JB,

Chernoff J, and Clapp DW. 2009. P21-activated kinase regulates mast cell

degranulation via effects on calcium mobilization and cytoskeletal dynamics. Blood

113: 2695-2705.

27. Berrozpe G, Timokhina I, Yukl S, Tajima Y, Ono M, Zelenetz AD, and Besmer P.

1999. The Wsh, W57, and Ph Kit expression mutations define tissue-specific control

elements located between -23 and -154 kb upstream of Kit. Blood 94: 2658-2666.

28. Cable J, Jackson IJ, and Steel KP. 1995. Mutations at the W locus affect survival of

neural crest-derived melanocytes in the mouse. Mech of Devel 50: 139-150.

29. Yamazaki M, Tsujimura T, Morii E, Isozaki K, Onoue H, Nomura S, and Kitamura Y.

1994. C-kit gene is expressed by skin mast cells in embryos but not in puppies of

Wsh/Wsh mice: Age-dependent abolishment of c-kit gene expression. Blood 83: 3509-

3516.

30. Dorshkind K, Keller GM, Phillips RA, Miller RG, Bosma GC, O’Toole M, and

Bosma MJ. 1984. Functional status of cells from lymphoid and myeloid tissues in

mice with severe combined immunodeficiency disease. J of Immunol 132: 1804-1808.

31. Custer RP, Bosma GC, and Bosma MJ. 1985. Severe combined immunodeficiency

(SICD) in the mouse. Am J Pathol 120: 464-477.

32. Bosma MJ and Carroll AM. 1991. The SCID mouse mutant: Definition,

characterization, and potential uses. Annu Rev Immunol 9: 323-350.

33. Prochazka M, Gaskins HR, Shultz LD, and Leiter EH. 1992. The nonobese diabetic

scid mouse: Model for spontaneous thymomagenesis associated with

immunodeficiency. Immunol 89: 3290-3294.

34. Roths JB, Smith AL, and Sidman CL. 1993. Lethal exacerbation of pneumocystis

carinii pneumonia in severe combined immunodeficiency mice after infection by

pneumonia virus of mice. J Exp Med 177: 1193-1198.

35. Nonoyama S, Smith FO, Bernstein ID, and Ochs HD. 1993. Strain-dependent

leakiness of mice with severe combined immune deficiency. J Immunol 150: 3817-

3824.

36. Beamer WG, Shultz KL, Tennent BJ, and Shultz LD. 1993. Granulosa cell

tumorigenesis in genetically hypogonadal-immunodeficient mice grafted with ovaries

from tumor-susceptible donors. Canc Res 53: 3741-3746.

37. Blunt T, Finnie NJ, Taccioli GE, Smith GCM, Demengeot J, Gottlieb TM, Mizuta R,

Varghese AJ, Alt FW, Jeggo PA, and Jackson SP. 1995. Defective DNA-defependent

protein kinase activity is linked to V(D)J recombination and DNA repair defects

associated with the murine scid mutation. Cell 80: 813-829.

38. Christianson SW, Greiner DL, Schweitzer IB, Gott B, Beamer GL, Schweitzer PA,

Hesselton RM, and Shultz LD. 1996. Role of natural killer cells on engraftment of

human lymphoid cells and on metastasis of human T-lymphoblastoid leukemia cells

in c57BL/6J-scid mice and in c57BL/6J – scid bg mice. Cell Immunol 171: 186-199.

39. Paul WE. 1991. Interleukin-4: A prototypic immunoregulatory lymphokine. Blood 77:

1859-1870.

40. Metwali A, de Andres B, Blum A, Elliott D, Li J, Qadir K, Sandor M, Weinstock J.

2002. Th2-type granuloma development in acute murine schistosomiasis is only

partly dependent on CD4+ T cells as the source of IL-4. Eur J Immunol 32: 1242 –

1252.

41. McNally, A.K., Anderson, J.M., 2011. Foreign body-type multinucleated giant cells

induced by interleukin-4 express select lymphocyte co-stimulatory molecules and are

phenotypically distinct from osteoclasts and dendritic cells. Exp and Mole Path 91:

673-681.

Chapter III – Controlling Fibrous Capsule Formation through Long-Term Down-

Regulation of Collagen Type 1 (COL1A1) Expression by Nanofiber-Mediated siRNA

Gene Silencing

INTRODUCTION

The foreign body reaction (FBR) at the tissue–implant interface frequently elicits inflammation, wound healing responses and tissue fibrosis [1–3]. In general, monocytes/macrophages are activated at implant surfaces and modulate local host fibroblast function. This often leads to excessive deposition of collagen matrix around implanted devices, a phenomenon known as fibrous encapsulation [1,2]. Consequently, the formation of fibrous capsule surrounding implants has limited their applications in the form of glial scarring around neural probes [4], fibrotic tissue formation surrounding mammary implants [5,6], loss of glucose biosensor functionality [7] and pacemaker failure [8].While the modification of material surface chemistry/physics [9–12] and the incorporation of biological factors and proteins [13–17] have been developed to improve the biocompatibility of implanted devices, several potential drawbacks have also been reported. The use of a hydrogel-type coating, for instance, may display poor adhesion to the substrate and unacceptable mechanical properties for some applications, and can pose potential safety issues due to the use of chemical cross-linking agents [9,16]. The administration of anti-inflammatory agents, such as dexamethasone, while being able to minimize implantation-associated inflammation, can also inhibit endogenous blood vessel growth [17,18], thereby decreasing blood circulation surrounding the implant [15].

An alternative approach is to utilize RNA interference (RNAi) technology. RNAi

by small-interfering RNA (siRNA) delivery has found useful applications in the

treatment of cancer [19,20] and genetic diseases [21,22]. Its popularity stems from its

ability to knock down virtually any gene of interest, leading to the specific down-

regulation of the target protein. A potential target for modulating fibrous capsule

formation by RNAi is collagen type I, the major component of fibrous tissues [1,2]. The

sustained delivery of siRNA from electrospun poly(caprolactone) [23] and

poly(caprolactone-co-ethylene) (PCLEEP) nanofibers [24] has been demonstrated. The encapsulation of siRNAs protected the degradation of these labile molecules over prolonged time periods and enhanced cellular uptake by seeded cells. Nanofiber scaffolds possess similar architecture as the fibrillar components of the native extracellular matrix.

The biomimicking nature of these constructs may provide physical cues to direct cell fate

[25,26]. In addition, nanofiber topography decreased in vivo fibrous capsule formation and enhanced host–implant integration as compared to smooth, non-porous two- dimensional surfaces [27]. We hypothesize that the sustained release of COL1A1 siRNA from these nanofibers would permit further control over in vivo fibrous capsule formation.

Recently, Takahashi et al. [28] demonstrated that delivery of siRNA against the mammalian target of rapamycin (mTOR) from poly(ethylene glycol) (PEG)-based hydrogels decreased fibroblast proliferation and type I collagen mRNA expression in vitro. However, in vivo, this platform produced no significant reduction in fibrous capsule thickness and mTOR protein level. In this study, we evaluated the efficacy of

COL1A1 siRNA-encapsulated PCLEEP nanofibers in reducing fibrous capsule formation

through in vivo analyses. The transfection reagent TransIT-TKO was used to enable

efficient cellular uptake. However, in order to resolve cytotoxicity issues related to TKO

[24], cell penetrating peptides (CPPs) were introduced as an alternative for siRNA

complexation. CPPs such as MPG and CADY are natural peptide-based molecules that

mediate transfection through the formation of stable non-covalent complexes with nucleic

acids, thereby improving intracellular delivery in vitro [29–33] and in vivo [29,34,35]. In

addition, CPPs induced less cytotoxicity as compared to cationic lipid-based molecules

[36–38] and cationic polymers [38–40]. We evaluated the functionality of PCLEEP nanofibers that encapsulated COL1A1 siRNA–CPP complexes. Such siRNA nanofibers may find useful applications as direct implantable scaffolds or surface modifications to improve tissue–implant integration of medical devices.

MATERIALS AND METHODS

Poly(e-caprolactone-co-ethyl ethylene phosphate) (PCLEEP, Mw: 94,000, Mn:

48,000), with 1% ethyl ethylene phosphate (EEP), was synthesized through bulk ring-

opening polymerization of e-caprolactone and EEP as reported previously [41,42].

Scrambled negative siRNA (denoted as siNEGCy5-labeled oligonucleotides (Cy5-ODN)

diethylpyrocarbonate (DEPC)-treated phosphate-buffered saline (PBS, pH 7.4), DEPC-

treated tris(hydroxymethyl)aminomethane ethylenediaminetetraacetic acid (TE) buffer

(pH 8.0), DEPC-treated water and CPPs (purity >90%) were purchased from 1st Base,

Singapore. The CPPs MPGDNLS (GALFLGFLGAAGSTMGAWSQPKSKRKV) and

CADY (GLWRALWRLLRSLWRLLWRA) were acetylated at their N-terminus and

synthesized with a cysteamide group at their Cterminus. Silencer® COL1A1 siRNA

(denoted as siCOL1A1) targeting the human (NM_000088.3) and rat (NM_053304)

COL1A1 genes was purchased from Ambion (ID #: s3276), USA. The transfection

reagent TransIT-TKO was obtained from Mirusbio, USA. Poly(ecapolactone) (PCL, Mw:

65,000), bovine serum albumin (BSA),2,2,2-trifluoroethanol (TFE, P99.0), tetrahydrofuran (P99.9), chloroform (P99.9), dimethyl sulfoxide (DMSO), Triton X-100,

10% formalin and 100% ethanol were obtained from Sigma-Aldrich, USA. Aerrane_

isoflurane was obtained from Baxter Healthcare Corporation, Deerfield, IL, USA.

Betadine was obtained from The Purdue Frederick Co., Stamford, CT, USA. 0.5%

Marcaine solution was obtained from Abbott Laboratories, North Chicago, IL, USA. All

chemicals were used as received without any further purification.

Electrospinning of siRNA-encapsulated PCLEEP nanofibers Plain PCLEEP nanofibers (control group denoted as PCLEEP) and PCLEEP nanofibers encapsulating siRNA/TKO complexes corresponding to a volume ratio of 1/2 (denoted as siNEG/TKO and siCOL1A1/ TKO when scrambled negative siRNA and siRNA targeting COL1A1 were added, respectively) were fabricated according to previous work [24].

To obtain PCLEEP nanofibers that encapsulated siRNA/CPP complexes, a 20% w/v PCLEEP–TFE solution was prepared. siNEG or si- COL1A1 was reconstituted in

RNase-free water to obtain a stock solution of 50 lM concentration. Thereafter, 15 µL of siRNA was mixed with either 30, 45 or 60 µL of CPP (350 µM of MPG in DEPC-treated water and 370 µM of CADY in 2% DMSO–DEPC-treated water) to obtain volume ratios of 1/2, 1/3 or 1/4 respectively. Thereafter, the mixture was incubated for 20 min and

DEPC-treated TE buffer was then added to obtain a final volume of 100 µL. The siRNA/CPP mixture was then added into 500 µL of PCLEEP solution. The uniform

siRNA/CPP–polymer mixture was dispensed using a syringe pump (New Era Pump) at a

flow rate of 1.5 mL h-1 through a 21G needle and charged at +12 kV (GAMMA high

voltage research, USA) for electrospinning. The polymer supply was set at 12 cm away

from the target. A negatively charged stationary aluminum foil (-4 kV, 5 x 5 cm2) was

used as the target for randomly oriented nanofibers. In order to obtain aligned PCLEEP

nanofibers for in vivo studies, the fibers were deposited directly onto a PCL film that was

mounted on a grounded rotating target (2500 rpm). The spinning process was carried out

at 20–23 ºC and the humidity was 54–58%. The PCL film was obtained by solvent casting 0.15 g mL-1 of PCL–chloroform solution overnight, followed by lyophilization

for 12 h to remove any residual solvents. PCLEEP nanofibers that encapsulated

complexes of siNEG with MPG or CADY, and siCOL1A1 with MPG or CADY, were

fabricated and denoted as siNEG/MPG, siNEG/CADY, siCOL1A1/MPG and siCOL1A1/

CADY, respectively.

SURGICAL IMPLANTATION

Based on previous work [27], aligned electrospun nanofibers minimized the host

response, enhanced tissue–scaffold integration as compared to randomly oriented

nanofibers and elicited a thinner fibrous capsule than 2-D film substrates. Therefore,

aligned PCLEEP nanofibers were used for scaffold-mediated COL1A1 silencing in vivo.

Due to the poor mechanical property along the direction perpendicular to fiber alignment,

all nanofibers were supported on a film to ease implantation. The average thickness of

PCL film was 70.2 ± 8 µm as evaluated by SEM. All materials were sterilized under UV

irradiation for 1 h prior to implantation.

All procedures were approved by the Institutional Animal Care and Use

Committee (IACUC) and NIH Animal Care Guidelines of Case Western Reserve

University. Samples of each material (1 x 2 cm2) were implanted subcutaneously, two per

animal, in the posterior dorsal areas of female Sprague-Dawley rats (6– 8 weeks old,

Charles Rivers Laboratories, North Wilmington, MA, USA) for 2 and 4 weeks. A total of

three animals were used for each group at each time point. The animal studies were

conducted according to our previous protocol [43]. Briefly, the rats were anesthetized by

a gaseous mixture of Aerrane® isoflurane during implantation. Their backs were shaved

and cleaned with surgical- grade Betadine, followed by 100% ethanol. An incision 1.2 cm

in length was made in the skin about 2 cm above the tail and along the midline.

Subcutaneous pockets on both sides of the incision were created by blunt curved forceps

and the sterilized material was then introduced through the incision and positioned within

the pocket and away from the incision site. The insertion procedure was repeated for the

opposite side. The incision was then closed with 9 mm stainless steel surgical wound

clips (Becton Dickinson, Spark, MD, USA) and a small amount of 0.5% Marcaine

solution was applied onto the incision to minimize post-operative discomfort. The rats were maintained on Purina Rat Chow and water at the Animal Research Facilities of Case

Western Reserve University on 12 h light/dark cycles.

HISTOLOGICAL EVALUATION

Histological analyses were performed on the explanted tissues at 2 and 4 weeks using a previously reported protocol [44]. In particular, fibrous capsule measurements were taken in the middle part of the section to reduce artifacts such as the motion effect

and end effects. Fibrous capsule thickness and cell infiltration for each section were

measured as the average thickness at 10 different random locations and were determined

as the average thickness of three sections per explant. Three explants were measured for

each group. Therefore, 90 measurements were determined in each group at each time

point. The stained sections were visualized using light microscopy (Olympus, model No.

IX71) under 4X or 10X magnifications. The thickness of the fibrous capsule (and hence

the cell infiltration) was measured using H & E stained images and confirmed with

Masson’s Trichrome-stained images. ImageJ was used for all measurements.

STATISTICS

All quantitative values were expressed as a mean ± standard error (SE). Statistical

comparisons for fiber diameter, siRNA release kinetics and silencing efficiency were

performed using one-way analysis of variance and Tukey post-hoc tests after verifying

equal variances; a non-parametric test was used for unequal variances. Student’s t-test was used for statistical comparisons involving two samples. p < 0.05 was considered statistically significant.

RESULTS

For all scaffolds, no acute or chronic inflammation or necrosis that was indicative of toxicity was identified at any of the time periods as shown in Figure 1. High magnification histological evaluation (data not shown) also revealed no signs of toxicity.

At each time period, the tissue response at the interface was similar for all samples and no significant difference in the resolution of the inflammatory response and development

82 of granulation tissue and fibrous capsule was observed as expected for a biocompatible

(non-toxic) material scaffold.

Figure 1. Histological images showing fibrous capsule formation and cell infiltration on aligned nanofibers supported on film at (a–h) week 2 and (i–p) week 4 with hematoxylin & eosin staining (left) and Masson’s Trichrome staining (right). The distance between the arrowheads indicates the thickness of the aligned scaffold (without film) with cell infiltration and the thickness of the fibrous capsule. Scale bar = 100 μm.

Figure 2 and figure 1 show the histology tissue sections. In general, the large film thicknesses reflected in the sections are mainly due to the delamination of tissues and artifacts that were introduced during the tissue sectioning process. As indicated by

Masson’s Trichrome staining in blue, thicker collagen deposition was found at the interface between tissues and the supporting film as compared to that on the nanofiber surfaces. Detailed quantitative comparisons at weeks 2 and 4 (Fig. 2a) showed that significantly thicker fibrous capsules were formed around plain PCLEEP nanofibers as compared to siCOL1A1/CADY and siCOL1A1/TKO scaffolds (Fig. 2a, p < 0.05). No significant difference was observed between the CADY and TKO samples. Comparing the results between weeks 2 and 4, a significant decrease in fibrous capsule thickness was observed for the siCOL1A1/CADY and siCOL1A1/TKO samples. In general, the overall decrease in fibrous capsule thickness profile could be ranked as: TKO _ CADY > MPG _

PCLEEP.

As shown in figure 3b and figure 1, cell infiltration into aligned nanofibrous scaffolds was similar amongst samples and was approximately 20–40% after 2 weeks.

This trend remained constant up to week 4. As anticipated, cell infiltration was not observed at the film interface (figure 2 and figure 1) after 4 weeks post-implantation.

Figure 2 Histological images showing the fibrous capsule formation and cell infiltration on aligned nanofibers scaffolds that were supported on films at week 4 with hematoxylin & eosin staining (left) and Masson’s Trichrome staining (right). (a and b) siCOL1A1/CADY and (c and d) PCLEEP samples. The distance between the arrowheads indicates the thickness of the aligned scaffold (without film) with cell infiltration and the thickness of the fibrous capsule.

Figure 3 Quantitative analysis of (a) fibrous capsule thickness and (b) cell infiltration. *p < 0.05, unpaired t-test. % p < 0.05, Mann–Whitney U-test as compared to PCLEEP. #p < 0.05, Mann–Whitney U-test as compared to siCOL1A1/MPG. n = 90 for each transfection agent at each time period, mean ± SE. Scale bar = 100 µm.

DISCUSSION

The efficacy of scaffold-mediated gene silencing in modulating fibrous capsule

formation was verified in vivo. Similar to previous finding [27], nanofibers decreased

fibrous capsule formation as compared to the smooth surface of a film. It appears that

scaffolds with lower porosity are more likely to induce dense fibrous capsule formation,

so the thickness of the fibrous capsule can be greatly reduced when implants are more

porous [10,45,46]. Since the fiber diameter of PCLEEP in this study was similar to PCL

nanofibers [27], the porosity (83%) would not be expected to differ significantly.

Attempts to modulate collagen expression in fibroblasts by gene knockdown were also made previously. Shegogue and Trojanowska [47] and Takahashi et al. [28] demonstrated that in vitro inhibition of mTOR in fibroblasts influenced cell proliferation and collagen type I production. However, despite the success in in vitro gene knockdown, the introduction of mTOR siRNA in vivo using PEG-based hydrogels failed to demonstrate significant reductions in protein knockdown and fibrous capsule thickness after 2 weeks [28]. In contrast, our results demonstrate a significant decrease in fibrous capsule thickness in response to CADY- and TKO-mediated delivery of siCOL1A1 at weeks 2 and 4 as compared to PCLEEP samples. Specifically, the reductions of fibrous capsule thickness at week 4 were 50.5% and 61.9% for CADY and TKO, respectively, as compared to PCLEEP samples (Fig. 3a). The in vivo knockdown efficiency of CADY and TKO as compared to MPG agreed with our in vitro results. Collectively, the results indicated the potential of scaffold-mediated gene-silencing for long-term control of in vivo fibrous capsule formation. It is noted that a significant decrease in fibrous capsule

88 thickness was observed between weeks 2 and 4 for all samples. We believe that this is likely associated with the normal wound healing process, where an increase in density of fibrous capsule with a corresponding decrease in thickness is often observed as collagen type III remodels into collagen type I in mature fibrosis [46]. Although collagen type I is the major component of fibrous capsules, collagen types III and V may also be present.

Therefore, future incorporation of multiple siRNAs into nanofibers for controlling these collagens might be an alternative approach that is more effective in preventing fibrous capsule formation. Future experiments to measure the in vivo siRNA release profile and to evaluate the in vivo efficiency of COL1A1 silencing with respect to endogenous expression should also be conducted to provide informative assessment on the applicability of this gene-silencing platform.

Cell infiltration into the scaffolds is essential for a range of tissue- engineering applications. Contrary to the lack of in vitro cell infiltration that is frequently reported in electrospun scaffolds [48], we observed a degree of cell infiltration into PCLEEP nanofiber scaffolds. Such cell infiltration was also observed in previous study [27].

However, in the latter case, complete cell infiltration was seen as early as 1 week post- implantation. It is possible that variations in the chemistry and hydrophilicity of the polymers may have contributed to the difference in cell infiltration [49,50]. However, the exact reasons remain to be elucidated in further detailed studies. In addition, no significant difference in cell infiltration was observed for siCOL1A/CPP, siCOL1A1/TKO and PCLEEP samples. This suggests that siRNA, CPP and TKO molecules did not alter tissue–scaffold integration.

CONCLUSION

This paper demonstrates ‘‘proof of concept’’ of the in vivo reduction in fibrous capsule thickness through the down-regulation of collagen type I and the feasibility of delivering siCOL1A1 and CPP complexes within nanofiber constructs for scaffold- mediated long-term gene silencing applications. By encapsulating siRNA/CPP complexes within PCLEEP fibers, a sustained release of siRNA was obtained for at least 28 days. In contrast to conventional bolus delivery of siRNA, the sustained availability of siRNA from nanofibers prolonged in vitro silencing of collagen type I production by 2- to 3- fold.

In addition, a significant decrease in in vivo fibrous capsule formation was observed around siCOL1A1/CADY and siCOL1A1/ TKO samples at weeks 2 and 4. The combination of a gene-silencing approach with the biomimicking of nanofibers may find useful applications in regenerative medicine for controlling fibrous capsule formation.

REFERENCES

1. Ratner BD. Reducing capsular thickness and enhancing angiogenesis around implant

drug release systems. J Control Release 2002;78:211–8.

2. Anderson JM. Biological responses to materials. Annu Rev Mater Res 2001;31:81–

110.

3. Hashemi SM, Soudi S, Shabani I, Naderi M, Soleimani M. The promotion of

stemness and pluripotency following feeder-free culture of embryonic stem cells on

collagen-grafted 3-dimensional nanofibrous scaffold. Biomaterials 2011;32:7363–74.

4. Fawcett JW, Asher RA. The glial scar and central nervous system repair. Brain Res

Bull 1999;49:377–91.

5. Destouet JM, Monsees BS, Oser RF, Nemecek JR, Young VL, Pilgram TK.

Screening mammography in 350 women with breast implants: prevalence and

findings of implant complications. Am J Roentgenol 1992;159:973.

6. Joseph J, Mohanty M, Mohanan PV. Role of immune cells and inflammatory

cytokines in regulation of fibrosis around silicone expander implants. J Mater Sci

Mater Med 2010;21:1665–76.

7. Wisniewski N, Moussy F, Reichert WM. Characterization of implantable biosensor

membrane biofouling. Fresenius’ J Anal Chem 2000;366:611–21.

8. Zhao Q, Topham N, Anderson JM, Hiltner A, Lodoen G, Payet CR. Foreign-body

giant cells and polyurethane biostability: in vivo correlation of cell adhesion and

surface cracking. J Biomed Mater Res 1991;25:177–83.

9. Shen MC, Horbett TA. The effects of surface chemistry and adsorbed proteins on

monocyte/macrophage adhesion to chemically modified polystyrene surfaces. J

Biomed Mater Res 2001;57:336–45.

10. Ward WK, Slobodzian EP, Tiekotter KL, Wood MD. The effect of microgeometry,

implant thickness and polyurethane chemistry on the foreign body response to

subcutaneous implants. Biomaterials 2002;23:4185–92.

11. Sanders JE, Lamont SE, Karchin A, Golledge SL, Ratner BD. Fibro-porous meshes

made from polyurethane micro-fibers: effects of surface charge on tissue response.

Biomaterials 2005;26:813–8.

12. Klosterhalfen B, Junge K, Klinge U. The lightweight and large porous mesh concept

for hernia repair. Expert Rev Med Devices 2005;2:103–17.

13. Zuniga J, Fuenzalida M, Guerrero A, Illanes J, Dabancens A, Diaz E, et al. Effects of

steroidal and non-steroidal drugs on the neovascularization response induced by

tumoral TA3 supernatant on CAM from chick embryo. Biol Res 2003;36:233–40.

14. Norton LW, Tegnell E, Toporek SS, Reichert WM. In vitro characterization of

vascular endothelial growth factor and dexamethasone releasing hydrogels for

implantable probe coatings. Biomaterials 2005;26:3285–97.

15. Patil SD, Papadmitrakopoulos F, Burgess DJ. Concurrent delivery of dexamethasone

and VEGF for localized inflammation control and angiogenesis. J Control Release

2007;117:68–79.

16. Ravin AG, Olbrich KC, Levin LS, Usala AL, Klitzman B. Long- and short-term

effects of biological hydrogels on capsule microvascular density around implants in

rats.J Biomed Mater Res 2001;58:313–8.

17. Luo JC, Shin VY, Liu ESL, Ye YN, Wu WKK, So WHL, et al. Dexamethasone

delays ulcer healing by inhibition of angiogenesis in rat stomachs. Eur J Pharmacol

2004;485:275–81.

18. Chigurupati S, Kulkarni T, Thomas S, Shah G. Calcitonin stimulates multiple stages

of angiogenesis by directly acting on endothelial cells. Cancer Res 2005;65:8519–29.

19. Hu W, Lu CH, Han HD, Huang J, Shen DY, Stone RL, et al. Biological roles of the

delta family notch ligand Dll4 in tumor and endothelial cells in ovarian cancer.

Cancer Res 2011;71:6030–9.

20. Stany MP, Vathipadiekal V, Ozbun L, Stone RL, Mok SC, Xue H, et al. Identification

of novel therapeutic targets in microdissected clear cell ovarian cancers. PLoS ONE

2011;6:e21121.

21. Samakoglu S, Lisowski L, Budak-Alpdogan T, Usachenko Y, Acuto S, Di Marzo R,

et al. A genetic strategy to treat sickle cell anemia by coregulating globin transgene

expression and RNA interference. Nat Biotechnol 2006;24:89–94.

22. Leachman SA, Hickerson RP, Schwartz ME, Bullough EE, Hutcherson SL, Boucher

KM, et al. First-in-human mutation-targeted siRNA phase Ib trial of an inherited skin

disorder. Mol Ther 2010;18:442–6.

23. Cao HQ, Jiang X, Chai C, Chew SY. RNA interference by nanofiber-based siRNA

delivery system. J Control Release 2010;144:203–12.

24. Rujitanaroj PO, Wang YC, Wang J, Chew SY. Nanofiber-mediated controlled release

of siRNA complexes for long term gene-silencing applications. Biomaterials

2011;32:5915–23.

25. Bashur CA, Shaffer RD, Dahlgren LA, Guelcher SA, Goldstein AS. Effect of fiber

diameter and alignment of electrospun polyurethane meshes on mesenchymal

progenitor cells. Tissue Eng A 2009;15:2435–45.

26. Chew SY, Mi R, Hoke A, Leong KW. The effect of the alignment of electrospun

fibrous scaffolds on Schwann cell maturation. Biomaterials 2008;29:653–61.

27. Cao HQ, McHugh K, Chew SY, Anderson JM. The topographical effect of

electrospun nanofibrous scaffolds on the in vivo and in vitro foreign body reaction. J

Biomed Mater Res A 2010;93A:1151–9.

28. Takahashi H, Wang YW, Grainger DW. Device-based local delivery of siRNA

against mammalian target of rapamycin (mTOR) in a murine subcutaneous implant

model to inhibit fibrous encapsulation. J Control Release 2010;147:400–7.

29. Moschos SA, Jones SW, Perry MM, Williams AE, Erjefalt JS, Turner JJ, et al. Lung

delivery studies using siRNA conjugated to TAT (48–60) and penetratin reveal

peptide induced reduction in gene expression and induction of innate immunity.

Bioconjug Chem 2007;18:1450–9.

30. Simeoni F, Morris MC, Heitz F, Divita G. Insight into the mechanism of the peptide-

based gene delivery system MPG: implications for delivery of siRNA into

mammalian cells. Nucleic Acids Res 2003;31:2717–24.

31. Crombez L, Aldrian-Herrada G, Konate K, Nguyen QN, McMaster GK, Brasseur R,

et al. A new potent secondary amphipathic cell-penetrating peptide for siRNA

delivery into mammalian cells. Mol Ther 2009;17:95–103.

32. Davidson TJ, Harel S, Arboleda VA, Prunell GF, Shelanski ML, Greene LA, et al.

Highly efficient small interfering RNA delivery to primary mammalian neurons

induces microRNA-like effects before mRNA degradation. J Neurosci

2004;24:10040–6.

33. Lundberg P, El-Andaloussi S, Sutlu T, Johansson H, Langel U. Delivery of short

interfering RNA using endosomolytic cell-penetrating peptides. FASEB J

2007;21:2664- 71.

34. Crombez L, Morris MC, Dufort S, Aldrian-Herrada G, Nguyen Q, Mc Master G, et al.

Targeting cyclin B1 through peptide-based delivery of siRNA prevents tumour

growth. Nucleic Acids Res 2009;37:4559.

35. Moschos S, Williams A, Lindsay M. Cell-penetrating-peptide-mediated siRNA lung

delivery. Biochem Soc Trans 2007;35:807–10.

36. Lehto T, Simonson OE, Mager I, Ezzat K, Sork H, Copolovici DM, et al. A peptide

based vector for efficient gene transfer in vitro and in vivo. Mol Ther 2011;19:1457–

67.

37. Bell H, Kimber WL, Li MW, Whittle IR. Liposomal transfection efficiency and

toxicity on glioma cell lines: in vitro and in vivo studies. NeuroReport 1998;9:793–8.

38. Andersen MO, Howard KA, Paludan SR, Besenbacher F, Kjems J. Delivery of

siRNA from lyophilized polymeric surfaces. Biomaterials 2008;29:506–12.

39. Beyerle A, Irmler M, Beckers J, Kissel T, Stoeger T. Toxicity pathway focused gene

expression profiling of PEI-based polymers for pulmonary applications. Mol Pharm

2010;7:727–37.

40. Moghimi SM, Symonds P, Murray JC, Hunter AC, Debska G, Szewczyk A. A two

stage poly(ethylenimine)-mediated cytotoxicity: implications for gene

transfer/therapy. Mol Ther 2005;11:990–5.

41. Xiao CS, Wang YC, Du JZ, Chen XS, Wang J. Kinetics and mechanism of 2-

ethoxy-2-oxo-1,3,2-dioxaphospholane polymerization initiated by stannous octoate.

Macromolecules 2006;39:6825–31.

42. Wang YC, Li Y, Yang XZ, Yuan YY, Yan LF, Wang J. Tunable thermosensitivity of

biodegradable polymer micelles of poly(epsilon-caprolactone) and polyphosphoester

block copolymers. Macromolecules 2009;42:3026–32.

43. Voskerician G, Shive MS, Shawgo RS, von Recum H, Anderson JM, Cima MJ, et al.

Biocompatibility and biofouling of MEMS drug delivery devices. Biomaterials

2003;24:1959–67.

44. Voskerician G, Gingras PH, Anderson JM. Macroporous condensed

poly(tetrafluoroethylene). I. In vivo inflammatory response and healing

characteristics. J Biomed Mater Res A 2006;76A:234–42.

45. Xie JW, Wang CH. Electrospun micro- and nanofibers for sustained delivery of

paclitaxel to treat C6 glioma in vitro. Pharm Res 2006;23:1817–26.

46. Darby IA, Hewitson TD. Fibroblast differentiation in wound healing and fibrosis. In:

Kwang WJ, editor. International Review of Cytology. Academic Press; 2007. p. 143–

79.

47. Shegogue D, Trojanowska M. Mammalian target of rapamycin positively regulates

collagen type I production via a phosphatidylinositol 3-kinaseindependent pathway. J

Biol Chem 2004;279:23166–75.

48. Dahlin RL, Kasper FK, Mikos AG. Polymeric nanofibers in tissue engineering.

Tissue Eng B – Rev 2011;17:349–64.

49. Rnjak-Kovacina J, Weiss AS. Increasing the pore size of electrospun scaffolds.

Tissue Eng B – Rev 2011;17:365–72.

50. Vaquette C, Cooper-White JJ. Increasing electrospun scaffold pore size with tailored

collectors for improved cell penetration. Acta Biomater 2011;7:2544–57.