Micellized Î±-Cyclodextrin-Based Supramolecular ... - ACS Publications

Article pubs.acs.org/journal/abseba

Micellized α‑Cyclodextrin-Based Supramolecular Hydrogel Exhibiting pH-Responsive Sustained Release and Corresponding Oscillatory Shear Behavior Analysis Anis Abdul Karim,† Pei Lin Chee,† Meng Fai Chan,‡ and Xian Jun Loh*,†,‡,§ †

Institute of Materials Research and Engineering (IMRE), A*STAR (Agency for Science, Technology and Research), 2 Fusionopolis Way, Innovis, Singapore 138634 ‡ Department of Materials Science and Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576, Singapore § Singapore Eye Research Institute, 11 Third Hospital Avenue, Singapore 168751, Singapore S Supporting Information *

ABSTRACT: The fabrication of supramolecular hydrogels from micellized PLLA/DMAEMA/PEGMA polymers with αCD has been explored to design injectable gel formulations for sustained drug release. The tricomponent hydrogels (5% w/ v)/α-CD (10% w/v) were able to sustain protein (BSA and lysozyme) release for 60−120 h at different pH conditions (pH 3, 7 and 10). In-depth rheological analysis highlighted the role of pH in tuning hydrogel behavior upon shear at microscopic level affecting protein release profiles. Protein release involved complex interactions within the network (isoelectric point and diffusion coefficient of the protein, pKa of DMAEMA, and pore size of the hydrogel). Lissajous− Bowditch curves explained the microstructural response to increasing strain which weakened the supramolecular association and collapsed the formation of the porous hydrogel. Power Law was adopted to represent both transport mechanism and drug release phenomena. The release mechanism resulted from a combination of erosion- and diffusion-controlled release (non-Fickian and super case II). KEYWORDS: supramolecular hydrogels, protein release mechanism, Korsmeyer−Peppas model, Lissajous−Bowditch curves

1. INTRODUCTION The need for minimally invasive and efficient delivery of drugs has witnessed vast research and development over the past few years on injectable systems capable of forming polymeric matrices in-situ with targeted and sustained release action of therapeutic payload onto targeted sites.1−6 This approach is highly applicable in surgical implantation procedures where the importance of minimizing or totally avoiding the risk of infection is essential.7,8 “Smart” hydrogels have the ability to release drugs from polymeric matrices triggered by stimuli internal and external to the body such as temperature,9−11 pH,12,13 light,14,15 and magnetism.16,17 External stimuli (aided by devices) and internal stimuli (produced in the body) controlled swelling behavior, network architecture, and mechanical properties of the polymer matrix to exhibit desired drug release.18 In particular, extensive studies have been performed on pH-responsive systems outlined by variations in pH gradients that exist in biological systems.19−24 Recent studies reported supramolecular methods of forming in-situ hydrogels comprising interactions between cyclodextrins (CDs) and poly(ethylene glycol) (PEG)-based polymers.27−33 © XXXX American Chemical Society

The noncovalent nature of supramolecular hydrogels allowed for a tunable response of the soft material and stimuli response to alter supramolecular formation depending on the functional groups attached to the polymeric component.25,26 Delivery of protein therapeutics has gained significant attention in utilizing stimuli responsive supramolecular hydrogels as the delivery depot.27−31 These past studies, although successfully reported stimuli responsive behavior of supramolecular hydrogels in releasing protein, did not address major concerns associated with protein delivery to achieve minimal burst and a sustained long-term release profile. For most cases, burst release happened within 30 min to a few hours and more than 50% protein was released within 24 h.27,29,30 Chee et al. reported 100% protein release within 32 h in a PEO/α−CD supramolecular hydrogel system. This fast release kinetics associated with gel degradation demonstrated unstable characteristics of the proposed hydrogel-release system.29 Received: July 8, 2016 Accepted: October 27, 2016 Published: October 27, 2016 A

DOI: 10.1021/acsbiomaterials.6b00383 ACS Biomater. Sci. Eng. XXXX, XXX, XXX−XXX

Article

ACS Biomaterials Science & Engineering

DMAEMA(3g) tricomponent polymer (5% w/v) and α-CD (10% w/ v). 2.3. Hemolysis. Hemolytic assay of erythrocytes (diluted to 8% (v/v) suspension) from New Zealand white rabbit whole blood was used to determined the toxicity of the polymer. 100 μL of the blood suspension was mixed with 100 μL of the hydrogel solution (concentration range 1−4096 μg/mL) incubated for 1 h at 37 °C. The absorbance (576 nm) obtained was compared with that of the PEG 20 kDa control; untreated erythrocyte suspension; and 4% (v/v) Triton X treated erythrocytes suspension. The absorbance reading will indicate the percentage of hemolysis (release of hemoglobin from the erythrocytes) to determine if the polymers were toxic. This method was adopted from past published papers on hemolysis of erythrocytes.35−41 2.4. Cell Viability. The MTT assay was used to determine polymer cytotoxicity in CCD-112CoN human fibroblast cell lines. PEG-20 kDa was used as the control. DMEM was used to culture the cells with the addition of fetal bovine serum (10%, FBS), penicillin (100 units/mL), and streptomycin (100 μg/mL). This procedure was done at 37 °C under CO2 (5%) and relative humidity atmosphere (95%). The cells were seeded in 96-well plates (density 2 × 104 cells/well) in 100 μL of DMEM/well and incubated for 24 h. This was followed by replacement with fresh culture medium containing polymer solutions at serial concentrations of 10, 5, 2.5, 1.25, 0.625, and 0.313 mg/mL and incubated for another 24 h. Cell viability was determined by measuring the absorbance of MTT crystals (Infinite M200 microplate reader, Tecan, Männedorf, Switzerland, at 570 nm). Triplicates of each polymer concentration were performed and averaged out to determine the cell viability percentage. 2.5. Rheological Studies. The gels prepared were left overnight before analysis, to ensure consistency with the parameters set for protein release. Rheological data were analyzed to study the mechanical properties of hydrogels.42 A TA Instruments Discovery DHR-3 hybrid rheometer with a flat plate geometry (diameter: 20 mm) was used. Frequency sweeps were carried out under a frequency range of 0.01−100 Hz and a constant oscillatory shear strain of 0.1%. Stress amplitude sweep experiments were carried out at an oscillation strain % range of 0.01−100% and a constant frequency of 10 Hz. Amplitude sweeps at 2 strain % points (0.1% and 50%), each strain point with a duration of 300 s, were repeated for 10 cycles to demonstrate the reversible property of the polymer. All tests were performed at 37.0 °C to mimic human body temperature. 2.6. Preparation of Protein-Loaded Hydrogels. Protein release studies were conducted based on modified procedures from our previous studies.43−45 BSA or lysozyme were dissolved into the α-CD buffered stock solutions (0.2 g/mL) of pH 3, 7, and 10. 0.5 mL of the prepared α-CD/protein solution was added to 0.5 mL of polymer solution. Upon mixing the α-CD/protein and polymer solutions, a white gel was formed indicating inclusion complex formation. Even mixing and subsequent overnight standing at room temperature would ensure uniform formation of the gel. These gels were prepared in triplicates for three different pH values (3, 7, and 10) (Table S1). The final composition of hydrogels consist of PLLA(0.5 g)/PEGMA(3g)/ DMAEMA(3g) tricomponent polymer (5% w/v) and α-CD (10% w/ v). 2.7. Collection and Analysis of Samples for the Protein Release Study. To support our earlier hypothesis that a more stable gel network could be developed by designing a hydrogel having micelle architecture with CD, we performed a protein release study to investigate the duration of complete release of BSA and lysozyme. Protein release studies were conducted based on modified procedures from our previous studies.43−45 The CD-based supramolecular hydrogel formed was left to stand overnight. The following day, 5 mL of DI water at pH 3, 7, and 10 was added to different gel vials to simulate pH responsive release of proteins, incubated at 37 °C for 2 h. One milliliter aliquots were withdrawn from each sample solution and replaced with the same amount of fresh DI water of different pH at defined time intervals until no gels were visibility observed. Experiments for each set of pH conditions were done in triplicate. 0.5 mL of the withdrawn aliquots from each sample was quantitated

On the basis of our previous studies, we designed a supramolecular system that provided a potential solution for longer sustained release profiles and better gel stability.32,33 The system involved 2 degrees of association; first, micelle association of poly(L-lactide)/poly[(ethylene glycol) monomethyl ether methacrylate]/poly(dimethylamino ethyl methacrylate) (PLLA/DMAEMA/PEGMA) and second, CDPEGMA inclusion complexation.34 We hypothesized that association of CD with a micellized hydrogel network would create a more stable supramolecular system. This is coupled with the presence of PDMAEMA as a pH-responsive segment to introduce pH-triggered release. Formation of PLLA/DMAEMA/PEGMA polymeric micelles was initiated by self-rearrangement of the PLLA hydrophobic core and DMAEMA/PEGMA hydrophilic corona in aqueous solution. Introduction of α-CD in the micellized system induced intermolecular noncovalent interactions with the PEGMA segment. When strong enough collectively, these interactions would create a physically cross-linked macromolecular hydrogel network. The aim of this study was to analyze the protein release profiles of bovine serum albumin (BSA) and lysozyme (Figure S1), under three pH conditions (pH 3, 7, and 10). These proteins are shown to have pH-responsive behavior depending on their pI and relationship with the pH of the environment.1 Electrostatic attraction/repulsion between the charges on protein and hydrogel matrix at specific pH conditions would affect the overall protein release profile. Rheological tests were done to study the behavior of hydrogels involving dynamic oscillatory shear tests. Further in-depth analysis on oscillatory shear tests and complementary mathematical models aided in the microscopic analysis of material character in relation to protein release profiles. Herein, we exploited the structure of polymeric micelles and their noncovalent interactions with α-CD to form a stable supramolecular hydrogel, and its pH-responsive behavior in the release of BSA and lysozyme at pH values of 3, 7, and 10. Comprehensive study on soft matter behavior was discussed by analyzing rheological data of the hydrogels to correlate with protein release profiles. Material response (G′ and G″) was correlated to shear stress waveforms represented by Lissajous− Bowditch curves (stress vs strain).

2. MATERIALS AND METHODS 2.1. Materials. PLLA(0.5 g)/PEGMA(3g)/DMAEMA(3g) tricomponent polymer was synthesized by Atom Transfer Radical Polymerization (ATRP) and prepared according to the previous procedure.34 For the hydrogel-protein loaded formation, α-CD (98%, TCI); phosphate buffered saline (pH 7.4, diluted 10, Vivantis); hydrochloric acid (HCl, 1M); and sodium hydroxide (NaOH, 1M) (Sigma-Aldrich) were used. Lysozyme (Mw: 14 000 g/mol) and BSA (Mw: 67 000 g/mol) (Sigma-Aldrich) were purchased. For protein release analysis, Coomassie Plus (Bradford) Assay Kit (Thermo Scientific) was used. For cell studies, Dulbecco’s modified Eagle’s medium (DMEM), MTT, and cell culture reagents (Life Technologies, Carlsbad, CA, USA) were used. 2.2. Hydrogel Formation. Phosphate buffered solutions (pH 3, 7, and 10) were prepared. HCl or NaOH was added minimally to attain the desired pH. The ionic strength was kept at 0.1M. All subsequent steps were prepared in triplicate for each pH. Aqueous stock solutions of α-CD (0.2 g/mL) and the PLLA/PEGMA/DMAEMA polymer (0.1 g/mL) were prepared separately by dissolving in DI water. 0.5 mL of α-CD solution was added to 0.5 mL of polymer solution, mixed well, and left to stand overnight to form the hydrogel. The final composition of hydrogels consist of the PLLA(0.5 g)/PEGMA(3g)/ B


Article

ACS Biomaterials Science & Engineering using Coomassie Plus (Bradford) Assay Kit from Thermo Scientific and analyzed with a Shimadzu UV-2501PC spectrophotometer to determine the amount of protein released. 2.8. Erosion Studies. 0.5 mL of the withdrawn aliquots from each sample was collected in preweighed test tubes. Water was removed by evaporation, and the dry solid components were weighed to determine the amount of gel eroded overtime. Experiments were carried out in triplicate for each set of pH conditions.

temperature phase (Table 1). However, thermal degradation of PDMAEMA occurred in two stages with 50% degradation Table 1. Decomposition Temperature and Weight Loss % of Tricomponent Hydrogel and Its Precursors decomposition temperature (°C)

3. RESULTS AND DISCUSSION 3.1. Hemo- and Biocompatibility of Hydrogels. For applications that involved entry through the bloodstream, hemocompatibility or compatibility with blood is an important criterion to address. Therefore, as a preliminary study, the toxicity of the hydrogel against mammalian red blood cells has to be tested to ensure that the material can be used at high concentrations without being detrimental to red blood cells in the body. Blood incompatibility would disrupt red blood cells due to plasma protein adsorption on the material surfaces leading to hemolysis. Previous studies have shown polymer hemocompatibility enhanced by PEGylation.46,47 In this hemolytic study, 8% (v/v) rabbit blood was used to determine the toxicity of hydrogels against mammalian cells. Release of hemoglobin from the erythrocytes was used as an indicator to determine if the polymers were toxic. The greater the release (hemolysis %), the more toxic were the hydrogels. The hydrogels adjusted to either pH 3, pH 7, or pH 10 had undergone 1 h of incubation with the erythrocytes. The percentage values of hemolysis were less than 1% for all gels (Figure S2). The result suggested that the hydrogels were safe to use for antibacterial purposes and could be employed at a high concentration of up to 4 mg/mL without causing adverse impact on the mammalian cells. The MTT assay results showed that the polymer was biocompatible over the tested range of concentrations (0.313− 10 mg/mL), comparable to that of the PEG20 kDa control polymer as shown in Figure 1. In general, the cell viability

PLLA PEGMA PDMAEMA tricomponent hydrogel

decomposition temperature (°C)

start

end

weight loss %

start

end

weight loss %

270 300 265 260

380 440 340 350

100 100 45 30

340 350

450 460

45 65

occurring in each stage. As shown, since the tricomponent hydrogel is composed of all PLLA, PEGMA, and PDMAEMA, the hydrogel exhibited 2 distinct thermal degradation phases (Table 1). The analysis indicated that the degradation profile of the hydrogel was a complex combination of three different components and inclusion complex formation. Nevertheless, the degradation took place at >100 °C, signifying that the material was sufficiently thermally stable to be autoclaved for sterilization purposes. 3.3. Understanding Hydrogel Properties via Dynamic Rheological Tests. Prior to performing protein release studies, dynamic rheological tests were done to understand hydrogel properties at the microscopic level. Rheological study is an important tool in understanding microstructural deformation behavior of complex fluid.48 Information gathered from this analysis would establish the nature of hydrogel properties for correlation with protein release profiles. Frequency sweeps at a constant strain % of 0.1% with a frequency range of 0.01−100 Hz were initially performed (Figure S4(a)) to ensure subsequent amplitude sweep experiments were done within the LVE region. To prove that the hydrogel can be used as an injectable depot, cyclic dynamic oscillatory rheology at two different strain % were performed (Figure S4(b)). The gel demonstrated reversible behavior recovering to the original modulus after being subjected to high strain. This study was done at 2 different strain % points, 0.1% and 50% in each cycle, and repeated over 10 cycles. The immediate recoverable behavior over 10 cycles showed that the material was stable even after being subjected to multiple stress change. In real situations, the gel would be applied intravenously via injection, i.e., subjected to high stress, and the gel modulus would be low and can be easily injected. It would instantaneously revert back to gel state after injection to prevent minimum premature release of the encapsulated payload. Pore size of the hydrogel matrix could be derived from oscillatory strain sweeps carried out within the LVE region, under constant frequency of 10 Hz and oscillation strain % range of 0.01−100% (Figure S4(c)). Hydrogel pore size could be related to effective cross-links between molar weight, Mc, calculated by eq 149,50

Figure 1. Biocompatibility of the tricomponent polymer as compared to the control of PEG20 kDa, with the human fibroblast cells.

would decrease with increasing polymer concentration from approximately 100% to 70%. It should be highlighted that below 5 mg/mL (equivalent to 50% w/v), the polymer exhibits nontoxicity to cells of up to 80%. 3.2. Thermal Stability of Hydrogels. The thermal stability of the hydrogel was determined by thermogravimetric analysis (TGA). Figure S3 shows the TGA results of the tricomponent hydrogel-unloaded protein and its PLLA, PEGMA, and PDMAEMA precursors. Complete thermal degradation of pure PLLA and PEGMA occurred in one

G′ = ρRT /Mc

(1) −3

where ρ is the polymer concentration (g m ), R is the molar gas constant, and T is the absolute temperature. The variation in pore size values was due to complex interactions within the matrix; including hydrophilic−hydrophobic segment, inclusion C


Article

ACS Biomaterials Science & Engineering complex formation, net charge, and hydrophobic interactions. An indirect correlation between 2-dimensional metric length (nm) and 3-dimensional molecular size (kDa) can be made.51 The pore size range varies between 3.44 ± 0.15 and 10.79 ± 0.26 kDa (∼0.45 nm−1.44 nm). It is noteworthy to mention here that the average size of the BSA is 67 kDa and that of the lysozyme is 14 kDa. Lysozyme has a higher probability of being trapped within the matrix system due to small 3-D molecular size. This would suggest a predominant erosion-controlled release profile. In the meantime, BSA would most likely be released by syneresis due to the larger 3-D molecular size as compared to the gel pore size, leading to a predominant diffusion-controlled release profile. 3.4. Protein Release from Hydrogels. Upon addition of α-cyclodextrin/protein solution to the polymer solution, the mixture was vortexed for 10 s to ensure uniform interaction within the protein-loaded gel. The hydrogels were left to stand overnight to stabilize and ensure that all of the protein was adsorbed on the hydrogel before the release study was carried out the next day. This allowed all of the protein to be adsorbed on the hydrogel ensuring 100% loading. 5 mL of DI water at pH 3, 7, and 10 was added to different gel vials to simulate pH responsive release of proteins in a 37 °C water bath. The study indicated 100% protein release when gel was completely dissolved in the DI water. The gels took 60−120 h to release the proteins and fully disintegrate. Pictures of the gel taken just before and after the protein release study are shown in Figure 2.

Table 2. Net Charges of BSA, Lysozyme, and PDMAEMA and Pore Sizes of Hydrogels at pH 3, 7, and 10

pH 3 pH 7 pH 10

BSA (pI = 4.7)

lysozyme (pI = 11)

+ve −ve −ve

+ve +ve +ve

PDMAEMA (pKa = 7.5)

Mca

+ve, hydrophilic partially protonated uncharged, hydrophobic, lone pair of electrons

7.70 ± 0.31 3.44 ± 0.15 10.79 ± 0.26

Calculated from G′ = ρRT/Mc. G′ was derived from oscillatory strain sweeps carried out within the LVE region, under constant frequency of 10 Hz and an oscillation strain % range of 0.01−100% (Figure S4(c)). a

PDMAEMA resulted in swelling of the network due to electrostatic repulsive forces that would minimize the probability of aggregation between inclusion complexes. This pH-dependent swelling or deswelling mechanism would affect the payload release. Typically, swelling of the hydrogel would result in payload release. However, there were reports of drug release during syneresis of the hydrogel.55,56 Hydrogels with pore size smaller than the payload would induce syneresis, “squeezing” the content out of the gel matrix. Complexity would arise when proteins interact within the matrix system. Release kinetics would be affected by protein property and polymer system and changes in pH conditions that influence the overall underlying mass transport mechanism. These distinguishable profiles can be explained by analyzing the hydrogel−protein relationship (Figure 3). Figure 4 shows in vitro BSA and lysozyme release profiles with only 20−45% protein content released over 24 h. This was a much sustained release as compared to the study reported by Chee et al. where almost 80% of protein was released within 24 h.29 The explanations below identify various factors that affect release profiles. 3.4.1. Comparison among the Three pH Conditions for Each Protein Release. At pH 3, positively charged BSA and protonated tertiary amine groups of DMAMEA induced electrostatic repulsive forces within the matrix system. This was aided by the syneresis mechanism whereby BSA would be “squeezed” out of the gel since BSA has bigger molecular size than the pores. At pH 7, interactions between positively charged BSA and the hydrogel would be stronger due to interactions with partially protonated DMAEMA. Therefore, release would be slower than that at pH 3. At pH 10, release would be the slowest. A possible occurrence could be due to some BSA trapped in the hydrogel and the presence of hydrophobic interactions between the BSA and matrix system. In the case of lysozyme, at pH 3 the positively charged lysozyme and protonated tertiary amine groups of DMAMEA induced electrostatic repulsive forces within the matrix system. At the same time, lysozyme being 5 times smaller than BSA would have more free motion in the hydrogel network to induce fast release. At pH 7, interactions between the positively charged lysozyme and hydrogel would be stronger due to the partially protonated DMAEMA. Therefore, release would be slower than that at pH 3. pH 10 would lead to the strongest interaction due to lone pair DMAEMA−positive charge lysozyme interactions. There was a strong possibility that the positively charged lysozyme interacted with the nonprotonated lone pair of DMAEMA. This strong interaction prevented the lysozyme from being released, therefore enhancing erosioncontrolled mechanism of the protein at pH 10. 3.4.2. Comparison between BSA-Loaded and LysozymeLoaded Gel Release Profiles. The exponential type of BSA

Figure 2. Gel (a) before and (b) after a protein release study indicated complete dissolution of gel.

In protein release studies, isoelectric point (pI) of the protein which influenced the release mechanism had to be taken into account. Table 2 summarizes the net charges on proteins (BSA and lysozyme) and PDMAEMA segments at the three tested pH conditions. The calculated pore sizes of hydrogels are also summarized in the table. At physiological pH 7.4, carboxylic groups (−COOH) of BSA (pI 4.7) will be in deprotonated form (−COO−) with a net negative charge.52 A similar explanation is applied to lysozyme with a pI of 11.53 PDMAEMA has an average pKa of 7.5, and a pH below the pKa will render the DMAEMA segment protonated and highly hydrophilic (from [N(CH3)2] to [NH+(CH3)2]).54 Noncovalent interactions within the polymer matrix decreased with decreasing pH solution.34 Therefore, at low pH, these cationic charges on the D


Article


The approximate diffusion coefficient ranges for BSA and lysozyme are (4.98 to 8.21) × 10−7 cm2 s−1 and (1.15 to 1.56) × 10−6 cm2 s−1, respectively, in a 37 °C solution.57 This implied that BSA resisted diffusion within the porous hydrogel matrix (i.e., small diffusion coefficient). This explanation is different from the above diffusion controlled correlation involving hydrogel−protein charge interaction. This discrepancy therefore suggested that the protein release mechanism involves complex interactions that cannot be defined by one particular mathematical model or theory. The protein release profiles drew one major conclusion: release mechanism of protein from a hydrogel matrix involved complex interactions within the matrix. As shown, multiple factors affected the release mechanism of protein from the hydrogel matrix, which resulted in the complexity of the release profiles. Complex interactions within the network, which included factors such as pI of protein, size of protein, diffusion coefficient of protein, hydrophobic interaction between the polymer matrix and protein, and net charge of the hydrogel matrix provided a more credible rationale that resulted in two very different release profile curves. 3.5. Erosion Studies. Figure 5 establishes the relationship between polymer dissolution and amount of protein released.

Figure 3. Schematic representation of the proposed mechanisms at different conditions (a) pH 3, BSA (+ve), Lys (+ve), and PDMAEMA (+ve, hydrophilic); (b) pH 7, BSA (−ve), PDMAEMA (partially protonated); (c) pH 7, Lys (+ve) and PDMAEMA (partially protonated); (d) pH 10, BSA (−ve), PDMAEMA (uncharged, hydrophobic); (e) pH 10, Lys (+ve) and PDMAEMA (uncharged, hydrophobic).

Figure 5. Protein release from hydrogel loaded with (a) BSA and (b) lysozyme, plotted against the erosion profile of a tricomponent polymer/α-CD gel at different pH conditions. The dotted line depicts ideal conditions, y = x, whereby the erosion rate is directly proportional to protein release.

Using a y = x plot (erosion rate directly proportional to protein release) as a basis, distinct concave- and convex-shaped trends can be observed. Highlighting lysozyme release at pH 3 and pH 10, the pH 3 concave-shaped graph portrayed fast protein release depicting enlarged pore size due to electrostatic repulsive forces existing between positively charged DMAEMA in the network. This trend demonstrated that two factors affected the release: diffusion of protein and erosion of gel. At pH 10, a convex-shaped graph correlating slower protein release depicted interactions between the protein and polymer matrix retaining the protein and resisting fast release.

Figure 4. In vitro release profiles of (a) BSA and (b) lysozyme, at pH conditions of 3, 7, and 10.

release curve revealed that it was predominantly diffusion mediated. This was expected because BSA was released by syneresis due to the larger 3-D molecular size as compared to the pore size. On the other hand, the S-shaped type of lysozyme release curve depicted predominant erosion mediated release mechanism. The stronger the interaction with the gel matrix, the more predominant the erosion-controlled release. Because of its smaller size, it would be trapped in the pores and released together with gel erosion. pH 10 of lysozyme release showed a very distinct erosion-controlled release mechanism because the positively charged lysozyme interacted with the nonprotonated lone pair of DMAEMA, leading to stronger interaction.

4. OSCILLATORY SHEAR BEHAVIOR ANALYSIS Rheological studies were performed to correlate mechanical properties of the hydrogels with a release rate of proteins at different pH conditions. Current commercial rheometer software obtains models to assist in interpreting results via oscillatory shear behavior analysis. Such studies were necessary E


Article

ACS Biomaterials Science & Engineering to understand the microscopic behavior of fluid subjected to deformation in the nonlinear viscoelastic (LVE) region. Oscillatory shear tests described by Hyun et al. reflect useful additional information on the elastic and viscous behavior of supramolecular hydrogels upon stress Figure S5. Data generated in the non-LVE region, where the oscillatory shear test called LAOS (large amplitude oscillatory shear) could be associated with microstructural change of the material. Oscillation strain sweep experiments were done at a strain % range of 0.01−100% and a constant frequency of 10 Hz. This study goes into in-depth analysis of fluid behavior beyond the moduli (G′ and G″) data provided by the rheometer. Rheological analysis of our hydrogels demonstrated that they belong to LAOS Type III (weak strain overshoot). The characteristics of Type III are (1) G″ maximum, (2) G′−G″ crossover, and (3) strain thinning (Figure 6). Consisting of

interpretation could be justified by a network model based on the degree of interaction energy whereby competition existed between creation f(t) and rupture g(t) of network junctions within the sample.61 This response demonstrated a robust feature of soft glassy materials,58,62−71 including our soft hydrogel spheres dispersed in water.72 4.1. Network Model. Sim et al. developed a network theory to describe the relationship between network segments and junctions which would affect the complex LAOS behavior.61 Sim et al. used empirical functional relationships to represent f(t) and g(t) as exponential functions of shear stress σ12 (t):

f (t ) = exp(a|σ12(t )|)

(2)

g (t ) = exp(b|σ12(t )|)

(3)

where a and b constants are model parameters that represent creation and loss rates, respectively. In the case of our hydrogels, micellized tricomponent polymers (segments) were joined via the inclusion complexes (junctions) formed between the PEGMA of the micellized structures and α-CD. Subjected to varying shear stress, the magnitude of creation f(t) and loss rates g(t) of segments and junctions would change accordingly. Even though this prediction would not provide adequate quantitative analysis, it predicted the generic behavioral mechanism of LAOS deformation unavailable with conventional rheological measurements. Subsequently, the LAOS behavior was closely related to the material’s internal microstructure and molecular interactions, affecting nonlinear response. On the basis of the network model (eqs 2 and 3), creation and loss rate parameters of Type III fluid behavior were positive (a > 0, b > 0), with destruction rate growing faster than that of creation (a < b) and concurrent increase of both parameters with strain amplitude. The positive creation rate exponent (a) depicted an increase in interactions between segments of micellized tricomponent polymers in the network. The positive loss rate exponent (b) arose from overall decrease of both G′ and G″ when subjected to a larger strain amplitude. The distinct feature of Type III (overshoot of G″) could be a result of the balance between formation (creation rate exponent, a) and the destruction (loss rate exponent, b) of the network junctions. Specifically, the G″ maximum value is more dependent on the creation rate parameter a than loss rate parameter b. 4.2. Relationship between Power Law Exponents of G′/ G″ and Material Stability. All three hydrogels showed deviation from harmonic response beyond ∼0.1−0.2%

Figure 6. Schematic illustration of the oscillation strain sweep test of a hydrogel at pH 7, subjected to 0.01%−100% strain and a constant frequency of 10 Hz at 37 °C. This sweep test showed that the hydrogels belong to Type III complex fluid behavior.

only supramolecular interactions to hold the micellar polymer matrix in hydrogel form, the overall structure was relatively weak.58 The hydrogel structure would resist against deformation up to maximum strain before fluid behavior of the gel sets in. This critical strain applied would result in a slight increase in G″ due to dissipation of internal energy caused by rearrangements of the network structure.59 Beyond this critical strain, shear-induced fluidization occurred, where the polymer chains aligned with the flow field, and G″ decreased.60 This

Figure 7. Strain thinning gradient values marked by power law exponents υ′ and υ″. Strain sweep test at a fixed frequency of 10 Hz. υ′/υ″ ratio values for all three hydrogels increases with increasing pH (a) pH 3 1.46, (b) pH 7 1.74, and (c) pH 10 1.81. F


Article

ACS Biomaterials Science & Engineering oscillation strain (γ%) (i.e., LAOS region). The strain thinning region observed for 0.1 ≤ γ% ≤ 100 in Figure 7 was marked by decreasing power laws, G′(γ%) ∼ γ%−υ′ and G″ (γ%) ∼ γ%−υ″. The values of the power law exponents υ′ and υ″ were close to those found in soft hydrogel systems.73,74 For all pH conditions, the strain thinning region G′(γ%) exhibited power law exponents higher than G″(γ%). This signified dominance of deformation and viscous relaxation (deviation from elastic behavior) with increasing γ%. The power law exponent ratio υ′/υ″ revealed the implication of strain % on material microstructure. The higher the υ′/υ″ value, the higher is the deviation from elastic relaxation and the lower is the resistance to deformation. Interestingly, this study showed that the material easily deformed with increasing pH. The presence of positive charges in the matrix at pH < pKaDMAEMA imparted certain stability to the network, i.e., without these charges, the matrix would behave in a hydrophobic and brittle manner, easily susceptible to deformation. 4.3. Relationship between Sinusoidal Waveforms and Lissajous−Bowditch Curve. G′ and G″ data extracted from the rheometer only provided apparent moduli response values (i.e., the first harmonic contribution). However, to completely understand fluid behavior, there is a need to analyze the nonLVE response with higher-order contributions (i.e., the oscillation in an anharmonic region) of the distorted stress waveforms. Further in-depth analysis on oscillatory shear tests provided information about microstructure interaction when the material was subjected to sinusoidal deformation. This determined the mechanical response as a function of time. A parametric plot of stress vs strain or stress versus rate of strain (Lissajous−Bowditch curve) is required to understand the nonlinear behavior.75,76 See Figure S6 for an explanation of the Lissajous−Bowditch curve. Rothstein et al. described below the mathematical derivation of the LAOS test in dynamic oscillatory shear rheology.77 A sinusoidal strain equation: γ(t ) = y0 sin(ωt )

Figure 8. Sinusoidal waveforms for stress and strain functions of a hydrogel formed at pH 7, under 10% oscillatory strain %, at a frequency of 10 Hz at 37 °C.

Therefore, the first harmonic contribution (n = 1) did not fully describe the fluid behavior beyond the LVE limit. There was a need to account for fluid behavior beyond the LVE limit of higher harmonics (n > 1). A graphical approach developed known as the Lissajous−Bowditch curve (stress vs strain curve) explained the progressive transition of fluid behavior from linear to nonlinear viscoelastic nature (Figure 8). The Lissajous−Bowditch patterns took on distinctively different shapes upon increasing strain amplitude, i.e., distorted from ellipsoid to a rounded parallelogram. 4.4. Relationship between the Lissajous−Bowditch Pattern and Protein Release−Gel Erosion % Profiles. A parallel observation can be established between protein release−gel erosion % profiles (Figures 4 and 5) and the Lissajous−Bowditch pattern (Figure 9). In the release profiles, it was ascertained that the release of proteins was not solely determined by simple diffusion. The stability of the gel determined from power law exponents of G′/G″ (Figure 7)

(4)

For small strain amplitudes, where stress response is sinusoidal and within LVE region, the equation is σ(t ) = σ0 sin(ωt + δ)

(5)

It can also be rewritten as σ(t ) = γ0[G′1(ω1)sin(ω1t ) + G″1(ω1)cos(ω1t )

(6)

where y0 is the input strain amplitude; ω = 2πf is the input angular frequency; σ0 is the stress amplitude; t is time; and δ is the phase lag (loss angle). However, beyond a critical input strain amplitude value, the stress response becomes nonlinear (shear thinning occurs), and the phase lag gets bigger. The stress is no longer sinusoidal and has higher harmonic contributions. The equation is rewritten as, σ(t , γ , ω) =

∑ σn sin(nω1t + δn)

(7)

where (n > 1) represents higher harmonic stress components. A real-time sinusoidal waveform (Figure 8) showed distortion of the stress signal tilted forward with a sinusoidal shape. With increasing input strain amplitude, this “out-ofphase” phenomenon i.e., distortion and increase in δ would intensify (Figure S7).

Figure 9. Lissajous−Bowditch curves (stress (y-axis) vs strain (x-axis)) of hydrogels formed at three different pH conditions, arranged from small to large strain amplitude (0.01%−100%), at a fixed frequency of 10 Hz. G


Article


dominated by short-range noncovalent interaction potential within the polymer/α-CD matrix, i.e., “stick”. When higher strain was applied, the supramolecular association was weakened/destroyed, i.e., “slip”.

supported this claim by analyzing the implication of strain % on material microstructure at varying pH conditions, with the material easily deformed with increasing pH. The stability of gel structure could be further corroborated with the Lissajous− Bowditch pattern (Figure 9). Hydrogel network deformation in the LAOS region resulted internal rearrangement of within the gel microstructure.78 The molecular structure of the hydrogel was based on α-CD interaction with micelle structures of linear hydrophobic PLLA segment and random hydrophilic PEGMA/DMAEMA segments, with charged DMAEMA side chains at pH < pKa of DMAEMA.34 In aqueous solution at 37 °C, the micelles selfassembled by association with α-CD to form a supramolecular hydrogel network. Therefore, at low strain amplitude the material behaved like a soft-gel with sinusoidal waveform. Beyond a critical strain amplitude input, the stress response became nonlinear (shear thinning occurred) and no longer sinusoidal. At higher strain, waveform shapes took on rectangular forms. The shape evolution of the distorted stress waveforms of Lissajous−Bowditch curves could be correlated to the occurrence of interactions within the hydrogel matrix (Figure 10). Graham et al. explained (“stick”) fluid elasticity

5. KINETIC ANALYSIS OF DISSOLUTION DATA In addition to rheology, mathematical models for drug release studies played a significant role in establishing a mechanism of drug release and provided more general guidelines for further development. Different mathematical models have been developed as an instrumental tool to understand the drug release mechanism from delivery systems to overall enhance the safety and therapeutic efficacy of drugs. Random selection of mathematical variables has been successful in modeling drug delivery systems. However, selecting the right mathematical model still remains a challenging task because of the heterogeneous nature of the polymer matrix coupled with complex drug interaction. Nevertheless, adopting a mathematical model is essential to optimize the release kinetics, understand the underlying mass transport mechanism, and accurately predict drug release profiles. In this study, the Korsmeyer−Peppas model (power law) was adopted because it is one of the more seemly apt models to study drug release mechanisms in a polymeric system. This well-known exponential equation model was derived by Korsmeyer et al. in 1983.80 The first 60% drug release data were fitted to this equation model: M t /M 0 = Kt n

(8)

where Mt/M0 is the fraction of drug released; t = time; K = constant (geometrical and structural form of dosage); and n = release component (represents drug release mechanism). To determine the release exponent, log values of the percentage of drug dissolved was plotted against log time: log (Mt/M0) = log K + n log t, where n = 1, the release is zero order; at n = 0.5, the release is best described by the Fickian diffusion; at 0.5 < n < 1, the release is through anomalous diffusion (non-Fickian) (anomalous transport (non-Fickian) denotes a combination of both diffusion and erosion controlled drug release); and n > 1 indicates super case II release (super case II refers to only erosion of the polymeric chain81,82). Figure S8 established the Korsmeyer−Peppas model to describe the release kinetics of BSA and lysozyme at pH (a) 3, (b) 7, and (c) 10. The most significant inference from this model revealed that the release mechanism of BSA at pH 7 was primarily by erosion of the gel (Table 3). This was possible since electrostatic attraction existed between BSA and the polymer matrix and limits the release. Hence, gel erosion was a dominant factor in the release mechanism. Since lysozyme is lighter than BSA, it has more free motion within the hydrogel matrix. This led to faster release for both pH 3 and pH 7 conditions. pH 10 is the slowest due to the lone pair DMAEMA−positive charge lysozyme interaction.

Figure 10. Proposed hydrogel microstructure upon shear, and the corresponding Lissajous−Bowditch curves comparison between γ0 % = 0.01 and γ0 % = 100.

and “slip”(fluid deformation) dynamics to demonstrate such nonlinear behavior.69,79 At low strain, the behavior was

Table 3. Release Exponent (n) and Transport Mechanism Prediction Based on the Korsmeyer−Peppas Model 3 pH

BSA

release exponent (n) 0.7483 transport nonfickian diffusion mechanism

7

10

Lys

BSA

Lys

BSA

Lys

1.3872 super case II transport



0.7936 nonfickian diffusion


H



■

6. CONCLUSION The fabrication of pH-responsive micellized supramolecular hydrogel-loaded protein was explored in this study. The system proved longer gel stability with sustained protein release for 60−120 h. pI of proteins and pKa of the PDMAEMA segment played significant roles in affecting the overall pH-responsive release mechanism. Electrostatic interaction between the charges on protein and the DMAEMA segment of the hydrogel matrix at specific pH conditions affected the swelling or syneresis of the system. In-depth rheological analysis highlighted the role of pH in tuning hydrogel behavior upon shear at the microscopic level affecting protein release profiles. Oscillatory shear behavior analysis revealed complex fluid behavior of the hydrogels: LAOS type III behavior. The shape evolution of distorted stress waveforms of Lissajous−Bowditch curves confirmed the behavior of the microstructures when subjected to low to high strain, whereby the supramolecular association weakened and collapsed the formation of the porous hydrogel, with increasing strain. However, these stress waveforms seen in both rheological measurements and mathematical simulations were just one of the many models adopted. Complex interactions between the polymer matrix and protein, pore size of the hydrogels, and diffusion coefficient of protein were some of the challenges faced by rheologists when associating rheological measurements collected with changes in the material microstructure. Comprehensive studies need to be carried out to fully understand the chemistry and physical mechanism of complex fluids. Recent studies used “high sensitivity Fourier transform (FT) rheology” to analyze higher harmonic contributions in LAOS. This method converts stress data as a function of time into spectra in the Fourier domain with respect to their amplitude, phase angles, and frequencies.76 A mathematical model is an important precursor for predicting the elucidation of the exact behavior of drug release profiles from delivery systems. In this study, we adopted the Korsmeyer−Peppas model to represent both transport mechanism and drug release diffusion phenomena. The model inferred a release mechanism by both diffusion and erosion (non-Fickian and super case II). With numerous mathematical models to adopt, it is difficult to identify and develop the appropriate mathematical theory as there is no general model covering all of the possible chemical and physical processes that can occur in the complex system. Nevertheless, these studies provide preliminary data as a foundation to further expand research on injectable supramolecular hydrogels for sustained/triggered release.

■

Article

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We thank Dr. Aung Thet Tun for the blood collection, Ms. Eunice Goh Tze Leng for her guidance in the experiments, and the members of SERI for their useful comments and suggestions on hemolysis studies. We also thank the funding agency, Agency for Science, Technology and Research (A*STAR), Singapore.

■

REFERENCES

(1) Gupta, P.; Vermani, K.; Garg, S. Hydrogels: from controlled release to pH-responsive drug delivery. Drug Discovery Today 2002, 7 (10), 569−579. (2) He, C.; Kim, S. W.; Lee, D. S. In situ gelling stimuli-sensitive block copolymer hydrogels for drug delivery. J. Controlled Release 2008, 127 (3), 189−207. (3) Liow, S. S.; Dou, Q.; Kai, D.; Karim, A. A.; Zhang, K.; Xu, F.; Loh, X. J. Thermogels: In Situ Gelling Biomaterial. ACS Biomater. Sci. Eng. 2016, 2 (3), 295−316. (4) Li, Z.; Ye, E.; David; Lakshminarayanan, R.; Loh, X. J. Recent Advances of Using Hybrid Nanocarriers in Remotely Controlled Therapeutic Delivery. Small 2016, 12 (35), 4782−4806. (5) Li, Z.; Yang, J.; Loh, X. J. Polyhydroxyalkanoates: opening doors for a sustainable future. NPG Asia Mater. 2016, 8, e265. (6) Li, Z.; Loh, X. J. Recent advances of using polyhydroxyalkanoatebased nanovehicles as therapeutic delivery carriers. Wiley Interdiscip. Rev.: Nanomed. Nanobiotechnol. 2016, DOI: 10.1002/wnan.1429. (7) Gutowska, A.; Jeong, B.; Jasionowski, M. Injectable gels for tissue engineering. Anat. Rec. 2001, 263 (4), 342−9. (8) Packhaeuser, C. B.; Schnieders, J.; Oster, C. G.; Kissel, T. In situ forming parenteral drug delivery systems: an overview. Eur. J. Pharm. Biopharm. 2004, 58 (2), 445−455. (9) Lee, J. W.; Hua, F.-j.; Lee, D. S. Thermoreversible gelation of biodegradable poly(ε-caprolactone) and poly(ethylene glycol) multiblock copolymers in aqueous solutions. J. Controlled Release 2001, 73 (2−3), 315−327. (10) Ruel-Gariépy, E.; Leroux, J.-C. In situ-forming hydrogels review of temperature-sensitive systems. Eur. J. Pharm. Biopharm. 2004, 58 (2), 409−426. (11) Khodaverdi, E.; rajabi, O.; Farhadi, F.; Jalali, A.; Mirzazadeh Tekie, F. S. Preparation and Investigation of Poly (N-isopropylacrylamide-acrylamide) Membranes in Temperature Responsive Drug Delivery. Iranian Journal of Basic Medical Sciences 2010, 13 (3), 102− 110. (12) Zhang, S.; Bellinger, A. M.; Glettig, D. L.; Barman, R.; Lee, Y.-A. L.; Zhu, J.; Cleveland, C.; Montgomery, V. A.; Gu, L.; Nash, L. D.; Maitland, D. J.; Langer, R.; Traverso, G. A pH-responsive supramolecular polymer gel as an enteric elastomer for use in gastric devices. Nat. Mater. 2015, 14 (10), 1065−1071. (13) Yu, J.; Ha, W.; Chen, J.; Shi, Y.-p. pH-Responsive supramolecular hydrogels for codelivery of hydrophobic and hydrophilic anticancer drugs. RSC Adv. 2014, 4 (103), 58982−58989. (14) Knežević, N. Ž .; Trewyn, B. G.; Lin, V. S. Y. Light- and pHResponsive Release of Doxorubicin from a Mesoporous Silica-Based Nanocarrier. Chem. - Eur. J. 2011, 17 (12), 3338−3342. (15) Choi, S. K.; Verma, M.; Silpe, J.; Moody, R. E.; Tang, K.; Hanson, J. J.; Baker, J. R., Jr A photochemical approach for controlled drug release in targeted drug delivery. Bioorg. Med. Chem. 2012, 20 (3), 1281−1290. (16) Meenach, S. A.; Hilt, J. Z.; Anderson, K. W. Poly(ethylene glycol)-based magnetic hydrogel nanocomposites for hyperthermia cancer therapy. Acta Biomater. 2010, 6 (3), 1039−1046.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsbiomaterials.6b00383. Schematic representation of the native BSA and lysozyme structures, hydrogel/protein loading composition at different pH conditions, hemolysis profile, TGA curves, frequency sweep and cyclic amplitude sweep with pore size determination, schematic diagram of LAOS behavior, Lissajous−Bowditch representations, stress data, and Lissajous patterns of hydrogels, and the Korsmeyer−Peppas model to describe release kinetics (PDF) I


Article

ACS Biomaterials Science & Engineering (17) Li, Y.; Huang, G.; Zhang, X.; Li, B.; Chen, Y.; Lu, T.; Lu, T. J.; Xu, F. Magnetic Hydrogels and Their Potential Biomedical Applications. Adv. Funct. Mater. 2013, 23 (6), 660−672. (18) Lowman, A. M.; Brannon-Peppas, L. Hydrogels. In Controlled Drug Delivery; Mathiowitz, E., Ed.; John Wiley & Sons: New York, 1999; Vol. 1, pp 397−418. (19) Patel, V. R.; Amiji, M. M. Preparation and characterization of freeze-dried chitosan-poly(ethylene oxide) hydrogels for site-specific antibiotic delivery in the stomach. Pharm. Res. 1996, 13 (4), 588−93. (20) Bilia, A.; Carelli, V.; Di Colo, G.; Nannipieri, E. In vitro evaluation of a pH-sensitive hydrogel for control of GI drug delivery from silicone-based matrices. Int. J. Pharm. 1996, 130 (1), 83−92. (21) Dragan, E. S.; Apopei, D. F. Synthesis and swelling behavior of pH-sensitive semi-interpenetrating polymer network composite hydrogels based on native and modified potatoes starch as potential sorbent for cationic dyes. Chem. Eng. J. 2011, 178, 252−263. (22) Ferreira, L.; Vidal, M. M.; Gil, M. H. Evaluation of poly(2hydroxyethyl methacrylate) gels as drug delivery systems at different pH values. Int. J. Pharm. 2000, 194 (2), 169−180. (23) Sen, M.; Uzun, C.; Guven, O. Controlled release of terbinafine hydrochloride from pH sensitive poly(acrylamide/maleic acid) hydrogels. Int. J. Pharm. 2000, 203 (1−2), 149−57. (24) Shantha, K. L.; Harding, D. R. K. Preparation and in-vitro evaluation of poly[N-vinyl-2-pyrrolidone-polyethylene glycol diacrylate]-chitosan interpolymeric pH-responsive hydrogels for oral drug delivery. Int. J. Pharm. 2000, 207 (1−2), 65−70. (25) Harada, A.; Hashidzume, A.; Yamaguchi, H.; Takashima, Y. Polymeric Rotaxanes. Chem. Rev. 2009, 109 (11), 5974−6023. (26) Hoshino, T.; Miyauchi, M.; Kawaguchi, Y.; Yamaguchi, H.; Harada, A. Daisy Chain Necklace: Tri[2]rotaxane Containing Cyclodextrins. J. Am. Chem. Soc. 2000, 122 (40), 9876−9877. (27) Peng, K.; Tomatsu, I.; Kros, A. Light controlled protein release from a supramolecular hydrogel. Chem. Commun. 2010, 46 (23), 4094−4096. (28) Tian, Z.; Chen, C.; Allcock, H. R. Injectable and Biodegradable Supramolecular Hydrogels by Inclusion Complexation between Poly(organophosphazenes) and α-Cyclodextrin. Macromolecules 2013, 46 (7), 2715−2724. (29) Chee, P. L.; Prasad, A.; Fang, X.; Owh, C.; Yeo, V. J.; Loh, X. J. Supramolecular cyclodextrin pseudorotaxane hydrogels: a candidate for sustained release? Mater. Sci. Eng., C 2014, 39, 6−12. (30) Zou, H.; Guo, W.; Yuan, W. Supramolecular hydrogels from inclusion complexation of [small alpha]-cyclodextrin with densely grafted chains in micelles for controlled drug and protein release. J. Mater. Chem. B 2013, 1 (45), 6235−6244. (31) Larrañeta, E.; Isasi, J. R. Non-covalent hydrogels of cyclodextrins and poloxamines for the controlled release of proteins. Carbohydr. Polym. 2014, 102, 674−681. (32) Ye, H.; Owh, C.; Loh, X. J. A thixotropic polyglycerol sebacatebased supramolecular hydrogel showing UCST behavior. RSC Adv. 2015, 5 (60), 48720−48728. (33) Kai, D.; Low, Z. W.; Liow, S. S.; Abdul Karim, A.; Ye, H.; Jin, G.; Li, K.; Loh, X. J. Development of Lignin Supramolecular Hydrogels with Mechanically Responsive and Self-Healing Properties. ACS Sustainable Chem. Eng. 2015, 3 (9), 2160−2169. (34) Abdul Karim, A.; Loh, X. J. Design of a micellized [small alpha]cyclodextrin based supramolecular hydrogel system. Soft Matter 2015, 11 (27), 5425−5434. (35) Bauer, M.; Lautenschlaeger, C.; Kempe, K.; Tauhardt, L.; Schubert, U. S.; Fischer, D. Poly(2-ethyl-2-oxazoline) as Alternative for the Stealth Polymer Poly(ethylene glycol): Comparison of in vitro Cytotoxicity and Hemocompatibility. Macromol. Biosci. 2012, 12 (7), 986−998. (36) Lin, I. C.; Liang, M.; Liu, T.-Y.; Ziora, Z. M.; Monteiro, M. J.; Toth, I. Interaction of Densely Polymer-Coated Gold Nanoparticles with Epithelial Caco-2 Monolayers. Biomacromolecules 2011, 12 (4), 1339−1348. (37) Cai, X.; Yuan, J.; Chen, S.; Li, P.; Li, L.; Shen, J. Hemocompatibility improvement of poly(ethylene terephthalate) via

self-polymerization of dopamine and covalent graft of zwitterions. Mater. Sci. Eng., C 2014, 36, 42−48. (38) Cheng, H.; Feng, S.; Jia, X.; Li, Q.; Zhou, Y.; Ding, C. Structural characterization and antioxidant activities of polysaccharides extracted from Epimedium acuminatum. Carbohydr. Polym. 2013, 92 (1), 63− 68. (39) Ding, X.; Yang, C.; Lim, T. P.; Hsu, L. Y.; Engler, A. C.; Hedrick, J. L.; Yang, Y.-Y. Antibacterial and antifouling catheter coatings using surface grafted PEG-b-cationic polycarbonate diblock copolymers. Biomaterials 2012, 33 (28), 6593−6603. (40) Zhou, H. Y.; Zhang, Y. P.; Zhang, W. F.; Chen, X. G. Biocompatibility and characteristics of injectable chitosan-based thermosensitive hydrogel for drug delivery. Carbohydr. Polym. 2011, 83 (4), 1643−1651. (41) Li, Z.; Chee, P. L.; Owh, C.; Lakshminarayanan, R.; Loh, X. J. Safe and efficient membrane permeabilizing polymers based on PLLA for antibacterial applications. RSC Adv. 2016, 6 (34), 28947−28955. (42) Ye, H.; Owh, C.; Jiang, S.; Ng, C.; Wirawan, D.; Loh, X. A Thixotropic Polyglycerol Sebacate-Based Supramolecular Hydrogel as an Injectable Drug Delivery Matrix. Polymers 2016, 8 (4), 130. (43) Chee, P. L.; Prasad, A.; Fang, X.; Owh, C.; Yeo, V. J. J.; Loh, X. J. Supramolecular cyclodextrin pseudorotaxane hydrogels: A candidate for sustained release? Mater. Sci. Eng., C 2014, 39, 6−12. (44) Appel, E. A.; Loh, X. J.; Jones, S. T.; Dreiss, C. A.; Scherman, O. A. Sustained release of proteins from high water content supramolecular polymer hydrogels. Biomaterials 2012, 33 (18), 4646−4652. (45) Loh, X. J.; Goh, S. H.; Li, J. Hydrolytic degradation and protein release studies of thermogelling polyurethane copolymers consisting of poly[(R)-3-hydroxybutyrate], poly(ethylene glycol), and poly(propylene glycol). Biomaterials 2007, 28 (28), 4113−4123. (46) Guo, J.; Feng, Y.; Ye, Y.; Zhao, H. Construction of hemocompatible polycarbonate urethane with sulfoammonium zwitterionic polyethylene glycol. J. Appl. Polym. Sci. 2011, 122 (2), 1084−1091. (47) Kuo, W.-H.; Wang, M.-J.; Chang, C.-W.; Wei, T.-C.; Lai, J.-Y.; Tsai, W.-B.; Lee, C. Improvement of hemocompatibility on materials by photoimmobilization of poly(ethylene glycol). J. Mater. Chem. 2012, 22 (19), 9991−9999. (48) Larson, R. G. The Structure and Rheology of Complex Fluids. Oxford University Press: New York, 1999. (49) Goodwin, J. W.; Hughes, R. W. Rheology for Chemists: An Introduction; The Royal Society of Chemistry: London, U.K., 2000. DOI: 10.1039/9781847551832. (50) Censi, R.; Vermonden, T.; van Steenbergen, M. J.; Deschout, H.; Braeckmans, K.; De Smedt, S. C.; van Nostrum, C. F.; di Martino, P.; Hennink, W. E. Photopolymerized thermosensitive hydrogels for tailorable diffusion-controlled protein delivery. J. Controlled Release 2009, 140 (3), 230−6. (51) Spectrum, I. Pore Size Chart. http://www.spectrumlabs.com/ dialysis/PoreSize.html (accessed Jun 30, 2016). (52) Peters, T., Jr. Serum Albumin. In Advances in Protein Chemistry; Anfinsen, C. B., Frederic, M. R., Eds.; Academic Press: Cambridge, MA, 1985; Vol. 37, pp 161−245. DOI: http://dx.doi.org/10.1016/ S0065-3233(08)60065-0. (53) Conde, M. M.; Conde, O.; Trillo, J. M.; Minones, J., Jr. How to obtain a well-spread monolayer of lysozyme at the air/water interfaces. J. Colloid Interface Sci. 2011, 361 (1), 351−60. (54) van de Wetering, P.; Zuidam, N. J.; van Steenbergen, M. J.; van der Houwen, O. A. G. J.; Underberg, W. J. M.; Hennink, W. E. A Mechanistic Study of the Hydrolytic Stability of Poly(2(dimethylamino)ethyl methacrylate). Macromolecules 1998, 31 (23), 8063−8068. (55) Gutowska, A.; Seok Bark, J.; Chan Kwon, I.; Han Bae, Y.; Cha, Y.; Wan Kim, S. Squeezing hydrogels for controlled oral drug delivery. J. Controlled Release 1997, 48 (2−3), 141−148. (56) Boral, S.; Saxena, A.; Bohidar, H. B. Syneresis in agar hydrogels. Int. J. Biol. Macromol. 2010, 46 (2), 232−236. J


Article

ACS Biomaterials Science & Engineering (57) Liang, S.; Xu, J.; Weng, L.; Dai, H.; Zhang, X.; Zhang, L. Protein diffusion in agarose hydrogel in situ measured by improved refractive index method. J. Controlled Release 2006, 115 (2), 189−196. (58) Hyun, K.; Kim, S. H.; Ahn, K. H.; Lee, S. J. Large amplitude oscillatory shear as a way to classify the complex fluids. J. NonNewtonian Fluid Mech. 2002, 107 (1−3), 51−65. (59) Domenech, T.; Velankar, S. S. On the rheology of pendular gels and morphological developments in paste-like ternary systems based on capillary attraction. Soft Matter 2015, 11 (8), 1500−1516. (60) Wang, B.; Wang, L.-j.; Li, D.; Wei, Q.; Adhikari, B. The rheological behavior of native and high-pressure homogenized waxy maize starch pastes. Carbohydr. Polym. 2012, 88 (2), 481−489. (61) Sim, H. G.; Ahn, K. H.; Lee, S. J. Large amplitude oscillatory shear behavior of complex fluids investigated by a network model: a guideline for classification. J. Non-Newtonian Fluid Mech. 2003, 112 (2−3), 237−250. (62) Mason, T. G.; Bibette, J.; Weitz, D. A. Elasticity of Compressed Emulsions. Phys. Rev. Lett. 1995, 75 (10), 2051−2054. (63) Bower, C.; Gallegos, C.; Mackley, R. M.; Madiedo, M. J. The rheological and microstructural characterisation of the non-linear flow behaviour of concentrated oil-in-water emulsions. Rheol. Acta 1999, 38 (2), 145−159. (64) Klein, C. O.; Spiess, H. W.; Calin, A.; Balan, C.; Wilhelm, M. Separation of the Nonlinear Oscillatory Response into a Superposition of Linear, Strain Hardening, Strain Softening, and Wall Slip Response. Macromolecules 2007, 40 (12), 4250−4259. (65) Mason, T. G.; Weitz, D. A. Linear Viscoelasticity of Colloidal Hard Sphere Suspensions near the Glass Transition. Phys. Rev. Lett. 1995, 75 (14), 2770−2773. (66) Bossard, F.; Moan, M.; Aubry, T. Linear and nonlinear viscoelastic behavior of very concentrated plate-like kaolin suspensions. J. Rheol. 2007, 51 (6), 1253−1270. (67) Cloitre, M.; Borrega, R.; Leibler, L. Rheological Aging and Rejuvenation in Microgel Pastes. Phys. Rev. Lett. 2000, 85 (22), 4819− 4822. (68) Sim, H. G.; Ahn, K. H.; Lee, S. J. Three-dimensional dynamics simulation of electrorheological fluids under large amplitude oscillatory shear flow. J. Rheol. 2003, 47 (4), 879−895. (69) Hyun, K.; Nam, J. G.; Wilhellm, M.; Ahn, K. H.; Lee, S. J. Large amplitude oscillatory shear behavior of PEO-PPO-PEO triblock copolymer solutions. Rheol. Acta 2006, 45 (3), 239−249. (70) Daniel, C.; Hamley, W. I.; Wilhelm, M.; Mingvanish, W. Nonlinear rheology of a face-centred cubic phase in a diblock copolymer gel. Rheol. Acta 2001, 40 (1), 39−48. (71) Hyun, K.; Nam, J. G.; Wilhelm, M.; Ahn, K. H.; Lee, S. J. Nonlinear response of complex fluids under LAOS (large amplitude oscillatory shear) flow. Korea-Aust. Rheol. J. 2003, 15 (2), 97−105. (72) Wyss, H. M.; Miyazaki, K.; Mattsson, J.; Hu, Z.; Reichman, D. R.; Weitz, D. A. Strain-Rate Frequency Superposition: A Rheological Probe of Structural Relaxation in Soft Materials. Phys. Rev. Lett. 2007, 98 (23), 238303. (73) Roversi, T.; Piazza, L. Supramolecular assemblies from plant cell polysaccharides: Self-healing and aging behavior. Food Hydrocolloids 2016, 54 (Part A), 189−195. (74) Altmann, N.; Cooper-White, J. J.; Dunstan, D. E.; Stokes, J. R. Strong through to weak ‘sheared’ gels. J. Non-Newtonian Fluid Mech. 2004, 124 (1−3), 129−136. (75) Dealy, J. M.; Wissbrun, K. F. Melt Rheology and Its Role in Plastics Processing: Theory and Applications; Springer: Dordrecht, The Netherlands, 1999. DOI: 10.1007/978-94-009-2163-4. (76) Hyun, K.; Wilhelm, M.; Klein, C. O.; Cho, K. S.; Nam, J. G.; Ahn, K. H.; Lee, S. J.; Ewoldt, R. H.; McKinley, G. H. A review of nonlinear oscillatory shear tests: Analysis and application of large amplitude oscillatory shear (LAOS). Prog. Polym. Sci. 2011, 36 (12), 1697−1753. (77) Khandavalli, S.; Rothstein, J. P. Large amplitude oscillatory shear rheology of three different shear-thickening particle dispersions. Rheol. Acta 2015, 54 (7), 601−618.

(78) Ewoldt, R. H.; Winter, P.; Maxey, J.; McKinley, G. H. Large amplitude oscillatory shear of pseudoplastic and elastoviscoplastic materials. Rheol. Acta 2010, 49 (2), 191−212. (79) Graham, M. D. Wall slip and the nonlinear dynamics of large amplitude oscillatory shear flows. J. Rheol. 1995, 39 (4), 697−712. (80) Korsmeyer, R. W.; Gurny, R.; Doelker, E.; Buri, P.; Peppas, N. A. Mechanisms of solute release from porous hydrophilic polymers. Int. J. Pharm. 1983, 15 (1), 25−35. (81) Mehta, R.; Chawla, A.; Sharma, P.; Pawar, P. Formulation and in vitro evaluation of Eudragit S-100 coated naproxen matrix tablets for colon-targeted drug delivery system. Journal of Advanced Pharmaceutical Technology & Research 2013, 4 (1), 31−41. (82) Maharjan, S. Mathematical Models for Drug Release Studies; Kathmandu University: Dhulikhel, Nepal, 2014.

K


Micellized Î±-Cyclodextrin-Based Supramolecular ... - ACS Publications

Recommend Documents