3D Bioprinted Dopamine Based Matrix for Promoting Neural

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3D Bioprinted Dopamine Based Matrix for Promoting Neural Regeneration Xuan Zhou, Haitao Cui, Margaret Nowicki, Shida Miao, Sejun Lee, Fahed Masood, Brent T. Harris, and Lijie Grace Zhang ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b18197 • Publication Date (Web): 20 Feb 2018 Downloaded from http://pubs.acs.org on February 21, 2018

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ACS Applied Materials & Interfaces

3D Bioprinted Dopamine Based Matrix for Promoting Neural Regeneration

Xuan Zhou1, Haitao Cui1, Margaret Nowicki1, Shida Miao1, Se-Jun Lee1, Fahed Masood2, Brent T. Harris3, Lijie Grace Zhang1,4,5* 1. Department of Mechanical and Aerospace Engineering, The George Washington University, Washington DC 20052, USA 2. Department of Mechanical Engineering, University of Maryland, Collage Park, MD, USA 3. Department of Neurology and Pathology, Georgetown University, Washington, DC, USA 4. Department of Biomedical Engineering, The George Washington University, Washington DC 20052, USA 5. Department of Medicine, The George Washington University, Washington DC 20052, USA

*Corresponding Author: Dr. Lijie Grace Zhang Tel: 202-994-2479 Fax: 202-994-0238 Email: [email protected] Mailing Address: 800 22nd Street NW Science and Engineering Hall, Room 3590, Washington DC, 20052 1

ACS Paragon Plus Environment

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ABSTRACT Central nerve repair and regeneration remain challenging problems worldwide largely because of the extremely weak inherent regenerative capacity and accompanying fibrosis of native nerves. Inadequate solutions to unmet needs for clinical therapeutics encourage the development of novel strategies to promote nerve regeneration. Recently, 3D bioprinting techniques, as one of a set of valuable tissue engineering technologies, have shown great promise toward fabricating complex and customizable artificial tissue scaffolds. Gelatin methacrylate (GelMA) possesses excellent biocompatible and biodegradable properties because it contains many arginine-glycine-aspartic acids (RGD) and matrix metalloproteinase (MMP) sequences. DA, as an essential neurotransmitter, has proven effective in regulating neuronal development and enhancing neurite outgrowth. In this study, GelMA-DA neural scaffolds with hierarchical structures were 3D fabricated using our custom designed stereolithography-based printer. The DA was functionalized on the GelMA to synthesize a biocompatible, printable ink (GelMA-DA) for improving neural differentiation. Additionally, neural stem cells (NSCs) were employed as the primary cell source for these scaffolds because of their ability to terminally differentiate into a variety of cell types including neurons, astrocytes, and oligodendrocytes. The resultant GelMA-DA scaffolds exhibited a highly porous and interconnected 3D environment favorable for supporting NSC growth. Confocal microscopy analysis of neural differentiation demonstrated that a distinct neural network was formed on the GelMA-DA scaffolds. In particular, the most significant improvements were the enhanced neuron gene expression of TUJ1 and MAP2. Overall, our results demonstrated that 3D printed customizable, GelMA-DA scaffolds have a positive role

2


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in promoting neural differentiation, which is promising for advancing nerve repair and regeneration in the future. KEYWORDS: Dopamine; gelatin methacrylate; 3D bioprinting; neural stem cells; neural tissue engineering

1 INTRODUCTION The human nervous system, made up of the brain, spinal cord, and peripheral nerves, is an extremely complex, precise, and delicate structure. It plays a vital role in physiological regulation and functionality in the human body, including cognitive function, coordination, and neural signals (afferent and efferent) integration.1 Meanwhile, the central nervous system is also vulnerable to damage through both physical trauma (direct/indirect injury, stroke, swelling, and hyperthermia)

2-3

and

neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, Amyotrophic lateral sclerosis, Huntington's disease, and chronic traumatic encephalopathy).

4-5

2015 data shows neurological diseases have affected almost 100 million Americans with billions of dollars being spent on associated healthcare costs annually. Moreover, this number will continue to grow in the future with an increasing, and aging, population. 6-7 Gold standard surgical procedures (nerve autograft) and drug therapies for repairing and rebuilding neural systems are currently constrained by autologous transplantation resources, and limited neuroprosthetics.8-10 Although these approaches have been clinically performed on many occasions, the outcomes are still not satisfactory due to the extremely weak inherent regenerative capacity and fibrosis associated with central nerves.

5, 8

Consequently, inadequate and unsatisfactory 3



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therapeutic approaches drive an urgent need for the development novel strategies that effectively promote nerve regeneration leads to the restoration of neural function. The emergence of neural tissue engineering has provided an alternative option by combining sophisticated, biomimetic scaffolds and stem cells for improving nerve therapeutics, compared with traditional approaches.

11-12

Many scaffolds, including

electrospun-fibers,13 hydrogels,14 and 3D conduits,15 have been employed for neural tissue engineering and are based on an array of biocompatible, natural (extracellular matrix) and synthetic biomaterials (polylactic acid, poly-lactate glycolic acid, and polyvinyl alcohol). 11 However, even traditional tissue engineering techniques studied thus far are unsatisfactory because of low precision, multi-step manufacturing processes, high cost, and inefficiency. More importantly, an inability to customize replacement structures for diverse tissue defects is one of the most considerable drawbacks that cannot be ignored for optimal outcomes. Recently, increased attention to state-of-the-art 3D bioprinting technologies has shown great potential for fabricating complex and customizable 3D biomedical devices, tissues, and organs. In the field of biomedicine, 3D printing offers many advantages in producing high precision, cost effective, innovative scaffolds with intricate 3D microarchitectures using computer-aided design (CAD).16 Stereolithography (SLA), one type of 3D bioprinting, employs a rapid prototyping lithographic method to polymerize or crosslink a photocurable polymer ink under a light beam in a layer-by-layer approach. 16-18

Moreover, SLAs ability to fabricate hierarchical structures with high accuracy

and resolution make it a favorable candidate for neural tissue scaffold construction. In 4


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the current work, a custom designed table-top SL printer was used for manufacturing a unique neural tissue engineered matrix. To address pressing technical and clinical needs, the present work investigated 3D bioprinted gelatin methacrylate (GelMA) functionalized dopamine (DA) (GelMA-DA) scaffolds designed to enhance neuronal differentiation of NSCs. A schematic of the 3D printed dopamine based matrix for promoting neural regeneration is shown in Figure 1. The schematic mechanism of GelMA-DA crosslinking reaction after the UV exposure is shown in Figure 2. Choosing an appropriate bioink with bio/eco-friendly features for 3D printing is a top priority. GelMA is a gelatin derivative, which contains many arginine-glycine-aspartic acids (RGD) and matrix metalloproteinase (MMP) sequences. It is well known for possessing excellent biocompatible and biodegradable properties even after it is photocured under UV light. 17-18

DA, one in a series of famous neurotransmitters, has proven effective in

regulating neuronal development and enhancing neurite outgrowth.

19-26

GelMA-DA

was synthesized by modifying amino groups of DA on the carboxyl group of GelMA via covalent bond reaction. This ink was 3D printed through photocrosslinking under UV light while retaining the biological functionality of DA for neural tissue engineering.

5



Figure 1. Schematic diagram of 3D bioprinted dopamine-based matrix for promoting neural regeneration

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Figure 2. (A) Chemical structure of GelMA-DA. (B) Schematic of mechanism of GelMA-DA crosslinking reaction after the UV exposure. (C) The schematic of GelMA-DA hydrogel network.

Additionally, neural stem cells (NSCs), a subset of multipotent stem cell populations presents in the adult central nervous system, are one of the most multipotent cells. They hold great promise for neural repair after injury or disease because of their ability to terminally differentiate into neuronal and glial lineages, 7



such as neurons, astrocytes, and oligodendrocytes.

27-28

This versatile differentiation

capability of NCSs shows great potential to resolve nervous system diseases or neurodegenerative disorders. Furthermore, modifying substrate properties with functional molecules (such as dopamine) can induce differentiation of NSCs into neurons for diverse neuroregenerative applications. 11 For this purpose, 3D printed GelMA-DA scaffolds with hierarchical structures were uniquely manufactured using our custom designed SL-based printer. NSCs were cultured on the resultant scaffolds and specifically observed for differentiation into a neural network. Moreover, the relevant neural markers (TUJ1, MAP2, and NESTIN) were characterized to evaluate neuronal/glial differentiation of NSCs on the 3D scaffolds using real-time quantitative reverse transcription-polymerase chain reaction (RT-PCR) and immunocytochemical assays.

2. Materials and methods MATERIALS AND METHODS 2.1 Synthesis of GelMA and GelMA-DA GelMA was synthesized according to the method described in our previous work. 17-18

Briefly, 10% (w/v) of gelatin (Type A, Sigma-Aldrich) was fully dissolved into

phosphate buffered saline (PBS) under magnetic stirring at 60°C. Next, 4% (v/v) of methacrylic anhydride was added drop-wise into the gelatin solution under stirring conditions at 50°C for 2 h. Subsequently, the reacted mixture was dialyzed against pure water (8-14 kDa cutoff) at 40°C for 3 days to remove excess methacrylic acid and salts. Finally, the GelMA flock was obtained after lyophilization. 8


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GelMA-DA was synthesized by modifying the amino group of DA on the carboxyl group of GelMA via covalent bond reaction.29-30 Briefly, 10 g of GelMA was fully dissolved into 160 mL of PBS (pH 5.0) + dimethylformamide (DMF) (1:1) solution

under

magnetic

stirring

at

50°C.

N-(3-Dimethylaminopropyl)-N ′ -ethylcarbodiimide

Next, (EDC)

15 and

g 9

g

of of

N-Hydroxysuccinimide (NHS) was dissolved in 40 ml of DMF and added drop-wise into the mixture at 60°C for another 24 h to activate the carboxyl group of GelMA. Then 3 g of dopamine hydrochloride (DA, Sigma-Aldrich) was dissolved in 10 ml of PBS (pH 5.0) and added drop-wise into the activated mixture for 12 h. Subsequently, the reacted mixture was dialyzed against PBS (pH 5.0) using 8-14KDa cutoff dialysis bags at 40°C for 5 days. Lastly, the GelMA-DA flock was obtained after lyophilization. 2.2 3D printing neural tissue scaffolds 3D printed scaffolds were manufactured using our customized table-top SL printer, based on the existing Printrbot® rapid prototyping platform, as described in our previous work. distilled

water

16-18

GelMA and GelMA-DA (10 wt%) were fully dissolved in

containing

1

2-Hydroxy-4 ′ -(2-hydroxyethoxy)-2-

wt%

methylpropiophenone (Photoinitiator: Irgacure 2959) to form a photocurable ink. Next, the inks were placed on the z-control movable platform and cross-linked by X-Y axis controlled UV laser (355 nm) into preprogrammed computer aided design (CAD) models. The working parameters were set as follows: 200 µm fiber UV laser

9



beam, 25 µJ intensity output of 25 kHz emitted UV, and 7 mm/s printing speed for GelMA and GelMA-DA scaffolds. 2.3 Characterization of 3D printed scaffolds FTIR spectra of gelatin, GelMA, and GelMA-DA samples were performed and recorded with a Nicolet FTIR 5700 spectrophotometer (Madison, WI) between 4,000 and 400 cm−1 at room temperature. Proton nuclear magnetic resonance (1H NMR) spectra of Gelatin, GelMA, and GelMA-DA were measured using a 500 MHz NMR spectrometer (Bruker, Switzerland). The samples were dissolved in deuterium oxide (D2O) at 10 mg/ml at 40°C, and then transferred into a NMR tube for recording. The dry lyophilized hydrogels of GelMA and GelMA-DA were sputter coated with a 10 nm layer of gold and observed by scanning electron microscopy (SEM) (Zeiss Nvision 40FIB). The morphologies and surface plots of the 3D printed scaffolds were visualized with optical microscopy (Mu800, Amscope). The swelling behavior of the hydrogel was evaluated by quantifying the weight gain after equilibrium swelling. In brief, lyophilized GelMA hydrogels (100 mg, W0) were immersed in PBS at 37°C for different periods of time (0.5, 1, 2, 4, 8, 12, 16, and 24 h). At predetermined time intervals, samples were collected from the buffer solution and weighed as Wt. The equilibrium mass swelling ratios of matrices were calculated as the difference of (Wt-W0) divided by W0. 2.4 NSC culture Mouse derived NSCs were purchased from American Type Culture Collection (ATCC) (NE-4C, CRL-2925) and utilized for investigating the cell 10


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behavior on printed scaffolds. NSCs were cultured in Minimum Essential Medium Eagle (MEME) (ATCC) supplemented with 5% (v/v) fetal bovine serum (FBS) and (1%, v/v) L-glutamine. It is reported that NSCs can differentiate into neurons under specified retinoic acid (RA) inducing conditions.

28, 31-32

For neuronal differentiation

studies of NSCs, cells were cultured in aforementioned completed medium supplemented with all-trans RA (10-6 M).31-32 All cells were incubated in a 95% humidified atmosphere, with 5% CO2, at 37°C. 2.5. NSC proliferation on 3D scaffold NSC proliferation on the various 3D printed scaffolds was investigated for 6 days. Prior to cell assay, GelMA and GelMA-DA scaffolds were placed in a 48-well plate and immersed in 70% alcohol for 5min, then fully rinsed with PBS before immersing in culture medium for 12 h. NSCs were then seeded on the scaffolds at a density of 3 × 104 cells/well and continuously cultured for 2, 4 and 6 days. At the predetermined time interval, the old culture medium was replaced with a fresh medium containing 10% CCK-8 solution (Dojindo, Japan) and incubated for another 2 h. Following incubation, 100 µL of culture medium was transferred into a new 96-well plate and recorded by spectrophotometer (Thermo, USA) at a wavelength of 450 nm for absorbance quantification. Specifically, at each predetermined time, all scaffolds were rinsed sequentially with PBS, followed by fixation with 10% formalin and then permeabilized with 0.2% Triton-100 for 10 min, respectively. Next the scaffolds were stained with Texas Red-X phalloidin solution (1:100) for 30 min, followed by 4′, 6-diamidino- 2-phenylindole (DAPI) (1:100) solution for another 5 11



min. Scaffolds were fully rinsed with PBS prior to moving on to the next process. The NSC morphology on scaffolds was observed by using laser confocal microscopy (Carl Zeiss LSM 710). 2.7. Immunocytochemistry of neuronal differentiation on 3D scaffolds NSCs were seeded at a density of 2 × 104 cells/well on each scaffold and incubated in aforementioned differentiation medium for 12 days to evaluate the potential of GelMA-DA 3D scaffolds to induce neuronal differentiation. The medium was replaced with fresh medium every other day. At predetermined time intervals (4, 8, and 12 days); the samples were rinsed with PBS and fixed with 10% formalin for 10 min followed by permeabilization in 0.2% Triton-100 solution for 10min at room temperature. Next, the samples were incubated with blocking solution containing 1% BSA, 22.52 mg/mL glycine in PBST (PBS+ 0.1% Tween 20) for 2 h to block unspecific binding of the antibodies according to the Abcam manufacturer’s instructions. The first primary antibody of mouse anti-TuJ1 (1:1000; Covance 801202) and rabbit anti-Nestin antibody (1:500; Abcam ab176571) in 1% BSA in PBST, were gently mixed with samples in the dark for 24 h at 4°C. Next, the secondary antibodies of goat anti-mouse Alexa Fluor 594 (1:200; Life Technologies A-11005) and goat anti-rabbit Alexa Fluor 488 (1:200; Abcam ab150081) in 1% BSA in PBST, were incubated with samples in the dark for 2 h at room temperature. This was followed by DAPI (1:100) solution incubation for 5 min. In every process, the old solution was decanted and the samples were washed three times with PBS prior to moving on to the next step. The neuronal morphology on scaffolds was observed using laser 12


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confocal microscopy (Carl Zeiss LSM 710). Neuronal cells and neurite length were quantified by Image J analysis software (National Institutes of Health). Three visible areas were randomly selected for quantifying statistical analysis on each sample; there were three samples in each group. The average total neurite length and an average total length of the longest neurite were recorded. 19 2.8. Real-Time PCR analysis In order to investigate the specific differentiation patterns of NSCs on 3D printed scaffolds, the neuron-specific class III β-tubulin (TUJ1), microtubule-associated protein 2 (MAP2), and NESTIN marker gene expression levels were quantified by a Real Time-PCR assay. The cells were processed according to our previous work.18 Briefly, after 4, 8 and 12 days of neuronal differentiation, the samples were fully rinsed with pre-cold PBS and fully treated with 1 mL TRIzol Reagent (Thermolfisher, USA) for 30 min. Total RNA was extracted using a standard TRIzol protocol. Purity and yield ratio of RNA were examined with a NanoDrop spectrophotometer (NanoVue, Biochrom.). The complementary DNA was synthesized using a Real-time PT-PCR kit (PrimeScript RT Master Mix, Takara) according to the manufacturer's instructions. Quantitative PCR analysis was performed in triplicate per sample using SYBR qPCR kit (SYBR Premix Ex Taq II (Tli RNase H Plus), Takara) and CFX384 Real-Time System (Bio-Rad, USA). Relative quantification of gene expression was analyzed using standard 2-(∆∆Ct) method and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as the endogenous housekeeping gene. The detailed PCR primer sequences are available in Table S1.33-34 13



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2.9 Statistical analysis Data are reported as a mean ± standard deviation and statistically analyzed by one-way ANOVA methods. Statistically, a value of p < 0.05 was determined to evaluate the level of significance.

3. RESULTS AND DISCUSSION 3.1 Synthesis of GelMA and GelMA-DA We successfully synthesized the expected materials, GelMA and GelMA-DA. FTIR spectra of gelatin, GelMA, GelMA-DA, and DA are shown in Figure 3 (A, B). Although the methacrylate substituent groups were introduced successfully on the gelatin molecules, there was no significant new absorption peak in the FTIR spectra and only some absorption peaks were enhanced. This can be explained by the smaller number of amino groups on gelatin involved in the reaction process.

35

Gelatin is a

hydrolysate of collagen and composed of peptides. Amide bonds (-CO-NH-) are abundant in all peptides and proteins. Although the amino group (-NH2) is presents in DA molecules, and will transfer to amide bond after reaction. The new amide bond number is smaller when compared to that in original molecular (GelMA/Gelatin). Therefore, the new amide peaks are hard to detect in the spectra. The peak increased at 870 cm-1 which confirmed the presence of the catechol units in the GelMA-DA (Figure 3A).19 Moreover, this absorption was also found in the DA FTIR spectra (Figure 3B). This result revealed the DA groups were successfully modified on the GelMA molecules. 14


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The successful synthesis of the GelMA and GelMA-DA was also confirmed by 1

H NMR spectroscopy (Figure 3 (C, D)). The new peaks at 5.3 and 5.6 ppm in the

GelMA and GelMA-DA spectra, when compared to the gelatin spectrum, are assigned to the protons of the methacrylic acid (MA) residues (Figure 3C). These residues occur during GelMA synthesis through modifying methacrylate on the amino group of gelatin via amide reaction.

36-37

Similarly, the GelMA-DA was synthesized by

modifying the amino group of DA on the carboxyl group of GelMA via covalent bond reaction. The new peak at 2.9 ppm only in the spectrum of GelMA-DA is attributed to the proton residues of DA; this is confirmed by the spectrum of DA (Figure 3D). This new peak appears in the 1H NMR spectrum of GelMA-DA, when compared to GelMA, because of the introduction of DA.29 These results demonstrate that the MA and DA residues are effectively modified on the gelatin backbone.

15



Figure 3. (A)FTIR and (C)1H NMR spectra of gelatin, GelMA, GelMA-DA. The inset images are the GelMA and GelMA-DA inks, respectively. (B)FTIR and (D) 1H NMR spectra of dopamine (DA).

3.2 3D printed scaffold fabrication and characterization The 3D scaffolds were successfully printed according to Pre-designed CAD models (Figure 4A). The scaffolds with homogeneous pores and uniform channels were clearly visible in fluorescence micrographs (Texas Red-X phalloidin) (Figure 4B) and microscope images (Figure 4C), respectively. The surface plot feature of 3D printed scaffolds is shown in Figure 4D. After functional modification, both GelMA and GelMA-DA inks exhibited remarkable printability with hierarchical structures fabricated using our stereolithography based 3D printer. The SEM in the cross-sectional view of GelMA and GelMA-DA matrices are shown in Figure 4(E, F), respectively. Porous structures were observed in both matrices and will benefit nutrients storage, and provide platform for cell proliferation or differentiation.17 Moreover, the apparent pore size and porous framework in the GelMA- hydrogel are more compact than that in the GelMA-DA hydrogel. The GelMA-DA was synthesized from GelMA in acidic environment (pH 5.0). In these conditions, the GelMA molecular chains might be degraded into smaller ones after the DA modification. The GelMA ink became gel while the GelMA-DA ink maintained an aqueous status in the same concentration at room temperature, confirming this hypothesis. The number and proportion of methacrylate substituent group are relatively stable in each molecule of GelMA. But the proportion thereof will decrease after the GelMA molecules begin to degrade. The crosslink density will decrease 16


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simultaneously with the reduction in the proportion of methacrylate substituent group. Moreover, potential lower crosslink density lead to relative greater swellability and larger pore sizes in GelMA-DA hydrogel when compared to GelMA hydrogel. These phenomena contribute to the swellability difference between the two samples. Swelling behavior is a crucial physicochemical property for the matrix in aqueous solution. The swellability of GelMA and GelMA-DA matrices were recorded at various predetermined time-points (Figures 4G, H). The swelling rate of the GelMA-DA matrix was 38% greater than the GelMA matrix after 24 h. Furthermore, it takes nearly 8 h to reach a swelling balance for the GelMA matrix and 12 h for the GelMA-DA matrix. This may be explained by the aforementioned difference in porous structures and crosslink density as seen in the SEM image, Figure 4(E, F).

17



Figure 4. (A) Pre-designed CAD 3D scaffold model; (B) Fluorescence micrographs (Texas Red-X phalloidin); (C) light microscope image; and (D) surface plot of 3D printed scaffold; scale bar = 200 µm. Scanning electron micrographs (cross-sectional view) of (E) GelMA and 18


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(F) GelMA-DA porous matrices; scale bar = 10 µm. The inset images are photographs of the corresponding scaffolds. (G) The swellability of GelMA and GelMA-DA matrices. (H) The magnifying plot of G in 0-2 h. Data are mean ± standard deviation; n = 5.

3.3 Proliferation of NSCs on 3D scaffolds Cell behavior on 3D printed GelMA and GelMA-DA scaffolds was investigated by evaluating NSC proliferation for 2, 4 and 6 days (Figure 5). NSCs grew on both scaffolds over time and there were no significant differences between the two types of scaffolds. The results were validated by the corresponding confocal microscopy images (Figure 6). The F-actin and cell nuclei of NSCs were stained by Texas Red®-X phalloidin (red) and DAPI (blue), respectively. The visualized cytoskeletons showed notable spreading on both scaffolds over time. The results demonstrate that both GelMA and GelMA-DA materials have good cytocompatibility after functional modification.

19



Figure 5. Proliferation of NSCs cultured on the GelMA and GelMA-DA scaffolds for 2, 4, and 6 days. Cell count was quantified by CCK-8 assay. Data are a mean ± standard deviation, n = 8.

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Figure 6. Confocal microscopy images of NSC proliferation cultured on the surface of GelMA and GelMA-DA for 2, 4 and 6 days. The cytoskeleton and cell nuclei were stained with Texas Red®-X phalloidin (red) and DAPI (blue), respectively.

3.4 Neural differentiation of NSCs on 3D scaffolds The immunocytochemistry and morphocytology results were recorded and quantitatively analyzed at predetermined time-points (Figures 6, 7). TUJ1 and Nestin antibodies were selected as specific neuron and NSC biomarkers, separately. It was observed that enhanced TUJ1 staining was notable on GelMA and GelMA-DA scaffolds over time (Figure 7). The Nestin antibody staining area decreased with time in both scaffolds. Additionally, the TUJ1 synthesis on the GelMA-DA scaffolds was higher than that of the GelMA scaffolds at the same time-point. Furthermore, a visible neural network was observed on the GelMA-DA scaffold after 12 days (Figure 7(I, J)-Day 12). These phenomena implied that relatively more NSCs on the GelMA-DA scaffolds terminally differentiated into neurons after RA induction at the same time-point. These results were confirmed by a quantitative analysis of neural cells and neurite length (Figure 8). After 12 days of differentiation, the average total neurite length, and the average total of the longest neurite length, on the GelMA-DA scaffolds were dramatically greater than those on the GelMA scaffolds by 85% and 49%, respectively. These data directly demonstrate that GelMA-DA can significantly promote neural network formation. TUJ1 is a crucial βIII-tubulin of the microtubule family that plays a key role in intracellular/axonal transport, and structure maintenance. TUJ1 was expressed in early phase of neuronal differentiation and is recognized as an early maturing neuronal 21



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marker. 38 Nestin is a type of intermediate filament (IF) protein, is mostly synthesized in NSCs, and is considered a specific marker.

39-40

It has been reported that Nestin

expression was downregulated when NSCs/progenitor cells differentiate into neurons.39 Comparatively, neurons are mature nerve cells and lack renewable ability. Therefore, Nestin antibody staining area decreased with neural network formation after specific differentiation. These results are consistent with the other researchers’ studies that DA plays a key role in regulating neuronal development and enhancing neurite outgrowth due to the DA/DA-receptor cascade reaction. 19-26 Additionally, DA is most commonly used for surface adherent modification due to its extraordinary cell adhesion capability.

41-43

The cellular behavior observed in this study may be

explained by these biofunctionalities of DA which act as an inducer for promoting differentiation of NSCs into neurons. Some neurotransmitters, such as dopamine and acetylcholine, played a key role in regulating the strength and interaction of neuronal connectivity by ligand-receptor mode. Activation of dopamine receptors affects proliferation and differentiation of NSCs/progenitor cells. During development, high expression of dopamine receptors was found in proliferative zones that related to neurogenesis. Based on the cellular activity, combination of neurotransmitter functionalities into biomaterials may provide a valuable alternative to develop their synergistic

effect

for

enhancing

nerve

repairing

or

regeneration.

Neurotransmitter-modified substrate may induce axonal stretch and promote neuronal growth.21 The immunocytochemistry and quantitative analysis results, Figure 7,

22


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demonstrate that the GelMA-DA scaffold greatly enhanced neural differentiation of NSCs.

Figure 7. Confocal micrographs of the immunocytochemical stain of neural differentiation on the GelMA (A-C) and GelMA-DA (G-I) scaffolds for 4, 8, and 12 days. (D-F) and (J-L) micrographs were the magnification of (A-C) and (G-I) in specific area, respectively. The neuron, NSCs and cell nuclei were stained by TUJ1 (red), Nestin (green) and DAPI (gray), respectively.

Figure 8. Quantification of neurite length of neural differentiation on the GelMA and GelMA-DA scaffolds for 4, 8, and 12 days. (A) Total neurite length. (B) The average length of the longest neurite. Data are mean ±standard deviation, n=9, *p

3D Bioprinted Dopamine Based Matrix for Promoting Neural

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