Nanoengineered Micellar Hydrogel with Controllable Strain‐Dependent Behavior for Brain Slice‐Like Tissue Patch Bioprinting

ABSTRACT

The advancement of bioink tailored for extrusion‐based bioprinting (EBB) unveils the critical importance of the structure‐property relationship that calls for advanced characterization techniques. Particularly for soft hydrogel in printing central nervous tissues, it is essential to ensure cell viability and differentiation with customized architecture. This study introduces a nanoengineered chitosan micelle‐crosslinked hydrogel (CDP) system, achieving three distinct rheological properties by regulating the relative contribution of dynamic covalent crosslinking vs. micelle stacking through high shear‐induced crystallization to the final printing performance. The optimized CDP‐II bioink exhibits balanced shear strain tolerance and stability within 200% strain. Rheo‐SAXS analysis reveals the reversible lyotropic liquid crystal (LLC) structures, while SANS fitting identifies the radius (8.1 nm) and packing ratio (36%) for the micelles. The CDP‐II bioink with 0.6 kPa shear modulus demonstrates proper mechanical properties and biocompatibility for neural stem cells. The bioink supports the differentiation of neural stem cells while protecting cell death from extrusion. The brain slice‐like tissue patch printed from the CDP‐II bioink can be picked up, manipulated, and moved to the culture vessel, underscoring its potential in neural tissue engineering. The structure‐property relationship established through the model system can be used in the precise structure design of a binary hydrogel for bioprinting.

A nanoengineered bioink system is developed with tunable rheology and biocompatibility, enabling neural stem cell viability, differentiation, and 3D printing of brain slice‐like neural tissue constructs. The structure‐property relationship unveiled by rheo‐SAXS and SANS lays the foundation for designing soft materials optimized for extrusion‐based bioprinting.

1. Introduction

The emergence of 3D bioprinting and additive manufacturing technologies has brought immense potential for fabricating 3D structures that mimic natural tissues, driving advancements in precision medicine and tissue engineering applications [1]. In recent years, the introduction of smart bioink has aroused extensive research to facilitate the preparation of complex and homogeneous 3D‐printed structures containing living cells [2]. Natural‐based polymer bioinks exhibit good biocompatibility, while synthetic ones offer excellent viscoelastic properties and predictable performance [3]. To achieve structures with higher physical stability, bioinks are often chemically, physically, or enzymatically crosslinked to optimize mechanical stability, withstand physical stress, and improve the integrity of their structure and network in the biological microenvironment after 3D printing [4].

As potential bioink candidates, biopolymers of natural origin (such as collagen, gelatin, chitosan, alginate, fibrin, and hyaluronic acid [5, 6, 7, 8]) possess inherent bioactivity and exhibit excellent biocompatibility similar to extracellular matrixes (ECM). However, these natural biomaterials often have weak mechanical properties even after crosslinking [9]. In contrast, synthetic materials [such as polyε‐caprolactone, polylactic acid, polyethylene glycol (PEG), and Pluronic] have greater viscoelastic and mechanical advantages as they can be customized according to specific physical properties and offer higher uniformity [9, 10]. Currently, bioinks composed of a mix of natural and synthetic materials have been developed to integrate the advantages of both categories [11]. For example, a Ca²⁺ ion chelated double network hybrid bioink composed of polyurethane nanoparticles and gelatin demonstrated good degradability and adjustable elastic modulus [12]. Another bioink based on methacrylated chondroitin sulfate/hyaluronic acid with methacrylated poly[N‐(2‐hydroxypropyl) methacrylamide mono/dilactate]‐PEG triblock polymer showed promise for cartilage bioprinting [13]. However, the structure‐property relationship and the principle for tunability of property in such binary hydrogel systems remain unclear.

Human tissues are combinations of various cell types and well‐defined ECM gradient structures demonstrating complex viscoelasticity. Therefore, rheology is one of the most critical considerations when opting for 3D bioprinting materials [14]. Surprisingly, the role of rheology in bioink formulations is still poorly understood and being studied. For instance, a systematic approach revealed the relationship between printing windows and moduli of a gelatin‐alginate composite hydrogel [15]. Moreover, some bioinks exhibit complex rheological behaviors, such as strain‐hardening, an almost universal response of biological tissues to mechanical stimulation. Such property occurs in chitosan‐, alginate‐, agarose‐, and pectin‐ based hydrogel structures, which harden with increasing shear stress [16, 17]. This phenomenon arises from forming ordered and stiffer networks before the polymer chains start to have structural breaks. The temporary junctions formed by chain entanglement in stable crosslinks are the root of nonlinear elasticity [18]. Using polysaccharide hydrogels to mimic the nonlinear mechanics of natural tissues becomes highly attractive [19]. Meanwhile, understanding the mechanisms underlying this nonlinear elasticity is crucial for developing biomimetic materials.

The strain‐hardening and nonlinear properties of biological materials allow them to maintain structure and function against environmental deformation and damage, making them suitable for the long‐term cultivation of 3D bioprinted constructs. However, such biomimetic behavior also causes severe extrusion expansion during extrusion‐based printing, significantly affecting the resolution and stacking of the printed structures. At the same time, there is a need to define printability and evaluate optimization criteria based on structure and physical parameters, particularly for soft bioink with a modulus lower than 1 kPa. Herein, a nanoengineered micelle hydrogel consisting of Pluronic crosslinked chitosan network was developed. The hydrogel was constructed based on chemical dynamic Schiff‐based linkages and physical lyotropic liquid crystalline (LLC) association. The strain‐dependent behavior of this hydrogel was adjustable by regulating the concentration of micelles. Through in situ rheology‐small‐angle X‐ray scattering (rheo‐SAXS) and small‐angle neutron scattering (SANS) technologies, the real‐time relationship between hydrogel properties and microstructures was identified, giving insight into energy dissipation mechanisms under shear strain in such binary systems. By integrating a covalent network with physical gelation, the optimized hydrogel bioink effectively reduced extrusion expansion, maintained structural integrity, and improved printing resolution. In the meantime, the 3D‐printed neural tissue can be combined through the self‐healing nature of the bioink. The study on the micellar hydrogel model system lays certain functions for the structural design and modular system of extrusion‐based printing bioink in the future.

2. Materials and Methods

2.1. Synthesis of Chitosan Phenol (CP)

For synthesizing CP, 3‐(4‐hydroxyphenyl)propionic acid (249 mg, Alfa Aesar, UK), N‐(3‐dimethylaminopropyl)‐N′‐ethylcarbodiimide hydrochloride (287.5 mg, Sigma‐Aldrich, UK), and N‐hydroxysuccinimide, (173 mg, Sigma‐Aldrich, Japan) were sequentially added to 225 mL of 50 mM MES buffer [2‐(N‐morpholino)ethanesulfonic acid hydrate (Sigma‐Aldrich, USA)]. The 0.5 g of chitosan (∼145 kDa, Sigma‐Aldrich, Iceland) was dissolved in 0.25 N hydrochloric acid (25 mL, Echo) and subsequently mixed with the previously prepared MES buffer solution. The whole reaction was carried out at pH 5 under stirring and darkness for 24 h. The reaction mixture was dialyzed in deionized water through a dialysis membrane (MWCO 12–14 kDa, Cellu Sep, USA) under continuous stirring, and the resulting product was collected by lyophilization.

2.2. Synthesis of Difunctionalized‐Pluronic F127 (DP)

4‐Formylbenzoic acid (0.24 g, 1.6 mmol, Sigma, USA), 4‐(dimethylamino)pyridine (0.025 g, 0.2 mmol, Sigma, USA), N,N′‐diisopropylcarbodiimide (0.4 g, 3.2 mmol, Sigma, USA), and Pluronic F127 (PF, Mw ≈ 12.6 kDa, 2 g, 0.16 mmol, Sigma, USA) were successively introduced into anhydrous tetrahydrofuran (100 mL, Echo). The mixture was stirred under a nitrogen environment at ambient temperature for 48 h. The crude product was subsequently precipitated by the addition of anhydrous diethyl ether (700 mL, Echo). The white precipitate was removed by filtration. The solid product was purified by the other two resolving (tetrahydrofuran, 50 mL) and precipitating (diethyl ether anhydrate, 400 mL) cycles. The final product was collected as a white solid through three successive cycles of precipitation in diethyl ether (Echo, Taiwan) and redissolution in tetrahydrofuran.

Thermal transitions related to micelle formation were analyzed using a differential scanning calorimeter (DSC, Q‐20, TA Instruments) equipped with a temperature control system. Approximately 15 mg of sample was sealed in aluminum pans, and the measurements were conducted over a temperature range of 5–40°C at a heating rate of 5°C min⁻¹.

2.3. Rheological Analysis

CP (2 wt.%) and DP (5, 10, and 20 wt.%) were prepared as aqueous solutions. CDP hydrogels were prepared by mixing CP and DP solutions at 1:1 volume ratio. The components and composition are listed in Table 1. Rheological analyses of hydrogels (PF, DP, and CDP) were performed by a rheometer (HR‐2, TA Instruments, USA) using a 40 mm cone (2°) and plate geometry. The time sweep was conducted during gelation in the rheometer at 37°C. The shear moduli (G′ and G″) were recorded at 1 Hz frequency and 1% oscillatory strain. After the hydrogels reached equilibrium, the frequency sweep from 0.01 to 100 Hz was taken at 1% oscillatory strain. The dynamic strain sweeps in the range of 1%–600% oscillatory strain were measured at 1 Hz frequency. Temperature sweep tests were performed to investigate the thermoresponsive behavior of the CDP hydrogels. The temperature gradually increased and decreased between 15 and 37°C at a heating/cooling rate of 5°C min⁻¹, while maintaining an oscillatory strain of 1% and a frequency of 1 Hz to record the variations in G′ and G″ as a function of temperature. Damage–recovery cycles were subsequently conducted to evaluate the self‐healing capability of the hydrogels under alternative strains. The cyclic strain was switched between low strain (1%) and high strains (50% or 300%) at 1 Hz, with each step maintained for 120 s.

TABLE 1.

The applicable hydrogel bioinks in this study and the corresponding rheological characteristics.

Group	PF (wt.%)	DP(wt.%)	CP(wt.%)	G′ (kPa)	γbreak(%)	m	Type *
PF‐I	20	0	0	7	10	−0.15	I
DP‐I	0	20	0	1.1	10	−0.22	I
CDP‐II	0	10	1	0.6	230	0.04	II
CDP5	0	5	1	0.8	210	0.09	III
CDP‐III	0	2.5	1	1	210	0.8	III

^*Type I, II, and III of bioinks are defined as shown in the earlier scheme. γ_break represents the breaking strain, and m is the strain‐hardening index.

2.4. Rheology Small‐Angle X‐Ray Scattering (Rheo‐SAXS)

Rheo‐SAXS measurements were performed at the 25A1 beamline of the Taiwan Photon Source (TPS 25A1) at the National Synchrotron Radiation Research Center (NSRRC), Hsinchu, Taiwan. A coherent X‐ray beam with a cross‐sectional area of approximately 10 µm² was directed onto the sample, and the scattered signals were collected using a DECTRIS EIGER X 16M hybrid photon‐counting detector (Switzerland). The photon energy was fixed at 8.8 keV with a sample‐to‐detector distance of 6 m, corresponding to a q‐range of 0.0028–0.28 Å⁻¹. The momentum transfer q was determined according to:

$$q=\left(4\pi /\lambda \right)\sin \theta$$ (1)

where θ denotes the scattering angle and λ represents the X‐ray wavelength. The samples were placed in a custom‐made polycarbonate concentric‐cylinder cell (inner diameter = 20.5 mm; outer diameter = 21 mm) and subjected to oscillatory shear deformation using a stress‐controlled rheometer (MCR‐501, Anton Paar, Austria).

2.5. Time‐of‐Flight Small‐Angle Neutron Scattering (SANS)

Time‐of‐flight SANS measurements were conducted on the Bilby instrument [20] at the Australian Centre for Neutron Scattering (ACNS), ANSTO, Australia, operating in the monochromatic mode. A neutron wavelength (λ) of 6 Å was used in this work, providing a q‐range from ≈0.0028 to 0.6 Å⁻¹, where q is the scattering vector defined as Equation (1). The temperature was adjusted in three stages to 25, 37, and 50°C, with each stage maintained for 1 h to reach equilibrium. Data were reduced and radially averaged to 1D on an absolute scale by standard instrument procedures using the Mantid software [21].

2.6. Model Fitting

SAS‐view (4.2.2 version) software was utilized to analyze raw data.

The experimental SANS curves of CDP hydrogels were analyzed and fitted by the following model function.

$$I\left(q\right)=I_{\mathrm{net}}\left(q\right)+I_0{P}_{\mathrm{cs}}(q)S_{\mathrm{HS}}(q)+I_{\mathrm{bkg}}$$ (2)

where I(q) represents the overall intensity after data reduction from the experiment, and I₀ is the scaling factor. I_bkg denotes the background.

I_net is the power‐law model, defined as [22]:

$$I_{net}\left(\mathrm{q}\right)=I_{scale}{q}^{-Df}$$ (3)

where fractal dimension (D_f) indicates the large‐scale inhomogeneities in the hydrogel. I_scale is the scaling factor.

P_cs(q) is the core‐shell sphere form factor having a polydisperse core and uniform shell thickness defined by the following equations [23]:

$$P_{\mathrm{cs}}\left(q\right)=\frac{\mathrm{scale}}{V_{\mathrm{mic}}}\underset{0}{\overset{\infty }{\int }}f\left(R_{\mathrm{core}}\right){F_{\mathrm{core}-\mathrm{shell}}}^2\left(q\right)\mathrm{d}R$$ (4)

$$\begin{array}{cc}\hfill F_{\mathrm{core}-\mathrm{shell}}\left(q\right)& =\frac{3V_{\mathrm{core}}\left({\rho }_{\mathrm{core}}-{\rho }_{\mathrm{shell}}\right)j_1\left(q{R}_{\mathrm{core}}\right)}{q{R}_{\mathrm{core}}}\hfill \\ & +\frac{3V_{\mathrm{mic}}\left({\rho }_{\mathrm{shell}}-{\rho }_{\mathrm{solvent}}\right)j_1\left(q{R}_{\mathrm{mic}}\right)}{q{R}_{\mathrm{mic}}}\hfill \end{array}$$ (5)

where j₁(qr) = [sin(qr)‐qrcos(qr)]/(qr)² and the radius, R, can be either R_mic or R_core which represents the radius of the micelle or radius of the core. V_mic and V_core are calculated from V = 4π r³/3 represent the volume of the micelle or core. According to the literature, the scattering length density (SLD, ρ) of poly(propyl oxide), poly(ethyl oxide), and water are ρPPG = 0.34 × 10⁻⁶ Å⁻², ρPEG = 0.64 × 10⁻⁶ Å⁻², and ρWater = 6.33 × 10⁻⁶ Å⁻², respectively [24]. f(r) is the normalized Schulz distribution described as follows:

$$f\left(r\right)=\left(z+1\right)z+1uz\frac{e[-(z+1)u]}{r_{\mathrm{avg}}(z+1)}$$ (6)

where u = r/r_avg, and r_avg is the average radius. Γ(x) is the Gamma function and z is related to the polydispersity by z = 1/(p²–1), where p = σ/r_avg is the variance of the distribution.

S_HS(q) is the hard‐sphere structure factor using the Percus–Yevick approximation to model the correlation between the particles [25]:

$$S_{\mathrm{HS}}\left(\mathrm{q}\right)=\frac{1}{1+24\eta \mathrm{G}(2R_{\mathrm{HS}}\mathrm{q})/2R_{\mathrm{HS}}\mathrm{q}}$$ (7)

where R_HS is the hard‐sphere radius, which denotes as a half of the center‐to‐center distance between the particles. η is the hard‐sphere volume fraction that shows the correlating fraction of particles, and G is defined below:

$$\begin{array}{cc}\hfill G\left(x\right)& =\gamma \frac{\sin x-x\cos x}{x^2}+\frac{2x\sin x+\left(2-x^2\right)\cos x-2}{x^3}\hfill \\ & +\epsilon \frac{-x^4\cos x+4(32-6\cos x+(x3-6x\sin x+6))}{x^5}\hfill \end{array}$$ (8)

where γ = (1 + 2η)²/(1 − η)⁴, κ = −6η(1 + η/2)²/(1 − η)⁴, and ε = γη/2.

2.7. Injectability and 3D Printability

Injection experiments were performed through a syringe with a 26G (260 µm) needle to evaluate the linearity of the injected filaments. Cell‐free 3D printed constructs were fabricated through a 30G (159 µm) cone‐like nozzle from a commercial 3D bioprinter (Regenovo, China) to evaluate the printability, uniformity factor, and spreading ratio.

The printability characteristic, Pr, is defined by [26]:

$$\mathrm{Pr}=\left(\frac{\pi }{4}\times \frac{1}{C}\right)=\frac{L^2}{16A}$$ (9)

where C is the circularity calculated by the quotient of area (A) divided by the square of the perimeter (L) of the interconnected channel‐like pores of the printed construct. C is defined by:

$$C=\frac{4\pi A}{L^2}$$ (10)

The uniformity factor (UF) represents the ratio of the actual filament uniformity to its theoretical uniformity along the extrusion path.

$$\mathrm{UF}=\frac{l_{ext}}{l_{str}}$$ (11)

where l_ext represents length of extrusion strand, and l_str is theoretical straight length.

The spreading ratio (SR) is defined as the ratio between the measured average filament width (D_filament) and the nozzle inner diameter (D_{n eedle}), reflecting the degree of material spreading during extrusion:

$$\mathrm{SR}=\frac{D_{filament}}{D_{needle}}$$ (12)

2.8. Cell Culture and 3D Bioprinting

The NE‐4C cells (RRID: CVCL_B063), which is one of NSC cell lines and originally obtained from the American Type Culture Collection (ATCC), were purchased from Wuhan Sunncell Biotechnology Co., Ltd. The cells were cultured and passaged in Eagle's minimum essential medium (EMEM, Gibco, USA) containing 10% fetal bovine serum (Sigma‐Aldrich, USA) and 1% penicillin‐streptomycin antibiotics (PS, Gibco, USA) in a 37°C CO₂ incubator.

The cell‐loaded CDP hydrogels were prepared for following experiments. Pre‐hydrogel solutions were added with 2.5 × 10⁶ cells/mL NSCs and filled into the printing syringe of the 3D bioprinter. The parameters, including the nozzle size (23, 26, 30, and 32 G) and platform temperature (37°C) were kept constant, while the nozzle temperature (20–37°C) and air pressure (0.2–0.33 MPa) were adjusted for successful 3D printing. After bioprinting, cell‐laden constructs were soaked immediately in culture medium and moved into the 37°C incubator. Propidium iodide (PI, 5 µg/mL) was used to stain membrane‐compromised cells to assess cell death after printing with different nozzle gauges. Red fluorescence was observed using a confocal microscope (excitation = 514 nm, Nikon).

2.9. Cell Viability and Proliferation

The viability of NSCs loaded in hydrogel and injected within filaments was tested via dead and live staining. The live/dead cell imaging analysis was performed with the Live/Dead Cell Vitality Kits (C2015M, Beyotime, China). The viability of the cells was tested after the cell‐loaded hydrogel was extruded through needles and incubated in the 37°C incubator for 1 day. After incubation with the calcein/PI buffer for 30 min, the live or dead cells in the hydrogel were observed under a confocal laser scanning microscope (Axio Observer 7, Zeiss, Germany) excited at 488 and 514 nm. The quantification was analyzed using ImageJ software. The proliferation of NSCs encapsulated in the injected hydrogel filaments was analyzed by the Cell Counting Kit 8 (CCK‐8, Beyotime, China) within 7 day. The measurement with the CCK‐8 assay was performed at a wavelength of 450 nm using a microplate reader (Mutiskan SkyHigh 1550, Thermo Fisher, USA). The cell viability of both hydrogel groups was normalized to the absorbance at the initial day.

2.10. Cell Differentiation

The cell differentiation medium was changed at 70% full growth of NE‐4C cells to test the ability of hydrogel to promote stem cell differentiation. Cell differentiation medium was mainly composed of Neurobasal‐A (Gibco, USA) supplemented with 0.24 mg/mL GlutaMAX (Gibco, USA), 2% B‐27 without vitamin A (Gibco, USA), and 1% PS. For cell immunofluorescent staining (IF), primary antibodies used in this study included anti‐beta III tubulin antibody (1 µg/mL, ab18207, Abcam, UK) and anti‐GFAP antibody (1:500, ab4674, Abcam, UK). Then, neural stem cells were incubated with goat anti‐rabbit IgG H&L (1:500, Alexa Fluor 488) and goat anti‐chicken IgY H&L (1:500, Alkaline Phosphatase) secondary antibodies for 1 h at room temperature. Cell nuclei were counter‐stained with the DAPI staining solution (C1006, Beyotime, China). Photomicrographs were taken by a confocal laser scanning microscope (Axio Observer 7, Zeiss, Germany) excited at 488 and 680 nm. Quantitative data on the average fluorescence intensity of these micrographs were calculated using ImageJ software. The Western blot (WB) method was further employed to quantitate the protein expression levels. The cell lysates were vortexed intermittently every 10 min for 1 h at 4°C, mechanically homogenized by repeated pipetting, and centrifuged at 12 000 g for 10 min at 4°C. The supernatant was collected, and protein concentration was determined using a Bicinchoninic Acid (BCA) Protein Assay Kit (WB6501, NCM, China) according to the manufacturer's protocol. Samples containing 40 µg of total protein per lane were resolved on a 15% sodium dodecyl sulfate‐polyacrylamide gel electrophoresis and transferred onto a 0.45 µm polyvinylidene fluoride membrane (PVDF Immobilon‐P, IPVH00010, Millipore, USA). Membranes were blocked with 5% (w/v) skimmed milk in TBST for 2 h at room temperature. Primary antibodies included anti‐IL‐1β (1:1000, ∼55 kDa, ab18207, Abcam, UK), anti‐GFAP (1:1000, ∼50 kDa, ab4674, Abcam, UK), and anti‐β‐actin (1:5000, ∼42 kDa, AF7018; Affinity Biosciences, UK). Membranes were incubated overnight at 4°C, washed three times with Tris‐borate‐sodium Tween‐20 buffer, and probed with horseradish peroxidase‐conjugated goat anti‐rabbit IgG (H+L) secondary antibody (1:1000, A0208; Beyotime Biotech., China) in 5% skimmed milk for 2 h at room temperature. Protein bands were imaged with a ChemiDoc XRS+ Imaging System (Bio‐Rad, USA). Band intensities were quantified using ImageJ software.

2.11. Statistical Analysis

Data are presented as mean ± standard deviation. All samples were prepared independently at least three times. All studies were performed in at least three independent replicates (n ≥ 3) to confirm reproducibility. One‐way ANOVA followed by Tukey's post hoc test or Student's t‐test was utilized to statistically differentiate between groups. Statistical analysis was carried out using commercially available GraphPad Prism 9 software. Data with the p‐values < 0.05 were considered statistically significant (^* p < 0.05, ^** p < 0.01, ^*** p < 0.001).

3. Results and Discussion

In extrusion‐based bioprinting (EBB), the 3D bioink is subjected to high shear force during the printing process, yet the printed construct has to maintain stability to ensure the integrity of the fine structure [27]. There is an urgent need for new bioink systems with customized and controllable viscoelasticity and thixotropy, as well as a series of systematic methods for qualitative and quantitative analysis of these complex behaviors. Recent studies have proposed various design strategies to regulate the interplay among rheological properties, viscoelastic behavior, and cell fate. These include single‐polymer systems with engineered molecular interactions and multi‐material formulations combining reversible/static single‐/double‐network networks [28, 29]. Representative approaches employ dynamic covalent chemistry (e.g., Schiff base, boronate ester, and oxime linkages), physical associations such as hydrophobic interactions and ionic coordination, and supramolecular host–guest assemblies, all of which allow decoupling of rheological tuning from viscoelastic modulus or biochemical signaling [30]. Such advances provide a versatile framework for tailoring the flowability, shape fidelity, and bioactivity of extrusion bioinks. Building upon these principles, the present study introduces a dual‐network CDP system that integrates micellar physical association, dynamic Schiff base chemistry, and phenolic coupling. This combination enables independent control of viscoelasticity and structural recovery while preserving high biocompatibility and print precision, thereby situating this work within the broader context of recent bioink design innovations.

Scheme 1 demonstrates three classical dynamic strain sweep diagrams of hydrogel‐based bioinks. The type I bioink (often a physical hydrogel) demonstrates significant shear‐thinning behavior within the linear viscoelastic region, and the printed construct exhibits uniform filament formation and requires minimal driving force during the printing process. These bioink systems are typically with a high degree of secondary force, such as hydrogen bonding and amphiphilic interaction, including water‐based polyurethane nanoparticles and Pluronic micelles [31, 32]. However, due to their prolonged shear‐thinning properties, hydrogel constructs printed with these materials are prone to damage from shear force during manipulation such as pick‐up, transfer, and bioapplication. In the type I bioink, the encapsulated cells undergo slight deformation due to the highly flowable matrix; however, the weak cohesion of the ink leads to significant material loss and structural disintegration, making it unsuitable for long‐term cell culture and tissue maturation. The type III bioink (often a chemical hydrogel) refers to that with a stable elastic modulus in the medium to high strain region and strain‐hardening characteristics before the shear‐induced gel‐to‐sol transition. This type III bioink is commonly present in a chemically crosslinked hydrogel system where the hydrogel is constructed from high molecular weight main chain, and a functionalized crosslinker, such as the chitosan hydrogel crosslinked by functionalized polyethylene glycol and the calcium ion crosslinked alginate bioink [33, 34]. The type III bioink offers good post‐printing property as it has stable viscoelasticity, reliable pick‐up capability, and biomimetic shear‐hardening. However, the pronounced strain‐hardening behavior generates localized compressive stress during extrusion, particularly near the syringe wall where shear gradients are highest. Cells located in these peripheral regions are more susceptible to mechanical deformation and membrane rupture, which can lead to cytoskeletal disruption and apoptosis. Although the printed constructs remain stable and mechanically robust, excessive wall‐induced stress may compromise long‐term cellular activity and viability. The type II bioink, typically formulated as a binary hydrogel, exhibits distinctive non‐Newtonian behaviors such as shear‐thinning and rapid structural recovery. These rheological characteristics minimize cellular damage during extrusion while maintaining high stacking fidelity, as well as favorable pickability and flexibility after printing. Within this balanced scenario, the physical network provides an optimal viscoelastic that enables cells to preserve their morphology during extrusion and sustain high post‐printing viability, while the chemically crosslinked hydrogel network subsequently contributes to mechanical buffering and facilitates efficient nutrient exchange. Such results in uniform cell distribution, continuous cellular proliferation, and overall rheological adaptability are particularly desirable for extrusion‐based bioprinting (EBB) systems [27]. In type III bioink, the physically crosslinked network provides an appropriate viscoelastic balance that allows cells to maintain their morphology during extrusion while supporting high post‐printing viability. The chemically crosslinked hydrogel network further offers mechanical buffering and facilitates nutrient exchange after printing, resulting in uniform cell distribution and sustained proliferation. Meanwhile, the type II bioink can be nanoengineered from the chemical network with a large number of nanoparticles. Examples include the thermoreversible shear‐thinning hydrogel composed of κ‐carrageenan and nanosilicate plates [35] and the composite bioink of laponite and glycosaminoglycan nanoparticles for bone tissue engineering applications [36].

SCHEME 1.

Common structure‐property‐printing relationships of a binary network hydrogel bioink system constructed from chemical network and physical interaction.

As illustrated in Figure 1A, the benzaldehyde‐terminated difunctional Pluronic (DP) was synthesized in this study. Being a typical type I hydrogel bioink, Pluronic hydrogel and its derivatives are widely utilized in the bioprinting field [31]. Their excellent shear‐thinning and stackability originated from their shear‐induced mixed‐oriented structures and great amounts of crystalline association. When Pluronic micelles associate and organize above the critical micelle temperature (CMT), they form the lyotropic liquid crystal (LLC) phase, a complex liquid phase with anisotropic crystalline solids and isotropic fluids [31]. The modified Pluronic, such as DP, still retains the self‐assembly ability of spherical micelles [37]. Chitosan phenol (CP) was synthesized as shown in Figure 1B through the EDC/NHS conjugation. The rapid gelation process of CP in the presence of DP has been reported, which becomes a CDP hydrogel [37]. The structure network of CDP hydrogel is established by dynamic covalent bonding between the aldehyde groups on DP and the amino groups on CP, i.e., Schiff base linkages. The CMT of DP micellization under different concentrations was examined using DSC analyses, as shown in Figure 1C. For DP at the concentrations of 15, 20, and 25 wt.% (each abbreviated as DP15, DP20, and DP25), the T_peak was observed at 19, 17.5, and 15.5°C, respectively. Meanwhile, the T_peak for the unmodified Pluronic (PF) at 15, 20, and 25 wt.% (PF15, PF20, and PF25) is 17, 14, and 11°C, respectively [38]. Comparing DP with PF15, PF20, and PF25, the deviation of the CMT after functionalization is about +2 to 5°C. Such deviation may be ascribed to the altered critical packing parameters (CPP) of DP micelles. As a result, DP micelle solutions require higher internal energy (high temperature) for self‐assembly. Similar to PF hydrogel, pure DP can form a physical gel mainly through crystalline association when micelles contact one another above CMT. The CDP hydrogel co‐constructed from dynamic covalent crosslinking between DP and CP, as well as crystalline association from DP, exhibits a stable hierarchical binary network structure, as schematized in Figure 1D. This binary network structure can be adjusted through changing the ratio of DP, thereby switching the behavior and performance of CDP hydrogel to fall into the category of type I, type II, or type III bioink (Figure 1E). As shown in Figure S1A,B, the single‐network DP‐I hydrogel exhibited poor structural stability during the swelling test. Due to the absence of long‐range crosslinking structures, more than 50% of its mass was lost after immersion in PBS for 6 h, primarily attributed to the dissolution and diffusion of Pluronic components. In contrast, the binary‐network hydrogels, CDP‐II and CDP‐III, maintained favorable swelling capacities (approximately 105.2% and 142.0%, respectively, at 12 h), which can be attributed to the presence of dynamic covalent crosslinking networks. In the 7‐day in vitro degradation test, both CDP‐II and CDP‐III showed approximately 50% weight loss initially, followed by a slower degradation phase. This behavior is likely due to the gradual diffusion of uncrosslinked DP molecules, while the remaining chemically crosslinked network retained structural integrity. Notably, residual hydrogel structures were still observable after three weeks, indicating prolonged stability conferred by the dynamic covalent and potentially dityrosine crosslink chemistry. To evaluate the structural integrity of the hydrogel constructs, we premolded the hydrogels into geometries compatible with the rheometer fixtures and conducted mechanical assessments at 0 and 7 days of incubation (Figure S1C,D). After 7 days, the hydrogels showed signs of degradation and shrinkage (40%) yet maintained a well‐defined shape and structure. Rheological measurements showed that in the cell‐laden CDP‐II group at 7 days, the storage modulus decreased to approximately 860 Pa, representing a ∼10% reduction. In contrast, the acellular CDP‐II group incubated in PBS exhibited a significant decrease to ∼470 Pa, corresponding to a ∼50% reduction. These results suggest that the presence of cells may enhance hydrogel stability, likely due to the secretion of extracellular matrix components by cells and the interaction between the hydrogel and proteins in the medium, which incorporates the hydrogel structure and regulates degradation behavior. Moreover, in both environments, the tan δ values declined from 0.26 to 0.06 or 0.11, indicating a shift toward more gel‐dominant behavior after incubation. This transition is likely due to the leaching of uncrosslinked physical networks during degradation, leaving behind a higher percentage of chemically crosslinked networks that dominate the remaining structure.

FIGURE 1.

Chemistry and thermal property analyses of CDP hydrogels. (A) The synthesis route of difunctional Pluronic F127 (DP). (B) The synthesis route of chitosan phenol (CP). (C) The DSC curves of DP solution at the concentrations of 15, 20, and 25 wt.%. (D) The schematic diagram showing the structure‐forming process of CDP hydrogel. PEO represents poly(ethylene oxide), and PPO represents poly(propylene oxide). (E) Hydrogels prepared with different contents of DP and CP at 37°C correspond to different regimes of viscoelasticity, drawn according to the rheological data. Types I, II, and III: refer to Scheme 1.

The hydrogels representing each of the three bioink types are listed in Table 1 for further rheological and structural characterizations. They are abbreviated as (C)DP‐x hydrogels, where “C” and “x” indicate the presence of chitosan and the shear type of the hydrogel, respectively. According to the time sweep tests shown in Figure 2A, the DP‐I hydrogel exhibited a steady storage modulus (G′) of 1.1 kPa. In contrast, the CDP‐II and CDP‐III hydrogels experienced a gradual rise of modulus during the first 200 s, which is attributed to the rapid gelation process via the Schiff base reaction. The stabilized G′ values for the CDP‐II and CDP‐III hydrogels were 0.6 kPa and 1 kPa, respectively. Notably, the loss modulus (G′′) of the CDP‐III hydrogel showed continuous oscillations (Figure 2A‐iii), a phenomenon frequently observed in chitosan self‐healing hydrogels formed through dynamic Schiff base bonds [39]. This behavior was absent in the DP‐I and CDP‐II groups, possibly because the Schiff base‐dominated network in the CDP‐III hydrogel gradually changed into a micelle‐dominated crystalline association network. In dynamic strain sweep tests, the G′ of the DP‐I hydrogel dropped suddenly as the strain increased and undertook a gel‐to‐sol transition at a 10% dynamic strain (Figure 2B‐i). The CDP‐II hydrogel exhibited a stable G′ up to 200% applied strain, with the gel‐to‐sol transition occurring at 230% strain (Figure 2B‐ii). Meanwhile, the CDP‐III hydrogel maintained a stable G′ below 50% applied strain and displayed strain‐hardening between 50% and 200% strain, followed by a gel‐to‐sol transition at 210% strain (Figure 2B‐iii). In the temperature sweep (Figure 2C), the DP‐I hydrogel showed a distinct increase in viscoelasticity between 16°C and 19°C, corresponding to the critical micellization temperature (CMT) of its amphiphilic segments. The abrupt rise in G′ reflects the thermally driven micellar self‐assembly and subsequent formation of a physically organized liquid‐crystalline network, which is the typical characteristic of Pluronic‐based systems. In contrast, the CDP‐II and CDP‐III hydrogels exhibited a different thermal response. Instead of a sharp transition near 16–19°C, both samples showed a gradual and continuous increase in G′ across 25–37°C. This broader and delayed stiffening indicates a progressive reinforcement of the network rather than a discrete sol‐gel transition. The shifted response is attributed to the interpenetration of chitosan main chains and dynamic covalent linkages within the CDP binary network, which restrict micellar rearrangement and slow aggregation. As a result, the combined physical and dynamic crosslinking produces a thermally resilient and predictable viscoelastic behavior, favorable for maintaining printing fidelity and supporting cell viability under physiological conditions.

FIGURE 2.

The rheological profiles of (i) DP‐I, (ii) CDP‐II, and (iii) CDP‐III hydrogels. (A) The time sweep test of CDP hydrogels, measured under 1% dynamic strain. (B) The strain sweep test of CDP hydrogels under varying strains. Dash lines denote 200% strain reference line. (C) The temperature sweep test of CDP hydrogels during heating and cooling cycles, showing thermoreversible sol‐gel transitions. (D) The damage‐recovery cycle tests of CDP hydrogels conducted under alternating low (1%) and high strains (50% or 300%), demonstrating reversible modulus recovery and self‐healing behavior. (E) Normalized differential modulus (K′/K₀) against normalized stress (σ/σ_c). CDP₅ is the hydrogel with formula in‐between CDP‐II and CDP‐III (Table 1).

In the damage‐recovery tests (Figure 2D), all hydrogels demonstrated rapid and repeatable recovery of viscoelastic properties following large‐amplitude deformation, confirming their self‐healing capability. The Type I (DP‐I) hydrogel, characterized by strong shear‐thinning behavior, was disrupted at a relatively low strain amplitude of 50%, consistent with its weaker structural cohesion. In comparison, both Type II (CDP‐II) and Type III (CDP‐III) hydrogels with dual crosslinked networks withstood deformation up to 300% strain and quickly recovered their initial G′ values once the strain returned to 1%. This reversible modulus restoration highlights the excellent structural resilience of CDP hydrogels, where dynamic physical and covalent interactions cooperatively enable energy dissipation and network reconstruction after mechanical disruption. The plot of differential modulus (K′) as a function of shear stress (σ) revealed a nonlinear response at high σ for the CDP hydrogels. Here, K′ represents the derivative of σ with respect to shear strain (γ), defined as K′ = ∂σ/∂γ. The m‐value of the CDP‐III hydrogel was 0.8, as illustrated in Figure 2E. When the DP concentration increased, the m‐value of the CDP‐II hydrogel decreased to 0.04. In the meantime, CDP₅ hydrogel, which is a formula between CDP‐II and CDP‐III with a micelle content of 5% showed an m‐value of 0.09. This observation indicates that the change in the m‐value of the CDP system is largely attributed to the amount of micelles involved. Previously, m‐values for a series of difunctional PEG crosslinked chitosan hydrogel were reported to be 1.3–1.4 [16]. The degree of shear strain‐hardening in CDP gel may be inversely proportional to the order of magnitude of micellar crystalline association domains.

Pluronic hydrogel forms an orderly LLC phase via the association of highly concentrated micelles, which exist above the CMT [40]. The hydrogel matrix experiences shear stress, altering the spatial arrangement of the LLC and thereby affecting the macroscopic viscoelasticity [40]. The real‐time structural analyses of (C)DP hydrogels under different strains were analyzed using rheo‐SAXS (Figure 3A). As indicated by the marks in Figure 3B, the 1D scattering profiles of DP‐I hydrogel exhibit characteristic peaks at q* = 0.0348 (1,1,1), 0.056 (2,2,0), and 0.0695 (2,2,2) Å⁻¹. Based on the ratio of these peaks, the structure was identified as face‐centered cubic (FCC), which is in alignment with the literature for pure Pluronic F127 systems [41]. At the low dynamic strain (1%), the 2D scattering pattern displays the FCC polycrystalline structure, which gradually transits into the mixture of FCC and 2D‐HCP single‐crystal stacking under a higher (500%) strain. Compared with the scattering of PF‐I at 500% strain in Figure S2, the intensity of the first scattering ring (q*) is significantly lower than that of DP hydrogel, which is attributed to the higher lattice defects of DP hydrogel after surface modification that reduce the amount of continuous crystalline layers. It may also account for the lower G′ of DP hydrogel, which is only 1/7 of the G′ of PF‐I hydrogel, as shown in Figure S3. In the CDP‐II hydrogel (Figure 3C‐i), a high strain (500%) induces the appearance of crystalline peaks that are absent under low‐shear conditions. The influence of shear on the LLC structure is evident in the anisotropic 2D scattering profile. The transient shear results in a six‐fold symmetry feature in the 2D scattering pattern, which may correspond to locally ordered domains formed through heterogeneous nucleation, particularly under non‐uniform flow fields such as those occurring during injection [38]. It is noteworthy that six‐fold symmetry has not been reported in a Pluronic system with such low micelle composition (<15 wt.%). It is speculated that the permeation and crosslinking of chitosan chains resulted in the formation of a chitosan framework that partitioned the gel interior into multiple heterogeneous domains. These domains exhibited localized concentrated regions, where short‐range micellar crystallites formed under high dynamic shear. Furthermore, the scattering peak of CDP‐II hydrogel disappears immediately after strain recovers to 1% and reproducibly appears under the alternative 500% strain (Figure 3C‐ii). Different from the previous two types, CDP‐III hydrogel, which is mainly composed of a chemically crosslinked network, does not exhibit any observable anisotropic structures, even at the highest strain. This behavior may be attributed to the presence of numerous stretched crosslinked semi‐flexible CP fibers, which dominate the energy dissipation, rather than the stacking and arrangement of micelles. In literature, O‐carboxymethyl chitosan hydrogel networks crosslinked by aldehyde‐functionalized PEG exhibited biomimetic stiffening behavior upon dynamic shear, which was attributed to the dynamic covalent fixation of semi‐flexible chitosan fibers at high strains (entropy spring effect) [16].

FIGURE 3.

Rheo‐SAXS of CDP hydrogel under oscillatory strains. (A) Experimental set‐up and 2D scattering patterns of CDP hydrogels. (B) 1D scattering profiles of DP‐I hydrogel under varying dynamic strain (1%, 100%, and 500%). (C‐i) 1D scattering profiles of CDP‐II hydrogel under varying dynamic strain (1%, 50%, 100%, 300%, and 500%). (C‐ii) Scattering profiles under repeated high (500%) and low (1%) strains. (D) Azimuthal analysis for the three types of hydrogels at 500% strain.

The azimuthal diagrams for the three types of hydrogels under 500% strain are listed in Figure 3D. The ones in DP‐I and CDP‐II hydrogels show azimuthal anisotropic six‐fold symmetry. The response behaviors of the three types of hydrogels based on the mesoscale structural changes under applied dynamic strain are summarized in Scheme 2. Under high strain, the energy dissipation of DP‐I hydrogel is dominated by rearrangements of the LLC phase and the sliding of the crystalline layer. This process increases structural disorder, effectively dissipating the external energy applied to the system, increasing the system entropy, and resulting in shear‐thinning behavior. CDP‐III hydrogel can be reinforced by numerous semi‐flexible polysaccharide fibers that act as entropic springs. These provide instant elastic recovery and exhibit strain‐hardening behavior, enabling the hydrogel to maintain its integrity under high‐strain conditions. Type II CDP hydrogel combines characteristics of both type I and type III hydrogels. Under high shear, it forms transiently oriented LLC single crystals. Once the strain is relieved, the structure recovers to its original state through the action of entropic springs.

SCHEME 2.

Mesoscale structural changes of three types of bioinks during the injection process. Type I bioinks show LLC phase before and after injection and have an irreversible directional single crystal. Type II bioinks demonstrate reversible anisotropic crystals during the injection process. Type III bioinks denote isotropy in each strain stage and the injection expansion phenomenon.

The fine structural characterization of such a unique binary‐component CDP‐II hydrogel was done through the SANS techniques. Using deuterated solvent, the SANS provided highly precise and ultra‐high contrast scattering profiles for structural fitting. The modeling was conducted via Equation (2), as referenced [37]. The analysis included forward scattering described by a power law for large‐scale inhomogeneities via Equation (3). The core‐shell spherical form factor and the hard‐sphere structure factor were applied to characterize the fractal dimension of network (D_f), micelle size (R_core and T_shell), inter‐particle center‐to‐center distance (R_hs), and the volume fraction (η) of correlated micelles. Table 2 presents the parameters obtained from the best fit of CPF at the applied temperature range through SANS analyses (Figure 4A,B). As the temperature gradually increases, the main peak at q = 0.0305 Å⁻¹ (25°C) shifts to q = 0.029 Å⁻¹ (50°C), indicating an increase in the size of DP micelles. The fitting analysis denotes that R_core increases from 4.0 ± 0.1 nm (25°C) to 4.9 ± 0.1 nm (50°C), while the T_shell rises from 3.1 ± 0.1 nm to 3.4 ± 0.1 nm. This growth in micelle size is attributed to the enhanced hydrophobic association induced by thermal conduction, revealing a transition from a micelle to a hard sphere. The inter‐particle distance derived from the structural factor indicates an average distance of 2𝑅_hs ranging from 20.2 to 21.4 nm, which is greater than the diameter of micelles (13.6–16.6 nm). This finding suggests that the spheres are not in continuous contact with one another. In the forward scattering region, the fractal‐like network structure constructed by chitosan chains and micelles was quantified by the fractal dimension (D_f). During the heating process, D_f increased from 2.61 (25°C) to 2.72 (50°C), indicating that the network became slightly compact as the temperature rose. The structure factor P(q) reveals that the hard‐sphere associated volume fraction (η) at all three temperatures is approximately 32%–36% only, which is significantly below the 74% packing density required for the formation of FCC or HCP stacking. Under shear‐induced conditions, however, the CDP‐II hydrogel with low micelle concentrations exhibits the local induction of LLC. It can be inferred that, under high shear strain conditions, the CDP‐II system composed of chitosan fibers and appropriately concentrated DP micelles (concentration > 8%) can form localized short‐range crystalline domains. This behavior is attributed to the local transient micelle packing density that approaches 74% under high shear strain. We interpret this phenomenon as shear‐induced LLC, where the short‐range crystalline domains provide the CDP system with approved shear properties. Notably, this process is reversible under the alternative high and low strains. Owing to the presence of entropy springs provided from chitosan chain conformation, removal of high strain causes the crystalline domains to return to the original packing density, thereby disintegrating the LLC structure.

TABLE 2.

The best‐fit parameters in SANS identification of CDP‐II hydrogel within the temperature range of operation for the 3D printing ink.

T (°C)	Df	Form factor		Structure factor
		Rcore (nm)	Tshell (nm)	Rhs (nm)	η (%)
25	2.61	4.0 ± 0.1	3.1 ± 0.1	10.2 ± 0.1	32
37	2.67	4.5 ± 0.1	3.6 ± 0.1	10.7 ± 0.1	36
50	2.72	4.9 ± 0.1	3.4 ± 0.1	10.6 ± 0.1	33

FIGURE 4.

SANS profiles and fitting results of CDP‐II hydrogel. (A) SANS profiles at three different temperatures. (B) The best fit curve at 37°C and the separated dashed line contributed from various factors.

When injected by a 26G syringe needle (Figure 5A), DP‐I and CDP‐II produced smooth filaments with minimal volume expansion, whereas CDP‐III exhibited elastic curling due to its high ratio of semi‐flexible fibrillar networks. Figure 5B presents the resolution evaluation of CDP inks after extrusion from a 30G (159 µm) cone‐like nozzle using the 3D bioprinter. The interconnective channel index Pr was applied to quantify the printability [26]. The Pr value for DP‐I ink is close to 1, indicating nearly square pores of the printed construct. CDP‐II ink demonstrated a slightly rounded boundary with a Pr value of approximately 1.05. CDP‐III ink exhibited an irregular boundary with a Pr value of 1.24. According to the literature [26], bioinks with a Pr range of 0.9–1.1 are considered to have superior printability. The uniformity factor (UF) was used to assess the filament consistency along the extrusion path. The DP‐I construct exhibited a UF value close to 1, suggesting highly uniform filament thickness with minimal fluctuation during printing. Slight deviations were observed in CDP‐II (UF ≈ 1.02) and CDP‐III (UF ≈ 1.05) constructs, indicating minor irregularities possibly caused by intermittent flow instability and increased structural resistance in more crosslinked networks. The spreading ratio (SR), which reflects the extent of filament expansion after deposition, further revealed differences in extrusion behavior among the inks. DP‐I showed moderate spreading (SR ≈ 1.16), whereas CDP‐II maintained a comparable level (SR ≈ 1.14), suggesting stable deposition with balanced viscosity and shear response. In contrast, CDP‐III displayed a noticeably higher SR (≈ 1.4), likely due to higher internal elasticity and post‐deposition relaxation. Together, these printability metrics demonstrate that DP‐I and CDP‐II hydrogels fall within the optimal range for structural fidelity, while the increased crosslink density in CDP‐III compromises filament definition despite its enhanced mechanical stability.

FIGURE 5.

The nanoengineered CDP hydrogel applied in 3D bioprinting. (A) Filaments of different CDP bioinks were extruded from a 26G (260 µm) syringe needle. The scale bar is 1 cm. (B) 3D printed constructs extruded from a 30G (159 µm) cone‐like nozzle using the 3D bioprinter. The scale bar represents 200 µm. The symbols I, II, and III represent DP‐I, CDP‐II, and CDP‐III. The filament width distribution was quantified using Image J. (C) Square constructs printed using CDP‐II bioink with culture medium as solvent. (D) Experimental diagram of the printing paths for brain modules generated by modeling the (i) pig brain computed tomography (CT) image (thickness: 3 mm, 8 layers) and (ii) human half‐brain (thickness: 7 mm, 18 layers) CT image. The macroscopic photograph of the bioprinted CDP‐II hydrogel construct can be picked up and combined. The construct was printed with the 30G cone‐like nozzle. The scale bars are 0.5 cm.

The moduli of CDP hydrogels are in the range of 0.6 to 1.1 kPa, which is comparable to the mechanical strength of brain/neural tissues [42]. Hence, neural stem cells were selected for evaluating bioprinting and biocompatibility of CDP hydrogels. The cell‐laden CDP bioinks were extruded from the 3D bioprinter through a 30G needle‐like nozzle with an inner diameter of 159 µm to assess cell survival under extremely high shear strain. Among the three types of CDP hydrogels, DP‐I demonstrated strong shear‐thinning behavior with good stacking properties, but the printed construct was fragile and could not be picked up due to the lack of long‐range crosslinked structure, as illustrated in Figure S4. Therefore, it was excluded from further experiments. CDP‐II exhibited moderate stacking and printing characteristics. Meanwhile, CDP‐III bioink, characterized by a high proportion of chemically crosslinked network, showed pronounced nozzle expansion behavior and resulted in unevenly printed filaments. CDP‐II bioink prepared in culture medium showed high stability and resolution in the square‐shaped construct (8 × 8 mm, 4 layers Figure 5C). In Figure 5D‐i, a brain slice patch with a thickness of 3 mm (18 × 14 mm 8 layers) can be printed based on a porcine brain CT scan. In Figure 5D‐ii, two brain hemispheres (10 × 15 mm, 18 layers) were constructed by a human brain CT image. The modules are combined at the interface to form a complete brain, and the brain is pickable. Given the complex functionally compartmentalized architecture of the brain, the modular 3D bioprinting enables the individual fabrication of distinct functional regions, allowing for the encapsulation of specific neural cell types, vascular endothelial cells, and other supporting cell populations within each module. After modeling and generating the printing path, the brain slice patch printed by CDP‐II bioink with neural stem cells can be repeatedly picked up, moved, and cultured in the medium.

The printed NSCs in CDP‐II bioink exhibited a spherical and aggregated morphology (Figure 6A), consistent with the typical spheroidal shape reported in previous studies [43, 44]. This spherical appearance reflects the inherent tendency of NSCs to minimize surface contact and maintain stemness within soft hydrogel environments. When printed through nozzles of different gauges, a clear correlation between nozzle diameter and cell damage was observed. In the case of the 23G nozzle, nearly no dead cells were detected, indicating minimal shear stress during extrusion. Mild red fluorescence signals appeared in the 26G and 30G groups, suggesting limited cell injury and partial membrane disruption. In contrast, the 32G nozzle induced pronounced cell deformation and a high proportion of dead cells, implying severe mechanical stress within the narrow flow channel. Notably, the printing direction and the cell orientation could be visualized in the groups of 30G and 32G, supporting the presence of localized velocity gradients. In addition, time‐lapse imaging (Video S1) was conducted to continuously monitor neural stem cell behavior within the bioink at 5 days. Throughout this period, cells exhibited sustained viability, active movement, axon spreading, and migratory behavior, confirming that the rounded morphology does not correspond to cellular inactivity or degeneration. Collectively, these results demonstrate that the CDP‐II bioink provides a permissive microenvironment that supports both cell survival and long‐term biological activity following extrusion.

FIGURE 6.

Assessment of viability, structural fidelity, and proliferation of printed NSCs in hydrogels. (A) Bright field and confocal images of the CDP‐II construct extruded through nozzles with different gauges (23G, 26G, 30G, and 32G). The red fluorescence indicates dead cells after extrusion. The black arrow indicates the direction of printing. (B) The live‐dead staining to evaluate the cell death distribution of NSCs in the CDP hydrogel and printed through 32G nozzle. Live cells, green; dead cells, red. (C) Quantification of size expansion ratio of printed filaments after CDP hydrogel injection. (D) Distribution of apoptotic cells in printed hydrogel filaments. (E) The percentage of live cells after printing. (F) Cell proliferation of NSCs encapsulated in hydrogels, evaluated by the CCK‐8 assay over a 7‐day culture period. The results were normalized to the values at day 0 and presented as a percentage of the initial cell number. Data are represented as mean ± SD (n ≥ 3). ^* p < 0.05, ^*** p < 0.001, and ^**** p < 0.0001 between the indicated groups.

As the 32G nozzle induced the highest level of shear‐related apoptosis, the CDP bioink extruded through this nozzle was selected for subsequent analyses of filament expansion, cell distribution, and viability to further demonstrate the distinct printing behaviors of CDP‐II and CDP‐III. The post‐extrusion cellular viability within the printed filaments is presented Figure 6B, where the image was labeled by green fluorescence for live cells and red fluorescence for apoptotic cells. Image quantification revealed three key results. First of all, the CDP‐III bioink showed thicker printed filaments than CDP‐II bioink and had evident nozzle expansion behavior. Figure 6C indicated that the filament expansion ratio for the CDP‐III bioink was 143 ± 6%, compared to 112% ± 4.6% for the CDP‐II bioink, i.e., the CDP‐II bioink had better shape fidelity. Second, apoptotic cells in the CDP‐III group were observed to be predominantly distributed near the edge of the filaments, as opposed to a more uniform distribution in CDP‐II filaments. According to the red fluorescence intensity quantified in Figure 6D, the apoptotic cells were more distributed in the nozzle boundary, which may be due to the stronger shear forces exerted in the case of filament expansion. Lastly, the overall cell viability within the printed filaments was evaluated. The cells in the CDP‐II bioink showed a real‐time survival rate of 86.6 ± 3.2%, compared to 75.1 ± 2.9% for the ones in CDP‐III group (Figure 6E). The optimized shear performance of CDP‐II bioink contributed to its superior cell viability under the high shear strain extrusion process. The proliferation rate of NSCs in two injected hydrogel filaments over 7 days was confirmed by CCK8, as shown in Figure 6F. The proliferation rate of NSCs in CDP‐II was dramatically higher than that in CDP‐III at each point tested within 7 days, e.g., ∼701% vs. ∼411% in 7 days. Judging from the present results, a hydrogel subjected to high shear force during extrusion (such as CDP‐III) can cause more pronounced damage to the cells therein and a substantial decrease in cell proliferation and viability, consistent with common knowledge. Meanwhile, the shear‐adaptive CDP‐II bioink offers significant advantages over the other types of bioinks when printing highly sensitive cells with delicate cellular structures such as cells of the brain.

Through neural cell differentiation experiments, the differentiation tendencies of neural stem cells within the bioinks were determined through immunofluorescence staining and WB. The marker proteins β‐tubulin and GFAP were prominently expressed in the CDP bioinks (Figure 7A), together with proper quantification performed in Figure 7B,C, which indicates that the CDP bioinks have a positive effect on the differentiation of neural stem cells toward neurons and astrocytes. The results are consistent with the literature [45]. Further, the experimental results of WB, which are demonstrated in Figure 7D, were consistent with those of immunofluorescence staining. The corresponding quantification of WB bands is presented in Figure 7E,F. All the uncropped images for WB are supplemented in Figure S5. Based on the above summarized differentiated results, the CDP‐II bioink with a lower G′ (0.6 kPa) promotes neuronal differentiation, whereas the stiffer CDP‐III bioink with a higher G′ (1 kPa) favors the differentiation of neural stem cells into astrocytes. This is consistent with the trend reported in the literature [46]. Since neural cells are more sensitive to shear forces than other cell types, there is a scarcity of shear‐adaptive bioinks suitable for EBB [47]. Furthermore, it is important to note that the spheroidal morphology observed for NE‐4C cells in the three‐dimensional hydrogel environment reflects intrinsic cell‐type–dependent behavior rather than insufficient bioactivity of the matrix. NE‐4C cells, similar to neural stem and early neural progenitor cells, are known to preferentially maintain a compact or spheroid‐like morphology when cultured in three‐dimensional hydrogels, particularly during early to intermediate culture periods, due to limited focal adhesion formation and preservation of stem‐like characteristics [48, 49]. In contrast, neuron‐like cell models that readily undergo process elongation in response to microenvironmental cues provide a more direct readout of whether a given matrix supports axon‐like extension and early neuronal structural maturation. Based on this consideration, PC12 cells were introduced to evaluate neuron‐associated structural responses within the CDP‐II bioink. As shown in Figure S8, immunofluorescence analysis revealed pronounced βIII‐tubulin (TUBB3)–positive neurite‐like extensions, indicating the formation of neuronal cytoskeletal architecture required for axon‐like processes, together with synaptophysin signals distributed along these extensions, a presynaptic vesicle‐associated marker commonly linked to synapse‐related molecular organization. The spatial correspondence between TUBB3‐positive processes and synaptophysin expression suggests coordinated cytoskeletal development and synapse‐associated molecular features within the hydrogel microenvironment.

FIGURE 7.

Characterization of neural stem cell differentiation by immunofluorescent staining at 5 days of culture in CDP hydrogel. (A) DAPI stains the cell nuclei (blue), β‐tubulin staining (green) marks the neuron‐associated proteins, and GFAP staining (cyan) indicates mature astrocytes. The average fluorescent intensities were quantified and performed as graphics for (B) β‐tubulin III and (C) GFAP of each group. (D) Western blot (WB) analyses for the protein expression of GFAP and β‐tubulin were conducted, and the results were quantified by the densitometric analysis for the protein expression levels of (E) β‐tubulin and (F) GFAP normalized to that of β‐actin. Data are represented as mean ± SD (n ≥ 3). ^* p < 0.05, ^*** p < 0.001, and ^**** p < 0.0001 between the indicated groups.

The present efforts in developing the EBB bioink based on the binary nanoengineered CDP bioinks encompass the key points in modulus match, shear‐induced structure‐property relationship, and effects of shear field on cell fate. The CDP bioinks exhibit storage moduli ranging from 0.6 to 1 kPa and support the encapsulation and survival of neural stem cells (> 86%) after printing. This matrix stiffness for neural cells aligns with the 0.1–1 kPa range reported in the literature [50]. Compared with recently reported bioink based on biopolymer hydrogels for neural‐like patch bioprinting, the CDP bioink developed in this study demonstrates a distinctive advantage in its adaptability to small‐gauge extrusion while maintaining a competitive post‐printing cell viability. As summarized in Table 3, most previously reported neural cell‐laden hydrogels were printed through relatively large nozzles (typically ≥ 200 µm, corresponding to 27 G), where shear stress is substantially lower and cell survival is therefore less challenging post‐printing. Beyond this threshold, the steep escalation in cell apoptosis encountered when scaling down nozzle diameters represents a primary bottleneck that has historically constrained bioprinting resolution to these larger scales. In contrast, CDP was evaluated under a markedly more stringent extrusion condition using a 32G nozzle (108 µm) yet still achieved an 86% viability of NE‐4C cells postprinting, underscoring the intrinsic shear‐protective capability of the CDP microstructure rather than a reliance on mild printing parameters.

TABLE 3.

Postprinting cell viability across representative biopolymer‐based hydrogel bioinks for neural tissue engineering.

Bioink	Nozzle	Cell type	Postprinting cell viability (day 0)	Refs.
CDP	108 µm (32 G)	NE‐4C	86.6 ± 3.2%	This study
Alg/CMC/Aga	200 µm (∼27 G)	iPSC	∼98% (day 1)	[51]
Alg/CMC/Aga	200 µm	hNSC	∼75%	[52]
AlgMA/GelMA/HA	200 µm	NPC	86.3 ± 4.1%	[53]
O‐CMC/Alg/ Fibrin	413 µm (22 G)	hiPSC‐NPCs	∼91 ± 8% (day 1)	[54]
GelMa/PEDOT/ PEGDA	260 µm (25 G)	NSC	>85%	[55]
HBC/HA/MA	260 µm	NSC	95.45 ± 3.14%	[56]

Abbreviations: agarose (Aga);alginate (Alg); carboxymethyl chitosan (CMC); gelatin methacrylate (GelMa); hyaluronic acid (HA); hydroxypropyl chitosan (HBC); induced pluripotent stem cells (iPSC); matrigel (MA); neural progenitor cells (NPC); neural stem cell (NSC); O‐carboxymethyl chitosan (O‐CMC); poly(3,4‐ethylenedioxythiophene)(PEDOT); polyethylene glycol diacrylate (PEGDA); thiolated Pluronic F127 (PF127‐SH).

Notably, no existing system can simultaneously prepare three distinct bioinks with fixed compositional elements while exhibiting distinct shear properties of shear‐thinning, comprehensive, and strain‐hardening. In the reported Pluronic‐based (type I) bioink, shear‐induced permanent crystallization led to the shear‐thinning property [57]. Here in our study, the introduction of high molecular weight chitosan changed this behavior by introducing chemical crosslinking points within the network structure, providing overall elasticity and mitigating the shear‐thinning effect. Additionally, the strain‐induced micelle crystallization counteracts a part of the entropy spring effect caused by the chitosan crosslinked network. This mechanism provides the ability of CDP hydrogels to be adjustable between the three types of bioinks. On strain‐sweep diagrams, type II bioinks can be characterized by a flat and stable modulus prior to the failure strain. This feature has also been demonstrated in several high‐resolution and highly printable nanocomposite binary bioinks, such as the double‐network gelatin bioink incorporating water‐dispersible polyurethane nanoparticles for mesenchymal stem cell bioprinting [12] and the alginate‐based hydrogel integrated with silver‐patched silica nanoparticles for precision printing of human osteosarcoma cells [58], However, in most of these systems, the underlying structure‐property relationships and dynamic adaptation mechanisms during extrusion remain insufficiently elucidated, underscoring the need for a mechanistic framework such as the one proposed in this study.

In the current study, the survival and spatial distribution of neural stem cells in CDP hydrogels were analyzed under shear conditions. Groups with strain‐hardening properties exhibited high expansion rates (>140%) and elevated cell death at the boundaries. This study offers real‐time insights into the structure‐property relationship, which is essential for advancing the development of binary hydrogel systems. Moving forward, a more comprehensive optimization of CDP binary hydrogel systems can be envisioned from three complementary perspectives. First, future work will explore how ECM‐like proteins or growth factors interact with micellar assemblies and dynamic covalent networks to modulate structure–property relationships and printability under biologically relevant environments. Second, the introduction of secondary post‐printing crosslinking mechanisms (e.g., UV‐light induced reactions or phenol–phenol coupling, as shown in Figures S6 and S7) may further strengthen the constructs without compromising their printability. Third, the modulation of both physical and chemical interactions, such as enhancing physical associations (guest–host or ionic interaction) or introducing stronger dynamic covalent linkages (oxime bond and hydrazone bond), could tailor mechanical and structural properties to match the specific requirements of different tissue environments. Together, these strategies offer a rational framework for developing next‐generation bioinks capable of dynamic adaptation, long‐term stability, and improved biological performance.

4. Conclusions

The development of binary nanoengineered CDP hydrogels highlights a sophisticated approach to bioink design for neural stem cells, emphasizing structure‐property relationships and bioprinting performance. Meanwhile, modular 3D printing provides a new way to print complex brain structures. The strain‐induced crystal association and chemical network‐composited nanoengineered CDP bioinks can produce three distinct types of bioinks, offering mechanical versatility, including shear‐thinning (type I), comprehensive (type II), and strain‐hardening (type III). Using rheo‐SAXS and SANS fitting techniques, the structural changes of CDP hydrogels under shear fields and the corresponding energy dissipation mechanisms (entropy spring and micelle association) were discussed. The fine structure of CDP‐II hydrogels was characterized under different temperatures. This type of CDP bioink simultaneously demonstrated stable modulus, comprehensive shear behavior, and utility in high‐resolution bioprinting. The distribution of viable cells under shear provides important insights into the biomechanics of EBB bioink. These findings underline the importance of real‐time structure‐property analysis for advancing binary hydrogel systems in bioprinting.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File 1: smll73541‐sup‐0001‐SuppMat.docx.

Supporting File 2: smll73541‐sup‐0002‐VideoS1.mp4.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.