Catalase Detection via Membrane-Based Pressure Sensors.

Membrane-based sensors (MePSs) exhibit remarkable precision and sensitivity in detecting pressure changes. MePSs are commonly used to monitor catalytic reactions in solution, generating gas products crucial for signal amplification in bioassays. They also allow for catalyst quantification by indirectly measuring the pressure generated by the gaseous products. This is particularly interesting for detecting enzymes in biofluids associated with disease onset. To enhance the performance of a MePS, various structural factors influence membrane flexibility and response time, ultimately dictating the device's pressure sensitivity. In this study, we fabricated MePSs using polydimethylsiloxane (PDMS) and investigated how structural modifications affect the Young's modulus (E) and residual stress (σ0) of the membranes. These modifications have a direct impact on the sensors' sensitivity to pressure variations, observed as a function of the volume of the chamber (Σ) or of the mechanical properties of the membrane itself (S). MePSs exhibiting the highest sensitivities were then employed to detect catalyst quantities inducing the dismutation of hydrogen peroxide, producing dioxygen as a gaseous product. As a result, a catalase enzyme was successfully detected using these optimized MePSs, achieving a remarkable sensitivity of (22.7 ± 1.2) µm/nM and a limit of detection (LoD) of 396 pM.

Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction.

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R2) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.

Fiber Flexibility Reconciles Matrix Recruitment and the Fiber Modulus to Promote Cell Mechanosensing.

The mechanical interaction between cells and the extracellular matrix is pervasive in biological systems. On fibrous substrates, cells possess the ability to recruit neighboring fibers, thereby augmenting their own adhesion and facilitating the generation of mechanical cues. However, the matrices with high moduli impede fiber recruitment, restricting the cell mechanoresponse. Herein, by harnessing the inherent swelling properties of gelatin, the flexible gelatin methacryloyl network empowers cells to recruit fibers spanning a broad spectrum of physiological moduli during adhesion. The high flexibility concurrently facilitates the optimization of fiber distribution, deformability, and modulus, contributing to the promotion of cell mechanosensing. Consequently, the randomly distributed flexible fibers with high moduli maximize the cell adhesive forces. This study uncovers the impact of fiber recruitment on cell mechanosensing and introduces fiber flexibility as a previously unexplored property, offering an innovative perspective for the design and development of novel biomaterials.

Quantifying Elastic Properties of Environmental Biofilms using Optical Coherence Elastography.

Biofilms are complex biomaterials comprising a well-organized network of microbial cells encased in self-produced extracellular polymeric substances (EPS). This paper presents a detailed account of the implementation of optical coherence elastography (OCE) measurements tailored for the elastic characterization of biofilms. OCE is a non-destructive optical technique that enables the local mapping of the microstructure, morphology, and viscoelastic properties of partially transparent soft materials with high spatial and temporal resolution. We provide a comprehensive guide detailing the essential procedures for the correct implementation of this technique, along with a methodology to estimate the bulk Young's modulus of granular biofilms from the collected measurements. These consist of the system setup, data acquisition, and postprocessing. In the discussion, we delve into the underlying physics of the sensors used in OCE and explore the fundamental limitations regarding the spatial and temporal scales of OCE measurements. We conclude with potential future directions for advancing the OCE technique to facilitate elastic measurements of environmental biofilms.

Visual Gustation via Regulable Elastic Photonic Crystals.

The unique structural sensitivity of photonic crystals (PCs) endows them with stretchable or elastic tunability for light propagation and spontaneous emission modulation. Hydrogel PCs have been demonstrated to have biocompatibility and flexibility for potential human health detection and environmental security monitoring. However, current elastic PCs still possess a fixed elastic modulus and uncontrollable structural colors based on a tunable elastic modulus, posing considerable challenges for in situ detection, particularly in wearable or portable sensing devices. In this work, we introduced a novel chemo-mechanical transduction mechanism embedded within a photonic crystal nanomatrix, leading to the creation of structural colors and giving rise to a visual gustation sensing experience. By utilizing the captivating structural colors generated by the hydrogel PC, we employ abundant optical information to identify various analytes. The finite element analysis proved the electric field distribution in the PC matrix during stretch operations. The elastic-optical behaviors with various chemical cosolvents, including cations, anions, saccharides, or organic acids, were investigated. The mechanism of the Hofmeister effect regulating the elasticity of hydrogels was demonstrated with the network nanostructure of the hydrogels. The hydrogel PC matrix demonstrates remarkable capability in efficiently distinguishing a wide range of cations, anions, saccharides, and organic acids across various concentrations, mixtures, and even real food samples, such as tastes and soups. Through comprehensive research, a precise relationship between the structural colors and the elastic modulus of hydrogel PCs has been established, contributing to the biomatching elastic-optics platform for wearable devices, a dynamic environment, and clinical or health monitoring auxiliary.

Biomechanical analysis of alveolar bones with compromised quality supporting a 4-unit implant bridge; a possible association with implant-related sequestration (IRS).

OBJECTIVES: This study aimed to investigate the strain in the bone surrounding dental implants supporting a 4-unit bridge and assess the role of excessive strain as a possible risk factor for implant related sequestration (IRS) or peri-implant medication-related osteonecrosis of the jaw (PI-MRONJ). MATERIALS AND METHODS: A 3D-mandibular model was constructed using computed tomography and segmented it into cortical and cancellous bones. The 4-unit implant-supported bridges replacing the mandibular posteriors were constructed, and each featuring two, three, and four implants, respectively. The Young's modulus was assigned based on the quality of the bone. A maximum occlusal force of 200 N was applied to each implant in the axial and in a 30-degree oblique direction. RESULTS: The maximum principal strain of the fatigue failure range (> 3000 µÎµ) in the bone was analyzed. The volume fraction of fatigue failure was higher in poor-quality bone compared to normal bone and oblique load than in axial load. An increasing number of implants may dissipate excessive strain in poor-quality bones. CONCLUSIONS: Occlusal force applied to poor-quality bone can result in microdamage. Given that unrepaired microdamage may initiate medication-related osteonecrosis of the jaw, long-term occlusal force on fragile bones might be a risk factor. CLINICAL RELEVANCE: When planning implant treatment for patients with compromised bone status, clinical modifications such as strategic placement of implants and optimization of restoration morphology should be considered to reduce excessive strain which might be associated with IRS or PI-MRONJ.

Energy evolution mechanism of structural surfaces in sandstones with different dips based on the energy principle.

A uniaxial compression test was conducted on sandstone specimens at various inclination angles to determine the energy evolution characteristics during deformation and damage. Based on the principle of minimum energy dissipation, an intrinsic model incorporating the damage threshold was developed to investigate the mechanical properties of sandstone at different inclination angles, and the energy damage evolution during deformation and damage. This study indicated that when the inclination angle of the structural surface remained below 40°, sandstone exhibited varying mechanical properties based on different inclination angles. The peak strain was positively correlated with the inclination angle, whereas the compressive strength and modulus of elasticity showed negative correlations. From an energy perspective, the deformation and damage of sandstone under external loading entail processes of energy input, accumulation, and dissipation. Moreover, higher inclination angles of the structural surface resulted in a smaller absorbed peak strain and a reduced proportion of dissipated energy relative to the energy input, thereby affecting the evolution of energy damage throughout the process. As the inclination angle of the structural surface increased, the absorbed total strain at the peak value decreased, whereas the proportion of the dissipated energy increased. Additionally, the damage threshold and critical value of the rock specimens increased with the inclination angle. The critical value, a composite index comprising the peak strain, compressive strength, and elastic modulus, also increased accordingly. These findings can offer a novel perspective for analyzing geological disasters triggered by fissure zones within underground rock formations.

Study on crack resistance of self-healing microcapsules in asphalt pavement by multi-scale method.

Self-healing microcapsules in the asphalt pavement must be kept intact under vehicle load to ensure there is enough rejuvenator in capsules when cracks appear in asphalt pavement. In this paper, the crack resistance of self-healing microcapsules in asphalt pavement was evaluated. Firstly, an expanding multi-scale analysis was conducted based on proposed mesoscopic mechanical models with the aim to determine the mechanical parameters for the following contracting multi-scale analysis. Secondly, the periodic boundary condition was introduced for the contracting multi-scale analysis and the stress field of the capsule wall was obtained. Finally, the effects of the design parameters of the microcapsule on its crack resistance in asphalt pavement were investigated. The results showed that the incorporation of microcapsules has almost no effect on the elastic constants of the asphalt mixture. The core could be simplified as an approximately incompressible solid with the elastic constants determined by the proposed mesoscopic mechanical model. With the increase of the modulus of the capsule wall, the mean maximum tensile stress of the capsule wall increased from 0.372 MPa to 0.465 MPa, while with the decrease of the relative radius of the capsule core, the mean maximum tensile stress of the capsule wall increased from 0.349 MPa to 0.461 MPa. The change in the mean maximum tensile stress of the capsule wall caused by the change of capsule diameter was within 5%. The relative radius of the capsule core and the elastic modulus of capsule wall were two key parameters in capsule design. Besides, the microcapsules with the wall made of resin would not crack under the vehicle load before microcracks occurred in asphalt pavement.

Effect of density grading on the mechanical behaviour of advanced functionally graded lattice structures.

Lattice structures have found significant applications in the biomedical field due to their interesting combination of mechanical and biological properties. Among these, functionally graded structures sparked interest because of their potential of varying their mechanical properties throughout the volume, allowing the design of biomedical devices able to match the characteristics of a graded structure like human bone. The aim of this works is the study of the effect of the density grading on the mechanical response and the failure mechanisms of a novel functionally graded lattice structure, namely Triply Arranged Octagonal Rings (TAOR). The mechanical behaviour was compared with the same lattice structures having constant density ratio. Electron Beam Melting technology was used to manufacture titanium alloy specimens with global relative densities from 10% to 30%. Functionally graded structures were obtained by increasing the relative density along the specimen, by individually designing the lattice's layers. Scanning electron and a digital microscopy were used to evaluate the dimensional mismatch between actual and designed structures. Compressive tests were carried out to obtain the mechanical properties and to evaluate the collapse modes of the structures in relation to their average relative density and lattice grading. Open-source Digital Image Correlation algorithm was applied to evaluate the deformation behaviour of the structures and to calculate their elastic moduli. The results showed that uniform density structures provide higher mechanical properties than functionally graded ones. The Digital Image Correlation results showed the possibility of effectively designing the different layers of functionally graded structures selecting desired local mechanical properties to mimic the different characteristics of cortical and cancellous bone.

The effect of triglycerol diacrylate on the printability and properties of UV curable, bio-based nanohydroxyapatite composites.

3D printable biopolymer nanocomposites composed of hydroxyapatite nanoparticles and functionalized plant-based monomers demonstrate potential as sustainable and structural biomaterials. To increase this potential, their printability and performance must be improved. For extrusion-based 3D printing, such as Direct Ink Writing (DIW), printability is important for print fidelity. In this work, triglycerol diacrylate (TGDA) was added to an acrylated epoxidized soybean oil:polyethylene glycol diacrylate resin to increase hydrogen bonding. Greater hydrogen bonding was hypothesized to improve printability by increasing the ink's shear yield strength, and therefore shape holding after deposition. The effects of this additive on material and mechanical properties were quantified. Increased hydrogen bonding due to TGDA content increased the ink's shear yield stress and viscosity by 916% and 27.6%, respectively. This resulted in improved printability, with best performance at 3 vol% TGDA. This composition achieved an ultimate tensile strength (UTS) of 32.4 ± 2.1 MPa and elastic modulus of 1.15 ± 0.21 GPa. These were increased from the 0 vol% TGDA composite, which had an UTS of 24.8 ± 1.8 MPa and a modulus of 0.88 ± 0.06 GPa. This study demonstrates the development of bio-based additive manufacturing feedstocks for potential uses in sustainable manufacturing, rapid prototyping, and biomaterial applications.

Material characterization of human middle ear using machine-learning-based surrogate models.

This study aims to introduce a novel non-invasive method for rapid material characterization of middle-ear structures, taking into consideration the invaluable insights provided by the mechanical properties of ear tissues. Valuable insights into various ear pathologies can be gleaned from the mechanical properties of ear tissues, yet conventional techniques for assessing these properties often entail invasive procedures that preclude their use on living patients. In this study, in the first step, we developed machine-learning models of the middle ear to predict its responses with a significantly lower computational cost in comparison to finite-element models. Leveraging findings from prior research, we focused on the most influential model parameters: the Young's modulus and thickness of the tympanic membrane and the Young's modulus of the stapedial annular ligament. The eXtreme Gradient Boosting (XGBoost) method was implemented for creating the machine-learning models. Subsequently, we combined the created machine-learning models with Bayesian optimization (BoTorch) for fast and efficient estimation of the Young's moduli of the tympanic membrane and the stapedial annular ligament. We demonstrate that the resultant surrogate models can fairly represent the vibrational responses of the umbo, stapes footplate, and vibration patterns of the tympanic membrane at most frequencies. Also, our proposed material characterization approach successfully estimated the Young's moduli of the tympanic membrane and stapedial annular ligament (separately and simultaneously) with values of mean absolute percentage error of less than 7%. The remarkable accuracy achieved through the proposed material characterization method underscores its potential for eventual clinical applications of estimating mechanical properties of the middle-ear structures for diagnostic purposes.

Modeling of free vibrations and resonant frequencies of simply-supported submerged horizontal plate.

A theoretical approach was applied to study the vibration of simple-supported submerged horizontal plate. The derived analytical solution was used to determine natural frequencies for a horizontal plate vibrating in fluid. The investigations were conducted for a very wide range of material density and elasticity modulus covering all materials used in engineering practice. Analysis shows that plate vibration frequency decreases with increasing plate width and draft, and decreases with decreasing plate thickness. Moreover, the results show that a substantial effect on vibration of submerged plate has mass of water above plate. The results also show that plate vibration frequency decreases with increasing plate material density and decreases with decreasing elasticity modulus. The dominant factors affecting the vibration of the submerged plate are the plate width, the plate thickness, and elasticity modulus. For moderate and low values of elasticity modulus, vibration frequency is becoming lower than frequency of water waves. This is very important because wave frequencies overlap with the natural plate vibration frequencies, which may lead to resonance and failure of a structure. The problem is that the overlap of plate vibration frequencies and wave frequencies occurs for very wide range of wave and plate parameters. Laboratory experiments confirm theoretical results.

The effects of different grading approaches in additively manufactured dental implants on peri-implant bone stress: A finite element analysis.

Additive manufacturing enables local grading of the stiffness of dental implants through targeted adjustment of the manufacturing parameters to meet patient specific requirements. The extent to which such a manufacturing approach affects the interaction between the implant body and the surrounding bone, and what grading is optimal, is currently insufficiently investigated. This study investigates the effect of different Young's modulus grading approaches on stresses in the peri-implant bone via finite element analysis. The implant geometry was kept constant and in the case of the implant a node-dependent elastic modulus was assigned. In this way, a vertical, a radial and three torus based grading approaches were created and examined. A load was then applied directly to the occlusal surface of the implant crown. It was found that a local grading utilizing a torus shape was most favourable in terms of an effective stress peak reduction. The best torus shape tested achieved a 22 % reduction of maximum principal stress and 6 % reduction of minimum principal stress compared to the uniform material. In clinical settings, this may provide benefits in situations of overload. Based on the results, a graded stiffness in dental implants appears to be of interest for developing advanced, patient-specific implant solutions.

Fast-relaxing hydrogels with reversibly tunable mechanics for dynamic cancer cell culture.

The mechanics of the tumor microenvironment (TME) significantly impact disease progression and the efficacy of anti-cancer therapeutics. While it is recognized that advanced in vitro cancer models will benefit cancer research, none of the current engineered extracellular matrices (ECM) adequately recapitulate the highly dynamic TME. Through integrating reversible boronate-ester bonding and dithiolane ring-opening polymerization, we fabricated synthetic polymer hydrogels with tumor-mimetic fast relaxation and reversibly tunable elastic moduli. Importantly, the crosslinking and dynamic stiffening of matrix mechanics were achieved in the absence of a photoinitiator, often the source of cytotoxicity. Central to this strategy was Poly(PEGA-co-LAA-co-AAPBA) (PELA), a highly defined polymer synthesized by reversible addition-fragmentation chain transfer (RAFT) polymerization. PELA contains dithiolane for initiator-free gel crosslinking, stiffening, and softening, as well as boronic acid for complexation with diol-containing polymers to give rise to tunable viscoelasticity. PELA hydrogels were highly cytocompatible for dynamic culture of patient-derived pancreatic cancer cells. It was found that the fast-relaxing matrix induced mesenchymal phenotype of cancer cells, and dynamic matrix stiffening restricted tumor spheroid growth. Moreover, this new dynamic viscoelastic hydrogel system permitted sequential stiffening and softening to mimic the physical changes of TME.

Mechanical properties of native and decellularized reproductive tissues: insights for tissue engineering strategies.

Understanding the mechanical properties and porosity of reproductive tissues is vital for regenerative medicine and tissue engineering. This study investigated the changes in Young's modulus (YM), storage modulus (E'), loss modulus (E"), and porosity of native and decellularized bovine reproductive tissues during the estrous cycle. Testis tunica albuginea had significantly higher YM, E', and E" than the inner testis, indicating greater stiffness and viscoelasticity. Endometrium showed no distinct differences in YM, E', or E" across the estrous cycle or between horns. Ovaries exhibited significant variations in YM, E', E", and porosity, with higher YM and E' in the ipsilateral cortex and medulla during the luteal phase. Decellularized ovarian tissues displayed increased porosity. The oviduct displayed no significant differences in YM or E' in the isthmus, but the contralateral ampulla had reduced YM and E' in the luteal phase. These findings offer valuable insights into the dynamic mechanical properties and porosity of reproductive tissues, facilitating the development of biomimetic scaffolds for tissue engineering applications.

Optimization of Newtonian fluid pressure in microcantilever integrated flexible microfluidic channel for healthcare application.

The demand for microfluidic pressure sensors is ever-increasing in various industries due to their crucial role in controlling fluid pressure within microchannels. While syringe pump setups have been traditionally used to regulate fluid pressure in microfluidic devices, they often result in larger setups that increase the cost of the device. To address this challenge and miniaturize the syringe pump setup, the researcher introduced integrated T-microcantilever-based microfluidic devices. In these devices, microcantilevers are incorporated, and their deflections correlate with the microchannel's pressure. When the relative pressure of fluid (plasma) changes, the T-microcantilever deflects, and the extent of this deflection provides information on fluid pressure within the microchannel. In this work, finite element method (FEM) based simulation was carried out to investigate the role of material, and geometric parameters of the cantilever, and the fluid viscosity on the pressure sensing capability of the T-microcantilever integrated microfluidic channel. The T-microcantilever achieves a maximum deflection of 127µm at a 5000µm/s velocity for Young's modulus(E) of 360 kPa of PDMS by employing a hinged structure. On the other hand, a minimum deflection of 4.05 × 10-5µm was attained at 5000µm/s for Young's modulus of 1 TPa for silicon. The maximum deflected angle of the T-cantilever is 20.46° for a 360 kPa Young's modulus while the minimum deflection angle of the T-cantilever is measured at 13.77° for 900 KPa at a fluid velocity of 5000µm s-1. The T-cantilever functions as a built-in microchannel that gauges the fluid pressure within the microchannel. The peak pressure, set at 8.86 Pa on the surface of the cantilever leads to a maximum deflection of 0.096µm (approximately 1µm) in the T-cantilever at a 1:1 velocity ratio. An optimized microfluidic device embedded with microchannels can optimize fluid pressure in a microchannel support cell separation.

Mechanically Controlled Enzymatic Polymerization and Remodeling.

In nature, proteins possess the remarkable ability to sense and respond to mechanical forces, thereby triggering various biological events, such as bone remodeling and muscle regeneration. However, in synthetic systems, harnessing the mechanical force to induce material growth still remains a challenge. In this study, we aimed to utilize low-frequency ultrasound (US) to activate horseradish peroxidase (HRP) and catalyze free radical polymerization. Our findings demonstrate the efficacy of this mechano-enzymatic chemistry in rapidly remodeling the properties of materials through cross-linking polymerization and surface coating. The resulting samples exhibited a significant enhancement in tensile strength, elongation, and Young's modulus. Moreover, the hydrophobicity of the surface could be completely switched within just 30 min of US treatment. This work presents a novel approach for incorporating mechanical sensing and rapid remodeling capabilities into materials.

Development of a self-reinforced starch-derived film with biocompatibility and mechanical properties.

The scraps produced while processing packaging materials will cause a waste of resources. In this study, starch-based self-reinforced film (SSRF) using thermoplastic starch (TPS, 45 wt%) and polypropylene (PP, 53 wt%) was developed. The effect of extrusion times (1-4 times) on the film structure and performance was explored. The results show as the number of extrusions increases, the color of SSRF deepens from gray-white to brown, and the crystallinity increases. The mechanical properties of the four types of SSRF first increase and then decrease. The 2-SSRF has the best performance, with tensile strength of 13.23 MPa, elongation at break of 61.35%, Young's modulus of 1128.99 MPa, and flexural strength of 33.19 MPa. Proper extrusion improves the compatibility of TPS and PP. However, repeated extrusion will cause PP degradation and TPS carbonization, reducing interfacial interaction. This study developed new starch-based self-reinforced film and provided theoretical guidance for reusing packaging material scraps.

Gaussian random field-based characterization and reconstruction of cancellous bone microstructure considering the constraint of correlation structure.

The macro scale physical properties of cancellous bone materials are governed by the microstructural features, which is of great significance for the multi-scale research of cancellous bone and the inverse design of bone-mimicking materials. Therefore, it is essential to characterize the natural cancellous bone samples, and reconstruct the microstructures with the biomimetic osteointegration and mechanical properties. In this research, a novel approach for the characterization and reconstruction of cancellous bone was proposed, based on the medical image analysis and anisotropic three-dimensional Gaussian random field (GRF). The geometric similarity, i.e. the interface curvature distribution (ISD), was meticulously studied, which is important to the osteointegration ability. And the mechanical properties were validated by the stress-strain curves under the large compressive strain simulated by the smoothed particle hydrodynamic (SPH) method. In addition, the effects of the generation parameters of GRF-based biomimetic microstructures on the apparent properties were analyzed. The ISD results demonstrated that both GRF and micro-CT groups had the similar columnar morphological properties, while the latter had more hyperbolic features. And it was found that the GRF-based biomimetic microstructures and the natural bone samples based on micro-CT (MCT) had the similar failure mode. The concordance correlation coefficient between MCT and GRF pairs was 0.8685, with a Pearson ρ value of 0.8804, and significance level p<0.0001. The Bland-Altman LoA was 0.1647 MPa with 95 % (1.96SD) lower and upper bound value between -0.2892 and 0.6185 MPa. The two groups had almost the same elastic modulus with the mean absolute percentage error (MAPE) of 7.84 %. While the yield stress and total conversion energy of the GRF-based samples were lower than those of the natural bone samples, and the MAPE were 16.99 % and 16.27 %, respectively. Although it meant the lower structural efficiency, the huge design space of this approach and advanced 3D printing technology can provide great potential for the design of orthopedic implants.

A novel mussel-inspired desensitizer based on radial mesoporous bioactive nanoglass for the treatment of dentin exposure: An in vitro study.

OBJECTIVES: The dentin exposure always leads to dentin hypersensitivity and the acid-resistant/abrasion-resistant stability of current therapeutic approaches remain unsatisfatory. Inspired by the excellent self-polymerization/adherence activity of mussels and the superior mineralization ability of bioactive glass, a novel radial mesoporous bioactive nanoglass coated with polydopamine (RMBG@PDA) was developed for prevention and management of dentin hypersensitivity. METHODS: Radial mesoporous bioactive nanoglass (RMBG) was synthesized by the sol-gel process combined with the cetylpyridine bromide template self-assembly technique. RMBG@PDA was synthesized by a self-polymerization process involving dopamine and RMBG in an alkaline environment. Then, the nanoscale morphology, chemical structure, crystalline phase and Zeta potential of RMBG and RMBG@PDA were characterized. Subsequently, the ion release ability, bioactivity, and cytotoxicity of RMBG and RMBG@PDA in vitro were investigated. Moreover, an in vitro experimental model of dentin hypersensitivity was constructed to evaluate the effectiveness of RMBG@PDA on dentinal tubule occlusion, including resistances against acid and abrasion. Finally, the Young's modulus and nanohardness of acid-etched dentin were also detected after RMBG@PDA treatment. RESULTS: RMBG@PDA showed a typical nanoscale morphology and noncrystalline structure. The use of RMBG@PDA on the dentin surface could effectively occlude dentinal tubules, reduce dentin permeability and achieve excellent acid- and abrasion-resistant stability. Furthermore, RMBG@PDA with excellent cytocompatibility held the capability to recover the Young's modulus and nanohardness of acid-etched dentin. CONCLUSION: The application of RMBG@PDA with superior dentin tubule occlusion ability and acid/abrasion-resistant stability can provide a therapeutic strategy for the prevention and the management of dentin hypersensitivity.