Biomimetics最新文献

Supramolecular chemistry, a relatively newly grown field, has emerged as a useful tool to fabricate novel smart materials with multiple uses. Adhesives find numerous uses, from heavy engineering to biomedical science. Adhesives are available in nature; inspired by them and their mechanism of adhesion, several supramolecular adhesives have been developed. In this review, supramolecular chemistry for the design and fabrication of novel adhesives is discussed. The discussion is divided into two segments. The first one deals with key supramolecular forces, and their implication is designing novel adhesives. In the second part, key applications of supramolecular adhesives have been discussed with suitable examples. This type of review casts light on the current advancements in the field along with the prospects of development.

Biomaterials interact with biological systems, influencing their responses. Different types of polymers-both natural and synthetic-are widely used in biomedical engineering, among a plethora of healthcare applications, to promote tissue regeneration. The natural rubber latex extracted from Hevea brasiliensis is a biopolymer that whose biocompatibility makes it a valuable study object. Its great regenerative properties are largely associated with the fraction FrHB1, which has demonstrated angiogenic and wound-healing potential by inducing blood vessel formation, collagen synthesis, and fibroblast migration-crucial factors for tissue repair. This study aimed to develop scalable methods for extracting and purifying the F1 protein fraction from industrialized natural latex for biomedical applications. We tested two types of industrial latex, bi-centrifuged and pre-vulcanized latex as well as 60% centrifuged natural latex to determine the most effective composition used in subsequent extractions and fractionation steps. Then, we isolated FrHB1 from the pre-vulcanized latex using selective precipitation, ultrafiltration, and affinity chromatography. The yield of the first batch of this serum was 40.62% with protein concentration of 1.52 ± 0.06 mg/mL. The second batch had a yield of 49.74%; however, due to results lying outside the analytical curve, its protein concentration could not be calculated. The yield of the third batch was 57.19%, and its protein concentration was 1.8477 ± 0.033 mg/mL. This approach facilitates large-scale therapeutic applications utilizing a commercially viable and accessible resource. Moreover, these findings highlight industrialized natural latex as a sustainable source of bioactive molecules, contributing to advancements in regenerative medicine and tissue engineering.

This paper presents a novel variable stiffness mechanism, namely the SBTDTS (Spinal Biomimetic Two-Dimensional Tensegrity Structure), which is constructed by integrating bioinspiration derived from biological spinal structures with the T-Bar mechanical design within tensegrity structures. A method for determining the torsional stiffness of the SBTDTS around a virtual rotational center is established based on parallel mechanism theory. The relationship between various structural parameters is analyzed through multiple sets of typical parameter combinations. Ultimately, the PSO (Particle Swarm Optimization) algorithm is employed to identify the optimal combination of structural parameters for maximizing the stiffness ratio, Kθ_time, of SBTDTS under different constraint conditions. This optimal configuration is then compared with the RAPRPM (a type of rotational parallel mechanism) under different values of μ, with an analysis of the distinct advantages of both variable stiffness structures.

The ability to predict lift is crucial for enabling flapping flights on planets with varying air densities and gravities. After determining the lift required for a flapping flight on Earth, it can be predicted under different conditions using a scaling equation as a function of air density and gravity, assuming the cycle-average lift coefficient remains constant. However, in flapping wings, passive deformation due to aerodynamic and inertial forces may alter the flapping-wing kinematics, complicating predictions. In this study, we investigated changes in the lift coefficient of flapping wings under various air density and gravity conditions simulated using a low-pressure chamber and tilting stand, respectively. The current study found that the cycle-averaged lift coefficients remained nearly constant, varying by less than 7% across the air density and gravity conditions. The difference between the measured and predicted hovering frequencies increased under a lower air density due to the higher vibration-induced friction. The power consumption analysis demonstrated higher energy demands in thinner atmospheres and predicted a required power of 5.14 W for a hovering flight on Mars, which is a 66% increase compared to that on Earth. Future experiments will test Martian air density and gravity conditions to enable flapping flights on Mars.

Biomechanical bite analysis is essential for understanding occlusal forces and their distribution, especially in the design and validation of dental prostheses. Although the finite element method (FEM) has been widely used to evaluate these forces, the existing models often lack accuracy due to simplified geometries and limited material properties.

Methods: A detailed finite element model was developed using Abaqus Standard 2023 software (Dassault Systemes, Vélizy-Villacoublay, France), incorporating scanned 3D geometries of mandibular and maxillary bones. The model included cortical and cancellous bones (Young's modulus: 5.5 GPa and 13.7 GPa, respectively) and was adjusted to simulate bite forces of 220.7 N based on experimental data. Occlusal forces were evaluated using flexible connectors that replicate molar-to-molar interactions, and the stress state was analyzed in the maxillary and mandibular bones.

Results: The FEM model consisted of 1.68 million elements, with mesh sizes of 1-1.5 mm in critical areas. Bite forces on the molars were consistent with clinical trials: first molar (59.3 N), second molar (34.4 N), and third molar (16.7 N). The results showed that the maximum principal stresses in the maxillary bones did not exceed ±5 MPa, validating the robustness of the model for biomechanical predictions.

Conclusion: The developed model provides an accurate and validated framework for analyzing the distribution of occlusal forces in intact dentures. This approach allows the evaluation of complex prosthetic configurations and their biomechanical impact, optimizing future designs to reduce clinical complications and improve long-term outcomes. The integration of high-resolution FEM models with clinical data establishes a solid foundation for the development of predictive tools in restorative dentistry.

Due to the bio-inert nature of titanium (Ti) and subsequent accompanying chronic inflammatory response, an implant's stability and function can be significantly affected, which is why various surface modifications have been employed, including the deposition of titanium oxide (TiO₂) nanotubes (TNTs) onto the native surface through the anodic oxidation method. While the influence of nanotube diameter on cell behaviour and osteogenesis is very well documented, information regarding the effects of nanotube lateral spacing on the in vivo new bone formation process is insufficient and hard to find. Considering this, the present study's aim was to evaluate the mechanical properties and the osteogenic ability of two types of TNTs-based pins with different lateral spacing, e.g., 25 nm (TNTs) and 92 nm (spTNTs). The mechanical properties of the TNT-coated implants were characterised from a morphological point of view (tube diameter, spacing, and tube length) using scanning electron microscopy (SEM). In addition, the chemical composition of the implants was evaluated using X-ray photoelectron spectroscopy, while surface roughness and topography were characterised using atomic force microscopy (AFM). Finally, the implants' hardness and elastic modulus were investigated using nanoindentation measurements. The in vivo new bone formation was histologically evaluated (haematoxylin and eosin-HE staining) at 6 and 30 days post-implantation in a rat model. Mechanical characterisation revealed that the two morphologies presented a similar chemical composition and mechanical strength, but, in terms of surface roughness, the spTNTs exhibited a higher average roughness. The microscopic examination at 1 month post-implantation revealed that spTNTs pins (57.21 ± 34.93) were capable of promoting early new bone tissue formation to a greater extent than the TNTs-coated implants (24.37 ± 6.5), with a difference in the average thickness of the newly formed bone tissue of ~32.84 µm, thus highlighting the importance of this parameter when designing future dental/orthopaedic implants.

Biomimetic nanoassemblies derived from natural products are considered promising nanomaterials due to their self-assembling ability and their favorable interactions with biological molecules leading to their numerous applications as therapeutic agents or as molecular probes. In this work, we have created peptide nanoconjugates of two natural products, β-Boswellic acid (BA) and β-glycyrrhetinic acid (GH). Both BA and GH are known for their medicinal value, including their role as strong antioxidants, anti-inflammatory, neuroprotective and as anti-tumor agents. To enhance the bioavailability of these molecules, they were functionalized with three short peptides (YYIVS, MPDAHL and GSGGL) to create six conjugates with amphiphilic structures capable of facile self-assembly. The peptides were also derived from natural sources and have been known to display antioxidant activity. Depending upon the conjugate, nanofibers, nanovesicles or a mixture of both were formed upon self-assembly. The binding interactions of the nanoconjugates with α-Synuclein, a protein implicated in Parkinson's disease (PD) was examined through in silico studies and FTIR, circular dichroism and imaging studies. Our results indicated that the nanoassemblies interacted with alpha-synuclein fibrils efficaciously. Furthermore, the nanoassemblies were found to demonstrate high viability in the presence of microglial cells, and were found to enhance the uptake and interactions of α-Synuclein with microglial cells. The nanoconjugates designed in this work may be potentially utilized as vectors for peptide-based drug delivery or for other therapeutic applications.

Convolutional neural networks (CNNs) have been widely and successfully demonstrated for closed set recognition in gait identification, but they still lack robustness in open set recognition for unknown classes. To improve the disadvantage, we proposed a convolutional neural network autoencoder (CNN-AE) architecture for user classification based on plantar pressure gait recognition. The model extracted gait features using pressure-sensitive mats, focusing on foot pressure distribution and foot size during walking. Preprocessing techniques, including region of interest (ROI) selection, feature image extraction, and data horizontal flipping, were utilized to establish a CNN model that assessed gait recognition accuracy under two conditions: without carried items and carrying a 500 g object. To extend the application of the CNN to open set recognition for unauthorized personnel, the proposed convolutional neural network-autoencoder (CNN-AE) architecture compressed the average foot pressure map into a 64-dimensional feature vector and facilitated identity determination based on the distances between these vectors. Among 60 participants, 48 were classified as authorized individuals and 12 as unauthorized. Under the condition of not carrying an object, an accuracy of 91.218%, precision of 93.676%, recall of 90.369%, and an F1-Score of 91.993% were achieved, indicating that the model successfully identified most actual positives. However, when carrying a 500 g object, the accuracy was 85.648%, precision was 94.459%, recall was 84.423%, and the F1-Score was 89.603%.

In nature, dynamic liquid interfaces play a vital role in regulating gas transport, as exemplified by the adaptive mechanisms of plant stomata and the liquid-lined alveoli, which enable efficient gas exchange through reversible opening and closing. These biological processes provide profound insights into the design of advanced gas control technologies. Inspired by these natural systems, liquid gating membranes have been developed utilizing capillary-stabilized liquids to achieve precise fluid regulation. These membranes offer unique advantages of rapid responses, stain resistance, and high energy efficiency. Particularly, they break through the limitations of traditional solid, porous membranes in gas transport. This perspective introduces bioinspired liquid gating gas valve membranes (LGVMs), emphasizing their opening/closing mechanism. It highlights how external stimuli can be exploited to enable advanced, multi-level gas control through active or passive regulation strategies. Diverse applications in gas flow regulation and selective gas transport are discussed. While challenges related to precise controllability, long-term stability, and scalable production persist, these advancements unlock significant opportunities for groundbreaking innovations across diverse fields, including gas purification, microfluidics, medical diagnostics, and energy harvesting technologies.

The convergence of 3D printing and auxetic materials is paving the way for a new era of adaptive structures. Auxetic materials, known for their unique mechanical properties, such as a negative Poisson's ratio, can be integrated into 3D-printed objects to enable them to morph or deform in a controlled manner, leading to the creation of 4D-printed structures. Since the first introduction of 4D printing, scientific interest has spiked in exploring its potential implementation in a wide range of applications, from deployable structures for space exploration to shape-adaptive biomechanical implants. In this context, the current paper aimed to develop 4D-printed arterial stents utilizing bioinspired architected auxetic materials made from biocompatible and biodegradable polymeric material. Specifically, three different auxetic materials were experimentally examined at different relative densities, under tensile and compression testing, to determine their mechanical behavior. Based on the extracted experimental data, non-linear hyperelastic finite element material models were developed in order to simulate the insertion of the stent into a catheter and its deployment in the aorta. The results demonstrated that among the three examined structures, the 'square mode 3' structure revealed the best performance in terms of strength, at the same time offering the necessary compressibility (diameter reduction) to allow insertion into a typical catheter for stent procedures.