Biomimetics

17 pages, 1714 KiB

Open AccessReview

Tissue-Engineered Tracheal Reconstruction

by Se Hyun Yeou and Yoo Seob Shin

Biomimetics 2025, 10(7), 457; https://doi.org/10.3390/biomimetics10070457 - 11 Jul 2025

Tracheal reconstruction remains a formidable clinical challenge, particularly for long-segment defects that are not amenable to standard surgical resection or primary anastomosis. Tissue engineering has emerged as a promising strategy for restoring the tracheal structure and function through the integration of biomaterials, stem [...] Read more.

Tracheal reconstruction remains a formidable clinical challenge, particularly for long-segment defects that are not amenable to standard surgical resection or primary anastomosis. Tissue engineering has emerged as a promising strategy for restoring the tracheal structure and function through the integration of biomaterials, stem cells, and bioactive molecules. This review provides a comprehensive overview of recent advances in tissue-engineered tracheal grafts, particularly in scaffold design, cellular sources, fabrication technologies, and early clinical experience. Innovations in biomaterial science, three-dimensional printing, and scaffold-free fabrication approaches have broadened the prospects for patient-specific airway reconstruction. However, persistent challenges, including incomplete epithelial regeneration and mechanical instability, have hindered its clinical translation. Future efforts should focus on the design of modular biomimetic scaffolds, the enhancement of immunomodulatory strategies, and preclinical validation using robust large animal models. Sustained interdisciplinary collaboration among surgical, engineering, and biological fields is crucial for advancing tissue-engineered tracheal grafts for routine clinical applications. Within this context, biomimetic approaches, including three-dimensional bioprinting, hybrid materials, and scaffold-free constructs, are gaining prominence as strategies to replicate the trachea’s native architecture and improve graft integration. Full article

(This article belongs to the Special Issue Biomimetic Application on Applied Bioengineering)

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19 pages, 3024 KiB

Open AccessArticle

Feedback-Driven Dynamical Model for Axonal Extension on Parallel Micropatterns

by Kyle Cheng, Udathari Kumarasinghe and Cristian Staii

Biomimetics 2025, 10(7), 456; https://doi.org/10.3390/biomimetics10070456 - 11 Jul 2025

Abstract

Despite significant advances in understanding neuronal development, a fully quantitative framework that integrates intracellular mechanisms with environmental cues during axonal growth remains incomplete. Here, we present a unified biophysical model that captures key mechanochemical processes governing axonal extension on micropatterned substrates. In these [...] Read more.

Despite significant advances in understanding neuronal development, a fully quantitative framework that integrates intracellular mechanisms with environmental cues during axonal growth remains incomplete. Here, we present a unified biophysical model that captures key mechanochemical processes governing axonal extension on micropatterned substrates. In these environments, axons preferentially align with the pattern direction, form bundles, and advance at constant speed. The model integrates four core components: (i) actin–adhesion traction coupling, (ii) lateral inhibition between neighboring axons, (iii) tubulin transport from soma to growth cone, and (iv) orientation dynamics guided by substrate anisotropy. Dynamical systems analysis reveals that a saddle–node bifurcation in the actin adhesion subsystem drives a transition to a high-traction motile state, while traction feedback shifts a pitchfork bifurcation in the signaling loop, promoting symmetry breaking and robust alignment. An exact linear solution in the tubulin transport subsystem functions as a built-in speed regulator, ensuring stable elongation rates. Simulations using experimentally inferred parameters accurately reproduce elongation speed, alignment variance, and bundle spacing. The model provides explicit design rules for enhancing axonal alignment through modulation of substrate stiffness and adhesion dynamics. By identifying key control parameters, this work enables rational design of biomaterials for neural repair and engineered tissue systems. Full article

(This article belongs to the Special Issue Innovative Biomimetics: Integrating Machine Learning, Neuropsychology, and Cognitive Neuroscience in Applied Psychological Research)

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15 pages, 33163 KiB

Open AccessArticle

An Optimised Spider-Inspired Soft Actuator for Extraterrestrial Exploration

by Jonah Mack, Maks Gepner, Francesco Giorgio-Serchi and Adam A. Stokes

Biomimetics 2025, 10(7), 455; https://doi.org/10.3390/biomimetics10070455 - 11 Jul 2025

Abstract

Extraterrestrial exploration presents unique challenges for robotic systems, as traditional rigid rovers face limitations in stowage volume, traction on unpredictable terrain, and susceptibility to damage. Soft robotics offers promising solutions through bio-inspired designs that can mimic natural locomotion mechanisms. Here, we present an [...] Read more.

Extraterrestrial exploration presents unique challenges for robotic systems, as traditional rigid rovers face limitations in stowage volume, traction on unpredictable terrain, and susceptibility to damage. Soft robotics offers promising solutions through bio-inspired designs that can mimic natural locomotion mechanisms. Here, we present an optimised, spider-inspired soft jumping robot for extraterrestrial exploration that addresses key challenges in soft robotics: actuation efficiency, controllability, and deployment. Drawing inspiration from spider physiology—particularly their hydraulic extension mechanism—we develop a lightweight limb capable of multi-modal behaviour with significantly reduced energy requirements. Our 3D-printed soft actuator leverages pressure-driven collapse for efficient retraction and pressure-enhanced rapid extension, achieving a power-to-weight ratio of 249 W/kg. The integration of a non-backdriveable clutch mechanism enables the system to hold positions with zero energy expenditure—a critical feature for space applications. Experimental characterisation and a subsequent optimisation methodology across various materials, dimensions, and pressures reveal that the robot can achieve jumping heights of up to 1.86 times its body length. The collapsible nature of the soft limb enables efficient stowage during spacecraft transit, while the integrated pumping system facilitates self-deployment upon arrival. This work demonstrates how biologically inspired design principles can be effectively applied to develop versatile robotic systems optimised for the unique constraints of extraterrestrial exploration. Full article

(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics: 2nd Edition)

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48 pages, 5383 KiB

Open AccessArticle

Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids

by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli and Mohammad AL-Rawi

Biomimetics 2025, 10(7), 454; https://doi.org/10.3390/biomimetics10070454 - 10 Jul 2025

Abstract

This theoretical research study proposes a novel hybrid algorithm that integrates an improved quasi-dynamical oppositional learning mutation scheme into the Mountain Gazelle Optimization method, augmented with chaotic sequences, for the thermal and economical design of a shell-and-tube heat exchanger operating with nanofluids. The [...] Read more.

This theoretical research study proposes a novel hybrid algorithm that integrates an improved quasi-dynamical oppositional learning mutation scheme into the Mountain Gazelle Optimization method, augmented with chaotic sequences, for the thermal and economical design of a shell-and-tube heat exchanger operating with nanofluids. The Mountain Gazelle Optimizer is a recently developed metaheuristic algorithm that simulates the foraging behaviors of Mountain Gazelles. However, it suffers from premature convergence due to an imbalance between its exploration and exploitation mechanisms. A two-step improvement procedure is implemented to enhance the overall search efficiency of the original algorithm. The first step concerns substituting uniformly random numbers with chaotic numbers to refine the solution quality to better standards. The second step is to develop a novel manipulation equation that integrates different variants of quasi-dynamic oppositional learning search schemes, guided by a novel intelligently devised adaptive switch mechanism. The efficiency of the proposed algorithm is evaluated using the challenging benchmark functions from various CEC competitions. Finally, the thermo-economic design of a shell-and-tube heat exchanger operated with different nanoparticles is solved by the proposed improved metaheuristic algorithm to obtain the optimal design configuration. The predictive results indicate that using water + SiO₂ instead of ordinary water as the refrigerant on the tube side of the heat exchanger reduces the total cost by 16.3%, offering the most cost-effective design among the configurations compared. These findings align with the demonstration of how biologically inspired metaheuristic algorithms can be successfully applied to engineering design. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 3rd Edition)

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24 pages, 1908 KiB

Open AccessPerspective

Biomimetic Additive Manufacturing: Engineering Complexity Inspired by Nature’s Simplicity

by Antreas Kantaros, Theodore Ganetsos, Evangelos Pallis and Michail Papoutsidakis

Biomimetics 2025, 10(7), 453; https://doi.org/10.3390/biomimetics10070453 - 10 Jul 2025

Abstract

Nature’s principles offer design references for additive manufacturing (AM), enabling structures that achieve remarkable efficiency through hierarchical organization rather than material excess. This perspective article proposes a framework for integrating biomimetic principles into AM beyond morphological mimicry, focusing on functional adaptation and sustainability. [...] Read more.

Nature’s principles offer design references for additive manufacturing (AM), enabling structures that achieve remarkable efficiency through hierarchical organization rather than material excess. This perspective article proposes a framework for integrating biomimetic principles into AM beyond morphological mimicry, focusing on functional adaptation and sustainability. By emulating biological systems like nacre, spider silk, and bone, AM utilizes traditional geometric replication to embed multifunctionality, responsiveness, and resource efficiency. Recent advances in the fields of 4D printing, soft robotics, and self-morphing systems demonstrate how time-dependent behaviors and environmental adaptability can be engineered through bioinspired material architectures. However, challenges in scalable fabrication, dynamic material programming, and true functional emulation (beyond morphological mimicry) necessitate interdisciplinary collaboration. In this context, the synthesis of biological intelligence with AM technologies offers sustainable, high-performance solutions for aerospace, biomedical, and smart infrastructure applications, once challenges related to material innovation and standardization are overcome. Full article

(This article belongs to the Special Issue Biomimetic Additive Manufacturing: Nature-Inspired Design and Fabrication for Advanced Applications)

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25 pages, 6826 KiB

Open AccessArticle

Multi-Class Classification Methods for EEG Signals of Lower-Limb Rehabilitation Movements

by Shuangling Ma, Zijie Situ, Xiaobo Peng, Zhangyang Li and Ying Huang

Biomimetics 2025, 10(7), 452; https://doi.org/10.3390/biomimetics10070452 - 9 Jul 2025

Abstract

Brain–Computer Interfaces (BCIs) enable direct communication between the brain and external devices by decoding motor intentions from EEG signals. However, the existing multi-class classification methods for motor imagery EEG (MI-EEG) signals are hindered by low signal quality and limited accuracy, restricting their practical [...] Read more.

Brain–Computer Interfaces (BCIs) enable direct communication between the brain and external devices by decoding motor intentions from EEG signals. However, the existing multi-class classification methods for motor imagery EEG (MI-EEG) signals are hindered by low signal quality and limited accuracy, restricting their practical application. This study focuses on rehabilitation training scenarios, aiming to capture the motor intentions of patients with partial or complete motor impairments (such as stroke survivors) and provide feedforward control commands for exoskeletons. This study developed an EEG acquisition protocol specifically for use with lower-limb rehabilitation motor imagery (MI). It systematically explored preprocessing techniques, feature extraction strategies, and multi-classification algorithms for multi-task MI-EEG signals. A novel 3D EEG convolutional neural network (3D EEG-CNN) that integrates time/frequency features is proposed. Evaluations on a self-collected dataset demonstrated that the proposed model achieved a peak classification accuracy of 66.32%, substantially outperforming conventional approaches and demonstrating notable progress in the multi-class classification of lower-limb motor imagery tasks. Full article

(This article belongs to the Special Issue Advances in Brain–Computer Interfaces 2025)

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15 pages, 1662 KiB

Open AccessArticle

YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System

by Xiaoge Wang, Yunlong Sheng, Qun Hao, Haiyuan Hou and Suzhen Nie

Biomimetics 2025, 10(7), 451; https://doi.org/10.3390/biomimetics10070451 - 8 Jul 2025

Viewed by 43

Abstract

To address challenges of background interference and limited multi-scale feature extraction in infrared small target detection, this paper proposes a YOLO-HVS detection algorithm inspired by the human visual system. Based on YOLOv8, we design a multi-scale spatially enhanced attention module (MultiSEAM) using multi-branch [...] Read more.

To address challenges of background interference and limited multi-scale feature extraction in infrared small target detection, this paper proposes a YOLO-HVS detection algorithm inspired by the human visual system. Based on YOLOv8, we design a multi-scale spatially enhanced attention module (MultiSEAM) using multi-branch depth-separable convolution to suppress background noise and enhance occluded targets, integrating local details and global context. Meanwhile, the C2f_DWR (dilation-wise residual) module with regional-semantic dual residual structure is designed to significantly improve the efficiency of capturing multi-scale contextual information by expanding convolution and two-step feature extraction mechanism. We construct the DroneRoadVehicles dataset containing 1028 infrared images captured at 70–300 m, covering complex occlusion and multi-scale targets. Experiments show that YOLO-HVS achieves mAP50 of 83.4% and 97.8% on the public dataset DroneVehicle and the self-built dataset, respectively, which is an improvement of 1.1% and 0.7% over the baseline YOLOv8, and the number of model parameters only increases by 2.3 M, and the increase of GFLOPs is controlled at 0.1 G. The experimental results demonstrate that the proposed approach exhibits enhanced robustness in detecting targets under severe occlusion and low SNR conditions, while enabling efficient real-time infrared small target detection. Full article

(This article belongs to the Special Issue Advanced Biologically Inspired Vision and Its Application)

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16 pages, 18636 KiB

Open AccessArticle

Design of a Modular Wall-Climbing Robot with Multi-Plane Transition and Cleaning Capabilities

by Boyu Wang, Weijian Zhang, Jianghan Luo and Qingsong Xu

Biomimetics 2025, 10(7), 450; https://doi.org/10.3390/biomimetics10070450 - 8 Jul 2025

Viewed by 57

Abstract

This paper presents the design and development of a new modular wall-climbing robot—Modular Wall Climbing-1 (MC-1)—for solving the problem of autonomous wall switching observed in wall-climbing robots. Each modular robot is capable of independently adhering to vertical surfaces and maneuvering, making it a [...] Read more.

This paper presents the design and development of a new modular wall-climbing robot—Modular Wall Climbing-1 (MC-1)—for solving the problem of autonomous wall switching observed in wall-climbing robots. Each modular robot is capable of independently adhering to vertical surfaces and maneuvering, making it a fully autonomous robotic system. Multiple modules of MC-1 are connected by an electromagnet-based magnetic attachment method, and wall transitions are achieved using a servo motor mechanism. Moreover, an ultrasonic sensor is employed to measure the unknown wall-inclination angle. Mechanical analysis is conducted for MC-1 at rest individually and in combination to determine the required suction force. Experimental investigations are performed to assess the robot’s crawling ability, loading capacity, and wall-transition performance. The results demonstrate that the MC-1 robot is capable of multi-angle wall transitions for executing multiple tasks. It provides a new approach for wall-climbing robots to collaborate during wall transitions through a quick attachment-and-disassembly device and an efficient wall detection method. Full article

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21 pages, 5444 KiB

Open AccessArticle

Diagnosis of Schizophrenia Using Feature Extraction from EEG Signals Based on Markov Transition Fields and Deep Learning

by Alka Jalan, Deepti Mishra, Marisha and Manjari Gupta

Biomimetics 2025, 10(7), 449; https://doi.org/10.3390/biomimetics10070449 - 7 Jul 2025

Viewed by 190

Abstract

Diagnosing schizophrenia using Electroencephalograph (EEG) signals is a challenging task due to the subtle and overlapping differences between patients and healthy individuals. To overcome this difficulty, deep learning has shown strong potential, especially given its success in image recognition tasks. In many studies, [...] Read more.

Diagnosing schizophrenia using Electroencephalograph (EEG) signals is a challenging task due to the subtle and overlapping differences between patients and healthy individuals. To overcome this difficulty, deep learning has shown strong potential, especially given its success in image recognition tasks. In many studies, one-dimensional EEG signals are transformed into two-dimensional representations to allow for image-based analysis. In this work, we have used the Markov Transition Field for converting EEG signals into two-dimensional images, capturing both the temporal patterns and statistical dynamics of the data. EEG signals are continuous time-series recordings from the brain, where the current state is often influenced by the immediately preceding state. This characteristic makes MTF particularly suitable for representing such data. After the transformation, a pre-trained VGG-16 model is employed to extract meaningful features from the images. The extracted features are then passed through two separate classification pipelines. The first uses a traditional machine learning model, Support Vector Machine, while the second follows a deep learning approach involving an autoencoder for feature selection and a neural network for final classification. The experiments were conducted using EEG data from the open-access Schizophrenia EEG database provided by MV Lomonosov Moscow State University. The proposed method achieved a highest classification accuracy of 98.51 percent and a recall of 100 percent across all folds using the deep learning pipeline. The Support Vector Machine pipeline also showed strong performance with a best accuracy of 96.28 percent and a recall of 97.89 percent. The proposed deep learning model represents a biomimetic approach to pattern recognition and decision-making. Full article

(This article belongs to the Special Issue New Biomimetic Advances in Signal and Image Processing for Biomedical Applications 2025)

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25 pages, 4232 KiB

Open AccessArticle

Multimodal Fusion Image Stabilization Algorithm for Bio-Inspired Flapping-Wing Aircraft

by Zhikai Wang, Sen Wang, Yiwen Hu, Yangfan Zhou, Na Li and Xiaofeng Zhang

Biomimetics 2025, 10(7), 448; https://doi.org/10.3390/biomimetics10070448 - 7 Jul 2025

Viewed by 182

Abstract

This paper presents FWStab, a specialized video stabilization dataset tailored for flapping-wing platforms. The dataset encompasses five typical flight scenarios, featuring 48 video clips with intense dynamic jitter. The corresponding Inertial Measurement Unit (IMU) sensor data are synchronously collected, which jointly provide reliable [...] Read more.

This paper presents FWStab, a specialized video stabilization dataset tailored for flapping-wing platforms. The dataset encompasses five typical flight scenarios, featuring 48 video clips with intense dynamic jitter. The corresponding Inertial Measurement Unit (IMU) sensor data are synchronously collected, which jointly provide reliable support for multimodal modeling. Based on this, to address the issue of poor image acquisition quality due to severe vibrations in aerial vehicles, this paper proposes a multi-modal signal fusion video stabilization framework. This framework effectively integrates image features and inertial sensor features to predict smooth and stable camera poses. During the video stabilization process, the true camera motion originally estimated based on sensors is warped to the smooth trajectory predicted by the network, thereby optimizing the inter-frame stability. This approach maintains the global rigidity of scene motion, avoids visual artifacts caused by traditional dense optical flow-based spatiotemporal warping, and rectifies rolling shutter-induced distortions. Furthermore, the network is trained in an unsupervised manner by leveraging a joint loss function that integrates camera pose smoothness and optical flow residuals. When coupled with a multi-stage training strategy, this framework demonstrates remarkable stabilization adaptability across a wide range of scenarios. The entire framework employs Long Short-Term Memory (LSTM) to model the temporal characteristics of camera trajectories, enabling high-precision prediction of smooth trajectories. Full article

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3 pages, 123 KiB

Open AccessEditorial

Bio-Inspired Soft Robotics: Design, Fabrication and Applications

by Yong Zhong, Pei Jiang and Yi Sun

Biomimetics 2025, 10(7), 447; https://doi.org/10.3390/biomimetics10070447 - 7 Jul 2025

Viewed by 93

Abstract

The field of soft robotics has witnessed a remarkable surge in interest and innovation over the past decade, with bio-inspiration playing a pivotal role in driving forward the design, fabrication, and applications of these adaptable and resilient robotic systems [...] Full article

(This article belongs to the Special Issue Bio-Inspired Soft Robotics: Design, Fabrication and Applications)

34 pages, 5774 KiB

Open AccessArticle

Approach to Semantic Visual SLAM for Bionic Robots Based on Loop Closure Detection with Combinatorial Graph Entropy in Complex Dynamic Scenes

by Dazheng Wang and Jingwen Luo

Biomimetics 2025, 10(7), 446; https://doi.org/10.3390/biomimetics10070446 - 6 Jul 2025

Viewed by 165

Abstract

In complex dynamic environments, the performance of SLAM systems on bionic robots is susceptible to interference from dynamic objects or structural changes in the environment. To address this problem, we propose a semantic visual SLAM (vSLAM) algorithm based on loop closure detection with [...] Read more.

In complex dynamic environments, the performance of SLAM systems on bionic robots is susceptible to interference from dynamic objects or structural changes in the environment. To address this problem, we propose a semantic visual SLAM (vSLAM) algorithm based on loop closure detection with combinatorial graph entropy. First, in terms of the dynamic feature detection results of YOLOv8-seg, the feature points at the edges of the dynamic object are finely judged by calculating the mean absolute deviation (MAD) of the depth of the pixel points. Then, a high-quality keyframe selection strategy is constructed by combining the semantic information, the average coordinates of the semantic objects, and the degree of variation in the dense region of feature points. Subsequently, the unweighted and weighted graphs of keyframes are constructed according to the distribution of feature points, characterization points, and semantic information, and then a high-performance loop closure detection method based on combinatorial graph entropy is developed. The experimental results show that our loop closure detection approach exhibits higher precision and recall in real scenes compared to the bag-of-words (BoW) model. Compared with ORB-SLAM2, the absolute trajectory accuracy in high-dynamic sequences improved by an average of 97.01%, while the number of extracted keyframes decreased by an average of 61.20%. Full article

(This article belongs to the Special Issue Artificial Intelligence for Autonomous Robots: 3rd Edition)

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19 pages, 8205 KiB

Open AccessArticle

The Unilateral Jumping Structures of the Spotted Lanternfly, Lycorma delicatula (Hemiptera: Fulgoridae): A Highly Functional and Integrated Unit

by Xu Chen and Aiping Liang

Biomimetics 2025, 10(7), 444; https://doi.org/10.3390/biomimetics10070444 - 6 Jul 2025

Viewed by 116

Abstract

Previous research on the jumping structures of insects with strong leaping abilities mainly focused on overall jumping mechanisms. Our study reveals that the unilateral jumping structures (UJSs) of L. delicatula has relative functional autonomy. The UJSs consist of three distinct but interconnected parts: [...] Read more.

Previous research on the jumping structures of insects with strong leaping abilities mainly focused on overall jumping mechanisms. Our study reveals that the unilateral jumping structures (UJSs) of L. delicatula has relative functional autonomy. The UJSs consist of three distinct but interconnected parts: (1) energy storage component: it comprises the pleural arch and trochanteral depressor muscles, with the deformation zone extending about two-thirds of the pleural arch from the V-notch to the U-notch; (2) coupling component: made up of the coxa and trochanter, it serves as a bridge between the energy and lever components, connecting them via protuberances and pivots; and (3) lever component: it encompasses the femur, tibia, and tarsus. A complete jumping action lasts from 2.4 ms to 4.6 ms. During a jump, the deformation length of the pleural arch is 0.96 ± 0.06 mm. The angles ∠ct (angle between coxa and trochanter), ∠fp (angle between femur and pleural arch), and ∠ft (angle between femur and tibia) change by 57.42 ± 1.60, 101.40 ± 1.59, and 36.06 ± 2.41 degrees, respectively. In this study, we abstracted the jumping structures of L. delicatula and identified its critical components. The insights obtained from this study are anticipated to provide valuable inspiration for the design and fabrication of biomimetic jumping mechanisms. Full article

(This article belongs to the Special Issue Biomechanics and Biomimetics for Insect-Inspired MAVs)

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32 pages, 8000 KiB

Open AccessArticle

Sharpbelly Fish Optimization Algorithm: A Bio-Inspired Metaheuristic for Complex Engineering

by Jian Liu, Rong Wang, Yonghong Deng, Xiaona Huang and Zhibin Li

Biomimetics 2025, 10(7), 445; https://doi.org/10.3390/biomimetics10070445 - 5 Jul 2025

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Abstract

This paper introduces a novel bio-inspired metaheuristic algorithm, named the sharpbelly fish optimizer (SFO), inspired by the collective ecological behaviors of the sharpbelly fish. The algorithm integrates four biologically motivated strategies—(1) fitness-driven fast swimming, (2) convergence-guided gathering, (3) stagnation-triggered dispersal, and (4) disturbance-induced [...] Read more.

This paper introduces a novel bio-inspired metaheuristic algorithm, named the sharpbelly fish optimizer (SFO), inspired by the collective ecological behaviors of the sharpbelly fish. The algorithm integrates four biologically motivated strategies—(1) fitness-driven fast swimming, (2) convergence-guided gathering, (3) stagnation-triggered dispersal, and (4) disturbance-induced escape—which synergistically enhance the balance between global exploration and local exploitation. To assess its performance, the proposed SFO is evaluated on the CEC2022 benchmark suite under various dimensions. The experimental results demonstrate that SFO consistently achieves competitive or superior optimization accuracy and convergence speed compared to seven state-of-the-art metaheuristic algorithms. Furthermore, the algorithm is applied to three classical constrained engineering design problems: pressure vessel, speed reducer, and gear train design. In these applications, SFO exhibits strong robustness and solution quality, validating its potential as a general-purpose optimization tool for complex real-world problems. These findings highlight SFO’s effectiveness in tackling nonlinear, constrained, and multimodal optimization tasks, with promising applicability in diverse engineering scenarios. Full article

(This article belongs to the Section Biological Optimisation and Management)

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23 pages, 4011 KiB

Open AccessReview

Current Advances and Future Perspectives of Liver-on-a-Chip Platforms Incorporating Dynamic Fluid Flow

by Jingyeong Yun, Tae-Joon Jeon and Sun Min Kim

Biomimetics 2025, 10(7), 443; https://doi.org/10.3390/biomimetics10070443 - 4 Jul 2025

Viewed by 166

Abstract

The liver is a vital organ responsible for a broad range of metabolic functions, including glucose and lipid metabolism, detoxification, and protein synthesis. Its structural complexity, characterized by hexagonal hepatic lobules composed of diverse parenchymal and non-parenchymal cell types, supports its broad spectrum [...] Read more.

The liver is a vital organ responsible for a broad range of metabolic functions, including glucose and lipid metabolism, detoxification, and protein synthesis. Its structural complexity, characterized by hexagonal hepatic lobules composed of diverse parenchymal and non-parenchymal cell types, supports its broad spectrum of physiological activities. Traditional in vitro liver models have contributed significantly to our understanding of hepatic biology and the development of therapies for liver-related diseases. However, static culture systems fail to replicate the dynamic in vivo microenvironment, particularly the continuous blood flow and shear stress that are critical for maintaining hepatocyte function and metabolic zonation. Recent advances in microphysiological systems (MPS) incorporating dynamic fluid flow have addressed these limitations by providing more physiologically relevant platforms for modeling liver function. These systems offer improved fidelity for applications in drug screening, toxicity testing, and disease modeling. Furthermore, the integration of liver MPS with other organ models in multi-organ-on-chip platforms has enabled the investigation of inter-organ crosstalk, enhancing the translational potential of in vitro systems. This review summarizes recent progress in the development of dynamic liver MPS, highlights their biomedical applications, and discusses future directions for creating more comprehensive and predictive in vitro models. Full article

(This article belongs to the Special Issue Organ-on-a-Chip Platforms for Drug Delivery and Tissue Engineering)

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36 pages, 7153 KiB

Open AccessReview

Enhancing the Biological Functionality of Hydrogels Using Self-Assembling Peptides

by Woo Hyun Kwon, Kyoung Choi, Sang Jun Park, GeumByeol Park, Cho Young Park, Yoo Han Seo, Chun-Ho Kim and Jun Shik Choi

Biomimetics 2025, 10(7), 442; https://doi.org/10.3390/biomimetics10070442 - 4 Jul 2025

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Abstract

Hydrogels are ECM-mimicking three-dimensional (3D) networks that are widely used in biomedical applications; however, conventional natural and synthetic polymer-based hydrogels present limitations such as poor mechanical strength, limited bioactivity, and low reproducibility. Self-assembling peptides (SAPs) offer a promising alternative, as they can form [...] Read more.

Hydrogels are ECM-mimicking three-dimensional (3D) networks that are widely used in biomedical applications; however, conventional natural and synthetic polymer-based hydrogels present limitations such as poor mechanical strength, limited bioactivity, and low reproducibility. Self-assembling peptides (SAPs) offer a promising alternative, as they can form micro- and nanostructured hydrogels through non-covalent interactions and allow precise control over their biofunctionality, mechanical properties, and responsiveness to biological cues. Through rational sequence design, SAPs can be engineered to exhibit tunable mechanical properties, controlled degradation rates, and multifunctionality, and can dynamically regulate assembly and degradation in response to specific stimuli such as pH, ionic strength, enzymatic cleavage, or temperature. Furthermore, SAPs have been successfully incorporated into conventional hydrogels to enhance cell adhesion, promote matrix remodeling, and provide a more physiologically relevant microenvironment. In this review, we summarize recent advances in SAP-based hydrogels, particularly focusing on their novel biofunctional properties such as anti-inflammatory, antimicrobial, and anticancer activities, as well as bioimaging capabilities, and discuss the mechanisms by which SAP hydrogels function in biological systems. Full article

(This article belongs to the Special Issue Advancements in Regenerative Medicine: An Integrated Approach Using Nanotechnology and 3D Culture Platforms)

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13 pages, 4362 KiB

Open AccessArticle

Binder Jetting 3D Printing of Biomass–Fungi Composite Materials: A Preliminary Experimental Study

by Yeasir Mohammad Akib, Caleb Oliver Bedsole, Jackson Sanders, Harlie Warren, Zhijian Pei and Brian D. Shaw

Biomimetics 2025, 10(7), 441; https://doi.org/10.3390/biomimetics10070441 - 4 Jul 2025

Viewed by 271

Abstract

This paper reports on a preliminary experimental study on binder jetting 3D printing of biomass–fungi composite materials. Biomass–fungi composite materials have potential applications in the packaging, furniture, and construction industries. Biomass particles (prepared from agricultural residues) act as the substrate of the composite [...] Read more.

This paper reports on a preliminary experimental study on binder jetting 3D printing of biomass–fungi composite materials. Biomass–fungi composite materials have potential applications in the packaging, furniture, and construction industries. Biomass particles (prepared from agricultural residues) act as the substrate of the composite materials. The filamentous roots of fungi intertwine and bind biomass particles together. In this study, the biomass (hemp hurd) powders used had two distinct average particle sizes. The liquid binder used contained fungi (Trametes versicolor) cells. T-shaped samples were printed using a lab-designed binder jetting setup. Printed samples were kept inside an incubator oven for four days to allow fungi to grow. Afterward, loose biomass powder was removed from the T-shaped samples. The samples were then kept inside the incubator oven for eight more days to allow further fungal growth. The samples were subsequently placed in an oven at 120 °C for four hours to terminate all fungal activity in the samples. SEM micrographs were taken of the cross-sectional surfaces of the samples. The micrographs showed a significant presence of fungi hyphae inside the printed samples, providing evidence of the binding of biomass particles by the hyphae. Full article

(This article belongs to the Special Issue Biomimetic Design of Multifunctional Natural Macromolecular Materials)

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12 pages, 2660 KiB

Open AccessArticle

Fast and Fractionated: Correlation of Dose Attenuation and the Response of Human Cancer Cells in a New Anthropomorphic Brain Phantom

by Bernd Frerker, Elette Engels, Jason Paino, Vincent de Rover, John Paul Bustillo, Marie Wegner, Matthew Cameron, Stefan Fiedler, Daniel Häusermann, Guido Hildebrandt, Michael Lerch and Elisabeth Schültke

Biomimetics 2025, 10(7), 440; https://doi.org/10.3390/biomimetics10070440 - 3 Jul 2025

Viewed by 213

Abstract

The results of radiotherapy in patients with primary malignant brain tumors are extremely dissatisfactory: the overall survival after a diagnosis of glioblastoma is typically less than three years. The development of spatially fractionated radiotherapy techniques could help to improve this bleak prognosis. In [...] Read more.

The results of radiotherapy in patients with primary malignant brain tumors are extremely dissatisfactory: the overall survival after a diagnosis of glioblastoma is typically less than three years. The development of spatially fractionated radiotherapy techniques could help to improve this bleak prognosis. In order to develop technical equipment and organ-specific therapy plans, dosimetry studies as well as radiobiology studies are conducted. Although perfect spheres are considered optimal phantoms by physicists, this does not reflect the wide variety of head sizes and shapes in our patient community. Depth from surface and X-ray dose absorption by tissue between dose entry point and target, two key parameters in medical physics planning, are largely determined by the shape and thickness of the skull bone. We have, therefore, designed and produced a biomimetic tool to correlate measured technical dose and biological response in human cancer cells: a brain phantom, produced from tissue-equivalent materials. In a first pilot study, utilizing our phantom to correlate technical dose measurements and metabolic response to radiation in human cancer cell lines, we demonstrate why an anthropomorphic phantom is preferable over a simple spheroid phantom. Full article

(This article belongs to the Special Issue New Biomimetic Advances in Signal and Image Processing for Biomedical Applications 2025)

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43 pages, 1468 KiB

Open AccessReview

Biometric Strategies to Improve Vaccine Immunogenicity and Effectiveness

by Vicente Javier Clemente-Suárez, Laura Redondo-Flórez, Alvaro Bustamante-Sánchez, Alexandra Martín-Rodríguez, Rodrigo Yáñez-Sepúlveda and Jose Francisco Tornero-Aguilera

Biomimetics 2025, 10(7), 439; https://doi.org/10.3390/biomimetics10070439 - 3 Jul 2025

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Abstract

Background: Vaccines have revolutionized disease prevention, yet their effectiveness is challenged by variable immunogenicity, individual response differences, and emerging variants. Biomimetic strategies, inspired by natural immune processes, offer new avenues to enhance vaccine performance. Objectives: This narrative review examines how bioinspired approaches—grounded in [...] Read more.

Background: Vaccines have revolutionized disease prevention, yet their effectiveness is challenged by variable immunogenicity, individual response differences, and emerging variants. Biomimetic strategies, inspired by natural immune processes, offer new avenues to enhance vaccine performance. Objectives: This narrative review examines how bioinspired approaches—grounded in evolutionary medicine, immunology, and host–microbiota interactions—can improve vaccine immunogenicity and long-term protection. We further examine the evolutionary foundations of immune responses, highlighting how an evolutionary perspective can inform the development of durable, broadly protective, and personalized vaccines. Furthermore, mechanistic insights at the molecular and cellular level are explored, including Toll-like receptor (TLR) engagement, dendritic cell activation pathways, and MHC-I/MHC-II-mediated antigen presentation. These mechanisms are often mimicked in biomimetic systems to enhance uptake, processing, and adaptive immune activation. Results: The review highlights how immunosenescence, maternal immunity, genetic variation, and gut microbiota composition influence vaccine responses. Biomimetic platforms—such as nanoparticle carriers and novel adjuvants—enhance antigen presentation, boost adaptive immunity, and may overcome limitations in traditional vaccine approaches. Additionally, co-administration strategies, delivery systems, and microbiota-derived immunomodulators show promise in improving vaccine responsiveness. Conclusions: Integrating biomimetic and evolutionary principles into vaccine design represents a promising path toward safer, longer-lasting, and more effective immunizations Full article

(This article belongs to the Special Issue Biomimetic Approaches in Healthcare—Innovations Inspired by Nature: 3rd Edition)

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28 pages, 18319 KiB

Open AccessReview

Influence of Scaffold Structure and Biomimetic Properties on Adipose Stem Cell Homing in Personalized Reconstructive Medicine

by Doina Ramona Manu, Diana V. Portan, Monica Vuţă and Minodora Dobreanu

Biomimetics 2025, 10(7), 438; https://doi.org/10.3390/biomimetics10070438 - 3 Jul 2025

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Abstract

Human adipose stem cells (ASCs) are multipotent cells expressing mesenchymal stem cell (MSC) markers that are capable of multilineage differentiation and secretion of bioactive factors. Their “homing” to injured tissues is mediated by chemokines, cytokines, adhesion molecules, and signaling pathways. Enhancing ASC homing [...] Read more.

Human adipose stem cells (ASCs) are multipotent cells expressing mesenchymal stem cell (MSC) markers that are capable of multilineage differentiation and secretion of bioactive factors. Their “homing” to injured tissues is mediated by chemokines, cytokines, adhesion molecules, and signaling pathways. Enhancing ASC homing is critical for improving regenerative therapies. Strategies include boosting chemotactic signaling, modulating immune responses to create a supportive environment, preconditioning ASCs with hypoxia or mechanical stimuli, co-culturing with supportive cells, applying surface modifications or genetic engineering, and using biomaterials to promote ASC recruitment, retention, and integration at injury sites. Scaffolds provide structural support and a biomimetic environment for ASC-based tissue regeneration. Natural scaffolds promote adhesion and differentiation but have mechanical limitations, while synthetic scaffolds offer tunable properties and controlled degradation. Functionalization with bioactive molecules improves the regenerative outcomes of different tissue types. Ceramic-based scaffolds, due to their strength and bioactivity, are ideal for bone healing. Composite scaffolds, combining polymers, ceramics, or metals, further optimize mechanical and biological properties, supporting personalized regenerative therapies. This review integrates concepts from cell biology, biomaterials science, and regenerative medicine to offer a comprehensive understanding of ASC homing and its impact on tissue engineering and clinical applications. Full article

(This article belongs to the Section Biomimetics of Materials and Structures)

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33 pages, 5024 KiB

Open AccessArticle

An Enhanced Dynamic Model of a Spatial Parallel Mechanism Receiving Direct Constraints from the Base at Two Point-Contact Higher Kinematic Pairs

by Chen Cheng, Xiaojing Yuan and Yenan Li

Biomimetics 2025, 10(7), 437; https://doi.org/10.3390/biomimetics10070437 - 3 Jul 2025

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Abstract

In this paper, a biologically congruent parallel mechanism (PM) inspired by the masticatory system of human beings has been proposed to recreate complete chewing behaviours in three-dimensional space. The mechanism is featured by direct constraints from the base (DCFB) to its end effector [...] Read more.

In this paper, a biologically congruent parallel mechanism (PM) inspired by the masticatory system of human beings has been proposed to recreate complete chewing behaviours in three-dimensional space. The mechanism is featured by direct constraints from the base (DCFB) to its end effector at two higher kinematic pairs (HKPs), which greatly raise its topological complexity. Meanwhile, friction effects occur at HKPs and actuators, causing wear and then reducing motion accuracy. Regarding these, an inverse dynamic model that can raise the computational efficiency and the modelling fidelity is proposed, being prepared to be applied to realise accurate real-time motion and/or force control. In it, Euler parameters are employed to express the motions of the constrained end effector, and Newton–Euler’s law is applied, which can conveniently incorporate friction effects at both HKPs and actuators into the dynamic model. Numerical results show that the time consumption of the model using Euler parameters is only approximately 23% of that of the model using Euler angles, and friction effects significantly increase the model’s nonlinearity. Further, from the comparison between the models of the target PM and its counterpart free of DCFB, these constraints sharply raise the modelling complexity in terms of the transformation between Euler parameters and Euler angles in the end effector and the computational cost of inverse dynamics. Full article

(This article belongs to the Special Issue Recent Advances in Bioinspired Robot and Intelligent Systems)

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14 pages, 5041 KiB

Open AccessArticle

Coating Process of Oil and Gas Well Pipeline Preventive Repair Materials Inspired by Remora Suckerfish Structure

by Yuliang Lu, Dongtao Liu, Jiming Song, Qiaogang Xiao, Kezheng Du, Xinjie Wei, Lifeng Dang, Yajun Yu and Huiyan Zhao

Biomimetics 2025, 10(7), 436; https://doi.org/10.3390/biomimetics10070436 - 2 Jul 2025

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Abstract

To meet the special needs of preventive maintenance for oil and gas well pipelines, this study conducts a geometric dissection of remora suckerfish based on bionics. It combines the biological features with fiberboard tape and uses the discrete element method to construct a [...] Read more.

To meet the special needs of preventive maintenance for oil and gas well pipelines, this study conducts a geometric dissection of remora suckerfish based on bionics. It combines the biological features with fiberboard tape and uses the discrete element method to construct a particle model of solvent-free, epoxy-reinforced polymer materials, determining relevant parameters. The model accuracy is verified through volumetric density and drop tests, and the optimal parameter combination of the remora-inspired structure is obtained via multi-factor simulation analysis. Comparative tests confirm that the bionic structure enhances stability by approximately 43.29% compared to the original structure, effectively avoiding insufficient strength. It successfully addresses the gravitational segregation and fluid shear caused by uneven coating thickness, ensures stable and reliable interfacial properties of the composite structure during service, and provides strong support for the practical application of related materials in the preventive repair of oil and gas well pipelines. The findings promote the upgrade of oil and gas pipeline maintenance strategies from “passive response” to “active prevention”, laying the core technical foundation for the resilience of energy infrastructure. Full article

(This article belongs to the Special Issue Nature-Inspired Surfaces and Smart Devices for Multifunctional Applications)

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21 pages, 9720 KiB

Open AccessArticle

Rolling vs. Swing: A Strategy for Enhancing Locomotion Speed and Stability in Legged Robots

by Yongjiang Xue, Wei Wang, Mingyu Duan, Nanqing Jiang, Shaoshi Zhang and Xuan Xiao

Biomimetics 2025, 10(7), 435; https://doi.org/10.3390/biomimetics10070435 - 2 Jul 2025

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Abstract

Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the [...] Read more.

Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the energy efficiency and stability. First, a wheel-legged quadruped robot, R-Taichi, is developed, which is capable of switching to legged, wheeled, and RHex mobile modes. Second, the mechanical structure of the transformable two-degree-of-freedom leg is introduced, and the kinematics is analyzed. Finally, experiments are conducted to generate wheeled, legged, and RHex motion in both swing and rolling gaits, and the energy efficiency is further compared. The experimental results show that the rolling motion can ensure stable ground contact and mitigate cyclic collisions, reducing specific resistance by up to 30% compared with conventional swing gaits, achieving a top speed of 0.7 m/s with enhanced stability (root mean square error (RMSE) reduction of 22% over RHex mode). Furthermore, R-Taichi exhibits robust multi-terrain adaptability, successfully traversing gravel, grass, and obstacles up to 150 mm in height. Full article

(This article belongs to the Special Issue Biomimetic Robot Motion Control)

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13 pages, 3452 KiB

Open AccessArticle

Silk Fibroin Microparticle/Carboxymethyl Cellulose Composite Gel for Wound Healing Applications

by Alexander Pashutin, Ekaterina Podbolotova, Luidmila Kirsanova, Onur Dosi, Anton E. Efimov, Olga Agapova and Igor Agapov

Biomimetics 2025, 10(7), 434; https://doi.org/10.3390/biomimetics10070434 - 2 Jul 2025

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Abstract

Silk fibroin has recently gained considerable attention as a promising biomaterial for use in medical and bioengineering technologies due to its biocompatibility and favorable mechanical properties. In this study, composite gel based on silk fibroin microparticles and carboxymethyl cellulose was developed, characterized by [...] Read more.

Silk fibroin has recently gained considerable attention as a promising biomaterial for use in medical and bioengineering technologies due to its biocompatibility and favorable mechanical properties. In this study, composite gel based on silk fibroin microparticles and carboxymethyl cellulose was developed, characterized by a viscous, homogeneous white mass containing uniformly distributed fibroin microparticles ranging from 1 to 20 μm in size. The gel exhibited a kinematic viscosity of 36.5 × 10⁻⁶ St, allowing for convenient application to wounds using a syringe or spatula while preventing uncontrolled spreading. The cytocompatibility of the gel was confirmed using the methylthiazol tetrazolium (MTT) assay, which showed no cytotoxic effects on 3T3 fibroblast cells. Furthermore, the gel remained stable for over one year when stored at 10 °C, in contrast to conventional fibroin solutions, which typically lose stability within a month under similar conditions. In a full-thickness skin wound model in rats, the application of the gel significantly accelerated skin regeneration, with complete wound closure observed by day 15, compared with 30 days in the control group. Histological analysis confirmed the restoration of all skin layers. These findings demonstrate the high potential of the gel for applications in regenerative medicine and tissue engineering. Full article

(This article belongs to the Special Issue Advanced Biomaterials for Wound Healing Application)

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13 pages, 1653 KiB

Open AccessArticle

Evaluation of Shear Bond Strength in the Repair of Additively and Subtractively Manufactured CAD/CAM Materials Using Bulk-Fill Composites

by Selinsu Öztürk, Ezgi Altuntaş, Ayşe Aslı Şenol, Erkut Kahramanoğlu, Pınar Yılmaz Atalı, Bilge Tarçın and Cafer Türkmen

Biomimetics 2025, 10(7), 433; https://doi.org/10.3390/biomimetics10070433 - 1 Jul 2025

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Abstract

Biomimetic restorative protocols aim to preserve natural tooth structure while enhancing restoration longevity. This in vitro study aimed to evaluate the shear bond strength (SBS) in the repair of additively and subtractively manufactured CAD/CAM materials using bulk-fill resin composites and to assess the [...] Read more.

Biomimetic restorative protocols aim to preserve natural tooth structure while enhancing restoration longevity. This in vitro study aimed to evaluate the shear bond strength (SBS) in the repair of additively and subtractively manufactured CAD/CAM materials using bulk-fill resin composites and to assess the effect of thermocycling. Forty rectangular specimens (14.5 × 7 × 3 mm) were prepared from Grandio Blocs (GB, VOCO) and VarseoSmile Crown^Plus (VS, BEGO), and thermocycled (5000 cycles, 5–55 °C, 20 s dwell time). All surfaces were roughened with 50 μm Al₂O₃. Samples were repaired using VisCalor (VCB, VOCO) and Charisma Bulk Flow One (CBO, Kulzer) composites (n = 10 per group) with their respective adhesives. Each group was further divided into immediate and post-thermocycling subgroups. All specimens were tested under shear force until failure, and failure types were examined under a stereomicroscope. Representative samples were examined by SEM to evaluate filler morphology. Statistical analysis was performed with SPSS v23 (p < 0.05). No statistically significant differences in SBS were found between groups (p > 0.05). Mean SBS values were highest in VS-CBO and lowest in GB-CBO. Cohesive failures were more frequent in immediate groups, while adhesive failures predominated after thermocycling. Bulk-fill composites did not influence the repair bond strength of indirect materials. Thermocycling affected the failure type, though not the SBS values. Full article

(This article belongs to the Special Issue Biomimetic Bonded Restorations for Dental Applications: 2nd Edition)

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15 pages, 1519 KiB

Open AccessArticle

Comparative Evaluation of Color Stability in Bioactive and Conventional Resin Cements Under Thermal Stress Conditions

by Alaa Turkistani and Hanin E. Yeslam

Biomimetics 2025, 10(7), 432; https://doi.org/10.3390/biomimetics10070432 - 1 Jul 2025

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Abstract

Bioactive resin-based cements (RBCs) were recently introduced, but data on their color stability remain limited. This study analyzed the impact of thermal cycling on the color and whiteness of bioactive RBCs. Specimens (n = 10) were fabricated from Panavia SA Universal (PN), Predicta [...] Read more.

Bioactive resin-based cements (RBCs) were recently introduced, but data on their color stability remain limited. This study analyzed the impact of thermal cycling on the color and whiteness of bioactive RBCs. Specimens (n = 10) were fabricated from Panavia SA Universal (PN), Predicta Bioactive Cement (PR), and ACTIVA BioACTIVE cement (AC). CIE Lab* values were registered at baseline and after 5000, 10,000, and 15,000 thermal cycles (5–55 °C). Changes in color (ΔE₀₀) and whiteness index (ΔWI_D) were calculated and compared. Material type and thermal cycling significantly affected ΔE₀₀ and ΔWI_D (p < 0.001). AC showed the highest ΔE₀₀ values at all stages (p < 0.001), with a progressive increase over time. PN differed significantly between early and later cycles (p < 0.05), while PR remained stable (p > 0.05). Analysis of color parameters indicated that AC underwent the most pronounced changes, particularly in Δa and Δb, while PN exhibited the greatest shift in Δb. For ΔWI_D, PR had significantly lower values than PN (p < 0.05) and AC (p < 0.001), with no difference between PN and AC (p > 0.05), and thermal cycling significantly affected all groups, with PR and AC differing across all stages (p < 0.05). Thermal cycling significantly influenced the color stability and whiteness of bioactive RBCs, with AC exhibiting the greatest changes over time, while PR demonstrated superior stability. Full article

(This article belongs to the Special Issue Biomimetic Bonded Restorations for Dental Applications: 2nd Edition)

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20 pages, 4620 KiB

Open AccessArticle

An Interactive Human-in-the-Loop Framework for Skeleton-Based Posture Recognition in Model Education

by Jing Shen, Ling Chen, Xiaotong He, Chuanlin Zuo, Xiangjun Li and Lin Dong

Biomimetics 2025, 10(7), 431; https://doi.org/10.3390/biomimetics10070431 - 1 Jul 2025

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Abstract

This paper presents a human-in-the-loop interactive framework for skeleton-based posture recognition, designed to support model training and artistic education. A total of 4870 labeled images are used for training and validation, and 500 images are reserved for testing across five core posture categories: [...] Read more.

This paper presents a human-in-the-loop interactive framework for skeleton-based posture recognition, designed to support model training and artistic education. A total of 4870 labeled images are used for training and validation, and 500 images are reserved for testing across five core posture categories: standing, sitting, jumping, crouching, and lying. From each image, comprehensive skeletal features are extracted, including joint coordinates, angles, limb lengths, and symmetry metrics. Multiple classification algorithms—traditional (KNN, SVM, Random Forest) and deep learning-based (LSTM, Transformer)—are compared to identify effective combinations of features and models. Experimental results show that deep learning models achieve superior accuracy on complex postures, while traditional models remain competitive with low-dimensional features. Beyond classification, the system integrates posture recognition with a visual recommendation module. Recognized poses are used to retrieve matched examples from a reference library, allowing instructors to browse and select posture suggestions for learners. This semi-automated feedback loop enhances teaching interactivity and efficiency. Among all evaluated methods, the Transformer model achieved the best accuracy of 92.7% on the dataset, demonstrating the effectiveness of our closed-loop framework in supporting pose classification and model training. The proposed framework contributes both algorithmic insights and a novel application design for posture-driven educational support systems. Full article

(This article belongs to the Special Issue Biomimetic Innovations for Human–Machine Interaction)

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13 pages, 2327 KiB

Open AccessArticle

Biocompatible and Biodegradable Nanocarriers for Targeted Drug Delivery in Precision Medicine

by Xin Jin, Hu Qian, Yuxiang Xie, Changzhi Liu, Yuan Cheng, Jinsong Hou and Jiandong Zheng

Biomimetics 2025, 10(7), 430; https://doi.org/10.3390/biomimetics10070430 - 1 Jul 2025

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Abstract

Despite the promising natural origin, biocompatibility, and biodegradability of chitosan for biomedical applications, developing biodegradable nanocarriers with controllable sizes and precise drug delivery targeting remains a significant challenge, hindering its integration into precision medicine. To address this, we synthesized gold nanocage (AuNCs)/poly-(N-isopropylacrylamide-co-carboxymethyl chitosan) [...] Read more.

Despite the promising natural origin, biocompatibility, and biodegradability of chitosan for biomedical applications, developing biodegradable nanocarriers with controllable sizes and precise drug delivery targeting remains a significant challenge, hindering its integration into precision medicine. To address this, we synthesized gold nanocage (AuNCs)/poly-(N-isopropylacrylamide-co-carboxymethyl chitosan) core-shell multifunctional composite nanospheres (CPAu) through a two-step one-pot method. The resulting CPAu nanospheres (~146 nm in size) exhibited multi-sensitive release properties, excellent biocompatibility, and potent photothermal therapy (PTT) activity. These nanospheres effectively encapsulated diverse antitumor drugs while demonstrating triple responsiveness (thermo-, reduction-, and PTT-triggered) for targeted tumor cell delivery, thereby achieving enhanced antitumor efficacy in combinatorial chemotherapy. Full article

(This article belongs to the Special Issue Advances in Biogenic and Biomimetic Materials: From Bionanomedicine to Environmental Applications and Beyond)

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36 pages, 1647 KiB

Open AccessReview

Three-Dimensionally Printed Scaffolds and Drug Delivery Systems in Treatment of Osteoporosis

by Cosmin Iulian Codrea and Victor Fruth

Biomimetics 2025, 10(7), 429; https://doi.org/10.3390/biomimetics10070429 - 1 Jul 2025

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Abstract

The increasing incidence of osteoporotic fractures determines ongoing research on new methods and strategies for improving the difficult healing process of this type of fracture. Osteoporotic patients suffer from the intense side effects of accustomed drug treatment and its systemic distribution in the [...] Read more.

The increasing incidence of osteoporotic fractures determines ongoing research on new methods and strategies for improving the difficult healing process of this type of fracture. Osteoporotic patients suffer from the intense side effects of accustomed drug treatment and its systemic distribution in the body. To overcome these drawbacks, besides searching for new drugs, 3D-printed scaffolds and drug delivery systems have started to be increasingly seen as the main strategy employed against osteoporosis. Three-dimensionally printed scaffolds can be tailored in intricate designs and make use of nanoscale topographical and biochemical cues able to enhance bone tissue regeneration. Research regarding drug delivery systems is exploring bold new ways of targeting bone tissue, making use of designs involving nanoparticles and intricate encapsulation and support methods. The local administration of treatment with the help of a scaffold-based drug delivery system looks like the best option through its use of the advantages of both structures. Biomimetic systems are considered the future norm in the field, while stimuli-responsiveness opens the door for the next level of efficiency, patient compliance, and a drastic reduction in side effects. The successful approval of these products still requires numerous challenges throughout the development and regulatory processes, but the interest and effort in this direction are high. This review explored various strategies for managing osteoporosis, emphasizing the use of scaffolds for targeted drug delivery to bone tissue. Instead of covering the whole subject, we focused on the most important aspects, with the intention to provide an up-to-date and useful introduction to the management of osteoporosis. Full article

(This article belongs to the Special Issue Advancements in 3D Printing and Additive Manufacturing for Orthopedic Applications)

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26 pages, 3339 KiB

Open AccessReview

Research Progress and Challenges in 3D Printing of Bioceramics and Bioceramic Matrix Composites

by Xueni Zhao, Jizun Liu and Lingna Li

Biomimetics 2025, 10(7), 428; https://doi.org/10.3390/biomimetics10070428 - 1 Jul 2025

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Abstract

Three-dimensional printing techniques can prepare complex bioceramic parts and scaffolds with high precision and accuracy, low cost, and customized geometry, which greatly broadens their application of 3D-printed bioceramics and bioceramic matrix composites in the clinical field. Nevertheless, the inadequate mechanical properties of 3D-printed [...] Read more.

Three-dimensional printing techniques can prepare complex bioceramic parts and scaffolds with high precision and accuracy, low cost, and customized geometry, which greatly broadens their application of 3D-printed bioceramics and bioceramic matrix composites in the clinical field. Nevertheless, the inadequate mechanical properties of 3D-printed bioceramic scaffolds, such as compressive strength, wear resistance, flexural strength, fracture toughness, and other properties, are a bottleneck problem and severely limit their application, which are overcome by introducing reinforcements. Three-dimensional printing techniques and the mechanical property of bioceramics and bioceramic matrix composites with different reinforcements, as well as their potential applications for bone tissue engineering, are discussed. In addition, the biological performance of 3D-printed bioceramics and scaffolds and their applications are presented. To address the challenges of insufficient mechanical strength and mismatched biological performance in bioceramic scaffolds, we summarize current solutions, including the advantages and strengthening effects of fiber, particle, whisker, and ion doping. The effectiveness of these methods is analyzed. Finally, the limitations and challenges in 3D printing of bioceramics and bioceramic matrix composites are discussed to encourage future research in this field. Our work offers a helpful guide to research and medical applications, especially application in the tissue engineering fields of bioceramics and bioceramic matrix composites. Full article

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