Bioengineering

12 pages, 782 KB

Open AccessEditor’s ChoiceArticle

Development of an Immersive Virtual Reality-Based Nursing Program Involving Patients with Respiratory Infections

by Eun-Joo Ji, Sang Sik Lee and Eun-Kyung Lee

Bioengineering 2026, 13(1), 98; https://doi.org/10.3390/bioengineering13010098 - 15 Jan 2026

Viewed by 573

This study aimed to develop an immersive virtual reality (VR) program and conduct preliminary evaluation of its feasibility and learner perception for enhancing nursing students’ clinical practicum education. The VR program was designed using the ADDIE model (analysis, design, development, implementation, and evaluation) [...] Read more.

This study aimed to develop an immersive virtual reality (VR) program and conduct preliminary evaluation of its feasibility and learner perception for enhancing nursing students’ clinical practicum education. The VR program was designed using the ADDIE model (analysis, design, development, implementation, and evaluation) and implemented on the UNITY 3D platform. Expert evaluation was conducted through a VR application, and its effectiveness was further assessed among 25 fourth-year nursing students in terms of immersion, presence, and satisfaction. The expert evaluation yielded a mean score of 6.54 out of 7, indicating acceptable content validity. Among learners, evaluation demonstrated immersion at 42.28 ± 2.37 out of 50 (95% CI: 41.30–43.26), presence at 81.36 ± 7.32 out of 95 (95% CI: 78.34–84.38), and satisfaction at 13.48 ± 1.26 out of 15 (95% CI: 12.96–14.00). Overall, the developed VR program demonstrated acceptable expert validity and positive learner perceptions. These preliminary findings suggest feasibility as a supplementary practicum. However, the single-group design without control comparison and reliance on self-reported measures preclude conclusions about educational effectiveness. Full article

(This article belongs to the Section Biosignal Processing)

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16 pages, 1629 KB

Open AccessEditor’s ChoiceReview

Gut Microbiota and Dopamine: Producers, Consumers, Enzymatic Mechanisms, and In Vivo Insights

by Giovanni Albani, Vasuki Ranjani Chellamuthu, Lea Morlacchi, Federica Zirone, Maryam Youssefi, Marica Giardini, Yin-Xia Chao, Eng-King Tan and Salvatore Albani

Bioengineering 2026, 13(1), 55; https://doi.org/10.3390/bioengineering13010055 - 31 Dec 2025

Cited by 1 | Viewed by 1612

Abstract

The human gut microbiota plays a key role in neurochemical communication, especially through the gut–brain axis. There is growing evidence that the gut microbiota influences dopamine metabolism through both production and consumption mechanisms. Two key bacterial enzymes are central to this process: tyrosine [...] Read more.

The human gut microbiota plays a key role in neurochemical communication, especially through the gut–brain axis. There is growing evidence that the gut microbiota influences dopamine metabolism through both production and consumption mechanisms. Two key bacterial enzymes are central to this process: tyrosine decarboxylase (TDC), which primarily catalyzes the decarboxylation of tyrosine to tyramine but can also act on L-DOPA to produce dopamine in certain bacterial strains, and aromatic L-amino acid decarboxylase (AADC), which can convert precursors such as L-DOPA, tryptophan, or 5-hydroxytryptophan into bioactive amines including dopamine, tryptamine, and serotonin. Identifying the bacterial families corresponding to TDC and AADC enzymes opens new avenues for clinical intervention, particularly in neuropsychiatric and neurodegenerative disorders, such as Parkinson’s disease. Moreover, elucidating strain-specific microbial contribution and host-microbe interactions may enable personalized therapeutic strategies, such as selective microbial enzyme inhibitors or tailored probiotics, to optimize dopamine metabolism. Emerging technologies, including biosensors and organ-on-chip platforms, offer new tools to monitor and manipulate microbial dopamine activity. This article explores the bacterial taxa capable of producing or consuming dopamine, focusing on the enzymatic mechanisms involved and the methodologies available for studying these processes in vivo. Full article

(This article belongs to the Section Biochemical Engineering)

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19 pages, 3773 KB

Open AccessEditor’s ChoiceArticle

Engineering Resilience: How Irradiation Strategies Influence 3D-Bioprinted Adipose Stem Cells

by Nicki Amiri, Rafael Schmid, Stefan Schrüfer, Zan Lamberger, Philipp Stahlhut, Gregor Lang, Yvonne Kulicke, Andreas Arkudas, Raymund E. Horch and Wibke Müller-Seubert

Bioengineering 2026, 13(1), 25; https://doi.org/10.3390/bioengineering13010025 - 26 Dec 2025

Viewed by 1623

Abstract

Background: Reconstructive defect coverage after irradiation remains a challenge in reconstructive surgery, as ionizing radiation leads to tissue ischemia and fibrosis. Therefore, the application of adipose-derived stem cells (ASCs) might be a therapeutic strategy for improving flap survival. Nevertheless, the influence of irradiation [...] Read more.

Background: Reconstructive defect coverage after irradiation remains a challenge in reconstructive surgery, as ionizing radiation leads to tissue ischemia and fibrosis. Therefore, the application of adipose-derived stem cells (ASCs) might be a therapeutic strategy for improving flap survival. Nevertheless, the influence of irradiation on ASCs remains unclear. This study examines the effect of irradiation on 3D-printed ASCs. Methods: ASCs were 3D-cultured. The constructs were irradiated with 2 Gy and 5 Gy; one group treated with 0 Gy served as the non-irradiated control group. Cell viability was measured via a WST-8 assay, a live/dead assay and fluorescence microscopy 24 h, 48 h and 72 h after irradiation. Furthermore, qPCR analysis was performed to detect the expression of HIF-1α, p53 and IL-6 at the same timepoints. Results: Cell survival was high after 24 h. Expression of HIF1α after 24 h was 1.5 times significantly higher in the 2 Gy group compared with the 0 Gy group. The expression of other genes was not significantly affected by irradiation. Measurement of the metabolic activity and survival of the ASCs did not show differences between the different groups at all timepoints. Conclusions: 3D-cultured adipose-derived stem cells maintain high viability after moderate irradiation, suggesting radioresistance. Full article

(This article belongs to the Special Issue Advanced 3D Cell Culture Technologies and Formats, 2nd Edition)

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15 pages, 3698 KB

Open AccessEditor’s ChoiceArticle

Discovering the Effects of Superior-Surface Vocal Fold Lesions via Fluid–Structure Interaction Analysis

by Manoela Neves, Anitha Niyingenera, Norah Delaney and Rana Zakerzadeh

Bioengineering 2025, 12(12), 1360; https://doi.org/10.3390/bioengineering12121360 - 13 Dec 2025

Viewed by 698

Abstract

This study examines the impact of vocal fold (VF) lesions located on the superior surface on glottal airflow dynamics and tissue oscillatory behaviors using biomechanical simulations of a two-layered realistic VF model. It is hypothesized that morphological changes in the VFs due to [...] Read more.

This study examines the impact of vocal fold (VF) lesions located on the superior surface on glottal airflow dynamics and tissue oscillatory behaviors using biomechanical simulations of a two-layered realistic VF model. It is hypothesized that morphological changes in the VFs due to the presence of a lesion cause changes in tissue elasticity and rheological properties, contributing to dysphonia. Previous research has lacked the integration of lesions in computational simulations of anatomically accurate larynx-VF models to explore their effects on phonation and contribution to voice disorders. Addressing the current gap in literature, this paper considers a computational model of a two-layered VF structure incorporating a lesion that represents a hemorrhagic polyp. A three-dimensional, subject-specific, multilayered geometry of VFs is constructed based on STL files derived from a human larynx CT scan, and a fluid–structure interaction (FSI) methodology is employed to simulate the coupling of glottal airflow and VF tissue dynamics. To evaluate the effects of the lesion’s presence, two FSI models, one with a lesion embedded in the cover layer and one without, are simulated and compared. Analysis of airflow dynamics and tissue vibrational patterns between these two models is used to determine the impact of the lesion on the biomechanical characteristics of phonation. The polyp is found to slightly increase airflow resistance through the glottis and disrupt vibratory symmetry by decreasing the vibration frequency of the affected fold, leading to weaker and less rhythmic oscillations. The results also indicate that the lesion increases tissue stress in the affected fold, which agrees with clinical observations. While quantitative ranges depend on lesion size and tissue properties, these consistent and physically meaningful trends highlight the biomechanical mechanisms by which lesions influence phonation. Full article

(This article belongs to the Section Biomechanics and Sports Medicine)

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21 pages, 10700 KB

Open AccessEditor’s ChoiceArticle

A 3D ColMA-Based Tenogenic Microenvironment Unveils the Behavior of Tendon Stem/Progenitor Cells (TSPCs) from Tendinopathic Surgical Explants

by Giacomo Cortella, Erwin Pavel Lamparelli, Joseph Lovecchio, Emanuele Giordano, Nicola Maffulli and Giovanna Della Porta

Bioengineering 2025, 12(12), 1337; https://doi.org/10.3390/bioengineering12121337 - 8 Dec 2025

Viewed by 1990

Abstract

Tendon injuries present significant clinical challenges due to limited intrinsic healing and complex pathological mechanisms. Here, we developed a novel 3D bioprinted methacrylated type I collagen (ColMA) scaffold integrated with Growth Differentiation Factor-5 (GDF-5)-loaded Poly (lactic-co-glycolic acid) (PLGA) nanoparticles and dynamically cultured it [...] Read more.

Tendon injuries present significant clinical challenges due to limited intrinsic healing and complex pathological mechanisms. Here, we developed a novel 3D bioprinted methacrylated type I collagen (ColMA) scaffold integrated with Growth Differentiation Factor-5 (GDF-5)-loaded Poly (lactic-co-glycolic acid) (PLGA) nanoparticles and dynamically cultured it under perfusion to establish a tenogenic microenvironment in vitro. Pathological human Tendon Stem/Progenitor Cells (hTSPCs) derived from tendinopathic surgical explants were encapsulated to investigate their impaired extracellular matrix (ECM) deposition and associated pro-inflammatory signaling. GDF-5-loaded nanoparticles (average diameter 140 ± 40 nm) were fabricated via microfluidic-assisted nanoprecipitation and homogeneously incorporated within the ColMA synthetic ECM to enable sustained growth factor release. Continuous perfusion culture (1 mL/min) ensured efficient mass transfer and supported cell viability above 70% over 21 days. Pathological hTSPCs exhibited impaired ECM remodeling, characterized by the absence of type I collagen and a 2.56-fold increase in type III collagen at day 7, indicative of a fibrotic-like phenotype. Western blot densitometry demonstrated a 5.31-fold elevation in secreted tenomodulin at day 14, while ECM analysis verified a type III to type I collagen ratio of 4.5. In addition, a markedly pro-inflammatory cytokine profile was observed, with elevated secretion of interleukin-6 (IL-6) and interleukin-8 (IL-8) from day 7 onward, consistent with the chronic inflammatory status of cells derived from pathological tendon tissues. This modular 3D platform represents a robust in vitro model for mechanistic studies and the advancement of personalized regenerative strategies targeting chronic tendon disorders. Full article

(This article belongs to the Special Issue Biofabrication Technologies: Novel Tools for More Effective Personalized Medicine and Regenerative Therapies)

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22 pages, 6021 KB

Open AccessEditor’s ChoiceArticle

Deep Temporal Clustering of Pathological Gait Recovery Patterns in Post-Stroke Patients Using Joint-Angle Trajectories: A Longitudinal Study

by Jinwoo Kim, Teh-Hao Teng, Yun-Hee Kim, Seung-Jong Kim and Mun-Taek Choi

Bioengineering 2025, 12(12), 1314; https://doi.org/10.3390/bioengineering12121314 - 30 Nov 2025

Viewed by 893

Abstract

This study aims to analyze long-term gait recovery patterns in sub-acute post-stroke hemiplegic patients by applying end-to-end deep learning (DL)-based clustering to sagittal joint-angle trajectories throughout the gait cycle. To address the data scarcity issue in long-term follow-up patient gait trajectory datasets, two [...] Read more.

This study aims to analyze long-term gait recovery patterns in sub-acute post-stroke hemiplegic patients by applying end-to-end deep learning (DL)-based clustering to sagittal joint-angle trajectories throughout the gait cycle. To address the data scarcity issue in long-term follow-up patient gait trajectory datasets, two time-series data augmentation methods, TimeVAE and Diffusion-TS, were employed to generate high-fidelity synthetic joint-angle trajectories. The augmented dataset were subsequently analyzed using a Deep Temporal Clustering (DTC) model, which effectively captured individualized longitudinal recovery patterns by jointly learning temporal representations and cluster assignments. Based on the clustering evaluation criteria, the model identified six clusters as the optimal grouping. These clusters were statistically well represented by distinct kinematic characteristics. This study represents the first attempt to analyze longitudinal gait recovery patterns in post-stroke patients using a deep clustering model. While exploratory in nature, it provides a conceptual basis for future longitudinal research in stroke rehabilitation. Full article

(This article belongs to the Section Biomechanics and Sports Medicine)

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10 pages, 1210 KB

Open AccessEditor’s ChoiceReview

Agentic AI and Large Language Models in Radiology: Opportunities and Hallucination Challenges

by Sara Salehi, Yashbir Singh, Kelly K. Horst, Quincy A. Hathaway and Bradley J. Erickson

Bioengineering 2025, 12(12), 1303; https://doi.org/10.3390/bioengineering12121303 - 26 Nov 2025

Cited by 3 | Viewed by 3171

Abstract

The field of radiology is experiencing rapid adoption of large language models (LLMs), yet their tendency to generate hallucinations (plausible but incorrect information) remains a significant barrier to trust. This comprehensive review evaluates emerging agentic artificial intelligence (AI) approaches, including multi-agent role-based systems, [...] Read more.

The field of radiology is experiencing rapid adoption of large language models (LLMs), yet their tendency to generate hallucinations (plausible but incorrect information) remains a significant barrier to trust. This comprehensive review evaluates emerging agentic artificial intelligence (AI) approaches, including multi-agent role-based systems, retrieval-augmented generation (RAG), and uncertainty quantification, to assess their potential for reducing hallucinations in radiology workflows. Evidence from 2024 to 2025 demonstrates that agentic AI can improve diagnostic accuracy and reduce error rates, though these methods remain computationally demanding and lack comprehensive clinical validation. Multi-agent frameworks enable cross-validation through role-based specialization and systematic workflow orchestration, while RAG strategies enhance accuracy by grounding responses in verified medical literature. Within multi-agent systems, uncertainty quantification enables agents to communicate confidence levels to one another, allowing them to appropriately weigh each other’s contributions during collaborative analysis. While multi-agent frameworks and RAG strategies show significant promise, practical deployment will require careful integration with human oversight, robust evaluation metrics tailored to medical imaging tasks, and regulatory adaptation to ensure safe clinical use in diverse patient populations and imaging modalities. Full article

(This article belongs to the Special Issue Machine Learning-Driven Innovations in Biomedical Signal and Image Processing)

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16 pages, 3513 KB

Open AccessEditor’s ChoiceReview

Tinkering with Blood: Optimizing the Coagulation System for Therapeutic Purposes

by Eduardo Anitua and Sabino Padilla

Bioengineering 2025, 12(12), 1301; https://doi.org/10.3390/bioengineering12121301 - 26 Nov 2025

Viewed by 904

Abstract

Blood is a multitask, fluid tissue that is considered as an endless goldmine for regenerative therapies. This connective tissue carries myriad multidomain proteins as the workhorse of biological functions integrated in complex molecular networks. Among them, the coagulation system stands out, with platelets [...] Read more.

Blood is a multitask, fluid tissue that is considered as an endless goldmine for regenerative therapies. This connective tissue carries myriad multidomain proteins as the workhorse of biological functions integrated in complex molecular networks. Among them, the coagulation system stands out, with platelets and plasma coagulation proteins playing multiple roles in clotting, defense and tissue repair, the latter of which is the final byproduct process stemming from the hemostatic–inflammatory, cell-reprogramming and inflammation resolution after a tissue injury. By mimicking coagulation and hemostasis but lacking inflammatory properties, platelet-rich plasma (PRP) is emerging as an innovative autologous therapy operating as a local delivery system of growth factors. Processing of the patient blood to manufacture PRP encompasses blood anticoagulation; blood deconstruction through centrifugation and fractionation; and activation of plasma, endowing the applied product with anti-inflammatory, trophic, antifibrotic and antialgic properties in a context-dependent manner. However, the field of PRPs faces controversies due to the heterogeneity of their biological compositions and modalities of application. Moreover, there are some drawbacks derived from patient age and some other conditions, all impinging negatively on PRP clinical outcomes. Standardization of the manufacturing process, elaboration of guidelines of application and use of allogenic PRPs are emerging as possible solutions to surmount these pitfalls. Full article

(This article belongs to the Special Issue Advances in Biomolecular Engineering for Regenerative Therapeutics)

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20 pages, 2950 KB

Open AccessEditor’s ChoiceArticle

The Role of MER Processing Pipelines for STN Functional Identification During DBS Surgery: A Feature-Based Machine Learning Approach

by Vincenzo Levi, Stefania Coelli, Chiara Gorlini, Federica Forzanini, Sara Rinaldo, Nico Golfrè Andreasi, Luigi Romito, Roberto Eleopra and Anna Maria Bianchi

Bioengineering 2025, 12(12), 1300; https://doi.org/10.3390/bioengineering12121300 - 26 Nov 2025

Cited by 1 | Viewed by 649

Abstract

Microelectrode recording (MER) is commonly used to validate preoperative targeting during subthalamic nucleus (STN) deep brain stimulation (DBS) surgery for Parkinson’s Disease (PD). Although machine learning (ML) has been used to improve STN localization using MER data, the impact of preprocessing steps on [...] Read more.

Microelectrode recording (MER) is commonly used to validate preoperative targeting during subthalamic nucleus (STN) deep brain stimulation (DBS) surgery for Parkinson’s Disease (PD). Although machine learning (ML) has been used to improve STN localization using MER data, the impact of preprocessing steps on the accuracy of classifiers has received little attention. We evaluated 24 distinct preprocessing pipelines combining four artifact removal strategies, three outlier handling methods, and optional feature normalization. The effect of each data processing procedure’s component of interest was evaluated in function of the performance obtained using three ML models. Artifact rejection methods (i.e., unsupervised variance-based algorithm (COV) and background noise estimation (BCK)), combined with optimized outlier management (i.e., statistical outlier identification per hemisphere (ORH)) consistently improved classification performance. In contrast, applying hemisphere-specific feature normalization prior to classification led to performance degradation across all metrics. SHAP (SHapley Additive exPlanations) analysis, performed to determine feature importance across pipelines, revealed stable agreement with regard to influential features across diverse preprocessing configurations. In conclusion, optimal artifact rejection and outlier treatment are essential in preprocessing MER for STN identification in DBS, whereas preliminary feature normalization strategies may impair model performance. Overall, the best classification performance was obtained by applying the Random Forest model to the dataset treated using COV artifact rejection and ORH outlier management (accuracy = 0.945). SHAP-based interpretability offers valuable guidance for refining ML pipelines. These insights can inform robust protocol development for MER-guided DBS targeting. Full article

(This article belongs to the Special Issue AI and Data Analysis in Neurological Disease Management)

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19 pages, 7348 KB

Open AccessEditor’s ChoiceArticle

A Novel Approach to Pattern Dermal Papilla Spheroids in Dermal–Epidermal Composites Using Non-Adherent Microwell Arrays

by E. Cate Wisdom, Donald C. Aduba, Jr., Owen Lewis, Sandhya Xavier, Ernest O. N. Phillips, Kristin H. Gilchrist, Ira M. Herman, Vincent B. Ho, Thomas N. Darling and George J. Klarmann

Bioengineering 2025, 12(12), 1281; https://doi.org/10.3390/bioengineering12121281 - 21 Nov 2025

Viewed by 1189

Abstract

Bioengineered dermal–epidermal composites (DECs) have demonstrated promise initiating skin regeneration and hair follicle neogenesis after injury. DECs in our work comprise a collagen matrix embedded with human dermal papilla cells (HDPCs) overlaid with human keratinocytes. HDPCs, as three-dimensional spheroids, enhance hair follicle formation, [...] Read more.

Bioengineered dermal–epidermal composites (DECs) have demonstrated promise initiating skin regeneration and hair follicle neogenesis after injury. DECs in our work comprise a collagen matrix embedded with human dermal papilla cells (HDPCs) overlaid with human keratinocytes. HDPCs, as three-dimensional spheroids, enhance hair follicle formation, working in tandem with keratinocytes. Herein, 3D printed stamped PDMS microwell arrays were used as a strategy for spatially patterning dermal papilla spheroids in the dermal components of the DEC. DECs were transferred to cell culture media for 5 days followed by air–liquid interface culture for 2 days. Spheroid diameter, cell viability, and qPCR gene expression analyses were conducted. DECs were surgically grafted on immunocompromised mice, and healing was followed for 10 weeks. HDPCs cultured in the microwell arrays formed patterned viable spheroids and successfully transferred to the collagen dermal matrix. RNA analysis using qPCR showed upregulation of key HDPC markers (VCAN and BMP6) in DC microwell patterned HDPC spheroids compared to monolayers. This work represents a novel 3D printing strategy optimizing designing patterned HDPC spheroids in the extracellular matrix to regenerate functional human skin instead of scar tissue after injury. Full article

(This article belongs to the Special Issue Advances and Innovations in Wound Repair and Regeneration)

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18 pages, 616 KB

Open AccessEditor’s ChoiceArticle

Does Resistance Indicate Malposition? A Standardized Comparison of Pedicle Screw Placement

by Sascha Kurz, Benjamin Fischer, Janine Schultze, Florian Metzner, Toni Wendler, Christoph-Eckhard Heyde and Stefan Schleifenbaum

Bioengineering 2025, 12(11), 1254; https://doi.org/10.3390/bioengineering12111254 - 16 Nov 2025

Viewed by 691

Abstract

Pedicle screw malpositioning remains a frequent complication, with reported rates from 2% to 15%, often leading to revision surgeries. Analyzing mechanical resistance and torque encountered during screw insertion has been implicated as a promising approach for real-time detection. Five fresh-frozen human thoracolumbar spine [...] Read more.

Pedicle screw malpositioning remains a frequent complication, with reported rates from 2% to 15%, often leading to revision surgeries. Analyzing mechanical resistance and torque encountered during screw insertion has been implicated as a promising approach for real-time detection. Five fresh-frozen human thoracolumbar spine specimens were utilized in this study. Using 3D-printed templates, correct trajectories were systematically compared against four defined malpositions (medial, lateral, superior, superolateral), with offsets ranging from 2.0 mm to 3.5 mm. Drilling, tapping, and insertion phases were conducted at a constant speed and defined feed force. Contrary to the anticipated behavior, malpositioned trajectories showed no statistically significant difference in peak torque compared to correct trajectories across all phases (e.g., tapping

p = 0.944

,

r = 0.01

; insertion

p = 0.693

,

r = 0.05

). Regional stratification between thoracic and lumbar spine also failed to yield significant differences. The only statistically significant difference was observed between the correct trajectory and the superolateral malposition during drilling (

p = 0.038

). Under the tested standardized conditions, torque-based mechanical resistance during pedicle screw placement is generally not a reliable and consistent real-time indicator of malposition. Full article

(This article belongs to the Special Issue Spine Biomechanics)

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32 pages, 31629 KB

Open AccessEditor’s ChoiceArticle

Aspects Concerning Parallel Robots Used in Rehabilitation

by Adrian Todor, Daniel Vasile Banyai, Cornel Brisan and Adriana Daniela Banyai

Bioengineering 2025, 12(11), 1224; https://doi.org/10.3390/bioengineering12111224 - 9 Nov 2025

Cited by 1 | Viewed by 598

Abstract

This study presents a comprehensive simulation-based comparative analysis of four parallel robotic mechanisms, each developed to assist patient recovery through adaptive movement control and feedback, particularly for upper and lower limb therapy. Kinematic and dynamic models were developed and implemented in Matlab-Simulink, integrating [...] Read more.

This study presents a comprehensive simulation-based comparative analysis of four parallel robotic mechanisms, each developed to assist patient recovery through adaptive movement control and feedback, particularly for upper and lower limb therapy. Kinematic and dynamic models were developed and implemented in Matlab-Simulink, integrating force control via conventional regulators and real-time interaction with simulated patient-applied forces. The structural differences between spherical, rotational, and universal joints in each kinematic chain variant were evaluated. To systematically determine the most suitable design, a detailed Analytic Hierarchy Process was applied considering performance, precision, stability, and actuator effort. The study emphasizes the advantages of parallel robots in rehabilitation due to their precision, rigidity, and compact design, highlighting the potential of parallel robotic systems in customized and adaptive physical therapy interventions. These insights contribute to the optimal design selection of clinical motor therapy robots. Full article

(This article belongs to the Section Biomechanics and Sports Medicine)

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27 pages, 3246 KB

Open AccessEditor’s ChoiceReview

Biochar for Soil Amendment: Applications, Benefits, and Environmental Impacts

by Ujjwal Pokharel, Gururaj Neelgund, Ram L. Ray, Venkatesh Balan and Sandeep Kumar

Bioengineering 2025, 12(11), 1137; https://doi.org/10.3390/bioengineering12111137 - 22 Oct 2025

Cited by 3 | Viewed by 6083

Abstract

The excessive use of chemical fertilizers results in environmental issues, including loss of soil fertility, eutrophication, increased soil acidity, alterations in soil characteristics, and disrupted plant–microbe symbiosis. Here, we synthesize recent studies available from up to 2025, focusing on engineered biochar and its [...] Read more.

The excessive use of chemical fertilizers results in environmental issues, including loss of soil fertility, eutrophication, increased soil acidity, alterations in soil characteristics, and disrupted plant–microbe symbiosis. Here, we synthesize recent studies available from up to 2025, focusing on engineered biochar and its application in addressing issues of soil nutrient imbalance, soil pollution from inorganic and organic pollutants, soil acidification, salinity, and greenhouse gas emissions from fields. Application of engineered biochar enhanced the removal of Cr (VI), Cd²⁺, Ni²⁺, Zn²⁺, Hg²⁺, and Eu³⁺ by 85%, 73%, 57.2%, 12.7%, 99.3%, and 99.2%, respectively, while Cu²⁺ and V⁵⁺ removal increased by 4 and 39.9 times. Adsorption capacities for Sb⁵⁺, Tl⁺, and F⁻ were 237.53, 1123, and 83.05 mg g⁻¹, respectively, and the optimal proportion of polycyclic aromatic hydrocarbon (PAH) removal was 57%. Herbicides such as imazapyr were reduced by 23% and 78%. Low-temperature pyrolyzed biochar showed high cation exchange capacity (CEC) resulting from improved surface functional groups. Although biochar application led to a yield increase of 43.3%, the biochar–compost mix enhanced it by 155%. The analysis demonstrates the need for future studies on the cost-effectiveness of biochar post-processing, large-scale biochar aging studies, re-application impact, and studies on biochar–compost or biochar–fertilizer mix productivity. Full article

(This article belongs to the Section Biochemical Engineering)

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17 pages, 1190 KB

Open AccessEditor’s ChoiceArticle

The Effects of Neuromuscular Training on Electromyography, Lower Extremity Kinematics, and Ground Reaction Force During an Unanticipated Side-Cut on Recreational Female Hockey Players

by Tom Johnston, Stephanie Valentin, Susan J. Brown and Konstantinos Kaliarntas

Bioengineering 2025, 12(10), 1101; https://doi.org/10.3390/bioengineering12101101 - 13 Oct 2025

Viewed by 1827

Abstract

During an unpredictable side-cut, this study examined how a sport-specific neuromuscular training program (NMTP) influenced electromyography responses in the lower limb posterior muscles, leg movement angles, maximum vertical ground reaction force (vGRF), and the rate of force development of vGRF. Thirty-eight adult female [...] Read more.

During an unpredictable side-cut, this study examined how a sport-specific neuromuscular training program (NMTP) influenced electromyography responses in the lower limb posterior muscles, leg movement angles, maximum vertical ground reaction force (vGRF), and the rate of force development of vGRF. Thirty-eight adult female recreational hockey players were randomly allocated into an intervention group (INT) or a control group (CON). Before beginning training or matches, the INT carried out the NMTP three times per week for eight weeks, whereas the CON performed their routine warm-up. A 45° sidecut (dominant leg only) was performed at baseline and after eight-weeks and recorded with a motion capture system. The effect of group and time, and their interaction, was investigated using a mixed-design ANOVA. After landing, the participants in the INT had greater activation of their gastrocnemius lateralis, gastrocnemius medialis, and gluteus maximus muscles than those in the CON. INT participants showed significantly lower amounts of maximum knee abduction and knee excursion, while there was an increase in these variables for the CON. At week eight, the vGRF RFD decreased for the INT but increased for the CON. Although non-significant, the overall muscle activity showed an increasing trend for the INT when it came to supervised NMTP for eight weeks compared to the effect seen in the CON. This activity caused greater alterations in the motion and forces of the lower body for the INT than the CON. Full article

(This article belongs to the Special Issue Dynamic Insights: Unveiling the Biomechanics of Sport Through Motion Analysis)

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31 pages, 1305 KB

Open AccessEditor’s ChoiceReview

Artificial Intelligence in Cardiac Electrophysiology: A Clinically Oriented Review with Engineering Primers

by Giovanni Canino, Assunta Di Costanzo, Nadia Salerno, Isabella Leo, Mario Cannataro, Pietro Hiram Guzzi, Pierangelo Veltri, Sabato Sorrentino, Salvatore De Rosa and Daniele Torella

Bioengineering 2025, 12(10), 1102; https://doi.org/10.3390/bioengineering12101102 - 13 Oct 2025

Cited by 3 | Viewed by 5754

Abstract

Artificial intelligence (AI) is transforming cardiac electrophysiology across the entire care pathway, from arrhythmia detection on 12-lead electrocardiograms (ECGs) and wearables to the guidance of catheter ablation procedures, through to outcome prediction and therapeutic personalization. End-to-end deep learning (DL) models have achieved cardiologist-level [...] Read more.

Artificial intelligence (AI) is transforming cardiac electrophysiology across the entire care pathway, from arrhythmia detection on 12-lead electrocardiograms (ECGs) and wearables to the guidance of catheter ablation procedures, through to outcome prediction and therapeutic personalization. End-to-end deep learning (DL) models have achieved cardiologist-level performance in rhythm classification and prognostic estimation on standard ECGs, with a reported arrhythmia classification accuracy of ≥95% and an atrial fibrillation detection sensitivity/specificity of ≥96%. The application of AI to wearable devices enables population-scale screening and digital triage pathways. In the electrophysiology (EP) laboratory, AI standardizes the interpretation of intracardiac electrograms (EGMs) and supports target selection, and machine learning (ML)-guided strategies have improved ablation outcomes. In patients with cardiac implantable electronic devices (CIEDs), remote monitoring feeds multiparametric models capable of anticipating heart-failure decompensation and arrhythmic risk. This review outlines the principal modeling paradigms of supervised learning (regression models, support vector machines, neural networks, and random forests) and unsupervised learning (clustering, dimensionality reduction, association rule learning) and examines emerging technologies in electrophysiology (digital twins, physics-informed neural networks, DL for imaging, graph neural networks, and on-device AI). However, major challenges remain for clinical translation, including an external validation rate below 30% and workflow integration below 20%, which represent core obstacles to real-world adoption. A joint clinical engineering roadmap is essential to translate prototypes into reliable, bedside tools. Full article

(This article belongs to the Special Issue Mathematical Models for Medical Diagnosis and Testing)

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12 pages, 1349 KB

Open AccessEditor’s ChoiceArticle

Effect of the Ankle–Foot Orthosis Dorsiflexion Angle on Gait Kinematics in Individuals with Hemiparetic Stroke

by Hiroshi Hosokawa, Fumiaki Tamiya, Ren Fujii, Ryu Ishimoto, Masahiko Mukaino and Yohei Otaka

Bioengineering 2025, 12(10), 1091; https://doi.org/10.3390/bioengineering12101091 - 10 Oct 2025

Viewed by 2494

Abstract

Ankle-foot orthoses (AFOs) are widely used to improve gait; nonetheless, it remains unclear how specific settings, particularly the dorsiflexion angle, affect gait kinematics in individuals with stroke. This study investigated the effect of different AFO dorsiflexion angles on gait kinematics in ambulatory adults [...] Read more.

Ankle-foot orthoses (AFOs) are widely used to improve gait; nonetheless, it remains unclear how specific settings, particularly the dorsiflexion angle, affect gait kinematics in individuals with stroke. This study investigated the effect of different AFO dorsiflexion angles on gait kinematics in ambulatory adults with hemiparesis. Twenty-six individuals with post-stroke hemiparesis walked on a treadmill while wearing the same type of AFO at four ankle dorsiflexion angles: 0°, 5°, 10°, and 15°. Temporal-spatial variables, joint angles, and toe clearance and its components were quantified using three-dimensional analysis. The double-stance time before the paretic swing shortened significantly with increasing dorsiflexion angle, whereas the mean stride time and length did not significantly change. During the swing phase, increased AFO dorsiflexion was associated with reduced maximal knee flexion, in addition to its direct effect on ankle angles. The absolute toe clearance height was unaffected by the AFO settings; however, the contribution of ankle dorsiflexion to limb shortening increased stepwise from 0° to 15°, and the hip elevation and compensatory movement ratio declined. In conclusion, increasing the AFO dorsiflexion angle significantly altered gait kinematics, with distal ankle mechanics replacing inefficient hip compensation and reducing double-stance time. Full article

(This article belongs to the Section Biomechanics and Sports Medicine)

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17 pages, 1144 KB

Open AccessEditor’s ChoiceArticle

Modelling of Escherichia coli Batch and Fed-Batch Processes in Semi-Defined Yeast Extract Media

by Fabian Schröder-Kleeberg, Markus Zoellkau, Markus Glaser, Christian Bosch, Markus Brunner, Mariano Nicolas Cruz Bournazou and Peter Neubauer

Bioengineering 2025, 12(10), 1081; https://doi.org/10.3390/bioengineering12101081 - 4 Oct 2025

Viewed by 1940

Abstract

Model-based approaches provide increasingly advanced opportunities for optimizing and accelerating bioprocess development. However, to accurately capture the complexity of biotechnological processes, continuous refinement of suitable models remains essential. A crucial gap in this field has been the lack of suitable model for describing [...] Read more.

Model-based approaches provide increasingly advanced opportunities for optimizing and accelerating bioprocess development. However, to accurately capture the complexity of biotechnological processes, continuous refinement of suitable models remains essential. A crucial gap in this field has been the lack of suitable model for describing Escherichia coli growth in cultivation media containing yeast extract, while accounting for key bioprocess parameters such as biomass, substrate, acetate, and oxygen. To address this, a published mechanistic macro-kinetic model for E. coli was extended with a set of mathematical equations that describe key aspects of the uptake of yeast extract. The underlying macro-kinetic approach is based on the utilization of amino acids in E. coli, where growth is primarily influenced by two distinct classes of amino acids. Using fed-batch cultivation data from an E. coli K-12 strain supplemented with yeast extract, it was demonstrated that the proposed model extensions were essential for accurately representing the bioprocess. This approach was further validated through fitting the model on cultivation data from five different yeast extracts sourced from various manufacturers. Additionally, the model enabled reliable predictions of growth dynamics across a range of yeast extract concentrations up to 20 g L⁻¹. Further differentiation of the data into batch and fed-batch revealed that for less complex datasets, such as those obtained from a batch phase, a simplified model can be sufficient. Due to its modular structure, the developed model provides the necessary flexibility to serve as a tool for the development, optimization, and control of E. coli cultivations with and without yeast extract. Full article

(This article belongs to the Section Biochemical Engineering)

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20 pages, 1488 KB

Open AccessEditor’s ChoiceArticle

Attention-Fusion-Based Two-Stream Vision Transformer for Heart Sound Classification

by Kalpeshkumar Ranipa, Wei-Ping Zhu and M. N. S. Swamy

Bioengineering 2025, 12(10), 1033; https://doi.org/10.3390/bioengineering12101033 - 26 Sep 2025

Cited by 2 | Viewed by 1121

Abstract

Vision Transformers (ViTs), inspired by their success in natural language processing, have recently gained attention for heart sound classification (HSC). However, most of the existing studies on HSC rely on single-stream architectures, overlooking the advantages of multi-resolution features. While multi-stream architectures employing early [...] Read more.

Vision Transformers (ViTs), inspired by their success in natural language processing, have recently gained attention for heart sound classification (HSC). However, most of the existing studies on HSC rely on single-stream architectures, overlooking the advantages of multi-resolution features. While multi-stream architectures employing early or late fusion strategies have been proposed, they often fall short of effectively capturing cross-modal feature interactions. Additionally, conventional fusion methods, such as concatenation, averaging, or max pooling, frequently result in information loss. To address these limitations, this paper presents a novel attention fusion-based two-stream Vision Transformer (AFTViT) architecture for HSC that leverages two-dimensional mel-cepstral domain features. The proposed method employs a ViT-based encoder to capture long-range dependencies and diverse contextual information at multiple scales. A novel attention block is then used to integrate cross-context features at the feature level, enhancing the overall feature representation. Experiments conducted on the PhysioNet2016 and PhysioNet2022 datasets demonstrate that the AFTViT outperforms state-of-the-art CNN-based methods in terms of accuracy. These results highlight the potential of the AFTViT framework for early diagnosis of cardiovascular diseases, offering a valuable tool for cardiologists and researchers in developing advanced HSC techniques. Full article

(This article belongs to the Section Biosignal Processing)

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21 pages, 1795 KB

Open AccessEditor’s ChoiceReview

Nanoparticle-Based Delivery Systems for Synergistic Therapy in Lung Cancers

by Zicheng Deng, Ali Al Siraj, Isabella Lowry, Ellen Ruan, Rohan Patel, Wen Gao, Tanya V. Kalin and Vladimir V. Kalinichenko

Bioengineering 2025, 12(9), 968; https://doi.org/10.3390/bioengineering12090968 - 9 Sep 2025

Cited by 5 | Viewed by 2993

Abstract

Lung cancer remains the leading cause of cancer-related mortality worldwide, with conventional treatments often limited by systemic toxicity, different tumor sensitivity to the drugs, and the emergence of multidrug resistance. To address these challenges, nanoparticle-based delivery systems have emerged as an innovative strategy, [...] Read more.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with conventional treatments often limited by systemic toxicity, different tumor sensitivity to the drugs, and the emergence of multidrug resistance. To address these challenges, nanoparticle-based delivery systems have emerged as an innovative strategy, enabling the simultaneous transport of multiple agents, including chemotherapeutic drugs and expression vectors, to enhance treatment efficacy and overcome tumor resistance. This review explores various nanocarrier platforms, such as liposomes, solid lipid nanoparticles, polymeric micelles, and inorganic nanoparticles, specifically designed for lung cancer therapy. Synergistic effects and physicochemical properties of therapeutic agents must be carefully considered in the design of nanoparticle-based co-delivery systems for lung cancer therapy. We highlight the applications of these nanoparticle systems in drug–drug, gene–gene, and drug–gene co-delivery approaches. By addressing the limitations of traditional therapies, nanoparticle-based systems offer a promising avenue to improve outcomes in patients with lung cancers. Full article

(This article belongs to the Section Nanobiotechnology and Biofabrication)

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14 pages, 752 KB

Open AccessEditor’s ChoiceArticle

High-Precision Multi-Axis Robotic Printing: Optimized Workflow for Complex Tissue Creation

by Erfan Shojaei Barjuei, Joonhwan Shin, Keekyoung Kim and Jihyun Lee

Bioengineering 2025, 12(9), 949; https://doi.org/10.3390/bioengineering12090949 - 31 Aug 2025

Cited by 2 | Viewed by 1703

Abstract

Three-dimensional bioprinting holds great promise for tissue engineering, but struggles with fabricating complex curved geometries such as vascular networks. Though precise, traditional Cartesian bioprinters are constrained by linear layer-by-layer deposition along fixed axes, resulting in limitations such as the stair-step effect. Multi-axis robotic [...] Read more.

Three-dimensional bioprinting holds great promise for tissue engineering, but struggles with fabricating complex curved geometries such as vascular networks. Though precise, traditional Cartesian bioprinters are constrained by linear layer-by-layer deposition along fixed axes, resulting in limitations such as the stair-step effect. Multi-axis robotic bioprinting addresses these challenges by allowing dynamic nozzle orientation and motion along curvilinear paths, enabling conformal printing on anatomically relevant surfaces. Although robotic arms offer lower mechanical precision than CNC stages, accuracy can be enhanced through methods such as vision-based toolpath correction. This study presents a modular multi-axis robotic embedded bioprinting platform that integrates a six-degrees-of-freedom robotic arm, a pneumatic extrusion system, and a viscoplastic support bath. A streamlined workflow combines CAD modeling, CAM slicing, robotic simulation, and automated execution for efficient fabrication. Two case studies validate the system’s ability to print freeform surfaces and vascular-inspired tubular constructs with high fidelity. The results highlight the platform’s versatility and potential for complex tissue fabrication and future in situ bioprinting applications. Full article

(This article belongs to the Special Issue Insights in Tissue Engineering: Novel Developments, Current Challenges, and Future Perspectives)

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36 pages, 4960 KB

Open AccessEditor’s ChoiceSystematic Review

The Effects of Rehabilitation Programs Incorporating Breathing Interventions on Chronic Neck Pain Among Patients with Forward Head Posture: A Systematic Review and Meta-Analysis

by Seri Park, Kihyun Kim and Minbong Kang

Bioengineering 2025, 12(9), 947; https://doi.org/10.3390/bioengineering12090947 - 31 Aug 2025

Viewed by 6477

Abstract

The effectiveness of breathing interventions on postural alignment, pain reduction, and functional improvement in patients with forward head posture (FHP) and chronic neck pain remains uncertain. Previously conducted randomized controlled trials (RCTs) that involved breathing interventions were identified through searches of the PubMed, [...] Read more.

The effectiveness of breathing interventions on postural alignment, pain reduction, and functional improvement in patients with forward head posture (FHP) and chronic neck pain remains uncertain. Previously conducted randomized controlled trials (RCTs) that involved breathing interventions were identified through searches of the PubMed, Cochrane Library, Web of Science, and Scopus databases. Studies were included if they applied diaphragmatic breathing, breathing muscle training, or feedback breathing exercises for at least 2 weeks to chronic neck pain (duration ≥ 3 months) and/or forward head posture. The craniovertebral angle (CVA), the visual analog scale (VAS), and the neck disability index (NDI) were the primary outcome measures. The results showed that breathing interventions had a moderate effect size in terms of improving the CVA. Limited effects were observed for pain reduction, and improvements in neck disability approached statistical significance. However, despite these positive findings, the overall evidence was rated as ‘very low certainty’ in the GRADE assessment, primarily due to high heterogeneity among studies, limited sample sizes, and the potential for unit-of-analysis errors in diagnosis-based subgroup analyses. Consequently, their overall effectiveness in chronic neck pain was limited. Future research is needed to explore a multidisciplinary approach to neck pain using standardized protocols and larger samples. Full article

(This article belongs to the Special Issue Physical Therapy and Rehabilitation)

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52 pages, 44108 KB

Open AccessEditor’s ChoiceArticle

Experimental Validation of Time-Explicit Ultrasound Propagation Models with Sound Diffusivity or Viscous Attenuation in Biological Tissues Using COMSOL Multiphysics

by Nuno A. T. C. Fernandes, Shivam Sharma, Ana Arieira, Betina Hinckel, Filipe Silva, Ana Leal and Óscar Carvalho

Bioengineering 2025, 12(9), 946; https://doi.org/10.3390/bioengineering12090946 - 31 Aug 2025

Cited by 7 | Viewed by 4054

Abstract

Ultrasonic wave attenuation in biological tissues arises from complex interactions between mechanical, structural, and fluidic properties, making it essential to identify dominant mechanisms for accurate simulation and device design. This work introduces a novel integration of experimentally measured tissue parameters into time-explicit nonlinear [...] Read more.

Ultrasonic wave attenuation in biological tissues arises from complex interactions between mechanical, structural, and fluidic properties, making it essential to identify dominant mechanisms for accurate simulation and device design. This work introduces a novel integration of experimentally measured tissue parameters into time-explicit nonlinear acoustic wave simulations, in which the equations are directly solved in the time domain using an explicit solver. This approach captures the full transient waveform without relying on frequency-domain simplifications, offering a more realistic representation of ultrasound propagation in heterogeneous media. The study estimates both sound diffusivity and viscous damping parameters (dynamic and bulk viscosity) for a broad range of ex vivo tissues (skin, adipose tissue, skeletal muscle, trabecular/cortical bone, liver, myocardium, kidney, tendon, ligament, cartilage, and gray/white brain matter). Four regression models (power law, linear, exponential, logarithmic) were applied to characterize their frequency dependence between 0.5 and 5 MHz. Results show that attenuation is more strongly driven by bulk viscosity than dynamic viscosity, particularly in fluid-rich tissues such as liver and myocardium, where compressional damping dominates. The power-law model consistently provided the best fit for all attenuation metrics, revealing a scale-invariant frequency relationship. Tissues such as cartilage and brain showed weaker viscous responses, suggesting the need for alternative modeling approaches. These findings not only advance fundamental understanding of attenuation mechanisms but also provide validated parameters and modeling strategies to improve predictive accuracy in therapeutic ultrasound planning and the design of non-invasive, tissue-specific acoustic devices. Full article

(This article belongs to the Special Issue Recent Advances in the Application of Mathematical and Computational Models in Biomedical Science and Engineering (2nd Edition))

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16 pages, 1173 KB

Open AccessEditor’s ChoiceReview

by Ezra T. Yoseph, Rukayat Taiwo, Ali Kiapour, Gavin Touponse, Elie Massaad, Marinos Theologitis, Janet Y. Wu, Theresa Williamson and Corinna C. Zygourakis

Bioengineering 2025, 12(8), 858; https://doi.org/10.3390/bioengineering12080858 - 10 Aug 2025

Cited by 3 | Viewed by 7200

Abstract

Pregnancy induces substantial anatomical, hormonal, and biomechanical changes in the spine and pelvis to accommodate fetal growth and maintain postural adaptation. This narrative review synthesizes peer-reviewed evidence regarding pregnancy-related spinal biomechanics, with a particular focus on low back pain, spinopelvic alignment, sacroiliac joint [...] Read more.

Pregnancy induces substantial anatomical, hormonal, and biomechanical changes in the spine and pelvis to accommodate fetal growth and maintain postural adaptation. This narrative review synthesizes peer-reviewed evidence regarding pregnancy-related spinal biomechanics, with a particular focus on low back pain, spinopelvic alignment, sacroiliac joint dysfunction, and potential contributions to degenerative spinal conditions. A systematic search of PubMed, Embase, and Google Scholar was conducted using Boolean operators and relevant terms, yielding 1050 unique records, with 53 peer-reviewed articles ultimately cited. The review reveals that increased lumbar lordosis, ligamentous laxity, altered gait mechanics, and muscular deconditioning elevate mechanical load on the lumbar spine, predisposing up to 56% of pregnant individuals to low back pain. These changes are often associated with sacroiliac joint laxity, anterior pelvic tilt, and multiparity. Long-term risks may include degenerative disc disease and spondylolisthesis. Conservative interventions such as pelvic floor muscle training, prenatal exercise, and surface topography monitoring offer symptom relief and support early rehabilitation, although standardized protocols and longitudinal outcome data remain limited. Pregnancy-related spinal changes are multifactorial and clinically relevant; an interdisciplinary approach involving spinal biomechanics, physical therapy, and obstetric care is critical for optimizing maternal musculoskeletal health. Full article

(This article belongs to the Special Issue Spine Biomechanics)

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13 pages, 2210 KB

Open AccessEditor’s ChoiceArticle

The Use of Therapeutic Peptides in Combination with Full-Thickness Skin Columns to Improve Healing of Excisional Wounds

by Anders H. Carlsson, Ira M. Herman, Sean Christy, David Larson, Rodney K. Chan, Thomas N. Darling and Kristo Nuutila

Bioengineering 2025, 12(8), 856; https://doi.org/10.3390/bioengineering12080856 - 9 Aug 2025

Cited by 1 | Viewed by 1749

Abstract

Split-thickness skin grafting (STSG) is the standard of care for skin replacement therapy. While STSG is a well-established technique, it has several limitations at both the donor and recipient sites. Full-thickness skin column (FTSC) grafting is an alternative approach that involves the orthogonal [...] Read more.

Split-thickness skin grafting (STSG) is the standard of care for skin replacement therapy. While STSG is a well-established technique, it has several limitations at both the donor and recipient sites. Full-thickness skin column (FTSC) grafting is an alternative approach that involves the orthogonal harvesting of small skin columns containing the epidermis, dermis, and associated skin appendages. Peptides have been shown to promote wound repair through various reparative and regenerative mechanisms. In this study, we aimed to evaluate the extent to which FTSCs and the matrix-derived peptide TSN6, individually or in combination, influenced the rate and quality of healing, as assessed by metrics such as epithelialization, epithelial thickness, and the presence of adnexal structures. TSN6 peptide and its scrambled form was synthetized in a laboratory and mixed with a carboxymethylcellulose (CMC) hydrogel. Up to 16 standardized full-thickness excisional wounds (∅ 5 cm) were created on the dorsum of two anesthetized pigs. FTSC biopsies (∅ 1.5 mm) were harvested from donor sites located on the rump of the pig at a ratio of up to eight 1.5 mm-diameter skin columns/1 cm². Subsequently, the wounds were randomized to receive either (1) FTSC + TSN6, (2) FTSC + scrambled peptide, (3) FTSC alone, and (4) blank CMC hydrogel. Healing was monitored for 14 or 28 days. After euthanasia, the wounds were excised and processed for histology. Additionally, non-invasive imaging systems were utilized to assess wound healing. By day 14, wounds treated with FTSC or FTSC + TSN6 were significantly more re-epithelialized compared to those treated with blank CMC hydrogel. By day 28, all FTSC-transplanted wounds were fully re-epithelialized. Notably, wounds treated with FTSC + TSN6 exhibited improved healing quality, characterized by a thicker neo-epidermis and increased rete ridges at day 28 post-transplantation. All FTSC-transplanted wounds healed better than the untransplanted controls. The TSN6 peptide further improved healing quality when applied in combination with FTSCs, particularly by enhancing epidermal maturation. Full article

(This article belongs to the Special Issue Advanced Techniques and Applications in Burn Reconstruction: A Bioengineering Perspective)

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18 pages, 2593 KB

Open AccessEditor’s ChoiceArticle

Accuracy of Drill Sleeve Housing in 3D-Printed and Milled Implant Surgical Guides: A 3D Analysis Considering Machine Type, Layer Thickness, Sleeve Position, and Steam Sterilization

by Anna Seidel, Kai Zerrahn, Manfred Wichmann and Ragai Edward Matta

Bioengineering 2025, 12(8), 799; https://doi.org/10.3390/bioengineering12080799 - 25 Jul 2025

Cited by 2 | Viewed by 1596

Abstract

Successful dental implant therapy relies on accurate planning and placement, e.g., through static, computer-aided implant surgery using CAD/CAM-fabricated surgical guides. This study examined production methods’ influence on surgical guide sleeve housing geometry. A model with two edentulous spaces was digitized using intraoral scanning [...] Read more.

Successful dental implant therapy relies on accurate planning and placement, e.g., through static, computer-aided implant surgery using CAD/CAM-fabricated surgical guides. This study examined production methods’ influence on surgical guide sleeve housing geometry. A model with two edentulous spaces was digitized using intraoral scanning and CBCT, and two virtually positioned implants were planned. Ten guides per group were produced using milling (MCX5), DLP printing (ASIGA and SHERA), and SLA printing (FORM), printing with 50 µm and 100 µm layers each. Each guide (n = 70) was then digitized using an industrial scanner before and after sterilization. Superimposition of the actual guide data with the reference data allowed for evaluation of deviations at the drill sleeve housing along the x-, y-, z-, and dxyz-axes. Descriptive and statistical evaluation was performed (significance level: p ≤ 0.0125). Significant differences existed among the production methods: Milling and SLA showed higher deviations than the DLP group (p < 0.001). Milled guides post-sterilization showed the highest deviations (0.352 ± 0.08 mm), while one DLP printer at 50 μm layer thickness showed lowest deviations (0.091 ± 0.04 mm). The layer thickness was insignificant, whereas sterilization increased deviation (p < 0.001). DLP produced the most precise implant surgical guides. All 3D printers were suitable for fabricating clinically acceptable surgical guides. Full article

(This article belongs to the Special Issue Advances in Additive Manufacturing Technologies in the Clinical, Pharmaceutical and Biomedical Sectors)

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12 pages, 1338 KB

Open AccessEditor’s ChoiceReview

Most Custom Oral Appliances for Obstructive Sleep Apnea Do Not Meet the Definition of Custom

by Leonard A. Liptak, Erin Mosca, Edward Sall, Shouresh Charkhandeh, Sung Kim and John E. Remmers

Bioengineering 2025, 12(8), 798; https://doi.org/10.3390/bioengineering12080798 - 25 Jul 2025

Cited by 1 | Viewed by 3885

Abstract

Obstructive sleep apnea is a highly prevalent respiratory disease linked to increased morbidity and mortality, a reduced quality of life, and increased economic costs if not treated. Oral appliances are an emerging treatment option for obstructive sleep apnea. This review concluded that many [...] Read more.

Obstructive sleep apnea is a highly prevalent respiratory disease linked to increased morbidity and mortality, a reduced quality of life, and increased economic costs if not treated. Oral appliances are an emerging treatment option for obstructive sleep apnea. This review concluded that many oral appliances marketed as “custom” include modifications and prefabricated items, and therefore do not meet the definition of “custom” oral appliances. This misclassification could hinder the accurate characterization, evaluation, and appropriate prescription of oral appliances. To better inform the clinical utilization of custom oral appliances and to more closely align sleep medicine with the benefits of personalized medicine, we propose that the custom oral appliance classification be further refined into semi-custom and precision-custom categories. Full article

(This article belongs to the Section Biomedical Engineering and Biomaterials)

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11 pages, 584 KB

Open AccessEditor’s ChoiceSystematic Review

Artificial Intelligence for Non-Invasive Prediction of Molecular Signatures in Spinal Metastases: A Systematic Review

by Vivek Sanker, Sai Sanikommu, Alexander Thaller, Zhikai Li, Philip Heesen, Srinath Hariharan, Emil O. R. Nordin, Maria Jose Cavagnaro, John Ratliff and Atman Desai

Bioengineering 2025, 12(8), 791; https://doi.org/10.3390/bioengineering12080791 - 23 Jul 2025

Cited by 2 | Viewed by 1041

Abstract

Background: Spinal metastases (SMs) are associated with poor prognosis and significant morbidity. We hypothesize that artificial intelligence (AI) models can enhance the identification and clinical utility of genetic and molecular signatures associated with SMs, improving diagnostic accuracy and enabling personalized treatment strategies. Methods: [...] Read more.

Background: Spinal metastases (SMs) are associated with poor prognosis and significant morbidity. We hypothesize that artificial intelligence (AI) models can enhance the identification and clinical utility of genetic and molecular signatures associated with SMs, improving diagnostic accuracy and enabling personalized treatment strategies. Methods: A systematic review of five databases was conducted to identify studies that used AI to predict genetic alterations and SMs outcomes. Accuracy, area under the receiver operating curve (AUC), and sensitivity were used for comparison. Data analysis was performed in R. Results: Eleven studies met the inclusion criteria, covering three different primary tumor origins, comprising a total of 2211 patients with an average of 201 ± 90 patients (range: 76–359 patients) per study. EGFR, Ki-67, and HER-2 were studied in ten (90.9%), two (18.1%), and one (9.1%) study, respectively. The weighted average AUC is 0.849 (95% CI: 0.835–0.863) and 0.791 (95% CI: 0.738–0.844) for internal and external validation of the established models, respectively. Conclusions: AI, through radiomics and machine learning, shows strong potential in predicting molecular markers in SMs. Our study demonstrates that AI can predict molecular markers in SMs with high accuracy. Full article

(This article belongs to the Section Biosignal Processing)

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19 pages, 259 KB

Open AccessEditor’s ChoiceArticle

Understanding the Impact of Assistive Technology on Users’ Lives in England: A Capability Approach

by Rebecca Joskow, Dilisha Patel, Anna Landre, Kate Mattick, Catherine Holloway, Jamie Danemayer and Victoria Austin

Bioengineering 2025, 12(7), 750; https://doi.org/10.3390/bioengineering12070750 - 9 Jul 2025

Cited by 5 | Viewed by 2986

Abstract

This study presents an analysis of England’s 2023 national assessment of assistive technology (AT) access and use, with a particular focus on the qualitative impact of AT as described by users. It aims to address limitations in conventional AT impact assessments, which often [...] Read more.

This study presents an analysis of England’s 2023 national assessment of assistive technology (AT) access and use, with a particular focus on the qualitative impact of AT as described by users. It aims to address limitations in conventional AT impact assessments, which often prioritize clinical outcomes or user satisfaction, by offering a deeper account of how impact is experienced in everyday life. Drawing on data from a nationally representative survey of 7000 disabled adults and children, as well as six focus group discussions and 28 semi-structured interviews with stakeholders across the WHO 5Ps framework (People, Providers, Personnel, Policy, and Products), the study applies Amartya Sen and Martha Nussbaum’s Capability Approach to explore these experiences. Using inductive thematic analysis, we identify three main domains of user-reported impact: Functions and Activities (e.g., mobility, communication, vision, leisure, daily routines, and cognitive support), Outcomes (e.g., autonomy, quality of life, safety, social participation, wellbeing, and work and learning), and Lived Experience (e.g., access barriers, essentiality, identity and emotional connection, peace of mind, and sense of control and confidence). These findings offer a more user-centered understanding of AT impact and can inform the development of future measurement tools, research design, and government-led interventions to improve AT provision. Full article

(This article belongs to the Special Issue Measuring Outcomes and Impact Related to Assistive Technology and Accessibility for Disability)

11 pages, 2829 KB

Open AccessEditor’s ChoiceArticle

Biomimetic Full-Thickness Artificial Skin Using Stromal Vascular Fraction Cells and Autologous Keratinocytes in a Single Scaffold for Wound Healing

by Jung Huh, Seong-Ho Jeong, Eun-Sang Dhong, Seung-Kyu Han and Kyung-Chul Moon

Bioengineering 2025, 12(7), 736; https://doi.org/10.3390/bioengineering12070736 - 5 Jul 2025

Viewed by 1524

Abstract

We developed biomimetic full-thickness artificial skin using stromal vascular fraction (SVF) cells and autologous keratinocytes for the dermal and epidermal layers of skin, respectively. Full-thickness artificial skin scaffolds were fabricated using 4% porcine collagen and/or elastin in a low-temperature three-dimensional printer. Two types [...] Read more.

We developed biomimetic full-thickness artificial skin using stromal vascular fraction (SVF) cells and autologous keratinocytes for the dermal and epidermal layers of skin, respectively. Full-thickness artificial skin scaffolds were fabricated using 4% porcine collagen and/or elastin in a low-temperature three-dimensional printer. Two types of scaffolds with collagen-to-elastin ratios of 100:0 and 100:4 were printed and compared. The scaffolds were analyzed for collagenase degradation, tensile strength, and structural features using scanning electron microscopy. By 24 h, the collagen-only scaffolds showed gradual degradation, and the collagen-elastin scaffolds retained the highest structural integrity but were not degraded. In the tensile strength tests, the collagen-only scaffolds exhibited a tensile strength of 2.2 N, while the collagen-elastin scaffolds showed a tensile strength of 4.2 N. Cell viability tests for keratinocytes displayed an initial viability of 89.32 ± 3.01% on day 1, which gradually increased to 97.22 ± 4.99% by day 7. Similarly, SVF cells exhibited a viability of 93.68 ± 1.82% on day 1, which slightly improved to 97.12 ± 1.64% on day 7. This study presents a novel strategy for full-thickness artificial skin development, combining SVF and keratinocytes with an optimized single collagen scaffold and a gradient pore-density structure. Full article

(This article belongs to the Special Issue Advances and Innovations in Wound Repair and Regeneration)

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12 pages, 1893 KB

Open AccessEditor’s ChoiceArticle

Solid-State Anaerobic Digestion of Organic Solid Poultry Waste for Biomethane Production

by Faryal Fatima and Raghava R. Kommalapati

Bioengineering 2025, 12(7), 712; https://doi.org/10.3390/bioengineering12070712 - 29 Jun 2025

Cited by 1 | Viewed by 1793

Abstract

This study examines biodegradability (BD) and optimum conditions for the solid-state anaerobic digestion (SS-AD) of organic solid poultry waste (organs, intestines, offal, and unprocessed meat) to maximize biomethane production. Three main parameters, substrate-to-inoculum (S/I) ratio, pH, and temperature, were evaluated for the SS-AD [...] Read more.

This study examines biodegradability (BD) and optimum conditions for the solid-state anaerobic digestion (SS-AD) of organic solid poultry waste (organs, intestines, offal, and unprocessed meat) to maximize biomethane production. Three main parameters, substrate-to-inoculum (S/I) ratio, pH, and temperature, were evaluated for the SS-AD of organic solid poultry waste. pH was evaluated at non-adjusted pH, initially adjusted pH, and controlled pH conditions at a constant S/I ratio of 0.5 and temperature of 35 ± 1 °C. The S/I ratios were examined at (0.3, 0.5, 1, and 2) at a controlled pH of ≈7.9 and temperature of 35 ± 1 °C. The temperature was assessed at mesophilic (35 ± 1 °C) and thermophilic (55 ± 1 °C) conditions with a constant S/I ratio of 0.5 and controlled pH of ≈7.9. The results demonstrate that the highest biomethane production and BD were achieved with a controlled pH of ≈7.9 (689 ± 10 mg/L, 97.5 ± 1.4%). The initially adjusted pH (688 ± 14 mg/L, 97.3 ± 1.9%) and an S/I ratio of 0.3 (685 ± 8 mg/L, 96.8 ± 1.2%) had approximately equivalent outcomes. The thermophilic conditions yielded 78% lower biomethane yield than mesophilic conditions. The challenge of lower biomethane yield under thermophilic conditions will be resolved in future studies by determining the rate-limiting step. These observations highlight that SS-AD is a promising technology for biomethane production from solid organic poultry waste. Full article

(This article belongs to the Special Issue Anaerobic Digestion Advances in Biomass and Waste Treatment)

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44 pages, 1445 KB

Open AccessEditor’s ChoiceReview

Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions

by Giuseppe Miceli, Maria Grazia Basso, Elena Cocciola and Antonino Tuttolomondo

Bioengineering 2025, 12(7), 681; https://doi.org/10.3390/bioengineering12070681 - 21 Jun 2025

Cited by 5 | Viewed by 7106

Abstract

Artificial intelligence (AI) is revolutionizing the field of medical imaging, offering unprecedented capabilities in data analysis, image interpretation, and decision support. Transcranial Doppler (TCD) and Transcranial Color-Coded Doppler (TCCD) are widely used, non-invasive modalities for evaluating cerebral hemodynamics in acute and chronic conditions. [...] Read more.

Artificial intelligence (AI) is revolutionizing the field of medical imaging, offering unprecedented capabilities in data analysis, image interpretation, and decision support. Transcranial Doppler (TCD) and Transcranial Color-Coded Doppler (TCCD) are widely used, non-invasive modalities for evaluating cerebral hemodynamics in acute and chronic conditions. Yet, their reliance on operator expertise and subjective interpretation limits their full potential. AI, particularly machine learning and deep learning algorithms, has emerged as a transformative tool to address these challenges by automating image acquisition, optimizing signal quality, and enhancing diagnostic accuracy. Key applications reviewed include the automated identification of cerebrovascular abnormalities such as vasospasm and embolus detection in TCD, AI-guided workflow optimization, and real-time feedback in general ultrasound imaging. Despite promising advances, significant challenges remain, including data standardization, algorithm interpretability, and the integration of these tools into clinical practice. Developing robust, generalizable AI models and integrating multimodal imaging data promise to enhance diagnostic and prognostic capabilities in TCD and ultrasound. By bridging the gap between technological innovation and clinical utility, AI has the potential to reshape the landscape of neurovascular and diagnostic imaging, driving advancements in personalized medicine and improving patient outcomes. This review highlights the critical role of interdisciplinary collaboration in achieving these goals, exploring the current applications and future directions of AI in TCD and TCCD imaging. This review included 41 studies on the application of artificial intelligence (AI) in neurosonology in the diagnosis and monitoring of vascular and parenchymal brain pathologies. Machine learning, deep learning, and convolutional neural network algorithms have been effectively utilized in the analysis of TCD and TCCD data for several conditions. Conversely, the application of artificial intelligence techniques in transcranial sonography for the assessment of parenchymal brain disorders, such as dementia and space-occupying lesions, remains largely unexplored. Nonetheless, this area holds significant potential for future research and clinical innovation. Full article

(This article belongs to the Special Issue Advancements in Imaging Informatics: Radiology and Pathology from Diagnosis to Management)

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2 pages, 122 KB

Open AccessEditor’s ChoiceEditorial

Advances in Wearable Technologies for the In-Field Assessment of Biomechanical Risk

by Micaela Porta and Massimiliano Pau

Bioengineering 2025, 12(6), 632; https://doi.org/10.3390/bioengineering12060632 - 10 Jun 2025

Viewed by 695

Abstract

The exceptional improvements that have characterized the technology of wearable devices for biomedical applications in recent decades have made it possible for researchers and practitioners to provide advanced solutions for the assessment of biomechanical and physiological variables in the present day, exploiting miniaturized, [...] Read more.

The exceptional improvements that have characterized the technology of wearable devices for biomedical applications in recent decades have made it possible for researchers and practitioners to provide advanced solutions for the assessment of biomechanical and physiological variables in the present day, exploiting miniaturized, lightweight, and low-power-consumption devices at affordable costs [...] Full article

(This article belongs to the Special Issue Advances in Wearable Technologies for ”In-Field” Assessment of Biomechanical Risk)

21 pages, 1280 KB

Open AccessEditor’s ChoiceReview

A Review of Bioelectrochemical Strategies for Enhanced Polyhydroxyalkanoate Production

by Alejandro Chamizo-Ampudia, Raúl. M. Alonso, Luisa Ariza-Carmona, África Sanchiz and María Isabel San-Martín

Bioengineering 2025, 12(6), 616; https://doi.org/10.3390/bioengineering12060616 - 5 Jun 2025

Cited by 6 | Viewed by 3277

Abstract

The growing demand for sustainable bioplastics has driven research toward more efficient and cost-effective methods of producing polyhydroxyalkanoates (PHAs). Among the emerging strategies, bioelectrochemical technologies have been identified as a promising approach to enhance PHA production by supplying electrons to microorganisms either directly [...] Read more.

The growing demand for sustainable bioplastics has driven research toward more efficient and cost-effective methods of producing polyhydroxyalkanoates (PHAs). Among the emerging strategies, bioelectrochemical technologies have been identified as a promising approach to enhance PHA production by supplying electrons to microorganisms either directly or indirectly. This review provides an overview of recent advancements in bioelectrochemical PHA synthesis, highlighting the advantages of this method, including increased production rates, the ability to utilize a wide range of substrates (including industrial and agricultural waste), and the potential for process integration with existing systems. Various bioelectrochemical systems (BES), electrode materials, and microbial strategies used for PHA biosynthesis are discussed, with a focus on the roles of electrode potentials and microbial electron transfer mechanisms in improving the polymer yield. The integration of BES into PHA production processes has been shown to reduce costs, enhance productivity, and support the use of renewable carbon sources. However, challenges remain, such as optimizing reactor design, scaling up processes, and improving the electron transfer efficiency. This review emphasizes the advancement of bioelectrochemical technologies combined with the use of agro-industrial waste as a carbon source, aiming to maximize the efficiency and sustainability of PHA production for large-scale industrial applications. Full article

(This article belongs to the Special Issue Development of Bioelectrochemical Systems for Environmental Engineering)

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12 pages, 1627 KB

Open AccessEditor’s ChoiceArticle

Wheat Bran Polymer Scaffolds: Supporting Triple-Negative Breast Cancer Cell Growth and Development

by Abulquasem Rayat Hossain, Md Sultan Mahmud, Kaydee Koistinen, George Davisson, Brooke Roeges, Hayle Boechler, Md Abdur Rahim Badsha, Md Rakib Hasan Khan, Michael Kjelland, Dorsa Fereydoonpour, Mohiuddin Quadir, Sanku Mallik and Khwaja Hossain

Bioengineering 2025, 12(6), 568; https://doi.org/10.3390/bioengineering12060568 - 26 May 2025

Cited by 1 | Viewed by 1423

Abstract

Arabinoxylans (AX) are functional biopolymers, the main non-starch polysaccharides in cereals and other plants. AX is composed of xylose and arabinose, and the ester-linkage of ferulic acid to arabinose confers its bioactive properties. The backbone of AX resembles that of glycosaminoglycans, a major [...] Read more.

Arabinoxylans (AX) are functional biopolymers, the main non-starch polysaccharides in cereals and other plants. AX is composed of xylose and arabinose, and the ester-linkage of ferulic acid to arabinose confers its bioactive properties. The backbone of AX resembles that of glycosaminoglycans, a major component of the human extracellular matrix. This study explores the potential of wheat bran AX-based scaffolds as a novel platform for the growth and development of triple-negative breast cancer (TNBC) cells, an aggressive form of breast cancer. Importantly, patients face the worst prognosis due to the stemness of the TNBC cells and the formation of hypoxic cell clumps. Wheat bran constitutes 15–25% of the byproducts after milling and adds limited economic value. We have extracted AX from wheat bran (WBAX) and developed soft scaffolds with Na-alginate. The scaffolds were seeded with the triple-negative breast cancer cell line MDA-MB-231. Over 21 days, cell growth and development, cell migration within the hydrogels, and the formation of hypoxic regions within cell clumps were observed. These findings suggest that WBAX-based scaffolds provide a conducive environment for TNBC cell proliferation and development, offering a promising avenue for further research into cancer cell biology and potential therapeutic applications. Full article

(This article belongs to the Special Issue From Residues to Bio-Based Products through Bioprocess Engineering)

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19 pages, 1118 KB

Open AccessEditor’s ChoiceReview

Long-Acting Extracellular Vesicle-Based Biologics in Osteoarthritis Immunotherapy

by Philip Drohat, Max Baron, Lee D. Kaplan, Thomas M. Best and Dimitrios Kouroupis

Bioengineering 2025, 12(5), 525; https://doi.org/10.3390/bioengineering12050525 - 15 May 2025

Cited by 8 | Viewed by 3852

Abstract

Osteoarthritis (OA) is a chronic degenerative joint disease characterized by low-grade inflammation, cartilage breakdown, and persistent pain. Despite its prevalence, current therapeutic strategies primarily focus on symptom management rather than modifying disease progression. Monoclonal antibodies and cytokine inhibitors targeting inflammatory pathways, including TNF-α [...] Read more.

Osteoarthritis (OA) is a chronic degenerative joint disease characterized by low-grade inflammation, cartilage breakdown, and persistent pain. Despite its prevalence, current therapeutic strategies primarily focus on symptom management rather than modifying disease progression. Monoclonal antibodies and cytokine inhibitors targeting inflammatory pathways, including TNF-α and IL-1, have shown promise but remain limited by inconsistent efficacy and safety concerns. Long-acting biologic therapies—ranging from extended-release formulations, such as monoclonal antibodies and cytokine inhibitors, to gene therapy approaches—have emerged as promising strategies to enhance treatment durability and improve patient outcomes. Extracellular vesicles (EVs) have gained particular attention as a novel delivery platform due to their inherent stability, biocompatibility, and ability to transport therapeutic cargo, including biologics and immunomodulatory agents, directly to joint tissues. This review explores the evolving role of EVs in OA treatment, highlighting their ability to extend drug half-life, improve targeting, and modulate inflammatory responses. Additionally, strategies for EV engineering, including endogenous and exogenous cargo loading, genetic modifications, and biomaterial-based delivery systems, are discussed. Full article

(This article belongs to the Special Issue Integrating Novel Therapeutics and Personalized Medicine into Osteoarthritis Treatment: Advancements in Cartilage Regeneration and Joint Preservation)

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21 pages, 4080 KB

Open AccessEditor’s ChoiceReview

Integrating Artificial Intelligence in Orthopedic Care: Advancements in Bone Care and Future Directions

by Rahul Kumar, Kyle Sporn, Joshua Ong, Ethan Waisberg, Phani Paladugu, Swapna Vaja, Tamer Hage, Tejas C. Sekhar, Amar S. Vadhera, Alex Ngo, Nasif Zaman, Alireza Tavakkoli and Mouayad Masalkhi

Bioengineering 2025, 12(5), 513; https://doi.org/10.3390/bioengineering12050513 - 13 May 2025

Cited by 16 | Viewed by 6923

Abstract

Artificial intelligence (AI) is revolutionizing the field of orthopedic bioengineering by increasing diagnostic accuracy and surgical precision and improving patient outcomes. This review highlights using AI for orthopedics in preoperative planning, intraoperative robotics, smart implants, and bone regeneration. AI-powered imaging, automated 3D anatomical [...] Read more.

Artificial intelligence (AI) is revolutionizing the field of orthopedic bioengineering by increasing diagnostic accuracy and surgical precision and improving patient outcomes. This review highlights using AI for orthopedics in preoperative planning, intraoperative robotics, smart implants, and bone regeneration. AI-powered imaging, automated 3D anatomical modeling, and robotic-assisted surgery have dramatically changed orthopedic practices. AI has improved surgical planning by enhancing complex image interpretation and providing augmented reality guidance to create highly accurate surgical strategies. Intraoperatively, robotic-assisted surgeries enhance accuracy and reduce human error while minimizing invasiveness. AI-powered smart implant sensors allow for in vivo monitoring, early complication detection, and individualized rehabilitation. It has also advanced bone regeneration devices and neuroprosthetics, highlighting its innovation capabilities. While AI advancements in orthopedics are exciting, challenges remain, like the need for standardized surgical system validation protocols, assessing ethical consequences of AI-derived decision-making, and using AI with bioprinting for tissue engineering. Future research should focus on proving the reliability and predictability of the performance of AI-pivoted systems and their adoption within clinical practice. This review synthesizes recent developments and highlights the increasing impact of AI in orthopedic bioengineering and its potential future effectiveness in bone care and beyond. Full article

(This article belongs to the Section Biosignal Processing)

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31 pages, 5264 KB

Open AccessEditor’s ChoiceArticle

StructureNet: Physics-Informed Hybridized Deep Learning Framework for Protein–Ligand Binding Affinity Prediction

by Arjun Kaneriya, Madhav Samudrala, Harrish Ganesh, James Moran, Somanath Dandibhotla and Sivanesan Dakshanamurthy

Bioengineering 2025, 12(5), 505; https://doi.org/10.3390/bioengineering12050505 - 10 May 2025

Cited by 1 | Viewed by 3204

Abstract

Accurately predicting protein–ligand binding affinity is an important step in the drug discovery process. Deep learning (DL) methods have improved binding affinity prediction by using diverse categories of molecular data. However, many models rely heavily on interaction and sequence data, which impedes proper [...] Read more.

Accurately predicting protein–ligand binding affinity is an important step in the drug discovery process. Deep learning (DL) methods have improved binding affinity prediction by using diverse categories of molecular data. However, many models rely heavily on interaction and sequence data, which impedes proper learning and limits performance in de novo applications. To address these limitations, we developed a novel graph neural network model, called StructureNet (structure-based graph neural network), to predict protein–ligand binding affinity. StructureNet improves existing DL methods by focusing entirely on structural descriptors to mitigate data memorization issues introduced by sequence and interaction data. StructureNet represents the protein and ligand structures as graphs, which are processed using a GNN-based ensemble deep learning model. StructureNet achieved a PCC of 0.68 and an AUC of 0.75 on the PDBBind v.2020 Refined Set, outperforming similar structure-based models. External validation on the DUDE-Z dataset showed that StructureNet can effectively distinguish between active and decoy ligands. Further testing on a small subset of well-known drugs indicates that StructureNet has high potential for rapid virtual screening applications. We also hybridized StructureNet with interaction- and sequence-based models to investigate their impact on testing accuracy and found minimal difference (0.01 PCC) between merged models and StructureNet as a standalone model. An ablation study found that geometric descriptors were the key drivers of model performance, with their removal leading to a PCC decrease of over 15.7%. Lastly, we tested StructureNet on ensembles of binding complex conformers generated using molecular dynamics (MD) simulations and found that incorporating multiple conformations of the same complex often improves model accuracy by capturing binding site flexibility. Overall, the results show that structural data alone are sufficient for binding affinity predictions and can address pattern recognition challenges introduced by sequence and interaction features. Additionally, structural representations of protein–ligand complexes can be considerably improved using geometric and topological descriptors. We made StructureNet GUI interface freely available online. Full article

(This article belongs to the Section Biosignal Processing)

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23 pages, 4534 KB

Open AccessEditor’s ChoiceReview

Branding a New Technological Outlook for Future Orthopaedics

by Nicole Tueni and Farid Amirouche

Bioengineering 2025, 12(5), 494; https://doi.org/10.3390/bioengineering12050494 - 7 May 2025

Cited by 4 | Viewed by 4231

Abstract

Orthopedics is undergoing a transformative shift driven by personalized medical technologies that enhance precision, efficiency, and patient outcomes. Virtual surgical planning, robotic assistance, and real-time 3D navigation have revolutionized procedures like total knee arthroplasty and hip replacement, offering unparalleled accuracy and reducing recovery [...] Read more.

Orthopedics is undergoing a transformative shift driven by personalized medical technologies that enhance precision, efficiency, and patient outcomes. Virtual surgical planning, robotic assistance, and real-time 3D navigation have revolutionized procedures like total knee arthroplasty and hip replacement, offering unparalleled accuracy and reducing recovery times. Integrating artificial intelligence, advanced imaging, and 3D-printed patient-specific implants further elevates surgical precision, minimizes intraoperative complications, and supports individualized care. In sports orthopedics, wearable sensors and motion analysis technologies are revolutionizing diagnostics, injury prevention, and rehabilitation, enabling real-time decision-making and improved patient safety. Health-tracking devices are advancing recovery and supporting preventative care, transforming athletic performance management. Concurrently, breakthroughs in biologics, biomaterials, and bioprinting are reshaping treatments for cartilage defects, ligament injuries, osteoporosis, and meniscal damage. These innovations are poised to establish new benchmarks for regenerative medicine in orthopedics. By combining cutting-edge technologies with interdisciplinary collaboration, the field is redefining surgical standards, optimizing patient care, and paving the way for a highly personalized and efficient future. Full article

(This article belongs to the Special Issue Advanced Engineering Technologies in Orthopaedic Research)

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13 pages, 2387 KB

Open AccessEditor’s ChoiceArticle

WATCH-PR: Comparison of the Pulse Rate of a WATCH-Type Blood Pressure Monitor with the Pulse Rate of a Conventional Ambulatory Blood Pressure Monitor

by Mathini Vaseekaran, Marcus Wiemer, Sven Kaese, Dennis Görlich, Jochen Hinkelbein, Gerrit Jansen and Alexander Samol

Bioengineering 2025, 12(5), 492; https://doi.org/10.3390/bioengineering12050492 - 5 May 2025

Cited by 2 | Viewed by 2762

Abstract

Background: Monitoring pulse rate is fundamental to cardiovascular health management and early detection of rhythm disturbances. While oscillometric blood pressure measurement is well established and validated in clinical practice, its use for pulse rate monitoring, particularly via wrist-worn devices, remains largely unexplored. Objective: [...] Read more.

Background: Monitoring pulse rate is fundamental to cardiovascular health management and early detection of rhythm disturbances. While oscillometric blood pressure measurement is well established and validated in clinical practice, its use for pulse rate monitoring, particularly via wrist-worn devices, remains largely unexplored. Objective: This study investigates whether a smartwatch that performs oscillometric blood pressure measurements at the wrist can also deliver reliable pulse rate readings using the same method. Methods: This study compared pulse rates recorded by the Omron HeartGuide smartwatch and conventional ambulatory blood pressure monitors in 50 patients over 24 h. Measurements were taken consecutively, and data were analyzed using intraclass correlation coefficients (ICCs) and Bland–Altman plots. Results: The study showed a high ICC of 0.971, indicating excellent agreement between devices. The average pulse rate difference was 1.5 bpm, with the Omron HeartGuide reporting slightly lower rates, especially in patients with atrial fibrillation. Conclusions: This study demonstrates that oscillometric pulse-rate monitoring at the wrist can achieve a high degree of accuracy, comparable to conventional upper-arm devices. Given that oscillometric smartwatches like the Omron HeartGuide are already used for blood pressure monitoring, the findings suggest that they may also be suitable for pulse rate measurement, potentially enhancing their role in telemetric healthcare, but further research is needed, particularly in patients with arrhythmias. Full article

(This article belongs to the Special Issue Smart Applications and Technology for Cardiovascular Disease Management)

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19 pages, 5913 KB

Open AccessEditor’s ChoiceArticle

Putative Endoplasmic Reticulum Stress Inducers Enhance Triacylglycerol Accumulation in Chlorella sorokiniana

by Yoomi Roh, Sujeong Je, Naeun Sheen, Chang Hun Shin and Yasuyo Yamaoka

Bioengineering 2025, 12(5), 452; https://doi.org/10.3390/bioengineering12050452 - 25 Apr 2025

Cited by 2 | Viewed by 1925

Abstract

Chlorella, recognized for its high lipid and protein content, is increasingly studied for its potential in the food and bio industries. To enhance its production and understand the underlying mechanisms of lipid accumulation, this study investigated the role of endoplasmic reticulum (ER) [...] Read more.

Chlorella, recognized for its high lipid and protein content, is increasingly studied for its potential in the food and bio industries. To enhance its production and understand the underlying mechanisms of lipid accumulation, this study investigated the role of endoplasmic reticulum (ER) stress in modulating lipid metabolism in Chlorella sorokiniana UTEX 2714, using six putative ER stress inducers: 2-deoxy-D-glucose (2-DG), dithiothreitol (DTT), tunicamycin (TM), thapsigargin (TG), brefeldin A (BFA), and monensin (Mon). The results showed that 2-DG, DTT, TM, BFA, and Mon significantly inhibited cell growth in C. sorokiniana. Treatment with 2-DG, DTT, TM, BFA, or Mon resulted in substantial increases in the triacylglycerol (TAG) to total fatty acid (tFA) ratio, with fold changes of 14.8, 7.9, 6.2, 10.1, and 8.9, respectively. Among the tFAs, cells treated with these compounds exhibited higher levels of saturated fatty acids and lower levels of polyunsaturated fatty acids (PUFAs). In contrast, the fatty acid composition of TAGs showed the opposite trend, with relative enrichment in PUFAs. This study enhances our understanding of Chlorella lipid metabolism, providing valuable insights for optimizing lipid production, particularly TAGs enriched with PUFA content, for applications in functional foods, nutraceuticals, and sustainable bioresources. Full article

(This article belongs to the Special Issue Microalgae Biotechnology and Microbiology: Prospects and Applications)

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18 pages, 21454 KB

Open AccessEditor’s ChoiceArticle

Digital Workflow with Open-Source CAD-CAM Software Aimed to Design a Customized 3D Laser-Printed Titanium Mesh for Guided Bone Regeneration

by Claudio Cirrincione, Giulia Guarnieri and Annamaria Morelli

Bioengineering 2025, 12(5), 436; https://doi.org/10.3390/bioengineering12050436 - 22 Apr 2025

Cited by 2 | Viewed by 2093

Abstract

Guided bone regeneration (GBR) is a procedure used for the treatment of bone deficiencies. Computer-Aided Designed–Computer-Aided Manufacturing (CAD-CAM) allows us to design a titanium mesh (TM) for GBR directly on a 3D bone defect model (3DBM). The design and printing of TMs are [...] Read more.

Guided bone regeneration (GBR) is a procedure used for the treatment of bone deficiencies. Computer-Aided Designed–Computer-Aided Manufacturing (CAD-CAM) allows us to design a titanium mesh (TM) for GBR directly on a 3D bone defect model (3DBM). The design and printing of TMs are often delegated to specialized 3D printing centers, thus preventing the surgeon from controlling surgical parameters such as the thickness, pore width, texture, and stiffness. Therefore, we have here proposed a personalized digital workflow for designing a TM. The 3DBM was uploaded to an open-source CAD-CAM software. Following a GBR simulation, a TM was designed as a Standard Tesselation Language (STL) file and 3D laser-printed. The TM was applied to a graft of 50/50% autologous/xenogenic bone, fixed with a bone screw, and covered with a dermal membrane. No TM exposure was observed during the healing phase. The regenerated bone volume was 970 cc, and pseudoperiosteum was class 1. At the 6-month reentry, a 4.1 × 10 standard dental implant with a primary stability of 40 N/cm was placed and after 3 months a zirconia crown screw-on implant was placed. This proposed digital workflow enabled us to successfully tackle this clinical case. However, further clinical investigations will be necessary to confirm the long-term benefits of this procedure. Full article

(This article belongs to the Section Regenerative Engineering)

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20 pages, 6681 KB

Open AccessEditor’s ChoiceArticle

CRISPR-Cas9-Mediated ATF6B Gene Editing Enhances Membrane Protein Production in HEK293T Cells

by Ho Joong Choi, Ba Reum Kim, Ok-Hee Kim and Say-June Kim

Bioengineering 2025, 12(4), 409; https://doi.org/10.3390/bioengineering12040409 - 11 Apr 2025

Viewed by 2024

Abstract

This study aims to enhance membrane protein production in HEK293T cells through genetic modification. HEK293T cells are used for recombinant protein and viral vector production due to their human origin and post-translational modification capabilities. This study explores enhancing membrane protein production in these [...] Read more.

This study aims to enhance membrane protein production in HEK293T cells through genetic modification. HEK293T cells are used for recombinant protein and viral vector production due to their human origin and post-translational modification capabilities. This study explores enhancing membrane protein production in these cells by deleting the C-terminal of the ATF6B gene using CRISPR-Cas9 technology. The objective of this research is to investigate the effect of C-terminal deletion of the ATF6B gene on membrane protein production in HEK293T cells using CRISPR-Cas9 technology. To identify effective gene targets, sgRNAs were initially designed against multiple UPR-related genes, including ATF6A, IRE1A, IRE1B, PERK, and ATF6B. Among them, ATF6B was selected as the primary target for further investigation due to its superior editing efficiency. The efficiency of sgRNAs was evaluated using the T7E1 assay, and sequencing was performed to verify gene editing patterns. Membrane proteins were extracted from both ATF6B C-terminally deleted (ATF6B-ΔC) and wild-type (WT) cell lines for comparison. Flow cytometry was employed to assess membrane protein production by analyzing GFP expression in Membrane-GFP-expressing cells. HEK293T cells with C-terminally deleted ATF6B (ATF6B-ΔC) significantly increased membrane protein production by approximately 40 ± 17.6% compared to WT cells (p < 0.05). Sequencing revealed 11, 14, 1, and 10 bp deletions in the ATF6B-ΔC edited cells, which disrupted exon sequences, induced exon skipping, and introduced premature stop codons, suppressing normal protein expression. Flow cytometry confirmed a 23.9 ± 4.2% increase in GFP intensity in ATF6B-ΔC cells, corroborating the enhanced membrane protein production. These findings suggest that CRISPR-Cas9-mediated C-terminal deletion of the ATF6B gene can effectively enhance membrane protein production in HEK293T cells by activating the unfolded protein response pathway and improving the cell’s capacity to manage misfolded proteins. This strategy presents significant potential for the biotechnology and pharmaceutical industries, where efficient membrane protein production is essential for drug development and various applications. Full article

(This article belongs to the Section Cellular and Molecular Bioengineering)

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14 pages, 2718 KB

Open AccessEditor’s ChoiceArticle

An Explainable Fusion of ECG and SpO₂-Based Models for Real-Time Sleep Apnea Detection

by Tanmoy Paul, Omiya Hassan, Christina S. McCrae, Syed Kamrul Islam and Abu Saleh Mohammad Mosa

Bioengineering 2025, 12(4), 382; https://doi.org/10.3390/bioengineering12040382 - 3 Apr 2025

Cited by 4 | Viewed by 3018

Abstract

Obstructive sleep apnea (OSA) is a common disorder characterized by disrupted breathing during sleep, leading to serious health consequences such as daytime fatigue, hypertension, metabolic issues, and cardiovascular disease. Polysomnography (PSG) is the standard diagnostic method but is costly and uncomfortable for patients, [...] Read more.

Obstructive sleep apnea (OSA) is a common disorder characterized by disrupted breathing during sleep, leading to serious health consequences such as daytime fatigue, hypertension, metabolic issues, and cardiovascular disease. Polysomnography (PSG) is the standard diagnostic method but is costly and uncomfortable for patients, which has led to interest in artificial intelligence (AI) for automated OSA detection. To develop an explainable AI model that utilizes electrocardiogram (ECG) and blood oxygen saturation (SpO2) data for real-time apnea detection, providing visual explanations to enhance interpretability and support clinical decisions. It emphasizes giving visual explanations to show how specific segments of the signal contribute to the AI’s conclusions. Furthermore, it explores the combination of individual models to improve detection accuracy. The fusion of individual models demonstrates an enhanced performance in detection accuracy. Visual explanations for AI decisions highlight the importance of certain signal features, making the model’s operations transparent to healthcare providers. The proposed AI model addresses the crucial need for transparent and interpretable AI in healthcare. By providing real-time, explainable OSA detection, this approach represents a significant advancement in the field, potentially improving patient care and aiding in the early identification and management of OSA. Full article

(This article belongs to the Special Issue Wearable Sensors and Measurement Systems for Human Physiology Monitoring)

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31 pages, 55958 KB

Open AccessEditor’s ChoiceArticle

Computational Modelling of Protected and Unprotected Head Impacts in Rugby

by Thea Hodges, Adam Jones, Lucía Pérez del Olmo, Ashwin Mishra, Brian Caulfield, Tahar Kechadi, David MacManus and Michael D. Gilchrist

Bioengineering 2025, 12(4), 361; https://doi.org/10.3390/bioengineering12040361 - 31 Mar 2025

Cited by 1 | Viewed by 2484

Abstract

This study involved the simulation of five real-world head impact events in rugby, to assess the level of protection provided by a novel foam headguard, the N-Pro. The University College Dublin Brain Trauma Model (UCDBTM) was used to estimate the peak resultant head [...] Read more.

This study involved the simulation of five real-world head impact events in rugby, to assess the level of protection provided by a novel foam headguard, the N-Pro. The University College Dublin Brain Trauma Model (UCDBTM) was used to estimate the peak resultant head accelerations and brain tissue responses in different head impact scenarios. The input kinematics were obtained from two sources: video analysis of impact events, and real-time data obtained through instrumented mouthguards. The impact events were simulated under both unprotected and protected conditions. All simulations were performed against a rigid, non-compliant surface model. The results obtained in this study demonstrate the significant potential of the N-Pro in reducing peak head accelerations and brain tissue stress/strain responses by up to c. 70% compared to unprotected head impacts. This study highlights the headguard’s promising potential to reduce the severity of impact-related injuries by effectively attenuating stresses and strains, as well as linear and rotational kinematics. Additionally, the study supports the recommendation in the literature that kinematic data collected from wearable sensors should be supplemented by video analysis to improve accident reconstructions. Full article

(This article belongs to the Section Biomechanics and Sports Medicine)

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18 pages, 2351 KB

Open AccessEditor’s ChoiceReview

Pulsed Field Ablation: A Review of Preclinical and Clinical Studies

by Andrew P. Sullivan, Martin Aguilar and Zachary Laksman

Bioengineering 2025, 12(4), 329; https://doi.org/10.3390/bioengineering12040329 - 22 Mar 2025

Cited by 3 | Viewed by 8227

Abstract

Pulsed field ablation (PFA) is an emerging technology that utilizes ultra-short high-voltage electric pulses to create nanopores in cell membranes, leading to cell death through irreversible electroporation (IRE). PFA is touted to be highly tissue-selective, which may mitigate the risk of collateral injury [...] Read more.

Pulsed field ablation (PFA) is an emerging technology that utilizes ultra-short high-voltage electric pulses to create nanopores in cell membranes, leading to cell death through irreversible electroporation (IRE). PFA is touted to be highly tissue-selective, which may mitigate the risk of collateral injury to vital adjacent structures. In the field of cardiac electrophysiology, initial studies have shown promising results for acute pulmonary vein isolation (PVI) and lesion durability, with overall freedom from recurrent atrial arrhythmia comparable to traditional thermal ablation modalities. While further large studies are required for long-term efficacy and safety data, PFA has the potential to become a preferred energy source for cardiac ablation for some indications. This review outlines the basic principles and biophysics of IRE and its application to cardiac electrophysiology through a review of the existing preclinical and clinical data. Full article

(This article belongs to the Section Biomedical Engineering and Biomaterials)

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49 pages, 8327 KB

Open AccessEditor’s ChoiceReview

The Transformation Experiment of Frederick Griffith I: Its Narrowing and Potential for the Creation of Novel Microorganisms

by Günter A. Müller

Bioengineering 2025, 12(3), 324; https://doi.org/10.3390/bioengineering12030324 - 20 Mar 2025

Cited by 1 | Viewed by 4283

Abstract

The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely [...] Read more.

The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely related. One reason for this limitation of the “creative potential” of “classical” transformation is the requirement for adequate “fitting” of newly synthesized polypeptide components, directed by the donor genome, to interacting counterparts encoded by the pre-existing acceptor genome. Transformation was introduced in 1928 by Frederick Griffith in the course of the demonstration of the instability of pneumococci and their conversion from rough, non-pathogenic into smooth, virulent variants. Subsequently, this method turned out to be critical for the identification of DNA as the sole matter of inheritance. Importantly, the initial experimental design (1.0) also considered the inheritance of both structural (e.g., plasma membranes) and cybernetic information (e.g., metabolite fluxes), which, in cooperation, determine topological and cellular heredity, as well as fusion and blending of bacterial cells. In contrast, subsequent experimental designs (1.X) were focused on the use of whole-cell homogenates and, thereafter, of soluble and water-clear fractions deprived of all information and macromolecules other than those directing protein synthesis, including outer-membrane vesicles, bacterial prions, lipopolysaccharides, lipoproteins, cytoskeletal elements, and complexes thereof. Identification of the reasons for this narrowing may be helpful in understanding the potential of transformation for the creation of novel microorganisms. Full article

(This article belongs to the Section Biochemical Engineering)

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4 pages, 395 KB

Open AccessEditor’s ChoiceEditorial

Multiscale Modeling in Computational Biomechanics: A New Era with Virtual Human Twins and Contemporary Artificial Intelligence

by Tien-Tuan Dao

Bioengineering 2025, 12(3), 320; https://doi.org/10.3390/bioengineering12030320 - 20 Mar 2025

Viewed by 1230

Abstract

Over the last several decades, computational biomechanics has been intensively investigated as part of the study of human body systems (musculoskeletal, cardiovascular, digestive, etc [...] Full article

(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)

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3 pages, 144 KB

Open AccessEditor’s ChoiceEditorial

Musculoskeletal Disorders and Diseases: Biomechanical Modeling in Sport, Health, Rehabilitation and Ergonomics

by Philippe Gorce

Bioengineering 2025, 12(3), 300; https://doi.org/10.3390/bioengineering12030300 - 16 Mar 2025

Cited by 1 | Viewed by 1762

Abstract

Protecting people at work and at leisure, and improving their quality of life, is one of the major challenges faced in this century [...] Full article

(This article belongs to the Special Issue Musculoskeletal Disorders and Diseases: Biomechanical Modeling in Sport, Health, Rehabilitation and Ergonomics)

23 pages, 2755 KB

Open AccessEditor’s ChoiceReview

A Sensor-Based Classification for Neuromotor Robot-Assisted Rehabilitation

by Calin Vaida, Gabriela Rus and Doina Pisla

Bioengineering 2025, 12(3), 287; https://doi.org/10.3390/bioengineering12030287 - 13 Mar 2025

Cited by 3 | Viewed by 2812

Abstract

Neurological diseases leading to motor deficits constitute significant challenges to healthcare systems. Despite technological advancements in data acquisition, sensor development, data processing, and virtual reality (VR), a suitable framework for patient-centered neuromotor robot-assisted rehabilitation using collective sensor information does not exist. An extensive [...] Read more.

Neurological diseases leading to motor deficits constitute significant challenges to healthcare systems. Despite technological advancements in data acquisition, sensor development, data processing, and virtual reality (VR), a suitable framework for patient-centered neuromotor robot-assisted rehabilitation using collective sensor information does not exist. An extensive literature review was achieved based on 124 scientific publications regarding different types of sensors and the usage of the bio-signals they measure for neuromotor robot-assisted rehabilitation. A comprehensive classification of sensors was proposed, distinguishing between specific and non-specific parameters. The classification criteria address essential factors such as the type of sensors, the data they measure, their usability, ergonomics, and their overall impact on personalized treatment. In addition, a framework designed to collect and utilize relevant data for the optimal rehabilitation process efficiently is proposed. The proposed classifications aim to identify a set of key variables that can be used as a building block for a dynamic framework tailored for personalized treatments, thereby enhancing the effectiveness of patient-centered procedures in rehabilitation. Full article

(This article belongs to the Special Issue Wearable Sensors and Measurement Systems for Human Physiology Monitoring)

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16 pages, 6744 KB

Open AccessEditor’s ChoiceArticle

Effect of Decorin and Aligned Collagen Fibril Topography on TGF-β1 Activation of Corneal Keratocytes

by Nathaniel S. Tjahjono, Divya Subramanian, Tarik Z. Shihabeddin, Hudson D. Hicks, Victor D. Varner, W. Matthew Petroll and David W. Schmidtke

Bioengineering 2025, 12(3), 259; https://doi.org/10.3390/bioengineering12030259 - 5 Mar 2025

Cited by 5 | Viewed by 2588

Abstract

During corneal wound healing, transforming growth factor-beta 1 (TGF-β1) causes differentiation of quiescent keratocytes into myofibroblasts. Decorin has been investigated as a promising anti-fibrotic therapeutic for corneal healing due to its interaction with TGF-β1, collagen, and cell surface receptors. In this study, a [...] Read more.

During corneal wound healing, transforming growth factor-beta 1 (TGF-β1) causes differentiation of quiescent keratocytes into myofibroblasts. Decorin has been investigated as a promising anti-fibrotic therapeutic for corneal healing due to its interaction with TGF-β1, collagen, and cell surface receptors. In this study, a novel microfluidic method for coating aligned collagen fibrils with decorin was developed to mimic the presence of decorin within the corneal stroma. Decorin was found to bind selectively to collagen and remained bound for at least five days. To investigate the effects of decorin coatings on keratocyte activation, primary rabbit keratocytes were cultured in the presence of TGF-β1 for 5 days on substrates with or without decorin and stained for α-smooth muscle actin (α-SMA). The expression of α-SMA was reduced by similar amounts on monomeric collagen (40%), random collagen fibrils (32%), and aligned collagen fibrils (32%) coated with decorin as controls. However, α-SMA expression was differentially expressed between the collagen substrates not coated with decorin, with significantly lower expression on uncoated aligned collagen fibrils compared to uncoated collagen monomers. Addition of decorin directly to culture media, had a limited effect on reducing myofibroblast differentiation. Taken together, these results demonstrate the importance of topography and ECM composition on keratocyte activation. Full article

(This article belongs to the Special Issue Bioengineering and the Eye—2nd Edition)

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