Bioengineering

33 pages, 1316 KB

Open AccessReview

Advances in Decellularization of Fish Wastes for Extracellular Matrix Extraction in Sustainable Tissue Engineering and Regenerative Medicine

by Jady Lee Amarillas, Roger Dingcong, Jr., Lornie Grace Sabugaa, Maree Ivonne Kyla Domingo, Carl Angelo Samulde, Gerard Ian Pingoy, Abhel Ananoria, Roberto Malaluan, Ronald Bual, Gerard Dumancas and Arnold Lubguban

Bioengineering 2026, 13(2), 255; https://doi.org/10.3390/bioengineering13020255 - 23 Feb 2026

Viewed by 453

Abstract

Decellularization removes immunogenic intracellular components of fish tissues while keeping the extracellular matrix (dECM) structure, mechanical integrity, and bioactivity. Fish-derived dECM retains native bioactive components, exhibiting high biocompatibility, low immunogenicity, and biodegradability, while supporting cell adhesion, proliferation, and tissue regeneration. Due to its [...] Read more.

Decellularization removes immunogenic intracellular components of fish tissues while keeping the extracellular matrix (dECM) structure, mechanical integrity, and bioactivity. Fish-derived dECM retains native bioactive components, exhibiting high biocompatibility, low immunogenicity, and biodegradability, while supporting cell adhesion, proliferation, and tissue regeneration. Due to its abundance, minimal ethical concerns, and low zoonotic risks, fish wastes are emerging as sustainable sources of dECM, offering an eco-friendly alternative to mammalian biomaterials. This review highlights advances in decellularizing fish wastes such as skin, scales, bones, viscera, and swim bladders from species including tilapia, tuna, milkfish, carp, goldfish, and sturgeon. Physical, chemical, biological, and hybrid decellularization methods are assessed for cell removal, ECM preservation, and mechanical performance. Recent advances in polymer-dECM composites, crosslinking, and 3D bioprinting have significantly improved scaffold performance, making fish-derived dECM applicable for healing of wounds, regeneration of bone and cartilage, and repair of soft tissues. Despite its potential, challenges remain in optimizing perfusion rates, temperature variations, and tissue-specific protocols, as well as developing eco-friendly decellularization techniques using biodegradable reagents. Future perspectives include expanding decellularized fish tissue sources, innovating bio-inks for 3D bioprinting, and refining tissue-specific processing methods to maximize the potential of fish-derived dECM in regenerative medicine and tissue engineering. Full article

(This article belongs to the Special Issue Extracellular Matrix Biomaterial for Tissue Engineering and Regenerative Medicine)

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9 pages, 610 KB

Open AccessArticle

First Report of Pichia bruneiensis in a Spontaneous Sugarcane Juice Fermentation: A Case Study from an Artisanal Distillery in the Ecuadorian Amazon

by Marcos David Landívar Valverde, Mayra Vanessa Chiriboga Ruilova, Estela Guardado Yordi and Amaury Pérez Martínez

Bioengineering 2026, 13(2), 254; https://doi.org/10.3390/bioengineering13020254 - 22 Feb 2026

Viewed by 272

Abstract

Spontaneous fermentation of sugarcane juice for the production of artisanal sugarcane spirits in the Ecuadorian Amazon is driven by native microbial communities; however, the yeast diversity involved in this process remains poorly characterized. In this descriptive case study, sugarcane juice samples were collected [...] Read more.

Spontaneous fermentation of sugarcane juice for the production of artisanal sugarcane spirits in the Ecuadorian Amazon is driven by native microbial communities; however, the yeast diversity involved in this process remains poorly characterized. In this descriptive case study, sugarcane juice samples were collected from a single artisanal distillery at three fermentation stages (0, 48, and 96 h). Yeasts were isolated using selective culture techniques, yielding three distinct morphotypes (Y01, Y02, and Y03). A progressive reduction in morphological diversity was observed during fermentation, with isolate Y01 persisting at the final stage (96 h). Differences in crystal violet staining indicated variability in cellular metabolic activity among the isolates under the conditions tested. Biochemical characterization using the API 20C AUX system, combined with molecular identification based on ITS rDNA sequencing, was performed for isolate Y01, which showed ≥99% sequence identity with Pichia bruneiensis. To the best of our knowledge, this study represents the first report of P. bruneiensis associated with spontaneous sugarcane juice fermentation in an artisanal distillery from the Ecuadorian Amazon. These findings provide a descriptive baseline on yeast biodiversity in this traditional fermentation system and support future studies aimed at the functional characterization of native yeasts involved in artisanal sugarcane spirit production. Full article

(This article belongs to the Section Biochemical Engineering)

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14 pages, 1602 KB

Open AccessArticle

Limb-Salvage Reconstruction of the Proximal Humerus Using Patient-Specific 3D-Printed PEEK Implants: A Midterm Clinical Study

by Tran Duc Thanh, Le Duc Huy, Nguyen Duc Trung, Luong Nhat Anh, Vu Duc Thang, Luu Huu Phuc, Le The Hung, Vo Sy Quyen Nang, Pham Trung Hieu, Nguyen Tran Quang Sang, Dang Minh Quang and Tran Trung Dung

Bioengineering 2026, 13(2), 253; https://doi.org/10.3390/bioengineering13020253 - 22 Feb 2026

Viewed by 355

Abstract

Background: Reconstruction of the proximal humerus after wide tumor resection is technically demanding, and traditional methods such as allograft–prosthetic composites, reverse shoulder arthroplasty, and metal implants are limited by graft unavailability, pediatric size mismatch, their high cost, and metal-related stress shielding. Polyether ether [...] Read more.

Background: Reconstruction of the proximal humerus after wide tumor resection is technically demanding, and traditional methods such as allograft–prosthetic composites, reverse shoulder arthroplasty, and metal implants are limited by graft unavailability, pediatric size mismatch, their high cost, and metal-related stress shielding. Polyether ether ketone (PEEK), with its modulus closer to cortical bone and radiolucency, offers a promising alternative. Building upon the success in craniomaxillofacial surgery and its favorable physical characteristics, we applied personalized 3D-printed PEEK implants for proximal humerus reconstruction. This study reports the first evidence of applying patient-specific 3D-printed PEEK implants in the proximal humerus. Methods: A retrospective cohort study was conducted on seven patients who underwent wide resection of primary malignant bone tumors of the proximal humerus, followed by reconstruction using patient-specific 3D-printed PEEK implants. Implant design was based on preoperative computed tomography (CT) imaging, incorporating contralateral humeral mirroring and computer-aided design. The implants were fabricated using fused deposition modeling (FDM) with medical-grade PEEK under stringent thermal control (nozzle temperature > 400 °C and heated build chamber), followed by a controlled annealing process to minimize internal stress, optimize polymer crystallinity, and enhance mechanical durability. Outcomes assessed included implant survival, oncologic control, shoulder range of motion, and functional outcomes measured using the Musculoskeletal Tumor Society (MSTS) score. The mean follow-up duration was 56.3 months. Results: All patient-specific PEEK implants were successfully manufactured and implanted with satisfactory geometric accuracy. Mechanical implant survival was 85.7% at final follow-up, with one implant fracture occurring at 28 months. No cases of deep infection, dislocation, loosening, or permanent neurovascular injury were observed. Local soft-tissue recurrence occurred in two patients (28.6%), without distant metastasis or tumor-related mortality. The limb-salvage rate was 100%. At final follow-up, the mean MSTS score was 23.0 ± 1.6. Shoulder motion was limited but comparable to outcomes reported for conventional anatomic megaprosthetic reconstructions. Conclusions: Patient-specific 3D-printed PEEK implants provide a feasible and oncologically safe option for proximal humerus reconstruction after tumor resection, with acceptable midterm implant survival and functional outcomes. The favorable elastic modulus and radiolucency of PEEK offer distinct biomechanical and imaging advantages over metallic implants. Further design optimization and larger prospective studies are warranted to enhance mechanical durability and functional restoration. Full article

(This article belongs to the Special Issue Advanced Technology for Implant Polymers in Orthopaedics, Spine, and Trauma)

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15 pages, 1547 KB

Open AccessArticle

Development and Evaluation of a Urinary Na/K Ratio Prediction Model: A Systematic Comparison from Attention-Based Deep Learning to Classical Ensemble Approaches

by Emi Yuda, Itaru Kaneko and Daisuke Hirahara

Bioengineering 2026, 13(2), 252; https://doi.org/10.3390/bioengineering13020252 - 21 Feb 2026

Viewed by 304

Abstract

The urinary sodium-to-potassium (Na/K) ratio is a clinically established predictor of blood pressure and cardiovascular risk. This study aimed to develop and rigorously evaluate machine learning models for estimating the urinary Na/K ratio using four easily obtainable physiological variables: body weight, systolic blood [...] Read more.

The urinary sodium-to-potassium (Na/K) ratio is a clinically established predictor of blood pressure and cardiovascular risk. This study aimed to develop and rigorously evaluate machine learning models for estimating the urinary Na/K ratio using four easily obtainable physiological variables: body weight, systolic blood pressure, diastolic blood pressure, and pulse rate. A dataset of 82 participants was analyzed under a nested cross-validation framework to ensure strict generalization assessment. We first designed an attention-based deep learning model (MIDIP: Multi-Integrated Deep Ion Prediction). Although MIDIP showed reduced training error, nested validation revealed performance instability, indicating overfitting in this small-sample setting. We then compared classical machine learning models and ensemble strategies. Among all configurations, simple averaging of Random Forest, Gradient Boosting, and Linear Regression (Group A) achieved the best performance (MAE = 1.756, RMSE = 2.349, R² = 0.390). In contrast, incorporating a Transformer model (Group B) degraded performance (MAE = 1.855, R² = 0.294). Similarly, adaptive weighting (AWE) did not improve accuracy (Group A: MAE = 1.836, R² = 0.266; Group B: MAE = 2.133, R² = 0.035). These results demonstrate that, under limited sample conditions (N = 82), model simplicity and equal-weight ensemble integration provide superior generalization compared to attention-based or adaptively weighted deep architectures. The findings underscore the importance of strict validation and controlled model complexity when developing clinically applicable prediction models from small datasets. Full article

(This article belongs to the Section Biosignal Processing)

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22 pages, 2013 KB

Open AccessReview

Roles of the Complement System in Peripheral Nerve Injury and Repair

by Carmelina Azar, Kaixin Pan, Prini Jain, Elsa Sanchez-Lopez and Sameer B. Shah

Bioengineering 2026, 13(2), 251; https://doi.org/10.3390/bioengineering13020251 - 20 Feb 2026

Viewed by 590

Abstract

When nerves are severed, such as during traumatic injury, an acute injury state is induced, characterized by biological and physical changes in the proximal and distal stumps. Beyond the initial injury phase, over a time frame of weeks to months, nerves that remain [...] Read more.

When nerves are severed, such as during traumatic injury, an acute injury state is induced, characterized by biological and physical changes in the proximal and distal stumps. Beyond the initial injury phase, over a time frame of weeks to months, nerves that remain unrepaired progressively enter a chronic injury state, characterized by a change in the extracellular matrix structure of the distal stump, the down-regulation of neurotrophic factors and the loss of macrophages’ and Schwann cells’ ability to clear out degraded axons and myelin. There are also potential systemic impacts away from the site of injury, including in end organs such as muscle and bone. The literature suggests that several of these processes may be strongly influenced by innate and adaptive immune system responses, including a major role for complement pathways. This review details evidence in favor of such a possibility, as well as knowledge gaps and areas for future investigation. Full article

(This article belongs to the Special Issue Nerve Regeneration)

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14 pages, 525 KB

Open AccessReview

Mesenchymal Stem Cell Sheet Engineering: Refining Cell Delivery Strategies in Regenerative Medicine

by Delger Bayarsaikhan, Yoon Joong Kang, Ji Yeon Oh, Teruo Okano, Bonghee Lee and Kyungsook Kim

Bioengineering 2026, 13(2), 250; https://doi.org/10.3390/bioengineering13020250 - 20 Feb 2026

Viewed by 415

Abstract

Mesenchymal stem cells (MSCs) have been widely investigated in regenerative medicine owing to their immunomodulatory activity, paracrine signaling, and multilineage differentiation potential. However, accumulating clinical and preclinical evidence indicates that conventional MSC therapies based on single-cell injection often produce transient benefits due to [...] Read more.

Mesenchymal stem cells (MSCs) have been widely investigated in regenerative medicine owing to their immunomodulatory activity, paracrine signaling, and multilineage differentiation potential. However, accumulating clinical and preclinical evidence indicates that conventional MSC therapies based on single-cell injection often produce transient benefits due to rapid post-transplant cell loss and poor engraftment. These observations suggest that the limited efficacy of MSC therapy is not determined solely by cell type or disease context but may also be influenced by the delivery strategy. In this review, we focus on MSC-based cell sheet studies as an approach to improve cell retention and therapeutic persistence. Building on the clinical validation of cell sheet technology, we critically summarize preclinical evidence across distinct tissue environments. Preclinical studies in cardiac and cutaneous repair models demonstrate that MSC sheets enhance cell retention, sustain paracrine signaling, and promote tissue-level regeneration. Together, these findings highlight that effective MSC sheet therapy requires organ-specific, cell-source-dependent design strategies rather than a uniform approach across tissues. Finally, we propose that the MSC sheet engineering represents not a technical adjustment, but a conceptual shift from transient cell delivery toward structurally integrated, tissue-level regeneration engineering. Full article

(This article belongs to the Special Issue Engineering Mesenchymal Stem Cells for Regenerative Medicine)

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14 pages, 683 KB

Open AccessArticle

Simple Fed-Batch Strategy for Production of Capsular Polysaccharide by Haemophilus influenzae b at Pilot Scale

by Mateus Ribeiro da Silva, Silvia Maria Ferreira Albani, Joaquin Cabrera-Crespo, José Geraldo da Cruz Pradella and Mickie Takagi

Bioengineering 2026, 13(2), 249; https://doi.org/10.3390/bioengineering13020249 - 20 Feb 2026

Viewed by 318

Abstract

Haemophilus influenzae b (Hib) is a pathogenic bacterium that causes meningitis worldwide, mainly in children less than two years old. The capsular polysaccharide b (PRP) is an essential antigen for vaccine formulation. This study aimed to develop a high-yield, technically accessible production strategy [...] Read more.

Haemophilus influenzae b (Hib) is a pathogenic bacterium that causes meningitis worldwide, mainly in children less than two years old. The capsular polysaccharide b (PRP) is an essential antigen for vaccine formulation. This study aimed to develop a high-yield, technically accessible production strategy for PRP production to facilitate vaccine manufacturing in non-profit laboratories. Various fed-batch cultivation strategies were evaluated to address metabolic limitations and identify a robust, simplified process suitable for seamless scale-up to pilot scale. Glucose limitation strategies did not reduce inhibitory acetic acid accumulation due to deficiencies in Hib’s respiratory chain, whereas oxygen availability was identified as critical parameter. Increasing the specific air flow from 0.5 to 1.0 vvm in constant fed-batch (Cfb) resulted in a 33% yield increase, reaching 1706.40 mg PRP.L⁻¹. However, the highest PRP concentration was achieved using exponential fed-batch with cell recycling (EfbCR), resulting in 1879.28 mg PRP.L⁻¹. Although EfbCR offered high productivity, the Cfb strategy emerged to be the most technically feasible and robust solution and was successfully scaled up to an 80 L bioreactor, achieving 1885 mg PRP.L⁻¹. These results advance understanding of PRP production by Hib and provides valuable insight into an efficient and simplified strategy for producing this key/vital vaccine antigen. The findings support the potential for cost-effective local production in public health initiatives. Full article

(This article belongs to the Section Biochemical Engineering)

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Graphical abstract

15 pages, 2002 KB

Open AccessReview

Muscle Fatigue in Dynamic Movement: Limitations and Challenges, Experimental Design, and New Research Horizons

by Natalia Daniel, Jerzy Małachowski, Kamil Sybilski and Michalina Błażkiewicz

Bioengineering 2026, 13(2), 248; https://doi.org/10.3390/bioengineering13020248 - 20 Feb 2026

Viewed by 351

Abstract

Research on muscle fatigue during dynamic movement using surface electromyography (sEMG) constitutes a significant challenge within biomechanics. Despite a degree of standardization, measurements and their resultant findings continue to attract considerable debate, attributable to factors such as skin impedance, perspiration, and electrode displacement, [...] Read more.

Research on muscle fatigue during dynamic movement using surface electromyography (sEMG) constitutes a significant challenge within biomechanics. Despite a degree of standardization, measurements and their resultant findings continue to attract considerable debate, attributable to factors such as skin impedance, perspiration, and electrode displacement, as well as subjective fatigue perception. Further questions remain regarding signal normalization and the selection of appropriate analytical methodologies. Recent years have witnessed notable progress in dynamic fatigue research, highlighting the limitations of classical metrics (e.g., EMG Median Frequency) and introducing time–frequency methods, such as the wavelet transform (WT), which are better equipped to handle signal non-stationarity. Interest has also expanded to include non-linear metrics (e.g., entropy) and the analysis of multiple signals (EMG, accelerometers, fNIRS, EEG). The inherent complexity of conducting studies under conditions that approximate real-world sporting disciplines requires the consideration of the influence of various confounding factors. The judicious selection of relevant physical activities and the rigorous validation of the measurement apparatus are paramount for the accurate execution of the calculations. Current research is substantially predicated on artificial intelligence (AI) algorithms. The synergistic application of AI with wavelet transform, particularly in the decomposition and extraction of EMG signals, demonstrates efficacy in fatigue detection. Nevertheless, the full realization of these potential mandates requires further investigation into system generalization, the integration of data from multiple sensors, and the standardization of protocols, coupled with the establishment of publicly accessible datasets. This article delineates selected guidelines and challenges pertinent to the planning and execution of research on muscle fatigue in dynamic movement, focusing on activity selection, equipment validation, EMG signal analysis, and AI utilization. Full article

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

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17 pages, 2208 KB

Open AccessReview

Global Research Trends in Extracellular Vesicle–Based Therapy for Regenerative Medicine: A Bibliometric Analysis (2014–2024)

by Ramya Lakshmi Rajendran, Atharva Anand Mahajan, Sathish Muthu, Sathish Kumar Rajappan Chandra, Prakash Gangadaran and Byeong-Cheol Ahn

Bioengineering 2026, 13(2), 247; https://doi.org/10.3390/bioengineering13020247 - 20 Feb 2026

Viewed by 517

Abstract

Background: Extracellular vesicles (EVs) have emerged as promising cell-free therapeutic agents in regenerative medicine due to their ability to deliver bioactive molecules with enhanced stability and low immunogenicity. Their potential to replicate stem cell functions without the risks of live-cell transplantation has catalyzed [...] Read more.

Background: Extracellular vesicles (EVs) have emerged as promising cell-free therapeutic agents in regenerative medicine due to their ability to deliver bioactive molecules with enhanced stability and low immunogenicity. Their potential to replicate stem cell functions without the risks of live-cell transplantation has catalyzed a surge in global research. Objective: This study aims to perform a scientometric analysis of EV-based regenerative medicine research from 2014 to 2024, identifying publication trends, influential contributors, thematic clusters, and translational challenges. Methods: Data were retrieved from the Web of Science Core Collection and analyzed using CiteSpace software. The analysis included journal impact mapping, co-authorship networks, co-citation analysis, and thematic cluster identification. Metrics such as citation bursts, total link strength, and silhouette values were used to assess influence and thematic coherence. Results: The most prolific journals were Stem Cell Research & Therapy and International Journal of Molecular Sciences. China led in publication volume, while the USA dominated citation impact. Foundational works by Théry and Lai, including the MISEV guidelines, shaped methodological standards. Nine thematic clusters were identified, including oxidative stress, small EVs, mesenchymal stromal cells, muscle regeneration, and chronic kidney disease. A strategic shift toward engineered EVs and novel sources such as iPSCs and macrophages was evident. Key translational barriers include lack of standardization, scalability issues, and regulatory ambiguity. Conclusions: EV-based therapies are transitioning from foundational research to clinical application. Overcoming methodological and regulatory challenges will be critical to realizing their full therapeutic potential in regenerative medicine. Full article

(This article belongs to the Special Issue Injectable Hydrogels and Smart Biomaterials for Precision Regenerative Therapy)

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14 pages, 2998 KB

Open AccessArticle

Clinical Validation of rPPG-Enabled Contactless Pulse Rate Monitoring Software in Cardiovascular Disease Patients

by Jing Wei Chin, Po Him David Chan, Shutao Chen, Chun Hong Cheng, Richard H. Y. So, Elaine Chow, Benny S. P. Fok and Kwan Long Wong

Bioengineering 2026, 13(2), 246; https://doi.org/10.3390/bioengineering13020246 - 20 Feb 2026

Viewed by 425

Abstract

Background: Cardiovascular disease (CVD) is the leading cause of mortality worldwide, creating demand for continuous, unobtrusive monitoring solutions. This clinical validation evaluates the accuracy of remote photoplethysmography (rPPG), a contactless method using camera video, for measuring pulse rate (PR) in patients with CVD. [...] Read more.

Background: Cardiovascular disease (CVD) is the leading cause of mortality worldwide, creating demand for continuous, unobtrusive monitoring solutions. This clinical validation evaluates the accuracy of remote photoplethysmography (rPPG), a contactless method using camera video, for measuring pulse rate (PR) in patients with CVD. Methods: We enrolled 50 adults with confirmed CVD at a clinical trial center. In a 6 min rested session, synchronized facial video (under controlled lighting), electrocardiogram (ECG), and photoplethysmography (PPG) signals were recorded. PR was derived from 25 s video segments using rPPG-enabled software and compared to ECG-derived PR via regression and Bland–Altman analysis. Results: Data from 47 participants (n = 817 samples) were analyzed. rPPG-derived PR showed strong agreement with ECG, with a mean absolute error of 1.061 bpm, root-mean-squared error of 2.845 bpm, and Pearson correlation of 0.962. Mixed-effects regression analyses (after 2% outlier removal, n = 782) indicated minimal influence from demographic, environmental, or CVD factors on accuracy. PPG-ECG discrepancies reflected inherent methodological differences. Conclusion: The rPPG method provides accurate, contactless PR monitoring in CVD patients, supporting its potential for remote patient monitoring and early deterioration detection. Future work will validate rPPG for irregular rhythms, additional vital signs, and diverse cohorts to strengthen clinical robustness for cardiometabolic risk assessment. Full article

(This article belongs to the Special Issue Contactless Technologies for Patient Health Monitoring)

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18 pages, 12952 KB

Open AccessArticle

Synthetic Melanoma Image Generation and Evaluation Using Generative Adversarial Networks

by Pei-Yu Lin, Yidan Shen, Neville Mathew, Renjie Hu, Siyu Huang, Courtney M. Queen, Cameron E. West, Ana Ciurea and George Zouridakis

Bioengineering 2026, 13(2), 245; https://doi.org/10.3390/bioengineering13020245 - 20 Feb 2026

Viewed by 408

Abstract

Melanoma is the most lethal form of skin cancer, and early detection is critical for improving patient outcomes. Although dermoscopy combined with deep learning has advanced automated skin-lesion analysis, progress is hindered by limited access to large, well-annotated datasets and by severe class [...] Read more.

Melanoma is the most lethal form of skin cancer, and early detection is critical for improving patient outcomes. Although dermoscopy combined with deep learning has advanced automated skin-lesion analysis, progress is hindered by limited access to large, well-annotated datasets and by severe class imbalance, where melanoma images are substantially underrepresented. To address these challenges, we present the first systematic benchmarking study comparing four GAN architectures—DCGAN, StyleGAN2, and two StyleGAN3 variants (T and R)—for high-resolution (

512 \times 512

) melanoma-specific synthesis. We train and optimize all models on two expert-annotated benchmarks (ISIC 2018 and ISIC 2020) under unified preprocessing and hyperparameter exploration, with particular attention to R1 regularization tuning. Image quality is assessed through a multi-faceted protocol combining distribution-level metrics (FID), sample-level representativeness (FMD), qualitative dermoscopic inspection, downstream classification with a frozen EfficientNet-based melanoma detector, and independent evaluation by two board-certified dermatologists. StyleGAN2 achieves the best balance of quantitative performance and perceptual quality, attaining FID scores of 24.8 (ISIC 2018) and 7.96 (ISIC 2020) at

γ = 0.8

. The frozen classifier recognizes 83% of StyleGAN2-generated images as melanoma, while dermatologists distinguish synthetic from real images at only 66.5% accuracy (chance = 50%), with low inter-rater agreement (

κ = 0.17

). In a controlled augmentation experiment, adding synthetic melanoma images to address class imbalance improved melanoma detection AUC from 0.925 to 0.945 on a held-out real-image test set. These findings demonstrate that StyleGAN2-generated melanoma images preserve diagnostically relevant features and can provide a measurable benefit for mitigating class imbalance in melanoma-focused machine learning pipelines. Full article

(This article belongs to the Special Issue AI and Data Science in Bioengineering: Innovations and Applications)

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13 pages, 272 KB

Open AccessReview

Laser Therapy in Basal Cell Carcinoma: Current Evidence, Literature Gaps and Future Perspectives

by Alessandro Clementi, Giovanni Cannarozzo, Luca Guarino, Luca Gargano, Martina Tolone, Elena Zappia, Marco Gratteri, Annunziata Dattola, Caterina Longo, Giovanni Pellacani and Steven Paul Nisticò

Bioengineering 2026, 13(2), 244; https://doi.org/10.3390/bioengineering13020244 - 20 Feb 2026

Viewed by 404

Abstract

Basal cell carcinoma (BCC) is the most frequent skin cancer, and surgery remains the treatment of choice, particularly in high-risk subtypes and sites. However, in low-risk cases and in patients where cosmetic outcome is a priority, alternative strategies, including laser therapy, have been [...] Read more.

Basal cell carcinoma (BCC) is the most frequent skin cancer, and surgery remains the treatment of choice, particularly in high-risk subtypes and sites. However, in low-risk cases and in patients where cosmetic outcome is a priority, alternative strategies, including laser therapy, have been proposed. Different laser sources offer potential advantages in terms of minimal invasiveness, healing time, and cosmetic outcome, but their clinical role remains a matter of debate. This narrative review critically analyses the available evidence on the use of lasers in the treatment of basal cell carcinoma, with a focus on ablative lasers, vascular lasers, and laser-assisted photodynamic therapy. Mechanisms of action, main clinical results, limitations, and the emerging contribution of non-invasive imaging for case selection and response monitoring are discussed. Ablative lasers, in particular CO₂, show favourable results in superficial low-risk BCC, while clearance reliability decreases with increasing tumour depth. Vascular lasers may offer short-term control in selected lesions but with limited long-term data. Laser-assisted PDT represents a promising strategy to extend the indication of PDT to selected nodular forms. Overall, the literature is limited by methodological heterogeneity, incomplete stratification, and short follow-ups. Well-designed comparative studies, standardised protocols, and objective controls will be essential to define the real clinical space of laser therapy in basal cell carcinoma. Full article

(This article belongs to the Section Regenerative Engineering)

4 pages, 162 KB

Open AccessCommunication

Divergent Myelination or Divergent Trajectories? Insights from MPF Mapping in Bipolar Disorder and Recurrent Depressive Disorder

by Remigiusz Recław and Anna Grzywacz

Bioengineering 2026, 13(2), 243; https://doi.org/10.3390/bioengineering13020243 - 19 Feb 2026

Viewed by 247

Abstract

Quantitative magnetic resonance imaging has increasingly highlighted white matter abnormalities as a key component of affective disorders. Fast macromolecular proton fraction (MPF) mapping, a myelin-sensitive technique, recently revealed divergent patterns of white matter myelination in bipolar disorder (BD) and recurrent depressive disorder (RDD), [...] Read more.

Quantitative magnetic resonance imaging has increasingly highlighted white matter abnormalities as a key component of affective disorders. Fast macromolecular proton fraction (MPF) mapping, a myelin-sensitive technique, recently revealed divergent patterns of white matter myelination in bipolar disorder (BD) and recurrent depressive disorder (RDD), with reduced MPF in RDD but elevated MPF in BD. These findings challenge uniform hypomyelination models of mood disorders. In this Communication, we propose a trajectory-oriented reinterpretation of these results, suggesting that MPF differences may reflect distinct neurodevelopmental and lifespan-related myelination trajectories rather than a simple marker of tissue damage. Elevated MPF in BD—observed particularly in relatively young patients—may indicate accelerated or dysregulated white matter maturation or activity-dependent myelin plasticity, whereas reduced MPF in RDD may reflect impaired maintenance of myelin integrity. We emphasize that MPF should not be interpreted as a unidirectional index of pathology and argue that it may serve as a phenotype-differentiating biomarker between BD and RDD, warranting further longitudinal and multimodal studies. Full article

(This article belongs to the Special Issue Neuroimaging Techniques and Applications in Neuroscience)

21 pages, 1799 KB

Open AccessArticle

Comparing Regenerative and Rehabilitative Strategies for Female Stress Urinary Incontinence: Platelet-Rich Plasma vs. Pelvic Floor Muscle Training—A Prospective Study Evaluating Quality of Life

by Andreea Borislavschi, Cristian-Valentin Toma, Răzvan-Cosmin Petca, Răzvan Dănău and Aida Petca

Bioengineering 2026, 13(2), 242; https://doi.org/10.3390/bioengineering13020242 - 19 Feb 2026

Viewed by 284

Abstract

Background: Stress urinary incontinence (SUI) is one of the most common pelvic floor disorders in women, often impairing quality of life (QoL). Pelvic floor muscle training (PFMT) is the standard conservative therapy, while autologous platelet-rich plasma (PRP) is a newer minimally invasive regenerative [...] Read more.

Background: Stress urinary incontinence (SUI) is one of the most common pelvic floor disorders in women, often impairing quality of life (QoL). Pelvic floor muscle training (PFMT) is the standard conservative therapy, while autologous platelet-rich plasma (PRP) is a newer minimally invasive regenerative option. Objective: To compare the effectiveness of three periurethral PRP injections versus PFMT in women with SUI. Methods: This prospective cohort study included 169 women diagnosed with SUI, divided into a PRP group (n = 131), receiving three periurethral PRP injections at 4–6-month intervals, and a PFMT group (n = 38), completing a 12-week PFMT program. Outcomes were measured using the Stamey incontinence scale, visual analogue scale (VAS), and the King’s Health Questionnaire (KHQ). Results: At baseline, PRP patients had more severe symptoms and worse QoL scores. After one injection, PRP achieved improvements in Stamey and VAS scores comparable to PFMT (lower scores), though KHQ remained superior in PFMT (significantly higher baseline scores in the PRP group than the PFMT group). The PRP group showed consistently larger within-group improvements across all scales (p < 0.001), in contrast to the PFMT group, which produced smaller and less consistent changes. Conclusions: Repeated PRP treatment provides greater, controlled, and more consistent benefits than PFMT for SUI. Full article

(This article belongs to the Special Issue Artificial Intelligence and Wearable Biosensors for Precision Medicine: Integrating Technology)

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36 pages, 5121 KB

Open AccessArticle

Peripheral Artery Disease (P.A.D.): Vascular Hemodynamic Simulation Using a Printed Circuit Board (PCB) Design

by Claudiu N. Lungu, Aurelia Romila, Aurel Nechita and Mihaela C. Mehedinti

Bioengineering 2026, 13(2), 241; https://doi.org/10.3390/bioengineering13020241 - 19 Feb 2026

Viewed by 383

Abstract

Background: Arterial stenosis produces nonlinear changes in vascular impedance that are challenging to investigate in real time using either benchtop flow phantoms or high-fidelity computational fluid dynamics (CFD) models. Objective: This study aimed to develop and evaluate a low-cost printed circuit board (PCB) [...] Read more.

Background: Arterial stenosis produces nonlinear changes in vascular impedance that are challenging to investigate in real time using either benchtop flow phantoms or high-fidelity computational fluid dynamics (CFD) models. Objective: This study aimed to develop and evaluate a low-cost printed circuit board (PCB) analog capable of reproducing the hemodynamic effects of progressive arterial stenosis through an R–L–C mapping of vascular mechanics. Methods: A lumped-parameter (0D) electrical network was constructed in which voltage represented pressure, current represented flow, resistance modeled viscous losses, capacitance corresponded to vessel compliance, and inductance represented fluid inertance. A variable resistor simulated focal stenosis and was adjusted incrementally to represent progressive narrowing. Input U_in, output U_out, peak-to-peak V_pp, and mean V_avg voltages were recorded at a driving frequency of 50 Hz. Physiological correspondence was established using the canonical relationships.

R = \frac{8 μ l}{π r^{4}}

,

L = \frac{p l}{π r^{2}}

,

C = \frac{3 π r^{3}}{2 E h}

, where μ is blood viscosity, ρ is density, E is Young’s modulus, and h is wall thickness. A calibration constant was applied to convert measured voltage differences into pressure differences. Results: As simulated stenosis increased, the circuit exhibited a monotonic rise in U_out and V_pp, with a precise inflection beyond mid-range narrowing—consistent with the nonlinear growth in pressure loss predicted by fluid dynamic theory. Replicate measurements yielded stable, repeatable traces with no outliers under nominal test conditions. Qualitative trends matched those of surrogate 0D and CFD analyses, showing minimal changes for mild narrowing (≤25%) and a sharp increase in pressure loss for moderate to severe stenoses (≥50%). The PCB analog uses a simplified, lumped-parameter representation driven by a fixed-frequency sinusoidal excitation and therefore does not reproduce fully characterized physiological systolic–diastolic waveforms or heart–arterial coupling. In addition, the present configuration is intended for relatively straight peripheral arterial segments and is not designed to capture the complex geometry and branching of specialized vascular beds (e.g., intracranial circulation) or strongly curved elastic vessels (e.g., the thoracic aorta). Conclusions: The PCB analog successfully reproduces the characteristic hemodynamic signatures of arterial stenosis in real time and at low cost. The model provides a valuable tool for educational and research applications, offering rapid and intuitive visualization of vascular behavior. Current accuracy reflects assumptions of Newtonian, laminar, and lumped flow; future work will refine calibration, quantify uncertainty, and benchmark results against physiological measurements and full CFD simulations. Full article

(This article belongs to the Special Issue Machine Learning, Artificial Intelligence and Medicine: The Interface of Medicine, Computer Science and Engineering)

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13 pages, 1472 KB

Open AccessArticle

Preliminary Effects of Hyperbaric Oxygen Therapy on Hair Follicle Characteristics in Healthy Subjects

by Hee Young Lee, Ji Yong Lee, Seung Chan Kim and Yoonsuk Lee

Bioengineering 2026, 13(2), 240; https://doi.org/10.3390/bioengineering13020240 - 19 Feb 2026

Viewed by 358

Abstract

Background: Hyperbaric oxygen therapy (HBOT) has regenerative effects in various tissues, but its impact on hair follicles is unclear. This preliminary study evaluated HBOT-induced changes in hair and scalp characteristics in healthy adults. Methods: Nine healthy volunteers completed 50 HBOT sessions [...] Read more.

Background: Hyperbaric oxygen therapy (HBOT) has regenerative effects in various tissues, but its impact on hair follicles is unclear. This preliminary study evaluated HBOT-induced changes in hair and scalp characteristics in healthy adults. Methods: Nine healthy volunteers completed 50 HBOT sessions over three months (2.0 ATA, 100% oxygen, 90 min per session). Objective assessments included follicle density, hairs per follicle, hair volume, and shaft thickness using the Becon phototrichogram system. Subjective evaluations were conducted via a 7-point Likert questionnaire on scalp appearance, hair density, thickness, growth, and shedding. Pre- and post-treatment data were compared using paired statistical tests. Results: Positive trends were observed in follicle density (61.3→66.8 counts/cm²), hairs per follicle (1.24→1.33), and hair volume (24.9→27.7%), though not statistically significant. Hair shaft thickness decreased significantly (0.18→0.10 mm, p = 0.011), consistent with early anagen-phase regrowth. Subjective assessments showed significant improvements across all domains (p < 0.05). Scalp imaging visually supported these findings. Conclusions: HBOT may enhance hair follicle activation and scalp health in healthy adults. These preliminary findings justify further controlled studies to explore HBOT as a non-pharmacological approach to hair regeneration. Full article

(This article belongs to the Special Issue Advanced Physical Techniques in Tissue Engineering and Regenerative Medicine)

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16 pages, 1221 KB

Open AccessReview

Advances in the Measurement and Interpretation of Intervertebral Motion in the Lumbar Spine: A Scoping Review

by Alan Breen, Alexander Breen, Jonathan Branney, Alister du Rose and Mehdi Nematimoez

Bioengineering 2026, 13(2), 239; https://doi.org/10.3390/bioengineering13020239 - 18 Feb 2026

Viewed by 468

Abstract

Background: Intervertebral motion is a fundamental aspect of spinal biomechanics, crucial for understanding lumbar spine function, pain mechanisms, and surgical outcomes. Various methods exist for measuring and interpreting it, each with its own advantages, limitations, and specific applications. However, a comprehensive and standard [...] Read more.

Background: Intervertebral motion is a fundamental aspect of spinal biomechanics, crucial for understanding lumbar spine function, pain mechanisms, and surgical outcomes. Various methods exist for measuring and interpreting it, each with its own advantages, limitations, and specific applications. However, a comprehensive and standard taxonomy of study types for the measurement and interpretation of in vivo intervertebral motion in the lumbar spine is lacking. Objectives: This review aimed to systematically identify, characterise, and categorise the diverse study types deposited in the literature. Eligibility criteria: Only studies in English and of lumbar spine intervertebral motion in living subjects were considered, and only those that employed objective measurement of motion sequences were included. Sources of evidence: A comprehensive literature search was performed in PubMed, CINAHL, and SCOPUS for articles published between January 2000 and October 2025. Charting methods: After removal of duplicates, all studies were subjected to Title and abstract screening, followed by full-text screening of potentially eligible studies. Data selected were charted into tables under the headings: author, year, country, purpose, technology, participants, measurement, interpretation, radiation dosage, and significance of findings. Results: Forty-nine studies were abstracted and are described under 11 study types. These formed a taxonomy constituting the following six categories: normal biomechanical mechanisms, pathological and injury mechanisms, direct kinematic measurement, spinal stabilisation, dynamic radiography, and clinical markers. The resulting taxonomy will serve as a resource for researchers, clinicians, and policymakers by facilitating a more coherent understanding of the field and promoting standardisation in research design and reporting. Full article

(This article belongs to the Special Issue Spine Biomechanics)

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14 pages, 849 KB

Open AccessArticle

Short-Term Facility-Based Functional Electrical Stimulation for Chronic Post-Stroke Foot Drop: A Pilot Study

by Diana-Lidia Tache-Codreanu, Ioana Angela Rotaru, Mihai-Andrei Butum-Cristea, Georgeta Stefan, Andrei Tache-Codreanu, Corina Sporea and Ana-Maria Tache-Codreanu

Bioengineering 2026, 13(2), 238; https://doi.org/10.3390/bioengineering13020238 - 18 Feb 2026

Viewed by 401

Abstract

Background: Functional Electrical Stimulation (FES) for post-stroke drop foot is commonly applied in acute and subacute stroke rehabilitation or as part of long-term home-based programs in chronic patients. Evidence supporting short facility-based rehabilitation programs incorporating FES in chronic populations remains limited. The aim [...] Read more.

Background: Functional Electrical Stimulation (FES) for post-stroke drop foot is commonly applied in acute and subacute stroke rehabilitation or as part of long-term home-based programs in chronic patients. Evidence supporting short facility-based rehabilitation programs incorporating FES in chronic populations remains limited. The aim of this study was to explore functional outcomes associated with such a program in a chronic population. Materials and methods: A 10-day facility-based rehabilitation program incorporating FES therapy followed by 3-month follow-up was delivered to 14 chronic post-stroke patients with foot drop (8 women; aged 62.6 ± 12.2 years). FES was applied during walking with stimulation synchronized to the swing phase of gait (35 Hz, 300 μs, 15 min per session). Activities of daily living and mobility were assessed using clinical outcome measures. Statistical significance (p < 0.05), effect sizes, and minimal clinically important difference (MCID) responder rates were evaluated. Results: Statistically significant improvements were observed across all outcome measures post-treatment and at follow-up, with MCID responder rates exceeding 50%. Conclusions: A short facility-based multimodal rehabilitation program incorporating FES was associated with functional improvements in chronic post-stroke patients. Given the multimodal design, these findings cannot be attributed to FES alone and should be interpreted as exploratory. Full article

(This article belongs to the Special Issue Engineering Neural Motor Control: From Mechanisms to Neural Interfaces)

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19 pages, 23281 KB

Open AccessArticle

A Multiscale Evaluation of Erbium-Doped Yttrium-Aluminum-Garnet Laser Osteotomy: Integrating Macroscopic and Cellular Analyses

by Anjie Shen, Boxuan Huang, Hang Bao, Teng Zhang, Kaijun Zhang, Bin Zhao, Haoyuan Du, Junqiang Wang and Wei Han

Bioengineering 2026, 13(2), 237; https://doi.org/10.3390/bioengineering13020237 - 18 Feb 2026

Viewed by 396

Abstract

Background: Traditional high-speed mechanical osteotomes cause substantial thermal and mechanical trauma, impairing bone healing. Erbium-doped yttrium-aluminum-garnet (Er:YAG) lasers, with water-mediated non-contact ablation, offer precise osteotomy potential with minimal collateral damage. This study demonstrated the feasibility of Er:YAG laser use for complex osteotomies and [...] Read more.

Background: Traditional high-speed mechanical osteotomes cause substantial thermal and mechanical trauma, impairing bone healing. Erbium-doped yttrium-aluminum-garnet (Er:YAG) lasers, with water-mediated non-contact ablation, offer precise osteotomy potential with minimal collateral damage. This study demonstrated the feasibility of Er:YAG laser use for complex osteotomies and elucidated its multi-scale biological impacts on bone. Methods: A custom Er:YAG laser performed Z/arc-shaped osteotomies on fresh ovine bone (oscillating saw as control); paired rat tibial osteotomies; and compared laser vs. saw resection. Osteotomy surfaces were characterized by SEM/micro-CT; histological staining quantified thermal/mechanical damage. Bone marrow-derived mesenchymal stem cell (BMSC) adhesion, viability, and infiltration on cut surfaces were evaluated via LSCM. Result: In the ex vivo ovine model, the Er:YAG laser enabled precise execution of complex osteotomies (Z-shaped and arc-shaped), producing significantly narrower gaps than the oscillating saw (1.14 mm vs. 2.70 mm, p < 0.001) with high geometric fidelity and smooth surfaces free of burrs, micro-cracks, or debris. In the in vivo rat model, laser ablation simultaneously minimized both thermal and mechanical damage at the osteotomy interface: it reduced the thermal damage depth (154 vs. 592 µm, p < 0.001) and empty lacunae rate (16.8% vs. 41.8%, p < 0.001) while completely avoiding the mechanical damage zone (297 µm) induced by sawing. Furthermore, the laser-ablated surface established a highly bioactive interface, which significantly enhanced the adhesion (606 vs. 389 cells), viability (86.9% vs. 46.6%), and infiltration depth (196 vs. 75 µm) of bone marrow-derived mesenchymal stem cells (all p < 0.001). Conclusions: In conclusion, this proof-of-concept study demonstrates that the Er:YAG laser has the potential to enable precise bone resection while preserving microstructure. By establishing a pro-regenerative microenvironment, this technology shows promise as a biologically favorable alternative to conventional sawing, although further technical refinement and long-term validation are essential for its clinical translation. Full article

(This article belongs to the Special Issue Application of Bioengineering to Orthopedics)

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22 pages, 1746 KB

Open AccessArticle

WMCA-Net: Wavelet Multi-Scale Contextual Attention Network for Segmentation of the Intercondylar Notch

by Yi Wu, Xiangxin Wang, Hu Liu, Quan Zhou, Lingyan Zhang, Yujia Zhou and Qianjin Feng

Bioengineering 2026, 13(2), 236; https://doi.org/10.3390/bioengineering13020236 - 18 Feb 2026

Viewed by 227

Abstract

Accurate segmentation of the intercondylar notch of the femur is of great significance for the diagnosis of knee joint diseases, surgical planning, and anterior cruciate ligament (ACL) reconstruction. Among them, the obvious anatomical heterogeneity, the interference of structurally similar tissues, and the blurred [...] Read more.

Accurate segmentation of the intercondylar notch of the femur is of great significance for the diagnosis of knee joint diseases, surgical planning, and anterior cruciate ligament (ACL) reconstruction. Among them, the obvious anatomical heterogeneity, the interference of structurally similar tissues, and the blurred boundaries in MRI images make the segmentation of the intercondylar notch challenging. The segmentation of the intercondylar notch is often regarded as a standard semantic segmentation problem, but doing so leaves the inherent high-order internal variation and low-contrast features of its anatomical structure unresolved. We proposed a new Wavelet Multi-scale Contextual Attention Network (WMCA-Net). We have coordinated the Shallow High-frequency Feature Dense Extraction Block (SHFDEB) and Wavelet Split and Fusion Block (WSFB) modules with each other. The SHFDEB intensively extracts high-frequency detailed features at the shallowest layer of the network, while the WSFB effectively splits and fuses features at various resolutions, suppressing noise while better preserving the high-frequency detailed structural information we need. The Multi-scale Depth-wise Convolution Block (MDCB) captures cross-scale features from the narrow intercondylar notch (5–8 mm wide) to the surrounding femoral structure (approximately 50 mm diameter), dynamically adapting to different morphologies, including pathological changes caused by osteophyte formation. The Contextual-Weighted Attention Module (CWAM) establishes long-term semantic associations between fuzzy regions and clear anatomical landmarks by precisely locating uncertain regions through foreground and background decomposition. The Dice Similarity Coefficient of WMCA-Net on the intercondylar notch dataset is 93.16%, and the 95% Hausdorff Distance is 1.42 mm, demonstrating its advanced segmentation performance and good anatomical adaptability. Full article

(This article belongs to the Special Issue Application of Bioengineering to Orthopedics)

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29 pages, 3365 KB

Open AccessArticle

A Hybrid Automatic Model for Circle Detection in X-Ray Imagery: A Case Study on Hip Prosthesis Wear

by Mehmet Öztürk and Yahia Adwan

Bioengineering 2026, 13(2), 235; https://doi.org/10.3390/bioengineering13020235 - 17 Feb 2026

Viewed by 746

Abstract

This study presents a fully automatic hybrid framework for circle detection and geometric feature extraction from anteroposterior (AP) X-ray images. Detecting circular structures in X-ray imagery is challenging due to low contrast, noise, and metal-induced artifacts, which often limit the robustness of purely [...] Read more.

This study presents a fully automatic hybrid framework for circle detection and geometric feature extraction from anteroposterior (AP) X-ray images. Detecting circular structures in X-ray imagery is challenging due to low contrast, noise, and metal-induced artifacts, which often limit the robustness of purely learning-based or purely geometric approaches. To address these challenges, a hybrid deep learning and computer vision pipeline is proposed that combines data-driven region localization with robust geometric fitting. A YOLOv5-based detector is first employed to identify a compact region of interest (ROI) containing circular components. Within this ROI, edge-based processing using Canny detection is applied, followed by an Edge-Snap refinement stage and robust RANSAC-based circle fitting with a Hough-transform fallback to ensure anatomically plausible circle estimation. The resulting circle centers and radii provide stable geometric parameters that can be consistently extracted across images with varying contrast, noise levels, and prosthesis appearances. The applicability of the proposed framework is demonstrated through a case study on hip prosthesis wear analysis, where the automatically detected circle parameters are used to compute medial, superior, and resultant displacement components using established two-dimensional radiographic formulations. Experimental evaluation on AP hip radiographs shows that the YOLOv5 detector achieves high ROI localization performance (mAP@0.5 = 0.971) and that the hybrid pipeline produces consistent circle parameters across longitudinal image sequences. Overall, the proposed method provides an end-to-end automatic solution for robust circle detection in X-ray imagery, with hip prosthesis wear presented solely as a case study without clinical or diagnostic claims. Full article

(This article belongs to the Section Biosignal Processing)

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20 pages, 3322 KB

Open AccessArticle

Parametric Finite Element Evaluation of Load Redistribution Under Progressive Lumbar Disc Degeneration

by Oleg Ardatov, Sofia Rita Fernandes, Artūras Kilikevičius and Vidmantas Alekna

Bioengineering 2026, 13(2), 234; https://doi.org/10.3390/bioengineering13020234 - 17 Feb 2026

Viewed by 326

Abstract

This study presents a finite element (FE) investigation of intervertebral disc (IVD) degeneration in the human lumbar spine (L1–L3 segment). The model, based on CT-derived geometry and isotropic hyperelastic representation of disc tissues, incorporates controlled simplifications, detailed in the limitations section. Degenerative changes [...] Read more.

This study presents a finite element (FE) investigation of intervertebral disc (IVD) degeneration in the human lumbar spine (L1–L3 segment). The model, based on CT-derived geometry and isotropic hyperelastic representation of disc tissues, incorporates controlled simplifications, detailed in the limitations section. Degenerative changes were parametrically simulated across healthy, mild, moderate, and severe stages by reducing disc height (up to 60%), nucleus pulposus volume (up to 70%), and adjusting tissue stiffness to reflect dehydration and fibrosis. Displacement-controlled compressive loading was applied to assess von Mises stress distributions, reaction forces, and load transfer mechanisms. Results indicate significant load redistribution: annulus fibrosus stresses increased by up to 175% in severe degeneration, while nucleus pulposus stresses decreased by ~70%, indicating a diminished compressive load-bearing contribution of the nucleus. Model predictions were validated against cadaveric and in vivo data, confirming trends in intradiscal pressure (IDP) reductions (40–70%) and stress elevations. The parametric framework elucidates interactions between geometric and material changes, providing clinicians with insights into degeneration progression and guiding biomedical engineers in implant design and interventions. Full article

(This article belongs to the Special Issue Spine Biomechanics)

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17 pages, 5884 KB

Open AccessArticle

The Bacteriophage VMY 22 Has Enhanced the Stability of Its Functional Proteins via Adaptive Evolution in a Temperature-Varying Environment

by Junjie Shang, Chengqian Dong, Qian Zhou, Jinmei Chai and Yunlin Wei

Bioengineering 2026, 13(2), 233; https://doi.org/10.3390/bioengineering13020233 - 17 Feb 2026

Viewed by 296

Abstract

Temperature fluctuations strongly affect microbial viability, often inducing adaptive responses. In this study, we employed the psychrophilic bacterium Bacillus mycoides 41-22 and its associated phage VMY22, originally isolated from the Mingyong Glacier, to investigate phage adaptability under varied temperature conditions. Through selective enrichment [...] Read more.

Temperature fluctuations strongly affect microbial viability, often inducing adaptive responses. In this study, we employed the psychrophilic bacterium Bacillus mycoides 41-22 and its associated phage VMY22, originally isolated from the Mingyong Glacier, to investigate phage adaptability under varied temperature conditions. Through selective enrichment at 4 °C, 15 °C, 28 °C, and 32 °C, we observed clear differences in phage infectivity, as assessed by plaque assays, along with genomic mutations and protein structural changes. Notably, mutations predominantly occurred in functional genes (ATPase, endolysin), while the examined structural loci remained conserved. Homology modeling revealed distinct adaptations in protein tertiary structures corresponding to environmental temperatures, suggesting that phage evolution mainly affects post-adsorption processes. Our findings elucidate a novel mechanism of temperature-driven functional protein evolution among cold-adapted bacteriophages (phage) and providing insights into their potential applications in microbial ecology and biotechnology. Full article

(This article belongs to the Section Biochemical Engineering)

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18 pages, 1204 KB

Open AccessArticle

Artificial Intelligence Versus Human Dental Expertise in Diagnosing Periapical Pathosis on Periapical Radiographs: A Multicenter Study

by Fatma E. A. Hassanein, Radwa R. Hussein, Mohamed Riad Elgarhy, Shaymaa Mohamed Maher, Ahmed Hassen, Sherif Heidar, Marwa Ezz El Arab, Amr Edress, Asmaa Abou-Bakr and Mohamed Mekhemar

Bioengineering 2026, 13(2), 232; https://doi.org/10.3390/bioengineering13020232 - 17 Feb 2026

Viewed by 403

Abstract

Background: Periapical pathosis in periapical radiographs must be properly diagnosed for the success of endodontic treatment but is often muddled by 2D imaging limitations and subjective interpretation. Artificial intelligence (AI) offers a solution, but whether the diagnostic granularity of AI versus human [...] Read more.

Background: Periapical pathosis in periapical radiographs must be properly diagnosed for the success of endodontic treatment but is often muddled by 2D imaging limitations and subjective interpretation. Artificial intelligence (AI) offers a solution, but whether the diagnostic granularity of AI versus human clinicians in everyday clinical practice has been adequately explored remains to be addressed. The purpose of this study was to evaluate the diagnostic accuracy of ChatGPT-5 in detecting periapical radiographic abnormalities compared with the three-expert consensus reference standard. Methods: In this diagnostic accuracy retrospective study, 270 periapical radiographs were independently read by a large language model (ChatGPT-5) and a three-board-certified oral radiologist consensus. The AI was given a standardized prompt to label radiographic features, like the presence of periapical radiolucency, border, shape, and integrity of lamina dura. Diagnostic accuracy, agreement (Cohen’s κ), and predictors of correct AI classification were compared with the expert consensus reference standard. Results: ChatGPT-5 demonstrated high sensitivity (87.5%) but low specificity (12.5%), resulting in an overall diagnostic accuracy of 50.0%. This performance profile reflects a tendency toward over-identification of pathology, with the model classifying 87.5% of radiographs as abnormal compared with 50.0% by expert consensus. Agreement was almost perfect for anatomical localization (arch, κ = 0.857) but poor for binary abnormality detection (κ = 0.000). For morphological descriptors, statistically significant disagreement was observed for lesion border characterization (κ = 0.127; p < 0.001), whereas lesion shape demonstrated only descriptive divergence without reaching statistical significance (κ = 0.359). Root resorption assessment also differed significantly between evaluators (p = 0.046). Regression analysis showed that well-defined corticated borders (OR = 60.25, p < 0.001) and first molar-associated lesions (OR = 32.55, p < 0.001) were significant predictors of correct AI classification. Conclusions: This study demonstrates that while ChatGPT-5 Vision can visually interpret periapical radiographs with high sensitivity, limited specificity and inconsistent morphological feature characterization restrict its reliability for independent clinical diagnosis. The AI system tends to over-diagnose systematically and categorizes lesions more structurally and defined compared to dental experts. AI has the potential for being optimized as a sensitive first-screening test, but its findings must be validated by dental professionals to avoid false positives and ensure proper characterization. Full article

(This article belongs to the Special Issue Artificial Intelligence in Dentistry: Innovations, Applications, and Future Perspectives, 2nd Edition)

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12 pages, 2968 KB

Open AccessArticle

A Machine Learning-Based Decoder Framework for the Cortical Voltage-Sensitive Dye Responses to Retinal Neuromorphic Microstimulation: A Proof-of-Concept Simulation Study

by Keisuke Yamada, Yuina Terakura, Santa Fukuda and Yuki Hayashida

Bioengineering 2026, 13(2), 231; https://doi.org/10.3390/bioengineering13020231 - 16 Feb 2026

Viewed by 423

Abstract

Intracortical microstimulation (ICMS) is a promising approach for visual prostheses. We recently proposed using retinal neuromorphic spike trains derived from visual images as ICMS pulse sequences, and preliminarily recorded cortical voltage-sensitive dye (VSD) responses to such stimulation. To examine whether these cortical responses [...] Read more.

Intracortical microstimulation (ICMS) is a promising approach for visual prostheses. We recently proposed using retinal neuromorphic spike trains derived from visual images as ICMS pulse sequences, and preliminarily recorded cortical voltage-sensitive dye (VSD) responses to such stimulation. To examine whether these cortical responses contain image information, we explore the feasibility of machine-learning–based decoding. However, constructing such a decoder requires large-scale datasets linking visual images, spike trains, and cortical responses, which are not yet experimentally available. Therefore, we generated surrogate data with a Wiener-system model that simulates VSD responses of the visual cortex to ICMS pulse trains. A convolutional neural network trained on these synthetic datasets successfully reconstructed images from the simulated cortical responses. This simulation work serves as a proof-of-concept study, demonstrating the computational feasibility of estimating visual information contained in neuromorphic ICMS-evoked cortical activity and providing a foundation for future physiological validation. Full article

(This article belongs to the Topic Biomedical Engineering, Healthcare and Sustainability, 2nd Edition)

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17 pages, 10098 KB

Open AccessArticle

Development of Antibacterial Dentures Using Titanium Apatite Peening

by Hideaki Sato, Akiko Miyake, Nichika Harakawa, Issei Shoji, Yutaka Kameyama, Shuhei Kodama, Yuichiro Tashiro, Chizuko Ogata and Satoshi Komasa

Bioengineering 2026, 13(2), 230; https://doi.org/10.3390/bioengineering13020230 - 15 Feb 2026

Viewed by 393

Abstract

This study investigated antibacterial dentures fabricated by peening titanium apatite onto a polymethyl methacrylate (PMMA) denture base resin using a peening device. The effects of different peening mass flow rates and total peening masses on the deposition and antibacterial properties of titanium apatite [...] Read more.

This study investigated antibacterial dentures fabricated by peening titanium apatite onto a polymethyl methacrylate (PMMA) denture base resin using a peening device. The effects of different peening mass flow rates and total peening masses on the deposition and antibacterial properties of titanium apatite were investigated. Titanium apatite was peened onto PMMA specimens at mass flow rates of 1, 2, and 5 g/s, with total peening masses of 5, 10, and 15 g. The surface morphology, elemental distribution, and mass changes were analyzed before and after peening and after immersion and water rinsing. The antibacterial activity against Staphylococcus aureus was evaluated using a crystal violet assay. The results showed that reducing the peening mass flow rate increased the amount of titanium apatite transferred and enhanced the antibacterial properties, with the highest deposition achieved at 1 g/s. Varying the total peening mass did not significantly affect the deposition pattern or antibacterial activity. The arithmetic mean roughness of the denture base remained unchanged after peening, indicating its clinical applicability. In conclusion, peening titanium apatite onto PMMA at a lower mass flow rate enabled stronger bonding and incorporation of antibacterial properties, potentially contributing to the development of novel antibacterial denture base materials. Full article

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

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19 pages, 6361 KB

Open AccessArticle

Increased Cervical Disc Height and Decreased Neck Pain and Disability Following Improvement in Cervical Lordosis and Posture Using Chiropractic BioPhysics

by Evan A. Katz, Seana B. Katz, Sophie F. Katz, Curtis A. Fedorchuk, Cole G. Fedorchuk and Douglas F. Lightstone

Bioengineering 2026, 13(2), 229; https://doi.org/10.3390/bioengineering13020229 - 15 Feb 2026

Viewed by 1106

Abstract

Background/Objectives: Cervical degenerative disc disease (DDD) is associated with decreased disc height, spinal arthrosis, decreased spinal stability, neck pain (NP), and increased years living with disability and global disease burden. Methods: A total of 64 patients (19 males, 45 females) between 23 and [...] Read more.

Background/Objectives: Cervical degenerative disc disease (DDD) is associated with decreased disc height, spinal arthrosis, decreased spinal stability, neck pain (NP), and increased years living with disability and global disease burden. Methods: A total of 64 patients (19 males, 45 females) between 23 and 77 years (mean age of 49.05 ± 3.34 years) presented to a private practice with NP and disability. Pre-treatment radiographs revealed decreased cervical curvature (ARA C2–C7) measuring −6.18 ± 3.06° (ideal is −42.0°), anterior head translation (Tz C2–C7) measuring 22.03 ± 2.39 mm (ideal is 0 mm), anterior cervical disc height (ADH C2–C7) measuring 3.68 ± 0.20 mm, and posterior cervical disc height (PDH C2–C7) measuring 3.21 ± 0.15 mm. Pre-treatment NP numeric rating scale (NRS) scored 6.66 ± 0.27, and neck disability index (NDI) scored 40.28 ± 1.42%, indicating moderate disability due to NP. Patients were treated using Chiropractic BioPhysics^® (CBP^®) Mirror Image^® spinal rehabilitation for mean values of 37.80 ± 2.44 treatment visits over 19.48 ± 3.89 weeks at a frequency of 2.89 ± 0.45 treatment visits per week. Results: Post-treatment radiographs revealed improvements in ARA C2–C7 to −19.95 ± 3.05°, Tz C2–C7 to 12.11 ± 2.34 mm, ADH C2-C7 to 5.19 ± 0.21 mm, and PDH C2-C7 to 4.36 ± 0.16 mm. Post-treatment patient-reported outcomes showed improvements in NP NRS to 1.52 ± 0.26 and NDI to 12.66 ± 0.96, indicating minimal NP and disability. Conclusions: CBP^® helps improve sagittal cervical spinal alignment and posture, which may help improve cervical disc height and NP and disability in adult patients with cervical DDD. Full article

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

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25 pages, 2567 KB

Open AccessReview

A Review of Motion-Preserving Cervical Spinal Implants and Fusion Constructs

by Isabella Merem, Rodrigo Vasquez, Jaden Wise, Elizabeth Beaulieu, Samip Patel, Maohua Lin, Gui Pires and Frank D. Vrionis

Bioengineering 2026, 13(2), 228; https://doi.org/10.3390/bioengineering13020228 - 15 Feb 2026

Viewed by 443

Abstract

Spinal fusion remains a common surgical treatment for degenerative cervical spine pathology. By eliminating segmental motion, fusion alters spinal biomechanics and redistributes mechanical loads to adjacent levels. These changes contribute to adjacent segment degeneration (ASD). Motion-preserving spinal implants have been developed to address [...] Read more.

Spinal fusion remains a common surgical treatment for degenerative cervical spine pathology. By eliminating segmental motion, fusion alters spinal biomechanics and redistributes mechanical loads to adjacent levels. These changes contribute to adjacent segment degeneration (ASD). Motion-preserving spinal implants have been developed to address these limitations. Cervical disc arthroplasty (CDA) is the most widely used example. Such devices aim to maintain physiologic kinematics while preserving segmental stability. Their biomechanical behavior varies with implant design, material properties, and constraint characteristics. Previous research does not holistically compare fusion with motion-preserving treatments on the spine, resulting in an incomplete understanding of when motion-preserving devices should be considered in treatment over fusion constructs and which specific motion-preserving implants are most appropriate. This narrative review synthesizes experimental, computational, and clinical studies comparing rigid fusion constructs to motion-preserving technologies in the cervical spine. Emphasis is placed on segmental range of motion, load transmission, intradiscal pressure, facet joint forces, and adjacent-segment mechanics. By comparing effectiveness across motion-preserving treatments, alongside their effectiveness to fusion constructs, we found that CDA more closely preserves near-physiologic motion compared to fusion. Taken together, this review underscores the importance of biomechanics-informed implant design for guiding future innovation in spinal implant technologies. Full article

(This article belongs to the Special Issue Bioengineering Technologies for Spine Research)

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16 pages, 265 KB

Open AccessReview

When Intuition Meets the Algorithm: Medico-Legal Implications of Artificial Intelligence-Driven Decision-Making in Orthopedics

by Giuseppe Basile, Vittorio Bolcato, Giulia Bambagiotti, Luca Bianco Prevot and Livio Pietro Tronconi

Bioengineering 2026, 13(2), 227; https://doi.org/10.3390/bioengineering13020227 - 15 Feb 2026

Viewed by 433

Abstract

Orthopedic surgery is undergoing a transformation driven by artificial intelligence (AI), which is reshaping clinico-surgical decision-making. While the operative strategy and professional responsibility traditionally relied on the surgeon’s intuition and manual skills, advanced algorithms now provide predictive, analytical, and procedural decision supports. This [...] Read more.

Orthopedic surgery is undergoing a transformation driven by artificial intelligence (AI), which is reshaping clinico-surgical decision-making. While the operative strategy and professional responsibility traditionally relied on the surgeon’s intuition and manual skills, advanced algorithms now provide predictive, analytical, and procedural decision supports. This paradigm shift is redefining the concept of human error as well as the relationship between technological tools and human decision-makers. As a result, the foundational elements of the healthcare liability framework are being affected. This paper offers a narrative discussion on selected applications of artificial intelligence in orthopedic surgical practice, including patient risk stratification, surgical indication and prosthesis positioning, with a particular focus on the liability implications for healthcare professionals who rely on these systems in terms of therapeutic decision-making. The aim is then to provide a comprehensive medico-legal perspective within the highly regulated and high-risk field of biomedicine, acknowledging and critically assessing the roles and responsibilities of all stakeholders involved—patients, healthcare professionals, innovative technologies, healthcare organizations, and facility management—while balancing innovation, evidence-based practice, and accountability in healthcare delivery. Full article

(This article belongs to the Special Issue Biomedical Application of Big Data and Artificial Intelligence—Second Edition)

31 pages, 5849 KB

Open AccessArticle

Interpretable Machine Learning Identifies Key Inflammatory and Morphological Drivers of Intracranial Aneurysm Rupture Risk

by Epameinondas Ntzanis, Nikolaos Papandrianos, Petros Zampakis, Vasilios Panagiotopoulos, Constantinos Koutsojannis, Christina Kalogeropoulou and Elpiniki I. Papageorgiou

Bioengineering 2026, 13(2), 226; https://doi.org/10.3390/bioengineering13020226 - 15 Feb 2026

Viewed by 624

Abstract

Traditional statistical approaches identify group-level associations between biomarkers and rupture status in intracranial aneurysms (IAs) but often miss nonlinear interactions at the patient level. Methods: The authors retrospectively analyzed 35 saccular IAs in 35 patients (57.1% ruptured) from a single center (2021–2023). Demographics, [...] Read more.

Traditional statistical approaches identify group-level associations between biomarkers and rupture status in intracranial aneurysms (IAs) but often miss nonlinear interactions at the patient level. Methods: The authors retrospectively analyzed 35 saccular IAs in 35 patients (57.1% ruptured) from a single center (2021–2023). Demographics, detailed morphology (e.g., neck width, aspect ratio, VERTI, irregular shape), and multi-site inflammatory/immune markers (CRP; complement C3/C4; IgA/IgG/IgM) were included. After preprocessing (min–max scaling; one-hot encoding), five algorithms (DT, AdaBoost, GBM, XGBoost, RF) were evaluated with stratified five-fold CV and class balancing via random oversampling. The primary model (Random Forest) was tuned with Optuna and explained using global feature importance and LIME. The results showed that baseline RF achieved CV ROC-AUC 0.81 and test ROC-AUC 0.92 (test accuracy 0.857). The tuned RF (with oversampling and Optuna) yielded a mean CV accuracy of 0.85 ± 0.09 and CV ROC-AUC of 0.98 ± 0.07 while maintaining test ROC-AUC of 0.92. The average precision on the test PR curve was 0.97. The most influential predictors combined inflammatory markers (CRP, C3, C4) with morphology (neck width, irregular shape). LIME revealed consistent local patterns: low A.CRP/C.CRP and lower C3/C4 favored Not-Broken, whereas higher CRP/complement with smaller neck and irregular shape pushed toward Broken classifications. It can be concluded that an interpretable machine learning (ML) pipeline captured clinically plausible, nonlinear interactions between inflammation and aneurysm geometry. Integrating explainable ML with conventional statistics may enhance rupture risk stratification, enable patient-level rationale, and inform personalized management. These results could significantly contribute to the quality of treatment for patients with intracranial aneurysms. Full article

(This article belongs to the Special Issue Artificial Intelligence (AI) in Bioengineering)

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Bioengineering, Volume 13, Issue 2 (February 2026) – 129 articles

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