Bioengineering

18 pages, 8552 KiB

Open AccessArticle

Application of a Rational Crystal Contact Engineering Strategy on a Poly(Ethylene Terephthalate)-Degrading Cutinase

by Brigitte Walla, Anna-Maria Dietrich, Edwin Brames, Daniel Bischoff, Stefanie Fritzsche, Kathrin Castiglione, Robert Janowski, Dierk Niessing and Dirk Weuster-Botz

Bioengineering 2025, 12(6), 561; https://doi.org/10.3390/bioengineering12060561 (registering DOI) - 23 May 2025

Abstract

Industrial biotechnology offers a potential ecological solution for PET recycling under relatively mild reaction conditions via enzymatic degradation, particularly using the leaf branch compost cutinase (LCC) quadruple mutant ICCG. To improve the efficient downstream processing of this biocatalyst after heterologous gene expression with [...] Read more.

Industrial biotechnology offers a potential ecological solution for PET recycling under relatively mild reaction conditions via enzymatic degradation, particularly using the leaf branch compost cutinase (LCC) quadruple mutant ICCG. To improve the efficient downstream processing of this biocatalyst after heterologous gene expression with a suitable production host, protein crystallization can serve as an effective purification/capture step. Enhancing protein crystallization was achieved in recent studies by introducing electrostatic (and aromatic) interactions in two homologous alcohol dehydrogenases (Lb/LkADH) and an ene reductase (NspER1-L1,5) produced with Escherichia coli. In this study, ICCG, which is difficult to crystallize, was utilized for the application of crystal contact engineering strategies, resulting in ICCG mutant L50Y (ICCGY). Previously focused on the Lys-Glu interaction for the introduction of electrostatic interactions at crystal contacts, the applicability of the engineering strategy was extended here to an Arg-Glu interaction to increase crystallizability, as shown for ICCGY T110E. Furthermore, the rationale of the engineering approach is demonstrated by introducing Lys and Glu at non-crystal contacts or sites without potential interaction partners as negative controls. These resulting mutants crystallized comparably but not superior to the wild-type protein. As demonstrated by this study, crystal contact engineering emerges as a promising approach for rationally enhancing protein crystallization. This advancement could significantly streamline biotechnological downstream processing, offering a more efficient pathway for research and industry. Full article

(This article belongs to the Section Biochemical Engineering)

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17 pages, 4015 KiB

Open AccessArticle

Digitalized Thermal Inspection Method of the Low-Frequency Stimulation Pads for Preventing Low-Temperature Burn in Sensitive Skin

by HyungTae Kim, Jong-ik Song, Ji-won Seo, CheolWoong Ko, Gi-ho Seo and Sang Kuy Han

Bioengineering 2025, 12(6), 560; https://doi.org/10.3390/bioengineering12060560 (registering DOI) - 23 May 2025

Abstract

An accurate thermal measurement of low-frequency stimulation (LFS) pads for thermotherapy was investigated using background subtraction (BGS) methods. The safety of LFS thermal pads must be investigated to prevent low-temperature burns (LTBs), because they frequently contact the sensitive skin in neck, shoulder and [...] Read more.

An accurate thermal measurement of low-frequency stimulation (LFS) pads for thermotherapy was investigated using background subtraction (BGS) methods. The safety of LFS thermal pads must be investigated to prevent low-temperature burns (LTBs), because they frequently contact the sensitive skin in neck, shoulder and abdominal regions. The thermal measurement was based on thermal imaging using the active region-of-interest (ROI) from a foreground. The shape of the LFS thermal pad consists of complicated curves, thus it is difficult to extract the foreground using conventional shapes of ROIs. We proposed the foreground extraction using background subtraction (BGS) and digital and morphological filters to time-variant thermal images. The foreground extraction was implemented using open sources and experimented for abdominal, cervical and patellar pads. The results showed that the foreground can be separated from background regardless of the size, position, orientation and shape of the pad. The thermal characteristics of the LFS thermal pads were evaluated from the complicated shapes of the foreground with high accuracy. This study demonstrated that standard deviation of pixel history (SDPH) is a simple method for the BGS, but the SDPH is useful to find the safety risk of LTBs and prevent them in advance. The results also showed that the proposed SDPH was simple but had remarkable accuracy compared with the conventional BGS methods. These BGS methods are expected to increase the reliability of products used on the human body. Further, the BGS methods can be used to inspect the temperatures of static products in industrial processes. Full article

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

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13 pages, 250 KiB

Open AccessEditorial

Artificial Intelligence in Public Health: Bridging Today’s Trends with Tomorrow’s Possibilities

by Daniele Giansanti and Giovanni Costantini

Bioengineering 2025, 12(6), 559; https://doi.org/10.3390/bioengineering12060559 (registering DOI) - 23 May 2025

Abstract

Driven by the unprecedented challenges of the COVID-19 pandemic, the healthcare sector has witnessed remarkable—and at times sometimes overwhelming—advancements in the role of artificial intelligence (AI) [...] Full article

(This article belongs to the Topic Artificial Intelligence in Public Health: Current Trends and Future Possibilities)

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33 pages, 13568 KiB

Open AccessArticle

Are Artificial Intelligence Models Listening Like Cardiologists? Bridging the Gap Between Artificial Intelligence and Clinical Reasoning in Heart-Sound Classification Using Explainable Artificial Intelligence

by Sami Alrabie and Ahmed Barnawi

Bioengineering 2025, 12(6), 558; https://doi.org/10.3390/bioengineering12060558 - 22 May 2025

Abstract

In recent years, deep learning has shown promise in automating heart-sound classification. Although this approach is fast, non-invasive, and cost-effective, its diagnostic accuracy still mainly depends on the clinician’s expertise, making it particularly challenging to detect rare or complex conditions. This study is [...] Read more.

In recent years, deep learning has shown promise in automating heart-sound classification. Although this approach is fast, non-invasive, and cost-effective, its diagnostic accuracy still mainly depends on the clinician’s expertise, making it particularly challenging to detect rare or complex conditions. This study is motivated by two key concerns in the field of heart-sound classification. First, we observed that automatic heart-sound segmentation algorithms—commonly used for data augmentation—produce varying outcomes, raising concerns about the accuracy of both the segmentation process and the resulting classification performance. Second, we noticed inconsistent accuracy scores across different pretrained models, prompting the need for interpretable explanations to validate these results. We argue that without interpretability to support reported metrics, accuracy scores can be misleading because of ambiguity in how training data interact with pretrained models. Specifically, it remains unclear whether these models classify spectrogram images—generated from heart-sound signals—in a way that aligns with clinical reasoning, where experts focus on specific components of the heart cycle, such as S1, systole, S2, and diastole. To address this, we applied explainable AI (XAI) techniques with two primary objectives: (1) to assess whether the model truly focuses on clinically relevant features, thereby allowing classification results to be verified and trusted, and (2) to investigate whether incorporating attention mechanisms can improve both the performance and the model’s focus on meaningful segments of the signal. To the best of our knowledge, this is the first study conducted on a manually segmented dataset, which objectively evaluates the model’s behavior using XAI and explores performance enhancement by combining attention mechanisms with pretrained models. We employ the Grad-CAM method to visualize the model’s attention and gain insights into the decision-making process. The experimental results show that integrating multi-head attention significantly improves both the classification accuracy and interpretability. Notably, ResNet50 with multi-head attention achieved an accuracy of 97.3%, outperforming those of both the baseline and SE-enhanced models. Moreover, the mean intersection over union (mIoU) for interpretability increased from 75.7% to 82.0%, indicating the model’s improved focus on diagnostically relevant regions. Full article

(This article belongs to the Special Issue Biomedical Imaging and Data Analytics for Disease Diagnosis and Treatment, 2nd Edition)

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18 pages, 2404 KiB

Open AccessArticle

Efficient Production of High-Concentration Poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) from CO₂ Employing the Recombinant of Cupriavidus necator

by Kenji Tanaka, Izumi Orita and Toshiaki Fukui

Bioengineering 2025, 12(6), 557; https://doi.org/10.3390/bioengineering12060557 - 22 May 2025

Abstract

A copolymer of 3-hydroxybutyrate (3HB) and 3-hydoxyhexanoate (3HHx), PHBHHx, is a practical biodegradable plastic, and at present, the copolymer is produced at commercial scale via heterotrophic cultivation of an engineered strain of a facultative hydrogen-oxidizing bacterium, Cupriavidus necator, using vegetable oil as [...] Read more.

A copolymer of 3-hydroxybutyrate (3HB) and 3-hydoxyhexanoate (3HHx), PHBHHx, is a practical biodegradable plastic, and at present, the copolymer is produced at commercial scale via heterotrophic cultivation of an engineered strain of a facultative hydrogen-oxidizing bacterium, Cupriavidus necator, using vegetable oil as the carbon source. In our previous report, we investigated PHBHHx production from CO₂ via pH-stat jar cultivation of the newly created recombinants of C. necator under autotropic conditions, feeding the inorganic substrate gas mixture (H₂/O₂/CO₂ = 80:10:10 v/v%) into a recycled-gas closed-circuit (RGCC) culture system. The dry cell weight (DCW) and PHBHHx concentration with the best strain MF01/pBPP-ccr_MeJ_Ac-emd increased to 59.62 ± 3.18 g·L⁻¹ and 49.31 ± 3.14 g·L⁻¹, respectively, after 216 h. In this study, we investigated the high-concentration production of PHBHHx with a shorter cultivation time by using a jar fermenter equipped with a basket-shaped agitator to enhance oxygen transfer in the culture medium and by continuously supplying the gases with higher O₂ concentrations to maintain the gas composition within the reservoir at a constant ratio. The concentrations of ammonium and phosphate in the culture medium were maintained at low levels. As a result, the DCW and PHBHHx concentrations increased to 109.5 ± 0.30 g·L⁻¹ and 85.2 ± 0.62 g·L⁻¹ after 148 h, respectively. The 3HHx composition was 10.1 ± 0.693 mol%, which is suitable for practical applications. Full article

(This article belongs to the Special Issue Advances in Polyhydroxyalkanoate (PHA) Production, 4th Edition)

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13 pages, 1146 KiB

Open AccessArticle

Predictive Value of Optical Coherence Tomography Biomarkers in Patients with Persistent Diabetic Macular Edema Undergoing Cataract Surgery Combined with a Dexamethasone Intravitreal Implant

by Giuseppe Fasolino, Maryam Lazaar, Domenico Giovanni Della Rocca, Silke Oellerich and Sorcha Ní Dhubhghaill

Bioengineering 2025, 12(5), 556; https://doi.org/10.3390/bioengineering12050556 - 21 May 2025

Abstract

Background: Diabetic macular edema (DME) is the most common cause of vision loss among diabetic patients. The first-line treatments for DME are anti-vascular endothelial growth factor (VEGF)-drugs, while intravitreal steroids are generally reserved for second-line treatment. Limited data exist on the role of [...] Read more.

Background: Diabetic macular edema (DME) is the most common cause of vision loss among diabetic patients. The first-line treatments for DME are anti-vascular endothelial growth factor (VEGF)-drugs, while intravitreal steroids are generally reserved for second-line treatment. Limited data exist on the role of optical coherence tomography (OCT) biomarkers as predictors of success in non-responders to anti-VEGF treatment undergoing simultaneous cataract surgery and dexamethasone intravitreal implant (DEX-I). Methods: This study was designed as a retrospective analysis of patients with DME who were refractory to anti-VEGF treatment but underwent cataract surgery and received a DEX-I at the time of surgery. All procedures were performed between May 2021 and February 2024. The best-corrected visual acuity (BCVA) and central subfoveal thickness (CST) were recorded at baseline and at 1 week, 1 month, and 3 months. The following OCT-based biomarkers were also collected: ellipsoid zone (EZ) integrity, disorganization of the retinal inner layers (DRIL), CST, and hyperreflective foci (HRF). Correlations between the baseline biomarkers and the anatomical outcome were analyzed using linear mixed models (LMMs). Results: Eleven patients (eighteen eyes) met the inclusion criteria. The mean CST decreased significantly from 469.4 ± 53.8 µm at baseline, to 373.1 ± 34.7 µm at 1 week (p = 0.002) and 354.4 ± 24.1 µm at 1 month (p = 0.011). The mean BCVA improved significantly from 0.47 LogMAR to 0.33 LogMAR at 1 week (p = 0.001), 0.23 LogMAR at 1 month (p < 0.001), and 0.25 LogMAR at 3 months (p < 0.001). Baseline predictors significantly influencing CST included the presence of DRIL, a disrupted/absent EZ, and a higher CST. Conclusions: The administration of DEX-I for DME refractory to anti-VEGF treatment in patients undergoing cataract surgery promoted functional improvements persisting longer than the anatomical ones. Patients presenting with DRIL, disrupted EZ, and higher CST at baseline may be better candidates for the combination of DEX-I and cataract surgery. Full article

(This article belongs to the Special Issue Biomedical Applications of Optical Coherence Tomography, Second Edition)

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31 pages, 8144 KiB

Open AccessArticle

In Vitro and In Silico Analysis of Entrainment Characterization in Injection Jet-Assisted Fontan Circulation

by Arka Das, Ray O. Prather, Anthony Damon, Michael Farias, Alain Kassab, Eduardo Divo and William DeCampli

Bioengineering 2025, 12(5), 555; https://doi.org/10.3390/bioengineering12050555 - 21 May 2025

Abstract

Fontan circulation is a fragile system in which imperfections at any of multiple levels may compromise the quality of life, produce secondary pathophysiology, and shorten life span. Increased inferior vena caval pressure itself may play a role in “Fontan failure”. This study describes [...] Read more.

Fontan circulation is a fragile system in which imperfections at any of multiple levels may compromise the quality of life, produce secondary pathophysiology, and shorten life span. Increased inferior vena caval pressure itself may play a role in “Fontan failure”. This study describes a mock flow loop model (MFL) designed to quantitatively estimate pulmonary flow entrainment induced by continuous and pulsed flow injections. A patient generic 3D-printed phantom model of the total cavopulmonary connection (TCPC) with average dimensions matching those of a 2–4-year-old patient was inserted in an MFL derived from a reduced lumped parameter model (LPM) representing cardiovascular circulation. The LPM comprises four 2-element Windkessel compartments (compliance and resistance), approximating the upper and lower systemic circulations and the right and left pulmonary circulations. The prescribed cardiac output is about 2.3 L/min for a body surface area of

0.675 m^{2}

. The injections originate from an external pump through a 7–9 fr catheter, following a strict protocol suggested by the clinical team, featuring a variation in injection rate (flow rate), injection volume, and injection modality (continuous or pulsed). The key measurements in this study are the flow rates sampled at the distal pulmonary arteries, as well as at the upper and lower body boundaries. These measurements were then used to calculate effective entrainment as the difference between the measured and expected flow rates, as well as jet relaxation (rise and fall time of injection). The results show that for continuous or pulsed injections, varying the total volume injected has no significant influence on the entrainment rate across all injection rates. On the other hand, for both injection modalities, increasing the injection rate results in a reduction in entrainment that is consistent across all injected volumes. This study demonstrates the effectiveness of a high-speed injection jet entraining a slow co-flow while determining the potential for fluid buildup, which could ultimately cause an increase in caval pressure. To avoid the increase in caval pressure due to mass accumulation, we added a fenestration to our proposed injection jet shunt-assisted Fontan models. It was found that for a set of well-defined parameters, the jet not only can be beneficial to the local flow, but any adverse effect can be obviated by careful tuning. These results were also cross-validated with similar in silico findings. Full article

(This article belongs to the Special Issue Cardiovascular Hemodynamic Characterization: Prospects and Challenges)

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13 pages, 6421 KiB

Open AccessArticle

Advancing Tissue Engineering Through a Portable Perfusion and Incubation System

by Angie Zhu, Emmett Reid, Tilak Jain, Amatullah Mir, Usmaan Siddiqi, Olivia Dunne and Narutoshi Hibino

Bioengineering 2025, 12(5), 554; https://doi.org/10.3390/bioengineering12050554 - 21 May 2025

Abstract

Perfusion offers unique benefits to tissue-engineered systems, enhancing oxygen and nutrient transport, which improves tissue formation and growth. In this study, we present a novel and integrated portable perfusion system. Weighing < 10 lbs, the system can maintain continuous flow in a standard [...] Read more.

Perfusion offers unique benefits to tissue-engineered systems, enhancing oxygen and nutrient transport, which improves tissue formation and growth. In this study, we present a novel and integrated portable perfusion system. Weighing < 10 lbs, the system can maintain continuous flow in a standard incubation environment (37 °C, 5% CO₂), effectively functioning as a portable perfusion and tissue culturing system. To characterize the perfusion system’s flow parameters, we measured the volumetric flow rate across a range of pressures and found that the system could achieve flow velocities between 1.69 to 4.6

μ

m/s, which is similar to in vivo interstitial flow. Computational fluid dynamics revealed fully developed laminar flow within the sample-containing region of the perfusion system, helping ensure even fluid and nutrient distribution. To study the system’s compatibility with live tissues, bioengineered tissue patches were created and perfused. After 24 h of perfusion, no significant difference in cell viability was observed between the perfused samples and static controls, indicating no adverse effects on cell health. Perfusion also facilitated enhanced spatial organization within tissue patches, reducing the inter-spheroids distance. Furthermore, perfusion strengthened the tissue matrix and reduced the degradation rate of the hydrogel scaffold. Complemented by its ability to provide mobile perfusion and incubation, this novel integrated portable perfusion system holds promise for promoting tissue maturation and advancing tissue bioengineering studies. Full article

(This article belongs to the Special Issue The New Frontiers of Artificial Organs Engineering)

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Graphical abstract

18 pages, 748 KiB

Open AccessArticle

Analytical Basal-State Model of the Glucose, Insulin, and C-Peptide Systems for Type 2 Diabetes

by Ched C. Chichester, Munekazu Yamakuchi, Kazunori Takenouchi, Teruto Hashiguchi and Drew N. Maywar

Bioengineering 2025, 12(5), 553; https://doi.org/10.3390/bioengineering12050553 - 21 May 2025

Abstract

We present a mechanistic mathematical model of the basal state for type 2 diabetes mellitus (T2DM) in an analytical form and illustrate its use for in silico basal-state and dynamic studies. At the core of the basal-state model is a quartic equation that [...] Read more.

We present a mechanistic mathematical model of the basal state for type 2 diabetes mellitus (T2DM) in an analytical form and illustrate its use for in silico basal-state and dynamic studies. At the core of the basal-state model is a quartic equation that expresses the basal plasma glucose concentration solely in terms of model parameters. This analytical model avoids a computationally intensive numerical solver and is illustrated by an investigation of how glucose-utilization parameters impact basal glucose, insulin, insulin-dependent utilization, and hepatic extraction, leveraging median parameter values of early-stage T2DM. Furthermore, the presented basal-state model ensures accurate execution of the corresponding dynamic model, which contains basal quantities within its derivative functions; erroneous, unintended dynamics in plasma glucose, insulin, and C-peptide are illustrated using an incorrect basal glucose value. The presented basal model enables efficient and accurate basal-state and dynamic studies, facilitating the understanding of T2DM pathophysiology and the development of T2DM diagnosis, treatment, and management strategies. Full article

(This article belongs to the Section Biosignal Processing)

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22 pages, 3829 KiB

Open AccessArticle

Brain Tumour Segmentation and Grading Using Local and Global Context-Aggregated Attention Network Architecture

by Ahmed Abdulhakim Al-Absi, Rui Fu, Nadhem Ebrahim, Mohammed Abdulhakim Al-Absi and Dae-Ki Kang

Bioengineering 2025, 12(5), 552; https://doi.org/10.3390/bioengineering12050552 - 21 May 2025

Abstract

Brain tumours (BTs) are among the most dangerous and life-threatening cancers in humans of all ages, and the early detection of BTs can make a huge difference to their treatment. However, grade recognition is a challenging issue for radiologists involved in automated diagnosis [...] Read more.

Brain tumours (BTs) are among the most dangerous and life-threatening cancers in humans of all ages, and the early detection of BTs can make a huge difference to their treatment. However, grade recognition is a challenging issue for radiologists involved in automated diagnosis and healthcare monitoring. Recent research has been motivated by the search for deep learning-based mechanisms for segmentation and grading to assist radiologists in diagnostic analysis. Segmentation refers to the identification and delineation of tumour regions in medical images, while classification classifies based on tumour characteristics, such as the size, location and enhancement pattern. The main aim of this research is to design and develop an intelligent model that can detect and grade tumours more effectively. This research develops an aggregated architecture called LGCNet, which combines a local context attention network and a global context attention network. LGCNet makes use of information extracted through the task, dimension and scale. Specifically, a global context attention network is developed for capturing multiple-scale features, and a local context attention network is designed for specific tasks. Thereafter, both networks are aggregated, and the learning network is designed to balance all the tasks by combining the loss functions of the classification and segmentation. The main advantage of LGCNet is its dedicated network for a specific task. The proposed model is evaluated by considering the BraTS2019 dataset with different metrics, such as the Dice score, sensitivity, specificity and Hausdorff score. Comparative analysis with the existing model shows marginal improvement and provides scope for further research into BT segmentation and classification. The scope of this study focuses on the BraTS2019 dataset, with future work aiming to extend the applicability of the model to different clinical and imaging environments. Full article

(This article belongs to the Section Biosignal Processing)

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13 pages, 564 KiB

Open AccessArticle

Evidence for the Link Between Non-Motor Symptoms, Kinematic Gait Parameters, and Physical Function in People with Parkinson’s Disease

by Eren Timurtas, Ahmed-Abou Sharkh, Kedar K. V. Mate, Helen Dawes and Nancy E. Mayo

Bioengineering 2025, 12(5), 551; https://doi.org/10.3390/bioengineering12050551 - 21 May 2025

Abstract

Background: Parkinson’s disease (PD) affects both motor and non-motor functions, but their interactions are understudied. This study aims to explore the relationships between non-motor and motor effects of PD, focusing on depression, fatigue, gait parameters, concentration, and physical function. Methods: This is a [...] Read more.

Background: Parkinson’s disease (PD) affects both motor and non-motor functions, but their interactions are understudied. This study aims to explore the relationships between non-motor and motor effects of PD, focusing on depression, fatigue, gait parameters, concentration, and physical function. Methods: This is a secondary analysis of baseline data from a randomized feasibility study using a commercially available Heel2Toe™ sensor, providing auditory feedback for gait quality. The sample included PD patients with gait impairments who walked without aids. Non-motor measures were depression, fatigue, and concentration, while motor measures included gait quality (angular velocity and variability during heel strike, push-off, foot swing) and physical function (6MWT, Mini-BESTest, Neuro-QoL). Path analysis was used to assess direct and indirect effects. Results: Among 27 participants, fatigue impacted heel strike, which affected Neuro-QoL. Mood influenced push-off and Neuro-QoL, with a direct link to 6MWT. Foot swing affected Mini-BESTest and Neuro-QoL directly. Conclusions: Non-motor PD effects directly influenced specific gait parameters and physical function indicators, highlighting potential digital biomarkers of fatigue and mood for targeted interventions. Full article

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

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21 pages, 43908 KiB

Open AccessArticle

WHA-Net: A Low-Complexity Hybrid Model for Accurate Pseudopapilledema Classification in Fundus Images

by Junpeng Pei, Yousong Wang, Mingliang Ge, Jun Li, Yixing Li, Wei Wang and Xiaohong Zhou

Bioengineering 2025, 12(5), 550; https://doi.org/10.3390/bioengineering12050550 - 21 May 2025

Abstract

The fundus manifestations of pseudopapilledema closely resemble those of optic disc edema, making their differentiation particularly challenging in certain clinical situations. However, rapid and accurate diagnosis is crucial for alleviating patient anxiety and guiding treatment strategies. This study proposes an efficient low-complexity hybrid [...] Read more.

The fundus manifestations of pseudopapilledema closely resemble those of optic disc edema, making their differentiation particularly challenging in certain clinical situations. However, rapid and accurate diagnosis is crucial for alleviating patient anxiety and guiding treatment strategies. This study proposes an efficient low-complexity hybrid model, WHA-Net, which innovatively integrates three core modules to achieve precise auxiliary diagnosis of pseudopapilledema. First, the wavelet convolution (WTC) block is introduced to enhance the model’s characterization capability for vessel and optic disc edge details in fundus images through 2D wavelet transform and deep convolution. Additionally, the hybrid attention inverted residual (HAIR) block is incorporated to extract critical features such as vascular morphology, hemorrhages, and exudates. Finally, the Agent-MViT module effectively captures the continuity features of optic disc contours and retinal vessels in fundus images while reducing the computational complexity of traditional Transformers. The model was trained and evaluated on a dataset of 1793 rigorously curated fundus images, comprising 895 normal optic discs, 485 optic disc edema (ODE), and 413 pseudopapilledema (PPE) cases. On the test set, the model achieved outstanding performance, with 97.79% accuracy, 95.55% precision, 95.69% recall, and 98.53% specificity. Comparative experiments confirm the superiority of WHA-Net in classification tasks, while ablation studies validate the effectiveness and rationality of each module’s combined design. This research provides a clinically valuable solution for the automated differential diagnosis of pseudopapilledema, with both computational efficiency and diagnostic reliability. Full article

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

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12 pages, 666 KiB

Open AccessArticle

Evaluation of Orthodontic Mini-Implants’ Stability Based on Insertion and Removal Torques: An Experimental Study

by Primavera Sousa-Santos, Sofia Sousa-Santos, Ana Catarina Oliveira, Cíntia Queirós, Joana Mendes, Carlos Aroso and José Manuel Mendes

Bioengineering 2025, 12(5), 549; https://doi.org/10.3390/bioengineering12050549 - 20 May 2025

Abstract

Orthodontic mini-implants (MIs) are excellent alternative skeletal anchorage devices. Their stability is important for their survival, requiring appropriate torque application during insertion and removal. Objective: This study aimed to evaluate the influences of the diameter and brand of MIs on their stability by [...] Read more.

Orthodontic mini-implants (MIs) are excellent alternative skeletal anchorage devices. Their stability is important for their survival, requiring appropriate torque application during insertion and removal. Objective: This study aimed to evaluate the influences of the diameter and brand of MIs on their stability by measuring the maximum insertion and removal torques after they had been aged in a pH 7 artificial saliva for 4 weeks at 37 °C. Methods: Forty Ti6Al4V alloy MIs of two different brands and diameters were divided into four groups. They were placed in artificial bone blocks using the NSK^® Surgic Pro coupled with a digital torque gauge (Centor Touch Star TH^®) to measure the maximum insertion and removal torques. Results: After ageing, the Fatscrew (Fts) MIs were more stable when removed than the white brand (WB) MIs. The WB MIs lost stability over time, while the Fts MIs—especially the 2.0 mm ones—maintained good stability. Conclusions: The significant differences between the tested groups, especially the stability observed in the 2.0 mm Fts MIs compared to the other groups, highlight the importance of brand and diameter size in the effectiveness of MIs. Full article

(This article belongs to the Special Issue Orthodontic Biomechanics)

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47 pages, 7533 KiB

Open AccessReview

Integrating Artificial Intelligence and Precision Therapeutics for Advancing the Diagnosis and Treatment of Age-Related Macular Degeneration

by Mini Han Wang

Bioengineering 2025, 12(5), 548; https://doi.org/10.3390/bioengineering12050548 - 20 May 2025

Abstract

Age-related macular degeneration (AMD) is a multifactorial retinal disease influenced by complex molecular mechanisms, including genetic susceptibility, inflammation, oxidative stress, and metabolic dysregulation. While substantial progress has been made in understanding its pathogenesis, the full molecular underpinnings of AMD remain unclear, impeding the [...] Read more.

Age-related macular degeneration (AMD) is a multifactorial retinal disease influenced by complex molecular mechanisms, including genetic susceptibility, inflammation, oxidative stress, and metabolic dysregulation. While substantial progress has been made in understanding its pathogenesis, the full molecular underpinnings of AMD remain unclear, impeding the effectiveness of current therapeutic strategies. This study provides an in-depth exploration of the molecular interactions involved in AMD progression, particularly focusing on genetic predispositions (such as CFH, ARMS2/HTRA1, and APOE), inflammatory pathways (including complement system dysregulation and cytokine responses), lipid metabolism (e.g., cholesterol homeostasis and drusen formation), and angiogenesis (VEGF signaling). Through a systematic review and bibliometric analysis of literature published between 2015 and 2025, the study identifies emerging research trends, existing gaps, and promising future therapeutic directions. It further investigates innovative precision medicine approaches, including gene editing (CRISPR), RNA therapeutics (siRNA, antisense oligonucleotides), immunomodulatory therapies, and nanotechnology-based drug delivery systems. Additionally, the study examines the role of metabolic disorders such as diabetes and dyslipidemia in AMD progression, highlighting the influence of systemic health factors on disease onset. Finally, the potential of artificial intelligence (AI) in enhancing AMD management through biomarker-based risk stratification, predictive modeling, and personalized treatment optimization is assessed. By mapping the intricate molecular networks underlying AMD and evaluating novel therapeutic strategies, this research aims to contribute to the development of more effective, individualized treatment protocols for patients with AMD. Full article

(This article belongs to the Special Issue Artificial Intelligence for Computer-Aided Detection in Biomedical Applications)

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37 pages, 6055 KiB

Open AccessReview

Recycled Sericin Biopolymer in Biotechnology and Bioelectronics

by Davide Vurro, Aris Liboà, Ilenia D’Onofrio, Giuseppe De Giorgio, Zirong Zhou, Vardan Galstyan, Yajie Qin, Xiongchuan Huang, Pasquale D’Angelo and Giuseppe Tarabella

Bioengineering 2025, 12(5), 547; https://doi.org/10.3390/bioengineering12050547 - 20 May 2025

Abstract

In a world characterized by rapid industrialization and a growing population, plastic or polymeric waste handling has undergone significant transformations. Recycling has become a major strategy where silk sericin has great potential among recyclable polymers. This naturally occurring biopolymer is a sustainable and [...] Read more.

In a world characterized by rapid industrialization and a growing population, plastic or polymeric waste handling has undergone significant transformations. Recycling has become a major strategy where silk sericin has great potential among recyclable polymers. This naturally occurring biopolymer is a sustainable and versatile material with a wide range of potential uses in biotechnology and sensing. Furthermore, preparing and studying new environmentally friendly functional polymers with attractive physicochemical properties can open new opportunities for developing next-generation materials and composites. Herein, we provide an overview of the advances in the research studies of silk sericin as a functional and eco-friendly material, considering its biocompatibility and unique physicochemical properties. The structure of silk sericin and the extraction procedures, considering the influence of preparation methods on its properties, are described. Sericin’s intrinsic properties, including its ability to crosslink with other polymers, its antioxidative capacity, and its biocompatibility, render it a versatile material for multifunctional applications across diverse fields. In biotechnology, the ability to blend sericin with other polymers enables the preparation of materials with varied morphologies, such as films and scaffolds, exhibiting enhanced mechanical strength and anti-inflammatory effects. This combination proves particularly advantageous in tissue engineering and wound healing. Furthermore, the augmentation of mechanical strength, coupled with the incorporation of plasticizers, makes sericin films suitable for the development of epidermal electrodes. Simultaneously, by precisely controlling hydration and permeability, the same material can be tailored for applications in packaging and the food industry. This work highlights the multidisciplinary and multifunctional nature of sericin, emphasizing its broad applicability. Full article

(This article belongs to the Special Issue Engineering Biodegradable-Implant Materials, 2nd Edition)

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21 pages, 4985 KiB

Open AccessArticle

Simulation of a Custom-Made Temporomandibular Joint—An Academic View on an Industrial Workflow

by Annchristin Andres, Kerstin Wickert, Elena Gneiting, Franziska Binmoeller, Stefan Diebels and Michael Roland

Bioengineering 2025, 12(5), 545; https://doi.org/10.3390/bioengineering12050545 - 20 May 2025

Abstract

Temporomandibular joint replacement is a critical intervention for severe temporomandibular joint disorders, enhancing pain levels, jaw function and overall quality of life. In this study, we compare two finite element method-based simulation workflows from both academic and industrial perspectives, focusing on a patient-specific [...] Read more.

Temporomandibular joint replacement is a critical intervention for severe temporomandibular joint disorders, enhancing pain levels, jaw function and overall quality of life. In this study, we compare two finite element method-based simulation workflows from both academic and industrial perspectives, focusing on a patient-specific case involving a custom-made temporomandibular joint prosthesis. Using computed tomography data and computer-aided design data, we generated different 3D models and performed mechanical testing, including wear and static compression tests. Our results indicate that the academic workflow, which is retrospective, purely image-based and applied post-operatively, produced peak stress values within 9–20% of those obtained from the industrial workflow. The industrial workflow is prospective, pre-operative, computer-aided design-based and guided by stringent regulatory standards and approval protocols. Observed differences between workflows were attributed primarily to distinct modelling assumptions, simplifications and constraints inherent in each method. To explicitly quantify these differences, multiple additional models were generated within the academic workflow using partial data from the industrial process, revealing specific sources of variation in stress distribution and implant performance. The findings underscore the potential of patient-specific simulations not only to refine temporomandibular joint prosthesis design and enhance patient outcomes, but also to highlight the interplay between academic research methodologies and industrial standards in the development of medical devices. 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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17 pages, 1910 KiB

Open AccessArticle

The Characterization of Serum-Free Media on Human Mesenchymal Stem Cell Fibrochondrogenesis

by Ka Yu Carissa Kwan, Ke Li, Yu Yang Wang, Wai Yi Tse, Chung Yan Tong, Xu Zhang, Dan Michelle Wang and Dai Fei Elmer Ker

Bioengineering 2025, 12(5), 546; https://doi.org/10.3390/bioengineering12050546 - 19 May 2025

Abstract

Developing fibrochondrogenic serum-free media is important for regenerating diseased and injured fibrocartilage but no defined protocols exist. Towards this goal, we characterized the effect of four candidate fibrochondrogenic serum-free media containing transforming growth factor beta-3 (TGF-β3), insulin-like growth factor-1 (IGF-1), and fibroblast growth [...] Read more.

Developing fibrochondrogenic serum-free media is important for regenerating diseased and injured fibrocartilage but no defined protocols exist. Towards this goal, we characterized the effect of four candidate fibrochondrogenic serum-free media containing transforming growth factor beta-3 (TGF-β3), insulin-like growth factor-1 (IGF-1), and fibroblast growth factor-2 (FGF-2) with high/low glucose and with/without dexamethasone on human mesenchymal stem cells (hMSCs) via proliferation and differentiation assays. In Ki67 proliferation assays, serum-free media containing low glucose and dexamethasone exhibited the highest growth. In gene expression assays, serum-free media containing low glucose and commercially available chondrogenic media (COM) induced high fibrochondrogenic transcription factor expression (scleraxis/SCX and SRY-Box Transcription Factor 9/SOX9) and extracellular matrix (ECM) protein levels (aggrecan/ACAN, collagen type I/COL1A1, and collagen type II/COL2A1), respectively. In immunofluorescence staining, serum-free media containing high glucose and COM induced high fibrochondrogenic transcription factor (SCX and SOX9) and ECM protein (COL1A1, COL2A1, and collagen type X/COL10A1) levels, respectively. In cytochemical staining, COM and serum-free media containing dexamethasone showed a high collagen content whereas serum-free media containing high glucose and dexamethasone exhibited high glycosaminoglycan (GAG) levels. Altogether, defined serum-free media containing high glucose exhibited the highest fibrochondrogenic potential. In summary, this work studied conditions conducive for fibrochondrogenesis, which may be further optimized for potential applications in fibrocartilage tissue engineering. Full article

(This article belongs to the Special Issue Tendon/Ligament and Enthesis Injuries: Repair and Regeneration)

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Graphical abstract

15 pages, 1280 KiB

Open AccessArticle

A Comparison of Machine Learning-Based Models and a Simple Clinical Bedside Tool to Predict Morbidity and Mortality After Gastrointestinal Cancer Surgery in the Elderly

by Barbara Frezza, Mario Cesare Nurchis, Gabriella Teresa Capolupo, Filippo Carannante, Marco De Prizio, Fabio Rondelli, Danilo Alunni Fegatelli, Alessio Gili, Luca Lepre and Gianluca Costa

Bioengineering 2025, 12(5), 544; https://doi.org/10.3390/bioengineering12050544 - 19 May 2025

Abstract

Frailty in the elderly population is associated with increased vulnerability to stressors, including surgical interventions. This study compared machine learning (ML) models with a clinical bedside tool, the Gastrointestinal Surgery Frailty Index (GiS-FI), for predicting mortality and morbidity in elderly patients undergoing gastrointestinal [...] Read more.

Frailty in the elderly population is associated with increased vulnerability to stressors, including surgical interventions. This study compared machine learning (ML) models with a clinical bedside tool, the Gastrointestinal Surgery Frailty Index (GiS-FI), for predicting mortality and morbidity in elderly patients undergoing gastrointestinal cancer surgery. In a multicenter analysis of 937 patients aged ≥65 years, the performance of various predictive models including Random Forest (RF), Least Absolute Shrinkage and Selection Operator (LASSO), Stepwise Regression, K-Nearest Neighbors, Neural Network, and Support Vector Machine algorithms were evaluated. The overall 30-day mortality and morbidity rates were 6.1% and 35.7%, respectively. For mortality prediction, the RF model demonstrated superior performance with an AUC of 0.822 (95% CI 0.714–0.931), outperforming the GiS-FI score (AUC = 0.772, 95% CI 0.675–0.868). For morbidity prediction, all models showed more modest discrimination, with stepwise regression and LASSO regression achieving the highest performance (AUCs of 0.652 and 0.647, respectively). Our findings suggest that ML approaches, particularly RF algorithm, offer enhanced predictive accuracy compared to traditional clinical scores for mortality risk assessment in elderly cancer patients undergoing gastrointestinal surgery. These advanced analytical tools could provide valuable decision support for surgical risk stratification in this vulnerable population. Full article

(This article belongs to the Special Issue Medical Artificial Intelligence and Data Analysis)

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14 pages, 1208 KiB

Open AccessReview

Zirconia in Dental Implantology: A Review of the Literature with Recent Updates

by Sami Aldhuwayhi

Bioengineering 2025, 12(5), 543; https://doi.org/10.3390/bioengineering12050543 - 19 May 2025

Abstract

Zirconia dental implants have emerged as a transformative material in implantology, offering a biocompatible, esthetic, and durable alternative to traditional titanium implants. This comprehensive review explores the key properties of zirconia, including high fracture resistance, esthetic superiority, and low bacterial affinity. The ability [...] Read more.

Zirconia dental implants have emerged as a transformative material in implantology, offering a biocompatible, esthetic, and durable alternative to traditional titanium implants. This comprehensive review explores the key properties of zirconia, including high fracture resistance, esthetic superiority, and low bacterial affinity. The ability of zirconia to integrate with bone through osseointegration, coupled with its resistance to plaque and inflammation, results in a product that is particularly suitable for patients with metal sensitivities or high esthetic demands. However, challenges such as brittleness and complex manufacturing processes persist. Advances in surface modification techniques and material optimization are poised to address these limitations, paving the way for broader applications. The purpose of this descriptive review was to emphasize the mechanical, antibacterial, osteointegration and survival rates of zirconia implants. This paper also summarizes findings from recent empirical studies, highlighting zirconia’s clinical performance, biological responses, and future potential as a mainstream implant material. Full article

(This article belongs to the Special Issue Translational Advances in Dental Implants)

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