Bioengineering

49 pages, 8327 KiB

Open AccessReview

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

by Günter A. Müller

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

Viewed by 663

Abstract

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

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

(This article belongs to the Section Biochemical Engineering)

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10 pages, 1250 KiB

Open AccessCommunication

Robustness of the Cupriavidus necator-Catalyzed Production of α-Humulene

by Lucas Becker, Emely Dietz and Dirk Holtmann

Bioengineering 2025, 12(3), 323; https://doi.org/10.3390/bioengineering12030323 - 20 Mar 2025

Viewed by 254

Abstract

The increasing global demand for natural substances such as the sesquiterpene α-humulene makes optimizing microbial production essential. A production process using the versatile host Cupriavidus necator has been recently improved by adjusting the minimal media and process parameters. Understanding microbial and process robustness [...] Read more.

The increasing global demand for natural substances such as the sesquiterpene α-humulene makes optimizing microbial production essential. A production process using the versatile host Cupriavidus necator has been recently improved by adjusting the minimal media and process parameters. Understanding microbial and process robustness is key to ensuring consistent performance under different conditions. This study is the first to investigate and quantify the robustness of microbial α-humulene production and biomass formation using C. necator pKR-hum. Established process improvements and the impact of common or individual precultures were analyzed and quantified for their effect on the robustness of product and biomass formation. We report a robust α-humulene production process with even more consistent biomass formation using C. necator pKR-hum. Even with a simulated process disturbance, 79% of the maximum α-humulene level was still produced. Overall, our results show that the α-humulene production process using C. necator pKR-hum is highly robust, demonstrating its resilience to process disturbances and suitability for further industrial applications. Full article

(This article belongs to the Section Biochemical Engineering)

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15 pages, 2888 KiB

Open AccessArticle

Kolmogorov–Arnold Network Model Integrated with Hypoxia Risk for Predicting PD-L1 Inhibitor Responses in Hepatocellular Carcinoma

by Mohan Huang, Xinyue Chen, Yi Jiang and Lawrence Wing Chi Chan

Bioengineering 2025, 12(3), 322; https://doi.org/10.3390/bioengineering12030322 - 20 Mar 2025

Viewed by 401

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths, with immunotherapy being a first-line treatment at the advanced stage and beyond. Hypoxia plays a critical role in tumor progression and resistance to therapy. This study develops and validates an artificial intelligence (AI) [...] Read more.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths, with immunotherapy being a first-line treatment at the advanced stage and beyond. Hypoxia plays a critical role in tumor progression and resistance to therapy. This study develops and validates an artificial intelligence (AI) model based on publicly available genomic datasets to predict hypoxia-related immunotherapy responses. Based on the HCC-Hypoxia Overlap (HHO) and immunotherapy response to hypoxia (IRH) genes selected by differential expression and enrichment analyses, a hypoxia model was built and validated on the TCGA-LIHC and GSE233802 datasets, respectively. The training and test sets were assembled from the EGAD00001008128 dataset of 290 HCC patients, and the response and non-response classes were balanced using the Synthetic Minority Over-sampling Technique. With the genes selected via the minimum Redundancy Maximum Relevance and stepwise forward methods, a Kolmogorov–Arnold Network (KAN) model was trained. Support Vector Machine (SVM) combined the Hypoxia and KAN models to predict immunotherapy response. The hypoxia model was constructed using 10 genes (IRH and HHO). The KAN model with 11 genes achieved a test accuracy of 0.7. The SVM integrating the hypoxia and KAN models achieved a test accuracy of 0.725. The established AI model can predict immunotherapy response based on hypoxia risk and genomic factors potentially intervenable in HCC patients. Full article

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

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17 pages, 1489 KiB

Open AccessArticle

Interpretable Machine Learning Predictions of Bruch’s Membrane Opening-Minimum Rim Width Using Retinal Nerve Fiber Layer Values and Visual Field Global Indexes

by Sat Byul Seo and Hyun-kyung Cho

Bioengineering 2025, 12(3), 321; https://doi.org/10.3390/bioengineering12030321 - 20 Mar 2025

Viewed by 297

Abstract

The aim of this study was to predict Bruch’s membrane opening-minimum rim Width (BMO-MRW), a relatively new parameter using conventional optical coherence tomography (OCT) parameter, using retinal nerve fibre layer (RNFL) thickness and visual field (VF) global indexes (MD, PSD, and VFI). We [...] Read more.

The aim of this study was to predict Bruch’s membrane opening-minimum rim Width (BMO-MRW), a relatively new parameter using conventional optical coherence tomography (OCT) parameter, using retinal nerve fibre layer (RNFL) thickness and visual field (VF) global indexes (MD, PSD, and VFI). We developed an interpretable machine learning model that integrates structural and functional parameters to predict BMO-MRW. The model achieved the highest predictive accuracy in the inferotemporal sector (R² = 0.68), followed by the global region (R² = 0.67) and the superotemporal sector (R² = 0.64). Through SHAP (SHapley Additive exPlanations) analysis, we demonstrated that RNFL parameters were significant contributing parameters to the prediction of various BMO-MRW parameters, with age and PSD also identified as critical factors. Our machine learning model could provide useful clinical information about the management of glaucoma when BMO-MRW is not available. Our machine learning model has the potential to be highly beneficial in clinical practice for glaucoma diagnosis and the monitoring of disease progression. Full article

(This article belongs to the Special Issue Translational AI and Computational Tools for Ophthalmic Disease)

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4 pages, 395 KiB

Open AccessEditorial

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

by Tien-Tuan Dao

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

Viewed by 256

Abstract

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

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

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22 pages, 2752 KiB

Open AccessArticle

Direct Consideration of Process History During Intensified Design of Experiments Planning Eases Interpretation of Mammalian Cell Culture Dynamics

by Samuel Kienzle, Lisa Junghans, Stefan Wieschalka, Katharina Diem, Ralf Takors, Nicole Erika Radde, Marco Kunzelmann, Beate Presser and Verena Nold

Bioengineering 2025, 12(3), 319; https://doi.org/10.3390/bioengineering12030319 - 19 Mar 2025

Viewed by 263

Abstract

Intra-experimental factor setting shifts in intensified design of experiments (iDoE) enhance understanding of bioproduction processes by capturing their dynamics and are thus essential to fulfill quality by design (QbD) ambitions. Determining the influence of process history on the cellular responses, often referred to [...] Read more.

Intra-experimental factor setting shifts in intensified design of experiments (iDoE) enhance understanding of bioproduction processes by capturing their dynamics and are thus essential to fulfill quality by design (QbD) ambitions. Determining the influence of process history on the cellular responses, often referred to as memory effect, is fundamental for accurate predictions. However, the current iDoE designs do not explicitly consider nor quantify the influence of process history. Therefore, we propose the one-factor-multiple-columns (OFMC)-format for iDoE planning. This format explicitly describes stage-dependent factor effects and potential memory effects as across-stage interactions (ASIs) during a bioprocess. To illustrate its utility, an OFMC-iDoE that considers the characteristic growth phases during a fed-batch process was planned. Data were analyzed using ordinary least squares (OLS) regression as previously described via stage-wise analysis of the time series and compared to direct modeling of end-of-process outcomes enabled by the OFMC-format. This article aims to provide the reader with a framework on how to plan and model iDoE data and highlights how the OFMC-format simplifies planning, and data acquisition, eases modeling and gives a straightforward quantification of potential memory effects. With the proposed OFMC-format, optimization of bioprocesses can leverage which factor settings are most beneficial in which state of the mammalian culture and thus elevate performance and quality to the next level. Full article

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

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15 pages, 7016 KiB

Open AccessArticle

Finite Element Analysis of the Effects of Different Shapes of Adult Cranial Sutures on Their Mechanical Behavior

by Han Yang, Shiguo Yuan, Yuan Yan, Li Zhou, Chao Zheng, Yikai Li and Junhua Li

Bioengineering 2025, 12(3), 318; https://doi.org/10.3390/bioengineering12030318 - 19 Mar 2025

Viewed by 594

Abstract

Cranial sutures play critical roles in load distribution and neuroprotection, with their biomechanical performance intimately linked to morphological complexity. The purpose of this study was to investigate the effect of different morphologies of cranial sutures on their biomechanical behavior. Based on the different [...] Read more.

Cranial sutures play critical roles in load distribution and neuroprotection, with their biomechanical performance intimately linked to morphological complexity. The purpose of this study was to investigate the effect of different morphologies of cranial sutures on their biomechanical behavior. Based on the different morphologies of the cranial sutures, six groups of finite element models (closed, straight, sine wave, tight sinusoidal wave, layered sinusoidal wave, and layered sinusoidal wave + sutural bone) of the bone–suture–bone composite structures that ranged from simple to complex were constructed. Each model was subjected to 50 kPa impact and 98 N bilateral tensile loads to evaluate von Mises stress and total deformation variations across all groups under combined loading conditions. Key findings reveal that morphological complexity directly governs stress dynamics and mechanical adaptation; layered sinusoidal configurations delayed peak stress by 19–36% and generated elevated von Mises stresses compared to closed sutures, with stress concentrations correlating with interfacial roughness. Under impact, sutures exhibited localized energy dissipation (<0.2 μm deformation), while tensile loading induced uniform displacements (≤11 μm) across all morphologies (p > 0.05), underscoring their dual roles in localized energy absorption and global strain redistribution. Craniosacral therapy relevant forces produced sub-micron deformations far below pathological thresholds (≥1 mm), which implies the biomechanical safety of recommended therapeutic force. Staggered suture–bone in open sutures (31.93% closure rate) enhances shear resistance, whereas closed sutures prioritize rigidity. The findings provide mechanistic explanations for suture pathological vulnerability and clinical intervention limitations, offering a quantitative foundation for future research on cranial biomechanics and therapeutic innovation. Full article

(This article belongs to the Special Issue Fundamentals and Novel Applications of Fluid Mechanics, Biomechanics, and Acoustics in Biomedical Engineering, 2nd Edition)

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25 pages, 18528 KiB

Open AccessArticle

The Utah Manipulation and Locomotion of Large Objects (MeLLO) Data Library

by Nathaniel G. Luttmer, Nathan I. Baum, Josue Flores-Gonzalez, John M. Hollerbach and Mark A. Minor

Bioengineering 2025, 12(3), 317; https://doi.org/10.3390/bioengineering12030317 - 19 Mar 2025

Viewed by 237

Abstract

The purpose of this paper is to provide researchers with a description of a data library representing human interaction with medium- to large-sized objects in everyday life. The library includes motion capture data characterizing human and object motion, as well as data for [...] Read more.

The purpose of this paper is to provide researchers with a description of a data library representing human interaction with medium- to large-sized objects in everyday life. The library includes motion capture data characterizing human and object motion, as well as data for characterizing haptic interaction with the object via force and torque measurements via a load cell and inertial measurement unit (IMU) readings of the object accelerations. Objects include a box, luggage, briefcase, walker, shopping cart, wheelbarrow, and door. The data collected includes multiple types of interactions with each object, such as manipulating the object and walking while interacting with the object (e.g., pulling, pushing, carrying, operating, etc.). Data processing techniques for synchronizing data, deriving human biomechanics, and segmenting trials are presented. Examples of how the data in the library can be manipulated and processed further are provided. This includes combining ten wheelbarrow lifts of one subject together and analyzing the knee motion, object acceleration, and load cell readings (force and torque) with mean trajectories and standard deviations of the trajectories. From there, the range of motion can be extracted, such as for the hip, knee, and ankle joint minimum angles, maximum angles, and range of motion. A comparison of walking with and without a wheelbarrow is presented using spatiotemporal parameters and cyclograms to demonstrate their differences. The database is available on AddBiomechanics, SimTK, and GitHub. Full article

(This article belongs to the Special Issue Biomechanics and Motion Analysis)

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11 pages, 405 KiB

Open AccessArticle

Exploring the Association of Hallux Limitus with Baropodometric Gait Pattern Changes

by Natalia Tovaruela-Carrión, Ricardo Becerro-de-Bengoa-Vallejo, Marta Elena Losa-Iglesias, Daniel López-López, Juan Gómez-Salgado and Javier Bayod-López

Bioengineering 2025, 12(3), 316; https://doi.org/10.3390/bioengineering12030316 - 19 Mar 2025

Viewed by 412

Abstract

Background: Hallux limitus (HL) is a condition marked by the restricted dorsiflexion of the first metatarsophalangeal joint, causing pain and functional limitations, especially during the propulsive phase of walking. This restriction affects the gait, particularly in the final phase, and impairs foot stability [...] Read more.

Background: Hallux limitus (HL) is a condition marked by the restricted dorsiflexion of the first metatarsophalangeal joint, causing pain and functional limitations, especially during the propulsive phase of walking. This restriction affects the gait, particularly in the final phase, and impairs foot stability and support. HL is more common in adults and leads to biomechanical and functional adaptations. The purpose of this study was to investigate the differences in the center of pressure between subjects with hallux limitus and those with healthy feet. Methods: A total of 80 participants (40 with bilateral HL and 40 healthy controls) aged 18 to 64 were selected from a biomechanics center at the Universidade da Coruña, Spain. The gait analysis focused on three key phases: initial contact, forefoot contact, and the loading response. Data were collected using a portable baropodometric platform and analyzed using IBM SPSS Statistics 29.0.2.0; statistical significance was set at p < 0.05, with a 95% confidence interval. Results: The gait analysis indicated that the case group exhibited statistically significant differences, showing lower values in the left foot load response during the foot contact time (77.83 ± 40.17) compared to the control group (100.87 ± 29.27) (p = 0. 010) and in the foot contact percentage (p = 0. 013) during the stance phase (10.02 ± 5.68) compared to the control group (13.05 ± 3.60). Conclusions: Bilateral HL causes subtle gait changes, with individuals showing greater contact time values in the total stance phase versus the control group. Early detection may improve quality of life and prevent complications. Full article

(This article belongs to the Special Issue Biomechanics and Motion Analysis)

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20 pages, 4600 KiB

Open AccessArticle

Investigation of the Effects of 3D Printing Parameters on the Mechanical Properties of Bone Scaffolds: Experimental Study Integrated with Artificial Neural Networks

by Rixiang Quan, Sergio Cantero Chinchilla and Fengyuan Liu

Bioengineering 2025, 12(3), 315; https://doi.org/10.3390/bioengineering12030315 - 19 Mar 2025

Viewed by 364

Abstract

Scaffolds are critical in regenerative medicine, particularly in bone tissue engineering, where they mimic the extracellular matrix to support tissue regeneration. Scaffold efficacy depends on precise control of 3D printing parameters, which determine geometric and mechanical properties, including Young’s modulus. This study examines [...] Read more.

Scaffolds are critical in regenerative medicine, particularly in bone tissue engineering, where they mimic the extracellular matrix to support tissue regeneration. Scaffold efficacy depends on precise control of 3D printing parameters, which determine geometric and mechanical properties, including Young’s modulus. This study examines the impact of nozzle temperature, printing speed, and feed rate on the Young’s modulus of polylactic acid (PLA) scaffolds. Using a Prusa MINI+ 3D printer (Prusa Research a.s., Prague, Czech Republic), systematic experiments are conducted to explore these correlations. Results show that higher nozzle temperatures decrease Young’s modulus due to reduced viscosity and weaker interlayer bonding, likely caused by thermal degradation and reduced crystallinity. Printing speed exhibits an optimal range, with Young’s modulus peaking at moderate speeds (around 2100 mm/min), suggesting a balance that enhances crystallinity and bonding. Material feed rate positively correlates with Young’s modulus, with increased material deposition improving scaffold density and strength. The integration of an Artificial Neural Network (ANN) model further optimized the printing parameters, successfully predicting the maximum Young’s modulus while maintaining geometric constraints. Notably, the Young’s modulus achieved falls within the typical range for cancellous bone, indicating the model’s potential to meet specific clinical requirements. These findings offer valuable insights for designing patient-specific bone scaffolds, potentially improving clinical outcomes in bone repair. Full article

(This article belongs to the Section Biosignal Processing)

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15 pages, 2573 KiB

Open AccessArticle

Development and Metrological Characterization of Low-Cost Wearable Pulse Oximeter

by Andrea Cataldo, Enrico Cataldo, Antonio Masciullo and Raissa Schiavoni

Bioengineering 2025, 12(3), 314; https://doi.org/10.3390/bioengineering12030314 - 19 Mar 2025

Viewed by 433

Abstract

Pulse oximetry is essential for monitoring arterial oxygen saturation (

S p O_{2}

) and heart rate (HR) in various medical scenarios. However, the traditional pulse oximeters face challenges related to high costs, motion artifacts, and susceptibility to ambient light interference. This [...] Read more.

Pulse oximetry is essential for monitoring arterial oxygen saturation (

S p O_{2}

) and heart rate (HR) in various medical scenarios. However, the traditional pulse oximeters face challenges related to high costs, motion artifacts, and susceptibility to ambient light interference. This work presents a low-cost experimental pulse oximeter prototype designed to address these limitations through design advancements. The device incorporates a 3D-printed finger support to minimize motion artifacts and excessive capillary pressure, along with an elastic element to enhance stability. Unlike conventional transmission-based oximetry, the prototype employs a reflectance-based measurement approach, improving versatility and enabling reliable readings even in cases of poor peripheral perfusion. Additionally, the integration of light-shielding materials mitigates the effects of ambient illumination, ensuring accurate operation in challenging environments such as surgical settings. Metrological characterization demonstrates that the prototype achieves accuracy comparable to that of the commercial GIMA Oxy-50 pulse oximeter while maintaining a production cost at approximately one-tenth of the commercial alternatives. This study highlights the potential of the prototype to deliver affordable and reliable pulse oximetry for different applications. Full article

(This article belongs to the Special Issue 10th Anniversary of Bioengineering: Biosignal Processing)

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Graphical abstract

19 pages, 1827 KiB

Open AccessSystematic Review

Advancing Gait Analysis: Integrating Multimodal Neuroimaging and Extended Reality Technologies

by Vera Gramigna, Arrigo Palumbo and Giovanni Perri

Bioengineering 2025, 12(3), 313; https://doi.org/10.3390/bioengineering12030313 - 19 Mar 2025

Viewed by 473

Abstract

The analysis of human gait is a cornerstone in diagnosing and monitoring a variety of neuromuscular and orthopedic conditions. Recent technological advancements have paved the way for innovative methodologies that combine multimodal neuroimaging and eXtended Reality (XR) technologies to enhance the precision and [...] Read more.

The analysis of human gait is a cornerstone in diagnosing and monitoring a variety of neuromuscular and orthopedic conditions. Recent technological advancements have paved the way for innovative methodologies that combine multimodal neuroimaging and eXtended Reality (XR) technologies to enhance the precision and applicability of gait analysis. This review explores the state-of-the-art solutions of an advanced gait analysis approach, a multidisciplinary concept that integrates neuroimaging, extended reality technologies, and sensor-based methods to study human locomotion. Several wearable neuroimaging modalities such as functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), commonly used to monitor and analyze brain activity during walking and to explore the neural mechanisms underlying motor control, balance, and gait adaptation, were considered. XR technologies, including virtual, augmented, and mixed reality, enable the creation of immersive environments for gait analysis, real-time simulation, and movement visualization, facilitating a comprehensive assessment of locomotion and its neural and biomechanical dynamics. This advanced gait analysis approach enhances the understanding of gait by examining both cerebral and biomechanical aspects, offering insights into brain–musculoskeletal coordination. We highlight its potential to provide real-time, high-resolution data and immersive visualization, facilitating improved clinical decision-making and rehabilitation strategies. Additionally, we address the challenges of integrating these technologies, such as data fusion, computational demands, and scalability. The review concludes by proposing future research directions that leverage artificial intelligence to further optimize multimodal imaging and XR applications in gait analysis, ultimately driving their translation from laboratory settings to clinical practice. This synthesis underscores the transformative potential of these approaches for personalized medicine and patient outcomes. Full article

(This article belongs to the Special Issue Multimodal Imaging Methodologies and Virtual/Augmented Reality for Biomedical Applications)

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45 pages, 3030 KiB

Open AccessReview

Leveraging Artificial Intelligence and Machine Learning for Characterizing Protein Corona, Nanobiological Interactions, and Advancing Drug Discovery

by Turkan Kopac

Bioengineering 2025, 12(3), 312; https://doi.org/10.3390/bioengineering12030312 - 18 Mar 2025

Viewed by 483

Abstract

Proteins are essential for all living organisms, playing key roles in biochemical reactions, structural support, signal transduction, and gene regulation. Their importance in biomedical research is highlighted by their role as drug targets in various diseases. The interactions between proteins and nanoparticles (NPs), [...] Read more.

Proteins are essential for all living organisms, playing key roles in biochemical reactions, structural support, signal transduction, and gene regulation. Their importance in biomedical research is highlighted by their role as drug targets in various diseases. The interactions between proteins and nanoparticles (NPs), including the protein corona’s formation, significantly affect NP behavior, biodistribution, cellular uptake, and toxicity. Comprehending these interactions is pivotal for advancing the design of NPs to augment their efficacy and safety in biomedical applications. While traditional nanomedicine design relies heavily on experimental work, the use of data science and machine learning (ML) is on the rise to predict the synthesis and behavior of nanomaterials (NMs). Nanoinformatics combines computational simulations with laboratory studies, assessing risks and revealing complex nanobio interactions. Recent advancements in artificial intelligence (AI) and ML are enhancing the characterization of the protein corona and improving drug discovery. This review discusses the advantages and limitations of these approaches and stresses the importance of comprehensive datasets for better model accuracy. Future developments may include advanced deep-learning models and multimodal data integration to enhance protein function prediction. Overall, systematic research and advanced computational tools are vital for improving therapeutic outcomes and ensuring the safe use of NMs in medicine. Full article

(This article belongs to the Section Nanobiotechnology and Biofabrication)

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15 pages, 1746 KiB

Open AccessArticle

Improved A-Line and B-Line Detection in Lung Ultrasound Using Deep Learning with Boundary-Aware Dice Loss

by Soolmaz Abbasi, Assefa Seyoum Wahd, Shrimanti Ghosh, Maha Ezzelarab, Mahesh Panicker, Yale Tung Chen, Jacob L. Jaremko and Abhilash Hareendranathan

Bioengineering 2025, 12(3), 311; https://doi.org/10.3390/bioengineering12030311 - 18 Mar 2025

Viewed by 431

Abstract

Lung ultrasound (LUS) is a non-invasive bedside imaging technique for diagnosing pulmonary conditions, especially in critical care settings. A-lines and B-lines are important features in LUS images that help to assess lung health and identify changes in lung tissue. However, accurately detecting and [...] Read more.

Lung ultrasound (LUS) is a non-invasive bedside imaging technique for diagnosing pulmonary conditions, especially in critical care settings. A-lines and B-lines are important features in LUS images that help to assess lung health and identify changes in lung tissue. However, accurately detecting and segmenting these lines remains challenging, due to their subtle blurred boundaries. To address this, we propose TransBound-UNet, a novel segmentation model that integrates a transformer-based encoder with boundary-aware Dice loss to enhance medical image segmentation. This loss function incorporates boundary-specific penalties into a hybrid Dice-BCE formulation, allowing for more accurate segmentation of critical structures. The proposed framework was tested on a dataset of 4599 LUS images. The model achieved a Dice Score of 0.80, outperforming state-of-the-art segmentation networks. Additionally, it demonstrated superior performance in Specificity (0.97) and Precision (0.85), with a significantly reduced Hausdorff Distance of 15.13, indicating improved boundary delineation and overall segmentation quality. Post-processing techniques were applied to automatically detect and count A-lines and B-lines, demonstrating the potential of the segmented outputs in diagnostic workflows. This framework provides an efficient solution for automated LUS interpretation, with improved boundary precision. Full article

(This article belongs to the Special Issue Artificial Intelligence in Auto-Diagnosis and Clinical Applications, 2nd Edition)

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20 pages, 1411 KiB

Open AccessArticle

CBR-Net: A Multisensory Emotional Electroencephalography (EEG)-Based Personal Identification Model with Olfactory-Enhanced Video Stimulation

by Rui Ouyang, Minchao Wu, Zhao Lv and Xiaopei Wu

Bioengineering 2025, 12(3), 310; https://doi.org/10.3390/bioengineering12030310 - 18 Mar 2025

Viewed by 347

Abstract

Electroencephalography (EEG)-basedpersonal identification has gained significant attention, but fluctuations in emotional states often affect model accuracy. Previous studies suggest that multisensory stimuli, such as video and olfactory cues, can enhance emotional responses and improve EEG-based identification accuracy. This study proposes a novel deep [...] Read more.

Electroencephalography (EEG)-basedpersonal identification has gained significant attention, but fluctuations in emotional states often affect model accuracy. Previous studies suggest that multisensory stimuli, such as video and olfactory cues, can enhance emotional responses and improve EEG-based identification accuracy. This study proposes a novel deep learning-based model, CNN-BiLSTM-Residual Network (CBR-Net), for EEG-based identification and establishes a multisensory emotional EEG dataset with both video-only and olfactory-enhanced video stimulation. The model includes a convolutional neural network (CNN) for spatial feature extraction, Bi-LSTM for temporal modeling, residual connections, and a fully connected classification module. Experimental results show that olfactory-enhanced video stimulation significantly improves the emotional intensity of EEG signals, leading to better recognition accuracy. The CBR-Net model outperforms video-only stimulation, achieving the highest accuracy for negative emotions (96.59%), followed by neutral (94.25%) and positive emotions (95.42%). Ablation studies reveal that the Bi-LSTM module is crucial for neutral emotions, while CNN is more effective for positive emotions. Compared to traditional machine learning and existing deep learning models, CBR-Net demonstrates superior performance across all emotional states. In conclusion, CBR-Net enhances identity recognition accuracy and validates the advantages of multisensory stimuli in EEG signals. Full article

(This article belongs to the Section Biosignal Processing)

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26 pages, 4369 KiB

Open AccessArticle

Encoder–Decoder Variant Analysis for Semantic Segmentation of Gastrointestinal Tract Using UW-Madison Dataset

by Neha Sharma, Sheifali Gupta, Dalia H. Elkamchouchi and Salil Bharany

Bioengineering 2025, 12(3), 309; https://doi.org/10.3390/bioengineering12030309 - 18 Mar 2025

Viewed by 396

Abstract

The gastrointestinal (GI) tract, an integral part of the digestive system, absorbs nutrients from ingested food, starting from the mouth to the anus. GI tract cancer significantly impacts global health, necessitating precise treatment methods. Radiation oncologists use X-ray beams to target tumors while [...] Read more.

The gastrointestinal (GI) tract, an integral part of the digestive system, absorbs nutrients from ingested food, starting from the mouth to the anus. GI tract cancer significantly impacts global health, necessitating precise treatment methods. Radiation oncologists use X-ray beams to target tumors while avoiding the stomach and intestines, making the accurate segmentation of these organs crucial. This research explores various combinations of encoders and decoders to segment the small bowel, large bowel, and stomach in MRI images, using the UW-Madison GI tract dataset consisting of 38,496 scans. Encoders tested include ResNet50, EfficientNetB1, MobileNetV2, ResNext50, and Timm_Gernet_S, paired with decoders UNet, FPN, PSPNet, PAN, and DeepLab V3+. The study identifies ResNet50 with DeepLab V3+ as the most effective combination, assessed using the Dice coefficient, Jaccard index, and model loss. The proposed model, a combination of DeepLab V3+ and ResNet 50, obtained a Dice value of 0.9082, an IoU value of 0.8796, and a model loss of 0.117. The findings demonstrate the method’s potential to improve radiation therapy for GI cancer, aiding radiation oncologists in accurately targeting tumors while avoiding healthy organs. The results of this study will assist healthcare professionals involved in biomedical image analysis. Full article

(This article belongs to the Special Issue Cutting-Edge Applications of Machine and Deep Learning in Biomedical Signal and Image Processing)

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17 pages, 4169 KiB

Open AccessArticle

Benchmarking Interpretability in Healthcare Using Pattern Discovery and Disentanglement

by Pei-Yuan Zhou, Amane Takeuchi, Fernando Martinez-Lopez, Malikeh Ehghaghi, Andrew K. C. Wong and En-Shiun Annie Lee

Bioengineering 2025, 12(3), 308; https://doi.org/10.3390/bioengineering12030308 - 18 Mar 2025

Viewed by 350

Abstract

The healthcare industry seeks to integrate AI into clinical applications, yet understanding AI decision making remains a challenge for healthcare practitioners as these systems often function as black boxes. Our work benchmarks the Pattern Discovery and Disentanglement (PDD) system’s unsupervised learning algorithm, which [...] Read more.

The healthcare industry seeks to integrate AI into clinical applications, yet understanding AI decision making remains a challenge for healthcare practitioners as these systems often function as black boxes. Our work benchmarks the Pattern Discovery and Disentanglement (PDD) system’s unsupervised learning algorithm, which provides interpretable outputs and clustering results from clinical notes to aid decision making. Using the MIMIC-IV dataset, we process free-text clinical notes and ICD-9 codes with Term Frequency-Inverse Document Frequency and Topic Modeling. The PDD algorithm discretizes numerical features into event-based features, discovers association patterns from a disentangled statistical feature value association space, and clusters clinical records. The output is an interpretable knowledge base linking knowledge, patterns, and data to support decision making. Despite being unsupervised, PDD demonstrated performance comparable to supervised deep learning models, validating its clustering ability and knowledge representation. We benchmark interpretability techniques—Feature Permutation, Gradient SHAP, and Integrated Gradients—on the best-performing models (in terms of F1, ROC AUC, balanced accuracy, etc.), evaluating these based on sufficiency, comprehensiveness, and sensitivity metrics. Our findings highlight the limitations of feature importance ranking and post hoc analysis for clinical diagnosis. Meanwhile, PDD’s global interpretability effectively compensates for these issues, helping healthcare practitioners understand the decision-making process and providing suggestive clusters of diseases to assist their diagnosis. Full article

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

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14 pages, 4736 KiB

Open AccessArticle

Development of Semi-Automated Image-Based Analysis Tool for CBCT Evaluation of Alveolar Ridge Changes After Tooth Extraction

by Anja Heselich, Joanna Śmieszek-Wilczewska, Louisa Boyo, Robert Sader and Shahram Ghanaati

Bioengineering 2025, 12(3), 307; https://doi.org/10.3390/bioengineering12030307 - 18 Mar 2025

Viewed by 292

Abstract

Following tooth extraction, the bone structure is prone to atrophic changes. Alveolar ridge resorption can compromise subsequent implant treatment not only at the extraction site itself but also by affecting the bone support of adjacent teeth. Various techniques, including the use of bone [...] Read more.

Following tooth extraction, the bone structure is prone to atrophic changes. Alveolar ridge resorption can compromise subsequent implant treatment not only at the extraction site itself but also by affecting the bone support of adjacent teeth. Various techniques, including the use of bone graft materials or autologous blood concentrates for ridge or socket preservation, aim to counteract this process. The efficacy of such methods can be evaluated non-invasively through radiological analysis of the treated region. However, existing radiological evaluation methods often focus only on isolated areas of the extraction socket, limiting their accuracy in assessing overall bone regeneration. This study introduces a novel, non-invasive, and semi-automated image-based analysis method that enables a more comprehensive evaluation of bone preservation using CBCT data. Developed with the open-source software “Fiji” (v2.15.0; based on ImageJ), the approach assesses bone changes at multiple horizontal and vertical positions, creating a near three-dimensional representation of the resorptive process. By analyzing the entire region around the extraction socket rather than selected regions, this method provides a more precise and reproducible assessment of alveolar ridge preservation. Although the approach requires some processing time and focuses exclusively on radiological evaluation, it offers greater accuracy than conventional methods. Its standardized and objective nature makes it a valuable tool for clinical research, facilitating more reliable comparisons of different socket preservation strategies. 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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11 pages, 1085 KiB

Open AccessArticle

Can the Novel Photon-Counting CT Scan Accurately Predict Aortic Wall Thickness? Preliminary Results

by Alessandra Sala, Carlo de Vincentiis, Francesco Grimaldi, Barbara Rubino, Manuela Cirami, Noemi Perillo, Renato Vitale, Rosanna Cardani, Sara Boveri, Michele Conti and Pietro Spagnolo

Bioengineering 2025, 12(3), 306; https://doi.org/10.3390/bioengineering12030306 - 18 Mar 2025

Viewed by 296

Abstract

Background: Surgical indication of ascending thoracic aortic aneurysms (ATAA) is generally performed in prevention. Guidelines use aortic diameter as a predictor of rupture and dissection; however, this single parameter alone has a limited value in predicting the real-world risk of acute aortic syndromes. [...] Read more.

Background: Surgical indication of ascending thoracic aortic aneurysms (ATAA) is generally performed in prevention. Guidelines use aortic diameter as a predictor of rupture and dissection; however, this single parameter alone has a limited value in predicting the real-world risk of acute aortic syndromes. The novel photon-counting CT scan(pc-CT) is capable of better-analyzing tissue composition and aortic characterization. The aim of the study is to assess whether the correlation between aortic wall thickness measured with a pc-CT scan and histology exists. Methods: 14 Patients, with a mean age of 47 years, undergoing cardiac surgery for ATAA, who had preoperatively undergone a pc-CT scan, were retrospectively analyzed. Histology analyses of the resected aortic wall aneurysm were reviewed, and minimum/maximum measurements of intima+media of the aortic wall were performed. Radiology images were also examined, and aortic wall thickness measures were taken. Bland-Altman plots and Passing-Bablock regression analyses were conducted to evaluate the correlation between the values. Results: pc-CT scan mean measurements were 1.05 and 1.69 mm, minimum/maximum, respectively. Mean minimum/maximum histology measurements were 1.66 and 2.82 mm, respectively. Bland Altman plots and Passing-Bablock regression analyses showed the absence of systematic bias and confirmed that measurement values were sufficiently similar (minimum −0.61 [CI 95% 0.16–1.38]; maximum −1.1 [0.73–2.99]). Conclusions: Despite results being merely preliminary, our study shows encouraging sufficiently similar results between aortic wall thickness measurements made with pc-CT scan and histology analyses. Full article

(This article belongs to the Special Issue Advancements in Computational Modelling and Imaging Techniques for Personalised Treatment of Aortic Aneurysms)

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15 pages, 5480 KiB

Open AccessArticle

Investigating Delayed Rupture of Flow Diverter-Treated Giant Aneurysm Using Simulated Fluid–Structure Interactions

by Pablo Jeken-Rico, Yves Chau, Aurèle Goetz, Jacques Sedat and Elie Hachem

Bioengineering 2025, 12(3), 305; https://doi.org/10.3390/bioengineering12030305 - 18 Mar 2025

Viewed by 311

Abstract

Giant intracranial aneurysms are frequently treated shortly after discovery due to their increased risk of rupture and commonly symptomatic nature. Among available treatments, flow diverters are often the sole viable option, though they carry a rare but serious risk of delayed post-operative rupture. [...] Read more.

Giant intracranial aneurysms are frequently treated shortly after discovery due to their increased risk of rupture and commonly symptomatic nature. Among available treatments, flow diverters are often the sole viable option, though they carry a rare but serious risk of delayed post-operative rupture. The underlying mechanisms of these ruptures remain unknown, due to the biomechanical complexity of giant aneurysms and challenges in replicating in vivo hemodynamic conditions within numerical simulation frameworks. This study presents a novel fluid–structure interaction simulation of a giant intracranial aneurysm treated with a flow diverter, based on high-resolution rotational angiography imaging. The resulting hemodynamics are compared to three established delayed-rupture hypotheses involving pressure rises, chaotic flow and autolysis. When considering wall compliance, the analysis reveals a consistent phase shift, dampening in pressure cycles, and an increased aneurysmal flow. These findings highlight the need for revisiting existing hypotheses and provide a foundation for advancing both computational modelling and clinical management strategies for giant intracranial aneurysms. Full article

(This article belongs to the Special Issue Interventional Radiology and Vascular Medicine)

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24 pages, 7758 KiB

Open AccessArticle

Heparin and Gelatin Co-Functionalized Polyurethane Artificial Blood Vessel for Improving Anticoagulation and Biocompatibility

by Jimin Zhang, Jingzhe Guo, Junxian Zhang, Danting Li, Meihui Zhong, Yuxuan Gu, Xiaozhe Yan and Pingsheng Huang

Bioengineering 2025, 12(3), 304; https://doi.org/10.3390/bioengineering12030304 - 18 Mar 2025

Viewed by 408

Abstract

The primary challenges in the tissue engineering of small-diameter artificial blood vessels include inadequate mechanical properties and insufficient anticoagulation capabilities. To address these challenges, urea-pyrimidone (Upy)-based polyurethane elastomers (PIIU-B) were synthesized by incorporating quadruple hydrogen bonding within the polymer backbone. The synthesis process [...] Read more.

The primary challenges in the tissue engineering of small-diameter artificial blood vessels include inadequate mechanical properties and insufficient anticoagulation capabilities. To address these challenges, urea-pyrimidone (Upy)-based polyurethane elastomers (PIIU-B) were synthesized by incorporating quadruple hydrogen bonding within the polymer backbone. The synthesis process employed poly(L-lactide-ε-caprolactone) (PLCL) as the soft segment, while di-(isophorone diisocyanate)-Ureido pyrimidinone (IUI) and isophorone diisocyanate (IPDI) were utilized as the hard segment. The resulting PIIU-B small-diameter artificial blood vessel with a diameter of 4 mm was fabricated using the electrospinning technique, achieving an optimized IUI/IPDI composition ratio of 1:1. Enhanced by multiple hydrogen bonds, the vessels exhibited a robust elastic modulus of 12.45 MPa, an extracellular matrix (ECM)-mimetic nanofiber morphology, and a high porosity of 41.31%. Subsequently, the PIIU-B vessel underwent dual-functionalization with low-molecular-weight heparin and gelatin via ultraviolet (UV) crosslinking (designated as PIIU-B@LHep/Gel), which conferred superior biocompatibility and exceptional anticoagulation properties. The study revealed improved anti-platelet adhesion characteristics as well as a prolonged activated partial thromboplastin time (APTT) of 157.2 s and thrombin time (TT) of 64.2 s in vitro. Following a seven-day subcutaneous implantation, the PIIU-B@LHep/Gel vessel exhibited excellent biocompatibility, evidenced by complete integration with the surrounding peri-implant tissue, significant cell infiltration, and collagen formation in vivo. Consequently, polyurethane-based artificial blood vessels, reinforced by multiple hydrogen bonds and dual-functionalized with heparin and gelatin, present as promising candidates for vascular tissue engineering. Full article

(This article belongs to the Special Issue Biomaterials for Angiogenesis)

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9 pages, 3264 KiB

Open AccessArticle

Development of a Low-Cost and Easy-Assembly Capillary Electrophoresis System for Separation of DNA

by Jiawen Li, Shuaiqiang Fan, Jiandong Zhu, Bo Yang, Zhenqing Li, Dawei Zhang and Yoshinori Yamaguchi

Bioengineering 2025, 12(3), 303; https://doi.org/10.3390/bioengineering12030303 - 17 Mar 2025

Viewed by 305

Abstract

Capillary electrophoresis based on laser-induced fluorescence (CE-LIF) plays an important role in the analysis of nucleic acids. However, the commercial CE-LIF is not only quite expensive but also inflexible, thus hindering its widespread use in the lab. Herein, we proposed a compact, low-cost, [...] Read more.

Capillary electrophoresis based on laser-induced fluorescence (CE-LIF) plays an important role in the analysis of nucleic acids. However, the commercial CE-LIF is not only quite expensive but also inflexible, thus hindering its widespread use in the lab. Herein, we proposed a compact, low-cost, and flexible CE-LIF system. We also investigated its stability by separating the DNA ladders. Experiments demonstrated that the relative standard error of the relative fluorescence intensity and migration time was lower than 6.2% and 1.1%, respectively. The aperture size of the light source illuminating the capillary can affect the separation performance. Smaller apertures offer higher resolution length for the adjacent DNA fragments but may reduce the number of theoretical plates. Various fluorescent dyes (e.g., SYBR Green I, Gel Green, EvaGreen) can be employed in the self-built system. The limit of detection of dsDNA was as low as 0.05 ng/μL. The working range for DNA was 0.05 ng/μL~10 ng/μL. Finally, we have successfully separated the PCR products of the target gene of Porphyromonas gingivalis and Candida albicans in the home-built CE system. Such a robust CE-LIF system is easy to assemble in the lab. The total cost of the assembled CE system did not exceed 1100 USD. We believe this work can advance the application of CE and hope it will facilitate the easy assembly of flexible CE instruments in labs. Full article

(This article belongs to the Special Issue Applications of Genomic Technology in Disease Outcome Prediction)

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18 pages, 8425 KiB

Open AccessArticle

A New Method Proposed for Analyzing Airflow Dynamics in Negative Pressure Isolation Chambers Using Particle Image Velocimetry

by Min Jae Oh, Jung Min Moon, Seung Cheol Ko, Min Ji Kim, Ki Sub Sung, Jung Woo Lee, Ju Young Hong, Joon Sang Lee and Yong Hyun Kim

Bioengineering 2025, 12(3), 302; https://doi.org/10.3390/bioengineering12030302 - 17 Mar 2025

Viewed by 282

Abstract

The COVID-19 pandemic has highlighted the significant infection risks posed by aerosol generating procedures (AGPs). We developed a hood that covers the patient’s respiratory area, incorporating a negative pressure system to contain aerosols. This study analyzed the movement and containment of aerosols within [...] Read more.

The COVID-19 pandemic has highlighted the significant infection risks posed by aerosol generating procedures (AGPs). We developed a hood that covers the patient’s respiratory area, incorporating a negative pressure system to contain aerosols. This study analyzed the movement and containment of aerosols within a developed negative pressure isolation chamber. Using particle image velocimetry (PIV) technology, in the optimized design, the characteristics of aerosols were analyzed under both negative and non-negative pressure conditions. The results demonstrated that in the absence of negative pressure, droplets dispersed widely, with diffusion angles ranging from 26.9° to 34.2°, significantly increasing the risk of external leakage. When negative pressure was applied, the diffusion angles narrowed to 20.0–35.1° and inward airflow effectively directed droplets away from the chamber boundary, preventing external dispersion. Additionally, sensor data measuring particle concentrations confirmed that droplets smaller than 10 µm were fully contained under negative pressure, strongly supporting the chamber’s effectiveness. The strong agreement between PIV flow patterns and sensor measurements underscores the reliability of the experimental methodology. These findings highlight the chamber’s ability to suppress external leakage while offering superior flexibility and portability compared to conventional isolation systems, making it ideal for emergency responses, mobile healthcare units, and large-scale infectious disease outbreaks. Full article

(This article belongs to the Section Biosignal Processing)

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17 pages, 3051 KiB

Open AccessArticle

Introduction of a Semi-Quantitative Image-Based Analysis Tool for CBCT-Based Evaluation of Bone Regeneration in Tooth Extraction Sockets

by Anja Heselich, Pauline Neff, Joanna Śmieszek-Wilczewska, Robert Sader and Shahram Ghanaati

Bioengineering 2025, 12(3), 301; https://doi.org/10.3390/bioengineering12030301 - 16 Mar 2025

Cited by 1 | Viewed by 294

Abstract

After tooth extraction, resorptive changes in extraction sockets and the adjacent alveolar ridge can affect subsequent tooth replacement and implantation. Several surgical concepts, including the application of autologous blood concentrate platelet-rich fibrin (PRF), aim to reduce these changes. While PRF’s wound-healing and pain-relieving [...] Read more.

After tooth extraction, resorptive changes in extraction sockets and the adjacent alveolar ridge can affect subsequent tooth replacement and implantation. Several surgical concepts, including the application of autologous blood concentrate platelet-rich fibrin (PRF), aim to reduce these changes. While PRF’s wound-healing and pain-relieving effects are well-documented, its impact on bone regeneration is less clear due to varying PRF protocols and measurement methods for bone regeneration. This study aimed to develop a precise, easy-to-use non-invasive radiological evaluation method that examines the entire extraction socket to assess bone regeneration using CBCT data from clinical trials. The method, based on the freely available Image J-based software “Fiji”, proved to be precise, reproducible, and transferable. As limitation remains the time requirement and its exclusive focus on radiological bone regeneration. Nevertheless, the method presented here is more precise than the ones currently described in the literature, as it evaluates the entire socket rather than partial areas. The application of the novel method to measure mineralized socket volume and radiological bone density of newly formed bone in a randomized, controlled clinical trial assessing solid PRF for socket preservation in premolar and molar sockets showed only slight, statistically non-significant trends toward better regeneration in the PRF group compared to natural healing. Full article

(This article belongs to the Special Issue Medical Imaging Analysis: Current and Future Trends)

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3 pages, 144 KiB

Open AccessEditorial

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

by Philippe Gorce

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

Viewed by 300

Abstract

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

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

14 pages, 1393 KiB

Open AccessArticle

Use of Wearable Inertial Sensors to Assess Trunk and Cervical Postures Among Surgeons: Effect of Surgical Specialties and Roles

by Giulia Casu, Micaela Porta, Luigi Isaia Lecca, Alessandro Murru, Fabio Medas, Massimiliano Pau and Marcello Campagna

Bioengineering 2025, 12(3), 299; https://doi.org/10.3390/bioengineering12030299 - 15 Mar 2025

Viewed by 906

Abstract

This study aimed to quantitatively assess trunk and cervical non-neutral postures assumed by surgeons during the performance of routine open procedures. Indeed, musculoskeletal disorders are frequently reported by surgeons, especially at the head and neck level, due to the prolonged time spent in [...] Read more.

This study aimed to quantitatively assess trunk and cervical non-neutral postures assumed by surgeons during the performance of routine open procedures. Indeed, musculoskeletal disorders are frequently reported by surgeons, especially at the head and neck level, due to the prolonged time spent in ergonomically challenging postures. Therefore, the posture of fourteen surgeons was monitored using wearable inertial sensors (and processed according to the ISO 11226 standard) by considering the effect of different surgical specialties (thyroid vs. breast) and roles (primary vs. assistants). Overall, surgeons spent most of their time in a standing posture, remaining within the acceptable limits of trunk flexion. More concerning results were observed analyzing the time spent in static head flexion and lateral bending (~72% and 48% of the time, respectively). Assistants, compared with primary surgeons, spent more than twice as much time in extreme neck flexion, although this was only when performing thyroid surgeries. The opposite was observed during breast surgeries. By spending most of their time in a standing posture with extreme forward neck flexion, surgeons are exposed to a high ergonomic risk, especially when frequently performing thyroid surgeries. The assumed role appeared to influence postural loading, with an effect that varies according to the surgical specialty. Full article

(This article belongs to the Special Issue Body-Worn Sensors for Biomedical Applications)

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19 pages, 4606 KiB

Open AccessArticle

Biorecognition-Based Nanodiagnostics: Maltotriose-Functionalized Magnetic Nanoparticles for Targeted Magnetic Resonance Imaging of Bacterial Infections

by Junshan Wan, Chuqiang Yin, Xiaotong Chen, Keying Wu, Chonghui Zhang, Yu Zhou, Yugong Feng, Jing Chang and Ting Wang

Bioengineering 2025, 12(3), 296; https://doi.org/10.3390/bioengineering12030296 - 15 Mar 2025

Viewed by 560

Abstract

Bacterial infections remain a global healthcare challenge, requiring precise diagnostic modalities to guide therapeutic interventions. Current molecular imaging agents predominantly detect nonspecific hemodynamic alterations and lack pathogen-specific targeting capabilities for magnetic resonance imaging (MRI). Leveraging the selective bacterial uptake of maltotriose via the [...] Read more.

Bacterial infections remain a global healthcare challenge, requiring precise diagnostic modalities to guide therapeutic interventions. Current molecular imaging agents predominantly detect nonspecific hemodynamic alterations and lack pathogen-specific targeting capabilities for magnetic resonance imaging (MRI). Leveraging the selective bacterial uptake of maltotriose via the maltodextrin transport pathway, we engineered maltotriose-functionalized magnetic nanoparticles (Malt-MNPs) as a novel MRI contrast agent. Basic physicochemical characterization confirmed the nanosystem’s colloidal stability, biocompatibility, and superparamagnetism (saturation magnetization > 50 emu/g). In a rat bacterial infection model, intravenously administered Malt-MNPs selectively accumulated at infection sites, inducing a >50% MRI signal change within 24 h while exhibiting minimal off-target retention in sterile inflammatory lesions (<10% signal change). This specificity enabled clear MRI-based differentiation between bacterial infections and noninfectious inflammation. These findings provide a promising strategy for clinical translation in infection imaging and treatment. Full article

(This article belongs to the Section Nanobiotechnology and Biofabrication)

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10 pages, 445 KiB

Open AccessFeature PaperArticle

Hallux Limitus: Exploring the Variability in Lower Limb Symmetry and Its Connection to Gait Parameters—A Case–Control Study

by Natalia Tovaruela Carrión, Ricardo Becerro-de-Bengoa-Vallejo, Marta Elena Losa-Iglesias, Daniel López-López, Juan Gómez-Salgado and Javier Bayod-López

Bioengineering 2025, 12(3), 298; https://doi.org/10.3390/bioengineering12030298 - 14 Mar 2025

Viewed by 547

Abstract

Hallux limitus pathology is defined as a limitation of the dorsiflexion movement of the first toe without degenerative involvement of the first metatarsophalangeal joint, which produces pain and generates functional impairment, especially in the propulsive phase of gait. It is very common to [...] Read more.

Hallux limitus pathology is defined as a limitation of the dorsiflexion movement of the first toe without degenerative involvement of the first metatarsophalangeal joint, which produces pain and generates functional impairment, especially in the propulsive phase of gait. It is very common to find this pathology in adulthood accompanied by other compensations at a biomechanical level as a consequence of blockage of the main pivot in the sagittal plane. The aim was to determine the symmetry index that occurs in dynamics affiliated with other gait parameters in subjects with and without hallux limitus. A total of 70 subjects were part of the sample, and these were separated into two groups, each consisting of 35 subjects, depending on whether they had bilateral hallux limitus or if they were healthy subjects. In this study, a platform was used to assess the load symmetry index and walking phases. The results showed significant differences in the symmetry index for lateral load (p = 0.023), the initial contact phase (p = 0.003), and the flatfoot phase (p < 0.001). The adults who had bilateral hallux limitus exhibited changes in the symmetry index during the lateral load as well as in the initial contact and flatfoot contact phases, demonstrating increased instability when compared to individuals with normal feet. Full article

(This article belongs to the Special Issue Biomechanics of Physical Exercise)

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14 pages, 1544 KiB

Open AccessArticle

Predictive Model of Gemtuzumab Ozogamicin Response in Childhood Acute Myeloid Leukemia on Event-Free Survival: Data Analysis Based on Trial AAML0531

by Kun-Yin Qiu, Xiong-Yu Liao, Jian-Pei Fang and Dun-Hua Zhou

Bioengineering 2025, 12(3), 297; https://doi.org/10.3390/bioengineering12030297 - 14 Mar 2025

Viewed by 443

Abstract

Purpose: We aimed to develop a simple nomogram and online calculator that can identify the optimal subpopulation of pediatric acute myeloid leukemia (AML) patients who would benefit most from gemtuzumab ozogamicin (GO) therapy. Methods: Within the framework of the phase Ⅲ AAML0531 randomized [...] Read more.

Purpose: We aimed to develop a simple nomogram and online calculator that can identify the optimal subpopulation of pediatric acute myeloid leukemia (AML) patients who would benefit most from gemtuzumab ozogamicin (GO) therapy. Methods: Within the framework of the phase Ⅲ AAML0531 randomized trial for GO, the event-free survival (EFS) probability was calculated using a predictor-based nomogram to evaluate GO treatment impact on EFS in relation to baseline characteristics. Nomogram performance was assessed by the area under the receiver operating characteristic curve (AUC) and the calibration curve with 500 bootstrap resample validations. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomogram. Results: A total of 705 patients were randomly assigned to two arms: the No-GO arm (n = 358) and the GO arm (n = 347). We performed a nomogram model for EFS among childhood AML. The AUC (C statistic) of the nomogram was 0.731 (95%CI: 0.614–0.762) in the development group and 0.700 (95% CI: 0.506–0.889) in the validation group. DCA showed that the model in the development and validation groups had a net benefit when the risk thresholds were 0–0.75 and 0–0.75, respectively. Notably, an intriguing observation emerged wherein pediatric patients with AML exhibited a favorable outcome in the GO arm when the predicted 5-year EFS probability fell below 60%, demonstrating a superior EFS compared to the No-GO Arm. Conclusions: We have developed a nomogram and online calculator that can be used to predict EFS among childhood AML based on trial AAML0531, and this might help deciding which patients can benefit from GO. Full article

(This article belongs to the Section Biosignal Processing)

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25 pages, 305 KiB

Open AccessReview

Electroencephalographic Biomarkers for Neuropsychiatric Diseases: The State of the Art

by Nayeli Huidobro, Roberto Meza-Andrade, Ignacio Méndez-Balbuena, Carlos Trenado, Maribel Tello Bello and Eduardo Tepichin Rodríguez

Bioengineering 2025, 12(3), 295; https://doi.org/10.3390/bioengineering12030295 - 14 Mar 2025

Viewed by 846

Abstract

Because of their nature, biomarkers for neuropsychiatric diseases were out of the reach of medical diagnostic technology until the past few decades. In recent years, the confluence of greater, affordable computer power with the need for more efficient diagnoses and treatments has increased [...] Read more.

Because of their nature, biomarkers for neuropsychiatric diseases were out of the reach of medical diagnostic technology until the past few decades. In recent years, the confluence of greater, affordable computer power with the need for more efficient diagnoses and treatments has increased interest in and the possibility of their discovery. This review will focus on the progress made over the past ten years regarding the search for electroencephalographic biomarkers for neuropsychiatric diseases. This includes algorithms and methods of analysis, machine learning, and quantitative electroencephalography as applied to neurodegenerative and neurodevelopmental diseases as well as traumatic brain injury and COVID-19. Our findings suggest that there is a need for consensus among quantitative electroencephalography researchers on the classification of biomarkers that most suit this field; that there is a slight disconnection between the development of increasingly sophisticated methods of analysis and what they will actually be of use for in the clinical setting; and finally, that diagnostic biomarkers are the most favored type in the field with a few caveats. The main goal of this state-of-the-art review is to provide the reader with a general panorama of the state of the art in this field. Full article

(This article belongs to the Special Issue New Sights of EEG and Brain Diseases: Updates and Directions)

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Bioengineering, Volume 12, Issue 3 (March 2025) – 114 articles

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