Journal Description
Bioengineering
Bioengineering
is an international, scientific, peer-reviewed, open access journal on the science and technology of bioengineering, published monthly online by MDPI. The Society for Regenerative Medicine (Russian Federation) (RPO) is affiliated with Bioengineering and its members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, CAPlus / SciFinder, Inspec, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Biomedical)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.7 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
4.6 (2022)
Latest Articles
Unraveling the Potential of Attentive Bi-LSTM for Accurate Obesity Prognosis: Advancing Public Health towards Sustainable Cities
Bioengineering 2024, 11(6), 533; https://doi.org/10.3390/bioengineering11060533 (registering DOI) - 23 May 2024
Abstract
The global prevalence of obesity presents a pressing challenge to public health and healthcare systems, necessitating accurate prediction and understanding for effective prevention and management strategies. This article addresses the need for improved obesity prediction models by conducting a comprehensive analysis of existing
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The global prevalence of obesity presents a pressing challenge to public health and healthcare systems, necessitating accurate prediction and understanding for effective prevention and management strategies. This article addresses the need for improved obesity prediction models by conducting a comprehensive analysis of existing machine learning (ML) and deep learning (DL) approaches. This study introduces a novel hybrid model, Attention-based Bi-LSTM (ABi-LSTM), which integrates attention mechanisms with bidirectional Long Short-Term Memory (Bi-LSTM) networks to enhance interpretability and performance in obesity prediction. Our study fills a crucial gap by bridging healthcare and urban planning domains, offering insights into data-driven approaches to promote healthier living within urban environments. The proposed ABi-LSTM model demonstrates exceptional performance, achieving a remarkable accuracy of 96.5% in predicting obesity levels. Comparative analysis showcases its superiority over conventional approaches, with superior precision, recall, and overall classification balance. This study highlights significant advancements in predictive accuracy and positions the ABi-LSTM model as a pioneering solution for accurate obesity prognosis. The implications extend beyond healthcare, offering a precise tool to address the global obesity epidemic and foster sustainable development in smart cities.
Full article
(This article belongs to the Special Issue Intelligent IoMT Systems for Brain–Computer Interface)
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Open AccessArticle
Press-Fit Placement of a Rectangular Block Implant in the Resorbed Alveolar Ridge: Surgical and Biomechanical Considerations
by
Efthimios Gazelakis, Roy B. Judge, Joseph E. A. Palamara, Shiva Subramanian and Mohsin Nazir
Bioengineering 2024, 11(6), 532; https://doi.org/10.3390/bioengineering11060532 (registering DOI) - 23 May 2024
Abstract
Rectangular Block Implant (RBIs) were manufactured, using computer-aided-design lathe turning, surface roughened with grit blasting and gamma irradiated. Implants were surgically placed into the resorbed edentulous mandibular ridges of both greyhound dogs (ex vivo and in vivo) and humans; the pooled total was
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Rectangular Block Implant (RBIs) were manufactured, using computer-aided-design lathe turning, surface roughened with grit blasting and gamma irradiated. Implants were surgically placed into the resorbed edentulous mandibular ridges of both greyhound dogs (ex vivo and in vivo) and humans; the pooled total was 17 placements. The aim was to achieve mechanical stability and full implant submergence without damage to the mandibular canal and without bone fracture: fulfilment of all of these criteria was deemed to be a successful surgical outcome. Rectangular osteotomy sites were prepared with piezo surgical instrumentation. Sixteen implants were fully submerged and achieved good primary stability without bone fracture and without evidence of impingement of the mandibular canal. One implant placement was deemed a failure due to bone fracture: the event of a random successful outcome was rejected (p < 0.01 confidence, binomial analysis). Technique of placement yielded excellent mechanical retention: key biomechanical factors that emerged in this process included under preparation of the osteotomy site with the use of specifically designed trial-fit gauges, the viscoelastic property of the peri-implant bone, the flat faces and cornered edges of the block surfaces which enhance stress distribution and mechanical retention, respectively. It was concluded that the surgical protocol for the RBI placement in the resorbed alveolus is a predictable clinical procedure tailored to its specific, unique biomechanical profile.
Full article
(This article belongs to the Special Issue Translational Advances in Dental Implants)
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Open AccessArticle
Exploring Predictive Factors for Heart Failure Progression in Hypertensive Patients Based on Medical Diagnosis Data from the MIMIC-IV Database
by
Jinmyung Jung, Doyoon Kim and Inkyung Hwang
Bioengineering 2024, 11(6), 531; https://doi.org/10.3390/bioengineering11060531 (registering DOI) - 23 May 2024
Abstract
Heart failure is associated with a significant mortality rate, and an elevated prevalence of this condition has been noted among hypertensive patients. The identification of predictive factors for heart failure progression in hypertensive individuals is crucial for early intervention and improved patient outcomes.
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Heart failure is associated with a significant mortality rate, and an elevated prevalence of this condition has been noted among hypertensive patients. The identification of predictive factors for heart failure progression in hypertensive individuals is crucial for early intervention and improved patient outcomes. In this study, we aimed to identify these predictive factors by utilizing medical diagnosis records for hypertension patients from the MIMIC-IV database. In particular, we employed only diagnostic history prior to hypertension to enable patients to anticipate the onset of heart failure at the moment of hypertension diagnosis. In the methodology, chi-square tests and XGBoost modeling were applied to examine age-specific predictive factors across four groups: AL (all ages), G1 (0 to 65 years), G2 (65 to 80 years), and G3 (over 80 years). As a result, the chi-square tests identified 34, 28, 20, and 10 predictive factors for the AL, G1, G2, and G3 groups, respectively. Meanwhile, the XGBoost modeling uncovered 19, 21, 27, and 33 predictive factors for these respective groups. Ultimately, our findings reveal 21 overall predictive factors, encompassing conditions such as atrial fibrillation, the use of anticoagulants, kidney failure, obstructive pulmonary disease, and anemia. These factors were assessed through a comprehensive review of the existing literature. We anticipate that the results will offer valuable insights for the risk assessment of heart failure in hypertensive patients.
Full article
(This article belongs to the Special Issue AI and Big Data Research in Biomedical Engineering)
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Open AccessArticle
A Novel Approach for the Detection and Severity Grading of Chronic Obstructive Pulmonary Disease Based on Transformed Volumetric Capnography
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Xiuying Mou, Peng Wang, Jie Sun, Xianxiang Chen, Lidong Du, Qingyuan Zhan, Jingen Xia, Ting Yang and Zhen Fang
Bioengineering 2024, 11(6), 530; https://doi.org/10.3390/bioengineering11060530 - 23 May 2024
Abstract
Chronic Obstructive Pulmonary Disease (COPD), as the third leading cause of death worldwide, is a major global health issue. The early detection and grading of COPD are pivotal for effective treatment. Traditional spirometry tests, requiring considerable physical effort and strict adherence to quality
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Chronic Obstructive Pulmonary Disease (COPD), as the third leading cause of death worldwide, is a major global health issue. The early detection and grading of COPD are pivotal for effective treatment. Traditional spirometry tests, requiring considerable physical effort and strict adherence to quality standards, pose challenges in COPD diagnosis. Volumetric capnography (VCap), which can be performed during natural breathing without requiring additional compliance, presents a promising alternative tool. In this study, the dataset comprised 279 subjects with normal pulmonary function and 148 patients diagnosed with COPD. We introduced a novel quantitative analysis method for VCap. Volumetric capnograms were converted into two-dimensional grayscale images through the application of Gramian Angular Field (GAF) transformation. Subsequently, a multi-scale convolutional neural network, CapnoNet, was conducted to extract features and facilitate classification. To improve CapnoNet’s performance, two data augmentation techniques were implemented. The proposed model exhibited a detection accuracy for COPD of 95.83%, with precision, recall, and F1 measures of 95.21%, 95.70%, and 95.45%, respectively. In the task of grading the severity of COPD, the model attained an accuracy of 96.36%, complemented by precision, recall, and F1 scores of 88.49%, 89.99%, and 89.15%, respectively. This work provides a new perspective for the quantitative analysis of volumetric capnography and demonstrates the strong performance of the proposed CapnoNet in the diagnosis and grading of COPD. It offers direction and an effective solution for the clinical application of capnography.
Full article
(This article belongs to the Section Biosignal Processing)
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Open AccessCommunication
Triple Encapsulation and Controlled Release of Vancomycin, Rifampicin and Silver from Poly (Methyl Methacrylate) or Poly (Lactic-Co-Glycolic Acid) Nanofibers
by
John Jackson
Bioengineering 2024, 11(6), 529; https://doi.org/10.3390/bioengineering11060529 - 23 May 2024
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Although the incidence of infections in orthopedic surgeries, including periprosthetic surgeries, remains low at approximately 1–2%, the number of surgeries and the incidence of drug-resistant bacteria is increasing. The cost and morbidity associated with revision surgeries are huge. More effective drug combinations and
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Although the incidence of infections in orthopedic surgeries, including periprosthetic surgeries, remains low at approximately 1–2%, the number of surgeries and the incidence of drug-resistant bacteria is increasing. The cost and morbidity associated with revision surgeries are huge. More effective drug combinations and delivery methods are urgently needed. In this paper, three anti-infective drugs (vancomycin, rifampicin, and silver sulfadiazine) have been jointly and effectively electrospun in thin (0.1 mm) flexible nanofiber mats of either poly (methyl methacrylate) (PMMA) or poly (lactic-co-glycolic acid) (PLGA). The inclusion of poly (ethylene glycol) (PEG) enabled optimal drug release with a reduced water contact angle for wetting. The controlled release of these three agents from 20% PEG (w/w to polymer)-blended PMMA or PLGA nanofiber mats may allow for the prophylactical prevention of implant-related infections or provide methods to treat orthopedic infections at the time of revision surgeries. These combinations of drugs provide excellent additive or synergistic antibiotic action against a broader spectrum of bacteria than each drug alone.
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Open AccessArticle
Quantification of Visceral Fat at the L5 Vertebral Body Level in Patients with Crohn’s Disease Using T2-Weighted MRI
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Favour Garuba, Aravinda Ganapathy, Spencer McKinley, Karan H. Jani, Adriene Lovato, Satish E. Viswanath, Scott McHenry, Parakkal Deepak and David H. Ballard
Bioengineering 2024, 11(6), 528; https://doi.org/10.3390/bioengineering11060528 - 22 May 2024
Abstract
The umbilical or L3 vertebral body level is often used for body fat quantification using computed tomography. To explore the feasibility of using clinically acquired pelvic magnetic resonance imaging (MRI) for visceral fat measurement, we examined the correlation of visceral fat parameters at
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The umbilical or L3 vertebral body level is often used for body fat quantification using computed tomography. To explore the feasibility of using clinically acquired pelvic magnetic resonance imaging (MRI) for visceral fat measurement, we examined the correlation of visceral fat parameters at the umbilical and L5 vertebral body levels. We retrospectively analyzed T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) MR axial images from Crohn’s disease patients who underwent MRI enterography of the abdomen and pelvis over a three-year period. We determined the area/volume of subcutaneous and visceral fat from the umbilical and L5 levels and calculated the visceral fat ratio (VFR = visceral fat/subcutaneous fat) and visceral fat index (VFI = visceral fat/total fat). Statistical analyses involved correlation analysis between both levels, inter-rater analysis between two investigators, and inter-platform analysis between two image-analysis platforms. Correlational analysis of 32 patients yielded significant associations for VFI (r = 0.85; p < 0.0001) and VFR (r = 0.74; p < 0.0001). Intraclass coefficients for VFI and VFR were 0.846 and 0.875 (good agreement) between investigators and 0.831 and 0.728 (good and moderate agreement) between platforms. Our study suggests that the L5 level on clinically acquired pelvic MRIs may serve as a reference point for visceral fat quantification.
Full article
(This article belongs to the Special Issue Biomedical Imaging and Data Analytics for Disease Diagnosis and Treatment)
Open AccessArticle
Electrical Stimulation of Mesenchymal Stem Cells as a Tool for Proliferation and Differentiation in Cartilage Tissue Engineering: A Scaffold-Based Approach
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Nicolas Lehmenkötter, Johannes Greven, Frank Hildebrand, Philipp Kobbe and Jörg Eschweiler
Bioengineering 2024, 11(6), 527; https://doi.org/10.3390/bioengineering11060527 - 22 May 2024
Abstract
Electrical stimulation (ES) is a widely discussed topic in the field of cartilage tissue engineering due to its ability to induce chondrogenic differentiation (CD) and proliferation. It shows promise as a potential therapy for osteoarthritis (OA). In this study, we stimulated mesenchymal stem
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Electrical stimulation (ES) is a widely discussed topic in the field of cartilage tissue engineering due to its ability to induce chondrogenic differentiation (CD) and proliferation. It shows promise as a potential therapy for osteoarthritis (OA). In this study, we stimulated mesenchymal stem cells (MSCs) incorporated into collagen hydrogel (CH) scaffolds, consisting of approximately 500,000 cells each, for 1 h per day using a 2.5 (119 mV/mm) 8 Hz sinusoidal signal. We compared the cell count, morphology, and CD on days 4, 7, and 10. The results indicate proliferation, with an increase ranging from 1.86 to 9.5-fold, particularly on day 7. Additionally, signs of CD were observed. The stimulated cells had a higher volume, while the stimulated scaffolds showed shrinkage. In the ES groups, up-regulation of collagen type 2 and aggrecan was found. In contrast, SOX9 was up-regulated in the control group, and MMP13 showed a strong up-regulation, indicating cell stress. In addition to lower stress levels, the control groups also showed a more spheroidic shape. Overall, scaffold-based ES has the potential to achieve multiple outcomes. However, finding the appropriate stimulation pattern is crucial for achieving successful chondrogenesis.
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(This article belongs to the Section Regenerative Engineering)
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Open AccessArticle
Unsupervised Segmentation of Knee Bone Marrow Edema-like Lesions Using Conditional Generative Models
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Andrew Seohwan Yu, Mingrui Yang, Richard Lartey, William Holden, Ahmet Hakan Ok, Sameed Khan, Jeehun Kim, Carl Winalski, Naveen Subhas, Vipin Chaudhary and Xiaojuan Li
Bioengineering 2024, 11(6), 526; https://doi.org/10.3390/bioengineering11060526 - 22 May 2024
Abstract
Bone marrow edema-like lesions (BMEL) in the knee have been linked to the symptoms and progression of osteoarthritis (OA), a highly prevalent disease with profound public health implications. Manual and semi-automatic segmentations of BMELs in magnetic resonance images (MRI) have been used to
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Bone marrow edema-like lesions (BMEL) in the knee have been linked to the symptoms and progression of osteoarthritis (OA), a highly prevalent disease with profound public health implications. Manual and semi-automatic segmentations of BMELs in magnetic resonance images (MRI) have been used to quantify the significance of BMELs. However, their utilization is hampered by the labor-intensive and time-consuming nature of the process as well as by annotator bias, especially since BMELs exhibit various sizes and irregular shapes with diffuse signal that lead to poor intra- and inter-rater reliability. In this study, we propose a novel unsupervised method for fully automated segmentation of BMELs that leverages conditional diffusion models, multiple MRI sequences that have different contrast of BMELs, and anomaly detection that do not rely on costly and error-prone annotations. We also analyze BMEL segmentation annotations from multiple experts, reporting intra-/inter-rater variability and setting better benchmarks for BMEL segmentation performance.
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(This article belongs to the Special Issue Recent Progress in Biomedical Image Processing)
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Open AccessReview
Delayed Union and Nonunion: Current Concepts, Prevention, and Correction: A Review
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Kristin M. Bowers and David E. Anderson
Bioengineering 2024, 11(6), 525; https://doi.org/10.3390/bioengineering11060525 - 22 May 2024
Abstract
Surgical management of fractures has advanced with the incorporation of advanced technology, surgical techniques, and regenerative therapies, but delayed bone healing remains a clinical challenge and the prevalence of long bone nonunion ranges from 10 to 15% of surgically managed fractures. Delayed bone
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Surgical management of fractures has advanced with the incorporation of advanced technology, surgical techniques, and regenerative therapies, but delayed bone healing remains a clinical challenge and the prevalence of long bone nonunion ranges from 10 to 15% of surgically managed fractures. Delayed bone healing arises from a combination of mechanical, biological, and systemic factors acting on the site of tissue remodeling, and careful consideration of each case’s injury-related, patient-dependent, surgical, and mechanical risk factors is key to successful bone union. In this review, we describe the biology and biomechanics of delayed bone healing, outline the known risk factors for nonunion development, and introduce modern preventative and corrective therapies targeting fracture nonunion.
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(This article belongs to the Special Issue Bone Tissue Engineering and Translational Research)
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Open AccessReview
Role of Mesenchymal Stem/Stromal Cells (MSCs) and MSC-Derived Extracellular Vesicles (EVs) in Prevention of Telomere Length Shortening, Cellular Senescence, and Accelerated Biological Aging
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Myrna Y. Gonzalez Arellano, Matthew VanHeest, Sravya Emmadi, Amal Abdul-Hafez, Sherif Abdelfattah Ibrahim, Ranga P. Thiruvenkataramani, Rasha S. Teleb, Hady Omar, Tulasi Kesaraju, Tarek Mohamed, Burra V. Madhukar and Said A. Omar
Bioengineering 2024, 11(6), 524; https://doi.org/10.3390/bioengineering11060524 - 21 May 2024
Abstract
Biological aging is defined as a progressive decline in tissue function that eventually results in cell death. Accelerated biologic aging results when the telomere length is shortened prematurely secondary to damage from biological or environmental stressors, leading to a defective reparative mechanism. Stem
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Biological aging is defined as a progressive decline in tissue function that eventually results in cell death. Accelerated biologic aging results when the telomere length is shortened prematurely secondary to damage from biological or environmental stressors, leading to a defective reparative mechanism. Stem cells therapy may have a potential role in influencing (counteract/ameliorate) biological aging and maintaining the function of the organism. Mesenchymal stem cells, also called mesenchymal stromal cells (MSCs) are multipotent stem cells of mesodermal origin that can differentiate into other types of cells, such as adipocytes, chondrocytes, and osteocytes. MSCs influence resident cells through the secretion of paracrine bioactive components such as cytokines and extracellular vesicles (EVs). This review examines the changes in telomere length, cellular senescence, and normal biological age, as well as the factors contributing to telomere shortening and accelerated biological aging. The role of MSCs—especially those derived from gestational tissues—in prevention of telomere shortening (TS) and accelerated biological aging is explored. In addition, the strategies to prevent MSC senescence and improve the antiaging therapeutic application of MSCs and MSC-derived EVs in influencing telomere length and cellular senescence are reviewed.
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(This article belongs to the Special Issue A Tribute to Professor Alexander Friedenstein and His Outstanding Achievements in the Area of Stromal Stem Cells)
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Open AccessArticle
Trial Analysis of Brain Activity Information for the Presymptomatic Disease Detection of Rheumatoid Arthritis
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Keisuke Maeda, Takahiro Ogawa, Tasuku Kayama, Takuya Sasaki, Kazuki Tainaka, Masaaki Murakami and Miki Haseyama
Bioengineering 2024, 11(6), 523; https://doi.org/10.3390/bioengineering11060523 - 21 May 2024
Abstract
This study presents a trial analysis that uses brain activity information obtained from mice to detect rheumatoid arthritis (RA) in its presymptomatic stages. Specifically, we confirmed that F759 mice, serving as a mouse model of RA that is dependent on the inflammatory cytokine
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This study presents a trial analysis that uses brain activity information obtained from mice to detect rheumatoid arthritis (RA) in its presymptomatic stages. Specifically, we confirmed that F759 mice, serving as a mouse model of RA that is dependent on the inflammatory cytokine IL-6, and healthy wild-type mice can be classified on the basis of brain activity information. We clarified which brain regions are useful for the presymptomatic detection of RA. We introduced a matrix completion-based approach to handle missing brain activity information to perform the aforementioned analysis. In addition, we implemented a canonical correlation-based method capable of analyzing the relationship between various types of brain activity information. This method allowed us to accurately classify F759 and wild-type mice, thereby identifying essential features, including crucial brain regions, for the presymptomatic detection of RA. Our experiment obtained brain activity information from 15 F759 and 10 wild-type mice and analyzed the acquired data. By employing four types of classifiers, our experimental results show that the thalamus and periaqueductal gray are effective for the classification task. Furthermore, we confirmed that classification performance was maximized when seven brain regions were used, excluding the electromyogram and nucleus accumbens.
Full article
(This article belongs to the Section Biosignal Processing)
Open AccessArticle
Endovascular Treatment of Intracranial Aneurysm: The Importance of the Rheological Model in Blood Flow Simulations
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Maria Antonietta Boniforti, Giorgia Vittucci and Roberto Magini
Bioengineering 2024, 11(6), 522; https://doi.org/10.3390/bioengineering11060522 - 21 May 2024
Abstract
Hemodynamics in intracranial aneurysm strongly depends on the non-Newtonian blood behavior due to the large number of suspended cells and the ability of red blood cells to deform and aggregate. However, most numerical investigations on intracranial hemodynamics adopt the Newtonian hypothesis to model
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Hemodynamics in intracranial aneurysm strongly depends on the non-Newtonian blood behavior due to the large number of suspended cells and the ability of red blood cells to deform and aggregate. However, most numerical investigations on intracranial hemodynamics adopt the Newtonian hypothesis to model blood flow and predict aneurysm occlusion. The aim of this study was to analyze the effect of the blood rheological model on the hemodynamics of intracranial aneurysms in the presence or absence of endovascular treatment. A numerical investigation was performed under pulsatile flow conditions in a patient-specific aneurysm with and without the insertion of an appropriately reconstructed flow diverter stent (FDS). The numerical simulations were performed using Newtonian and non-Newtonian assumptions for blood rheology. In all cases, FDS placement reduced the intra-aneurysmal velocity and increased the relative residence time (RRT) on the aneurysmal wall, indicating progressive thrombus formation and aneurysm occlusion. However, the Newtonian model largely overestimated RRT values and consequent aneurysm healing with respect to the non-Newtonian models. Due to the non-Newtonian blood properties and the large discrepancy between Newtonian and non-Newtonian simulations, the Newtonian hypothesis should not be used in the study of the hemodynamics of intracranial aneurysm, especially in the presence of endovascular treatment.
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(This article belongs to the Special Issue Interventional Radiology and Vascular Medicine)
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Open AccessArticle
A Comparative Sentiment Analysis of Greek Clinical Conversations Using BERT, RoBERTa, GPT-2, and XLNet
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Maria Evangelia Chatzimina, Helen A. Papadaki, Charalampos Pontikoglou and Manolis Tsiknakis
Bioengineering 2024, 11(6), 521; https://doi.org/10.3390/bioengineering11060521 - 21 May 2024
Abstract
In addressing the critical role of emotional context in patient–clinician conversations, this study conducted a comprehensive sentiment analysis using BERT, RoBERTa, GPT-2, and XLNet. Our dataset includes 185 h of Greek conversations focused on hematologic malignancies. The methodology involved data collection, data annotation,
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In addressing the critical role of emotional context in patient–clinician conversations, this study conducted a comprehensive sentiment analysis using BERT, RoBERTa, GPT-2, and XLNet. Our dataset includes 185 h of Greek conversations focused on hematologic malignancies. The methodology involved data collection, data annotation, model training, and performance evaluation using metrics such as accuracy, precision, recall, F1-score, and specificity. BERT outperformed the other methods across all sentiment categories, demonstrating its effectiveness in capturing the emotional context in clinical interactions. RoBERTa showed a strong performance, particularly in identifying neutral sentiments. GPT-2 showed promising results in neutral sentiments but exhibited a lower precision and recall for negatives. XLNet showed a moderate performance, with variations across categories. Overall, our findings highlight the complexities of sentiment analysis in clinical contexts, especially in underrepresented languages like Greek. These insights highlight the potential of advanced deep-learning models in enhancing communication and patient care in healthcare settings. The integration of sentiment analysis in healthcare could provide insights into the emotional states of patients, resulting in more effective and empathetic patient support. Our study aims to address the gap and limitations of sentiment analysis in a Greek clinical context, an area where resources are scarce and its application remains underexplored.
Full article
(This article belongs to the Special Issue Selected Papers from 1st International Workshop on Affective Computing and Health Care: New Research and Industrial Perspectives)
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Open AccessArticle
Zooming into the Complex Dynamics of Electrodermal Activity Recorded during Emotional Stimuli: A Multiscale Approach
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Laura Lavezzo, Andrea Gargano, Enzo Pasquale Scilingo and Mimma Nardelli
Bioengineering 2024, 11(6), 520; https://doi.org/10.3390/bioengineering11060520 - 21 May 2024
Abstract
Physiological phenomena exhibit complex behaviours arising at multiple time scales. To investigate them, techniques derived from chaos theory were applied to physiological signals, providing promising results in distinguishing between healthy and pathological states. Fractal-like properties of electrodermal activity (EDA), a well-validated tool for
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Physiological phenomena exhibit complex behaviours arising at multiple time scales. To investigate them, techniques derived from chaos theory were applied to physiological signals, providing promising results in distinguishing between healthy and pathological states. Fractal-like properties of electrodermal activity (EDA), a well-validated tool for monitoring the autonomic nervous system state, have been reported in previous literature. This study proposes the multiscale complexity index of electrodermal activity ( ) to discern different autonomic responses based on EDA signals. This method builds upon our previously proposed algorithm, , and it is empowered with a coarse-graining procedure to provide a view at multiple time scales of the EDA response. We tested ’s performance on the EDA signals of two publicly available datasets, i.e., the Continuously Annotated Signals of Emotion (CASE) dataset and the Affect, Personality and Mood Research on Individuals and Groups (AMIGOS) dataset, both containing physiological data recorded from healthy participants during the view of ultra-short emotional video clips. Our results highlighted that the values of were significantly different (p-value < 0.05 after Wilcoxon signed rank test with Bonferroni’s correction) when comparing high- and low-arousal stimuli. Furthermore, outperformed the single-scale approach in discriminating among different valence levels of high-arousal stimuli, e.g., showing significantly different values for scary and amusing stimuli (p-value = 0.024). These findings suggest that a multiscale approach to the nonlinear analysis of EDA signals can improve the information gathered on task-specific autonomic response, even when ultra-short time series are considered.
Full article
(This article belongs to the Special Issue Advances in Multivariate and Multiscale Physiological Signal Analysis)
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Open AccessArticle
Comparative Biomechanical Stability of the Fixation of Different Miniplates in Restorative Laminoplasty after Laminectomy: A Finite Element Study
by
Guoyin Liu, Weiqian Huang, Nannan Leng, Peng He, Xin Li, Muliang Lin, Zhonghua Lian, Yong Wang, Jianmin Chen and Weihua Cai
Bioengineering 2024, 11(5), 519; https://doi.org/10.3390/bioengineering11050519 - 20 May 2024
Abstract
A novel H-shaped miniplate (HSM) was specifically designed for restorative laminoplasties to restore patients’ posterior elements after laminectomies. A validated finite element (FE) model of L2/4 was utilized to create a laminectomy model, as well as three restorative laminoplasty models based on the
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A novel H-shaped miniplate (HSM) was specifically designed for restorative laminoplasties to restore patients’ posterior elements after laminectomies. A validated finite element (FE) model of L2/4 was utilized to create a laminectomy model, as well as three restorative laminoplasty models based on the fixation of different miniplates after a laminectomy (the RL-HSM model, the RL-LSM model, and the RL-THM model). The biomechanical effects of motion and displacement on a laminectomy and restorative laminoplasty with three different shapes for the fixation of miniplates were compared under the same mechanical conditions. This study aimed to validate the biomechanical stability, efficacy, and feasibility of a restorative laminoplasty with the fixation of miniplates post laminectomy. The laminectomy model demonstrated the greatest increase in motion and displacement, especially in axial rotation, followed by extension, flexion, and lateral bending. The restorative laminoplasty was exceptional in preserving the motion and displacement of surgical segments when compared to the intact state. This preservation was particularly evident in lateral bending and flexion/extension, with a slight maintenance efficacy observed in axial rotation. Compared to the laminectomy model, the restorative laminoplasties with the investigated miniplates demonstrated a motion-limiting effect for all directions and resulted in excellent stability levels under axial rotation and flexion/extension. The greatest reduction in motion and displacement was observed in the RL-HSM model, followed by the RL-LSM model and then the RL-THM model. When comparing the fixation of different miniplates in restorative laminoplasties, the HSMs were found to be superior to the LSMs and THMs in maintaining postoperative stability, particularly in axial rotation. The evidence suggests that a restorative laminoplasty with the fixation of miniplates is more effective than a conventional laminectomy due to the biomechanical effects of restoring posterior elements, which helps patients regain motion and limit load displacement responses in the spine after surgery, especially in axial rotation and flexion/extension. Additionally, our evaluation in this research study could benefit from further research and provide a methodological and modeling basis for the design and optimization of restorative laminoplasties.
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(This article belongs to the Special Issue Mechanobiology in Biomedical Engineering)
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Open AccessArticle
Structural and Organizational Strategies of Locomotor Modules during Landing in Patients with Chronic Ankle Instability
by
Tianle Jie, Datao Xu, Zanni Zhang, Ee-Chon Teo, Julien S. Baker, Huiyu Zhou and Yaodong Gu
Bioengineering 2024, 11(5), 518; https://doi.org/10.3390/bioengineering11050518 - 20 May 2024
Abstract
Background: Human locomotion involves the coordinated activation of a finite set of modules, known as muscle synergy, which represent the motor control strategy of the central nervous system. However, most prior studies have focused on isolated muscle activation, overlooking the modular organization of
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Background: Human locomotion involves the coordinated activation of a finite set of modules, known as muscle synergy, which represent the motor control strategy of the central nervous system. However, most prior studies have focused on isolated muscle activation, overlooking the modular organization of motor behavior. Therefore, to enhance comprehension of muscle coordination dynamics during multi-joint movements in chronic ankle instability (CAI), exploring muscle synergies during landing in CAI patients is imperative. Methods: A total of 22 patients with unilateral CAI and 22 healthy participants were recruited for this research. We employed a recursive model for second-order differential equations to process electromyographic (EMG) data after filtering preprocessing, generating the muscle activation matrix, which was subsequently inputted into the non-negative matrix factorization model for extraction of the muscle synergy. Muscle synergies were classified utilizing the K-means clustering algorithm and Pearson correlation coefficients. Statistical parameter mapping (SPM) was employed for temporal modular parameter analyses. Results: Four muscle synergies were identified in both the CAI and healthy groups. In Synergy 1, only the gluteus maximus showed significantly higher relative weight in CAI compared to healthy controls (p = 0.0035). Synergy 2 showed significantly higher relative weights for the vastus lateralis in the healthy group compared to CAI (p = 0.018), while in Synergy 4, CAI demonstrated significantly higher relative weights of the vastus lateralis compared to healthy controls (p = 0.030). Furthermore, in Synergy 2, the CAI group exhibited higher weights of the tibialis anterior compared to the healthy group (p = 0.042). Conclusions: The study suggested that patients with CAI exhibit a comparable modular organizational framework to the healthy group. Investigation of amplitude adjustments within the synergy spatial module shed light on the adaptive strategies employed by the tibialis anterior and gluteus maximus muscles to optimize control strategies during landing in patients with CAI. Variances in the muscle-specific weights of the vastus lateralis across movement modules reveal novel biomechanical adaptations in CAI, offering valuable insights for refining rehabilitation protocols.
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(This article belongs to the Special Issue Advances in Trauma and Injury Biomechanics)
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Open AccessArticle
Synergistic Antibacterial Properties of Silver Nanoparticles and Its Reducing Agent from Cinnamon Bark Extract
by
Araceli Granja Alvear, Nayely Pineda-Aguilar, Patricia Lozano, Cristóbal Lárez-Velázquez, Gottfried Suppan, Salomé Galeas, Alexis Debut, Karla Vizuete, Lola De Lima, Juan Pablo Saucedo-Vázquez, Frank Alexis and Floralba López
Bioengineering 2024, 11(5), 517; https://doi.org/10.3390/bioengineering11050517 - 20 May 2024
Abstract
Synthesis of silver nanoparticles with antibacterial properties using a one-pot green approach that harnesses the natural reducing and capping properties of cinnamon (Cinnamomum verum) bark extract is presented in this work. Silver nitrate was the sole chemical reagent employed in this
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Synthesis of silver nanoparticles with antibacterial properties using a one-pot green approach that harnesses the natural reducing and capping properties of cinnamon (Cinnamomum verum) bark extract is presented in this work. Silver nitrate was the sole chemical reagent employed in this process, acting as the precursor salt. Gas Chromatography-Mass Spectroscopy (GC-MS), High-Performance Liquid Chromatography (HPLC) analysis, and some phytochemical tests demonstrated that cinnamaldehyde is the main component in the cinnamon bark extract. The resulting bio-reduced silver nanoparticles underwent comprehensive characterization by Ultraviolet–Vis (UV-Vis) and Fourier Transform InfraRed spectrophotometry (FTIR), Dynamic Light Scattering (DLS), Transmission Electron Microscopy, and Scanning Electron Microscopy suggesting that cinnamaldehyde was chemically oxidated to produce silver nanoparticles. These cinnamon-extract-based silver nanoparticles (AgNPs-cinnamon) displayed diverse morphologies ranging from spherical to prismatic shapes, with sizes spanning between 2.94 and 65.1 nm. Subsequently, the antibacterial efficacy of these nanoparticles was investigated against Klebsiella, E. Coli, Pseudomonas, Staphylococcus aureus, and Acinetobacter strains. The results suggest the promising potential of silver nanoparticles obtained (AgNPs-cinnamon) as antimicrobial agents, offering a new avenue in the fight against bacterial infections.
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(This article belongs to the Section Nanotechnology Applications in Bioengineering)
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Quantitative Analysis of Stress–Stretch Curves in Canine Lumbar Vertebrae Using Modified Logistic Functions
by
Ernest Kostenko, Rimantas Stonkus, Jakov Šengaut, Nikolaj Višniakov and Algirdas Maknickas
Bioengineering 2024, 11(5), 516; https://doi.org/10.3390/bioengineering11050516 - 20 May 2024
Abstract
Background: The mechanical characteristics of bone are crucial for comprehending its functionality and response to different load conditions, which are essential for advancing medical treatments, implants, and prosthetics. By employing mathematical modeling to analyze the mechanical properties of bone, we can assess stress
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Background: The mechanical characteristics of bone are crucial for comprehending its functionality and response to different load conditions, which are essential for advancing medical treatments, implants, and prosthetics. By employing mathematical modeling to analyze the mechanical properties of bone, we can assess stress and deformation under both normal and abnormal conditions. This analysis offers valuable perspectives on potential fracture risks, the effects of diseases, and the effectiveness of various treatments. Therefore, researchers are attempting to find an adequate mathematical description of the mechanical properties of bone. Methods: Experimental stress–stretch external loading curves were obtained through investigations of canine vertebrae. The obtained experimental curves were fitted using the SciPy Python library with a slightly modified logistic function (logistic function plus additional const). Results: The resulting coefficient of determination (R squared) for most curves was near 0.999, indicating that an appropriate fitting function was selected for the description of the experimental stress–stretch curves. Conclusions: The stress–stretch behavior of canine vertebrae can be described using a logistic function modified by adding additional parameters for the most accurate fitting results.
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(This article belongs to the Section Biomechanics and Sports Medicine)
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Open AccessSystematic Review
Bone Bruises and Concomitant Meniscus and Cartilage Damage in Anterior Cruciate Ligament Injuries: A Systematic Review and Meta-Analysis
by
Sueen Sohn, Saad Mohammed AlShammari, Jeong Han Lee and Man Soo Kim
Bioengineering 2024, 11(5), 515; https://doi.org/10.3390/bioengineering11050515 - 20 May 2024
Abstract
(1) Background: Bone bruises in acute anterior cruciate ligament (ACL) injuries are closely linked to the occurrence of simultaneous meniscal and cartilage damage. Despite the frequent occurrence of associated injuries including bone bruises, meniscus, and cartilage damage in patients with ACL injuries, a
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(1) Background: Bone bruises in acute anterior cruciate ligament (ACL) injuries are closely linked to the occurrence of simultaneous meniscal and cartilage damage. Despite the frequent occurrence of associated injuries including bone bruises, meniscus, and cartilage damage in patients with ACL injuries, a systematic review of the relationships between the presence of bone bruises and the extent of meniscus and cartilage injuries has yet to be conducted. (2) Methods: Multiple comprehensive databases, including MEDLINE, EMBASE, and the Cochrane Library, were searched for studies that evaluated the relationship between bone bruises and meniscus or cartilage injuries following ACL injuries. Study selection, data extraction, and meta-analysis were performed. The Methodological Index for Non-Randomized Studies (MINORS) was used for quality assessments, and Review Manager 5.3 was used for data analysis. (3) Results: Data were extracted from 22 studies encompassing a total of 2891 patients with ACL injuries. Among the included studies, six studies investigated the relationships between bone bruises and medial meniscus (MM) or lateral meniscus (LM) injuries, while three studies investigated the relationships between bone bruises and cartilage injuries. There were no significant correlations between the presence of bone bruises and MM injuries (relative risk (RR) = 1.32; p = 0.61). A quantitative analysis indicated that individuals with bone bruises had a 2.71-fold higher likelihood of sustaining LM injuries than those without bone bruises (RR = 2.71; p = 0.0003). The analysis confirmed a significant relationship between bone bruises and cartilage injuries (RR = 6.18; p = 0.003). (4) Conclusions: Bone bruises occur most frequently in the lateral compartment. Bone bruises resulting from ACL injuries are related to accompanying LM injuries and cartilage injuries. Knowing these associations and the frequency of injuries may allow orthopedic surgeons to promptly address ACL-related meniscus and cartilage injuries on MRI results and in future clinical practice.
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(This article belongs to the Section Biomechanics and Sports Medicine)
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Open AccessReview
Cortical and Trabecular Bone Modeling and Implications for Bone Functional Adaptation in the Mammalian Tibia
by
Meir M. Barak
Bioengineering 2024, 11(5), 514; https://doi.org/10.3390/bioengineering11050514 - 20 May 2024
Abstract
Bone modeling involves the addition of bone material through osteoblast-mediated deposition or the removal of bone material via osteoclast-mediated resorption in response to perceived changes in loads by osteocytes. This process is characterized by the independent occurrence of deposition and resorption, which can
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Bone modeling involves the addition of bone material through osteoblast-mediated deposition or the removal of bone material via osteoclast-mediated resorption in response to perceived changes in loads by osteocytes. This process is characterized by the independent occurrence of deposition and resorption, which can take place simultaneously at different locations within the bone due to variations in stress levels across its different regions. The principle of bone functional adaptation states that cortical and trabecular bone tissues will respond to mechanical stimuli by adjusting (i.e., bone modeling) their morphology and architecture to mechanically improve their mechanical function in line with the habitual in vivo loading direction. This principle is relevant to various research areas, such as the development of improved orthopedic implants, preventative medicine for osteopenic elderly patients, and the investigation of locomotion behavior in extinct species. In the present review, the mammalian tibia is used as an example to explore cortical and trabecular bone modeling and to examine its implications for the functional adaptation of bones. Following a short introduction and an exposition on characteristics of mechanical stimuli that influence bone modeling, a detailed critical appraisal of the literature on cortical and trabecular bone modeling and bone functional adaptation is given. By synthesizing key findings from studies involving small mammals (rodents), large mammals, and humans, it is shown that examining both cortical and trabecular bone structures is essential for understanding bone functional adaptation. A combined approach can provide a more comprehensive understanding of this significant physiological phenomenon, as each structure contributes uniquely to the phenomenon.
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(This article belongs to the Section Biomedical Engineering and Biomaterials)
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