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
A Capillary-Force-Driven, Single-Cell Transfer Method for Studying Rare Cells
Bioengineering 2024, 11(6), 542; https://doi.org/10.3390/bioengineering11060542 - 24 May 2024
Abstract
The characterization of individual cells within heterogeneous populations (e.g., rare tumor cells in healthy blood cells) has a great impact on biomedical research. To investigate the properties of these specific cells, such as genetic biomarkers and/or phenotypic characteristics, methods are often developed for
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The characterization of individual cells within heterogeneous populations (e.g., rare tumor cells in healthy blood cells) has a great impact on biomedical research. To investigate the properties of these specific cells, such as genetic biomarkers and/or phenotypic characteristics, methods are often developed for isolating rare cells among a large number of background cells before studying their genetic makeup and others. Prior to using real-world samples, these methods are often evaluated and validated by spiking cells of interest (e.g., tumor cells) into a sample matrix (e.g., healthy blood) as model samples. However, spiking tumor cells at extremely low concentrations is challenging in a standard laboratory setting. People often circumvent the problem by diluting a solution of high-concentration cells, but the concentration becomes inaccurate after series dilution due to the fact that a cell suspension solution can be inhomogeneous, especially when the cell concentration is very low. We report on an alternative method for low-cost, accurate, and reproducible low-concentration cell spiking without the use of external pumping systems. By inducing a capillary force from sudden pressure drops, a small portion of the cellular membrane was aspirated into the reservoir tip, allowing for non-destructive single-cell transfer. We investigated the surface membrane tensions induced by cellular aspiration and studied a range of tip/tumor cell diameter combinations, ensuring that our method does not affect cell viability. In addition, we performed single-cell capture and transfer control experiments using human acute lymphoblastic leukemia cells (CCRF-CEM) to develop calibrated data for the general production of low-concentration samples. Finally, we performed affinity-based tumor cell isolation using this method to generate accurate concentrations ranging from 1 to 15 cells/mL.
Full article
(This article belongs to the Special Issue Bioanalysis Systems: Materials, Methods, Designs and Applications)
Open AccessReview
How Do Cartilage Lubrication Mechanisms Fail in Osteoarthritis? A Comprehensive Review
by
Manoj Rajankunte Mahadeshwara, Maisoon Al-Jawad, Richard M. Hall, Hemant Pandit, Reem El-Gendy and Michael Bryant
Bioengineering 2024, 11(6), 541; https://doi.org/10.3390/bioengineering11060541 - 24 May 2024
Abstract
Cartilage degeneration is a characteristic of osteoarthritis (OA), which is often observed in aging populations. This degeneration is due to the breakdown of articular cartilage (AC) mechanical and tribological properties primarily attributed to lubrication failure. Understanding the reasons behind these failures and identifying
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Cartilage degeneration is a characteristic of osteoarthritis (OA), which is often observed in aging populations. This degeneration is due to the breakdown of articular cartilage (AC) mechanical and tribological properties primarily attributed to lubrication failure. Understanding the reasons behind these failures and identifying potential solutions could have significant economic and societal implications, ultimately enhancing quality of life. This review provides an overview of developments in the field of AC, focusing on its mechanical and tribological properties. The emphasis is on the role of lubrication in degraded AC, offering insights into its structure and function relationship. Further, it explores the fundamental connection between AC mechano-tribological properties and the advancement of its degradation and puts forth recommendations for strategies to boost its lubrication efficiency.
Full article
(This article belongs to the Special Issue Inspired by Nature: Advanced Biomaterials and Manufacturing Solutions for Skeletal Tissue Regeneration and Osteoarthritis Treatment)
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Open AccessArticle
An Improved Two-Shot Tracking Algorithm for Dynamics Analysis of Natural Killer Cells in Tumor Contexts
by
Yanqing Zhou, Yiwen Tang and Zhibing Li
Bioengineering 2024, 11(6), 540; https://doi.org/10.3390/bioengineering11060540 - 24 May 2024
Abstract
Natural killer cells (NKCs) are non-specific immune lymphocytes with diverse morphologies. Their broad killing effect on cancer cells has led to increased attention towards activating NKCs for anticancer immunotherapy. Consequently, understanding the motion characteristics of NKCs under different morphologies and modeling their collective
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Natural killer cells (NKCs) are non-specific immune lymphocytes with diverse morphologies. Their broad killing effect on cancer cells has led to increased attention towards activating NKCs for anticancer immunotherapy. Consequently, understanding the motion characteristics of NKCs under different morphologies and modeling their collective dynamics under cancer cells has become crucial. However, tracking small NKCs in complex backgrounds poses significant challenges, and conventional industrial tracking algorithms often perform poorly on NKC tracking datasets. There remains a scarcity of research on NKC dynamics. In this paper, we utilize deep learning techniques to analyze the morphology of NKCs and their key points. After analyzing the shortcomings of common industrial multi-object tracking algorithms like DeepSORT in tracking natural killer cells, we propose Distance Cascade Matching and the Re-Search method to improve upon existing algorithms, yielding promising results. Through processing and tracking over 5000 frames of images, encompassing approximately 300,000 cells, we preliminarily explore the impact of NKCs’ cell morphology, temperature, and cancer cell environment on NKCs’ motion, along with conducting basic modeling. The main conclusions of this study are as follows: polarized cells are more likely to move along their polarization direction and exhibit stronger activity, and the maintenance of polarization makes them more likely to approach cancer cells; under equilibrium, NK cells display a Boltzmann distribution on the cancer cell surface.
Full article
(This article belongs to the Special Issue Recent Advances in Optical Imaging and Machine Learning in Biomedicine)
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Open AccessArticle
Trivial State Fuzzy Processing for Error Reduction in Healthcare Big Data Analysis towards Precision Diagnosis
by
Mohd Anjum, Hong Min and Zubair Ahmed
Bioengineering 2024, 11(6), 539; https://doi.org/10.3390/bioengineering11060539 - 24 May 2024
Abstract
There is a significant public health concern regarding medical diagnosis errors, which are a major cause of mortality. Identifying the root cause of these errors is challenging, and even if one is identified, implementing an effective treatment to prevent their recurrence is difficult.
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There is a significant public health concern regarding medical diagnosis errors, which are a major cause of mortality. Identifying the root cause of these errors is challenging, and even if one is identified, implementing an effective treatment to prevent their recurrence is difficult. Optimization-based analysis in healthcare data management is a reliable method for improving diagnostic precision. Analyzing healthcare data requires pre-classification and the identification of precise information for precision-oriented outcomes. This article introduces a Cooperative-Trivial State Fuzzy Processing method for significant data analysis with possible derivatives. Trivial State Fuzzy Processing operates on the principle of fuzzy logic-based processing applied to structured healthcare data, focusing on mitigating errors and uncertainties inherent in the data. The derivatives are aided by identifying and grouping diagnosis-related and irrelevant data. The proposed method mitigates invertible derivative analysis issues in similar data grouping and irrelevance estimation. In the grouping and detection process, recent knowledge of the diagnosis progression is exploited to identify the functional data for analysis. Such analysis improves the impact of trivial diagnosis data compared to a voluminous diagnosis history. The cooperative derivative states under different data irrelevance factors reduce trivial state errors in healthcare big data analysis.
Full article
(This article belongs to the Special Issue Biomedical Application of Big Data and Artificial Intelligence)
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Open AccessReview
The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions
by
Paolo De Pasquale, Mirjam Bonanno, Sepehr Mojdehdehbaher, Angelo Quartarone and Rocco Salvatore Calabrò
Bioengineering 2024, 11(6), 538; https://doi.org/10.3390/bioengineering11060538 - 24 May 2024
Abstract
In recent years, there has been a notable increase in the clinical adoption of instrumental upper limb kinematic assessment. This trend aligns with the rising prevalence of cerebrovascular impairments, one of the most prevalent neurological disorders. Indeed, there is a growing need for
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In recent years, there has been a notable increase in the clinical adoption of instrumental upper limb kinematic assessment. This trend aligns with the rising prevalence of cerebrovascular impairments, one of the most prevalent neurological disorders. Indeed, there is a growing need for more objective outcomes to facilitate tailored rehabilitation interventions following stroke. Emerging technologies, like head-mounted virtual reality (HMD-VR) platforms, have responded to this demand by integrating diverse tracking methodologies. Specifically, HMD-VR technology enables the comprehensive tracking of body posture, encompassing hand position and gesture, facilitated either through specific tracker placements or via integrated cameras coupled with sophisticated computer graphics algorithms embedded within the helmet. This review aims to present the state-of-the-art applications of HMD-VR platforms for kinematic analysis of the upper limb in post-stroke patients, comparing them with conventional tracking systems. Additionally, we address the potential benefits and challenges associated with these platforms. These systems might represent a promising avenue for safe, cost-effective, and portable objective motor assessment within the field of neurorehabilitation, although other systems, including robots, should be taken into consideration.
Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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Open AccessArticle
Biomechanical Modelling of Porcine Kidney
by
Aadarsh Mishra and Robin O. Cleveland
Bioengineering 2024, 11(6), 537; https://doi.org/10.3390/bioengineering11060537 - 24 May 2024
Abstract
In this study, the viscoelastic properties of porcine kidney in the upper, middle and lower poles were investigated using oscillatory shear tests. The viscoelastic properties were extracted in the form of the storage modulus and loss modulus in the frequency and time domain.
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In this study, the viscoelastic properties of porcine kidney in the upper, middle and lower poles were investigated using oscillatory shear tests. The viscoelastic properties were extracted in the form of the storage modulus and loss modulus in the frequency and time domain. Measurements were taken as a function of frequency from 0.1 Hz to 6.5 Hz at a shear strain amplitude of 0.01 and as function of strain amplitude from 0.001 to 0.1 at a frequency of 1 Hz. Measurements were also taken in the time domain in response to a step shear strain. Both the frequency and time domain data were fitted to a conventional Standard Linear Solid (SLS) model and a semi-fractional Kelvin–Voigt (SFKV) model with a comparable number of parameters. The SFKV model fitted the frequency and time domain data with a correlation coefficient of 0.99. Although the SLS model well fitted the time domain data and the storage modulus data in the frequency domain, it was not able to capture the variation in loss modulus with frequency with a correlation coefficient of 0.53. A five parameter Maxwell–Wiechert model was able to capture the frequency dependence in storage modulus and loss modulus better than the SLS model with a correlation of 0.85.
Full article
(This article belongs to the Special Issue Biomechanics Analysis in Tissue Engineering)
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Open AccessSystematic Review
Fracture Resistance of Direct versus Indirect Restorations on Posterior Teeth: A Systematic Review and Meta-Analysis
by
Carol Moussa, Guillaume Savard, Gael Rochefort, Matthieu Renaud, Frédéric Denis and Maha H. Daou
Bioengineering 2024, 11(6), 536; https://doi.org/10.3390/bioengineering11060536 - 24 May 2024
Abstract
The aim of this systematic review and meta-analysis was to compare static compression forces between direct composite resin restorations and indirect restorations for posterior teeth. All studies comparing mechanical properties of direct versus indirect restorations of posterior teeth were included from 2007 up
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The aim of this systematic review and meta-analysis was to compare static compression forces between direct composite resin restorations and indirect restorations for posterior teeth. All studies comparing mechanical properties of direct versus indirect restorations of posterior teeth were included from 2007 up to February 2024. A meta-analysis was conducted for static compression fracture resistance. Medline, Central, and Embase databases were screened. Twenty-four articles were included in the qualitative synthesis, and sixteen studies were finally included in the quantitative synthesis. There was no difference in terms of fracture resistance between direct and indirect restorations for posterior teeth (p = 0.16 for direct and indirect composite resin restorations and p = 0.87 for direct composite resin restorations and indirect ceramic restorations). Also, sub-group analysis with or without cusp coverage in each group revealed no discernable difference. Based on this study, it can be concluded that the choice between direct and indirect restoration approaches may not significantly impact fracture resistance outcomes. There was no statically significant difference between direct and indirect restorations for posterior teeth in all cases of restorations with or without cusp coverage and no matter the used materials. However, to better evaluate these materials, further studies are warranted.
Full article
(This article belongs to the Special Issue Bioceramic Strategy—the Game of Bioactivity in Endodontic)
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Open AccessReview
A Self-Polymerizing Mesh of Nano-Tethers for the Mechanical Constraint of Degraded Intervertebral Discs—A Review of 25 Years of Pre-Clinical and Early Clinical Research
by
Thomas Hedman, Adam Rogers and Douglas Beall
Bioengineering 2024, 11(6), 535; https://doi.org/10.3390/bioengineering11060535 - 24 May 2024
Abstract
Genipin polymers are self-forming tensile-load-carrying oligomers, derived from the gardenia fruit, that covalently bond to amines on collagen. The potential therapeutic mechanical benefits of a non-discrete in situ forming mesh of genipin oligomers for degraded spinal discs were first conceived in 1998. Over
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Genipin polymers are self-forming tensile-load-carrying oligomers, derived from the gardenia fruit, that covalently bond to amines on collagen. The potential therapeutic mechanical benefits of a non-discrete in situ forming mesh of genipin oligomers for degraded spinal discs were first conceived in 1998. Over more than two decades, numerous studies have demonstrated the immediate mechanical effects of this injectable, intra-annular polymeric mesh including an early demonstration of an effect on clinical outcomes for chronic or recurrent discogenic low back pain. This literature review focused on articles investigating mechanical effects in cadaveric animal and human spinal discs, biochemical mechanism of action studies, articles describing the role of mechanical degradation in the pathogenesis of degenerative disc disease, initial clinical outcomes and articles describing current discogenic low back pain treatment algorithms. On the basis of these results, clinical indications that align with the capabilities of this novel injectable polymer-based treatment strategy are discussed. It is intended that this review of a novel nano-scale material-based solution for mechanical deficiencies in biologically limited tissues may provide a helpful example for other innovations in spinal diseases and similarly challenging musculoskeletal disorders.
Full article
(This article belongs to the Special Issue Bioengineering Strategies for the Improvement of Therapies in Spinal Diseases)
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Open AccessReview
Alexander Friedenstein, Mesenchymal Stem Cells, Shifting Paradigms and Euphemisms
by
Donald G. Phinney
Bioengineering 2024, 11(6), 534; https://doi.org/10.3390/bioengineering11060534 - 23 May 2024
Abstract
Six decades ago, Friedenstein and coworkers published a series of seminal papers identifying a cell population in bone marrow with osteogenic potential, now referred to as mesenchymal stem cells (MSCs). This work was also instrumental in establishing the identity of hematopoietic stem cell
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Six decades ago, Friedenstein and coworkers published a series of seminal papers identifying a cell population in bone marrow with osteogenic potential, now referred to as mesenchymal stem cells (MSCs). This work was also instrumental in establishing the identity of hematopoietic stem cell and the identification of skeletal stem/progenitor cell (SSPC) populations in various skeletal compartments. In recognition of the centenary year of Friedenstein’s birth, I review key aspects of his work and discuss the evolving concept of the MSC and its various euphemisms indorsed by changing paradigms in the field. I also discuss the recent emphasis on MSC stromal quality attributes and how emerging data demonstrating a mechanistic link between stromal and stem/progenitor functions bring renewed relevance to Friedenstein’s contributions and much needed unity to the field.
Full article
(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
Unraveling the Potential of Attentive Bi-LSTM for Accurate Obesity Prognosis: Advancing Public Health towards Sustainable Cities
by
Hina Ayub, Murad-Ali Khan, Syed Shehryar Ali Naqvi, Muhammad Faseeh, Jungsuk Kim, Asif Mehmood and Young-Jin Kim
Bioengineering 2024, 11(6), 533; https://doi.org/10.3390/bioengineering11060533 - 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 - 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 - 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
by
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.
Full article
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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
by
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
by
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.
Full article
(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
by
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.
Full article
(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
by
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
by
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
by
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.
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(This article belongs to the Section Biosignal Processing)
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