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
Ultra-High Contrast MRI: Using Divided Subtracted Inversion Recovery (dSIR) and Divided Echo Subtraction (dES) Sequences to Study the Brain and Musculoskeletal System
Bioengineering 2024, 11(5), 441; https://doi.org/10.3390/bioengineering11050441 (registering DOI) - 29 Apr 2024
Abstract
Divided and subtracted MRI is a novel imaging processing technique, where the difference of two images is divided by their sum. When the sequence parameters are chosen properly, this results in images with a high T1 or T2 weighting over a
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Divided and subtracted MRI is a novel imaging processing technique, where the difference of two images is divided by their sum. When the sequence parameters are chosen properly, this results in images with a high T1 or T2 weighting over a small range of tissues with specific T1 and T2 values. In the T1 domain, we describe the implementation of the divided Subtracted Inversion Recovery Sequence (dSIR), which is used to image very small changes in T1 from normal in white matter. dSIR has shown widespread changes in otherwise normal-appearing white matter in patients suffering from mild traumatic brain injury (mTBI), substance abuse, and ischemic leukoencephalopathy. It can also be targeted to measure small changes in T1 from normal in other tissues. In the T2 domain, we describe the divided echo subtraction (dES) sequence that is used to image musculoskeletal tissues with a very short T2*. These tissues include fascia, tendons, and aponeuroses. In this manuscript, we explain how this contrast is generated, review how these techniques are used in our research, and discuss the current challenges and limitations of this technique.
Full article
(This article belongs to the Special Issue Novel MRI Techniques and Biomedical Image Processing)
Open AccessArticle
Unveiling the Unpredictable in Parkinson’s Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life
by
Alessandro Zampogna, Luigi Borzì, Domiziana Rinaldi, Carlo Alberto Artusi, Gabriele Imbalzano, Martina Patera, Leonardo Lopiano, Francesco Pontieri, Gabriella Olmo and Antonio Suppa
Bioengineering 2024, 11(5), 440; https://doi.org/10.3390/bioengineering11050440 (registering DOI) - 29 Apr 2024
Abstract
Background: Dyskinesias and freezing of gait are episodic disorders in Parkinson’s disease, characterized by a fluctuating and unpredictable nature. This cross-sectional study aims to objectively monitor Parkinsonian patients experiencing dyskinesias and/or freezing of gait during activities of daily living and assess possible changes
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Background: Dyskinesias and freezing of gait are episodic disorders in Parkinson’s disease, characterized by a fluctuating and unpredictable nature. This cross-sectional study aims to objectively monitor Parkinsonian patients experiencing dyskinesias and/or freezing of gait during activities of daily living and assess possible changes in spatiotemporal gait parameters. Methods: Seventy-one patients with Parkinson’s disease (40 with dyskinesias and 33 with freezing of gait) were continuously monitored at home for a minimum of 5 days using a single wearable sensor. Dedicated machine-learning algorithms were used to categorize patients based on the occurrence of dyskinesias and freezing of gait. Additionally, specific spatiotemporal gait parameters were compared among patients with and without dyskinesias and/or freezing of gait. Results: The wearable sensor algorithms accurately classified patients with and without dyskinesias as well as those with and without freezing of gait based on the recorded dyskinesias and freezing of gait episodes. Standard spatiotemporal gait parameters did not differ significantly between patients with and without dyskinesias or freezing of gait. Both the time spent with dyskinesias and the number of freezing of gait episodes positively correlated with the disease severity and medication dosage. Conclusions: A single inertial wearable sensor shows promise in monitoring complex, episodic movement patterns, such as dyskinesias and freezing of gait, during daily activities. This approach may help implement targeted therapeutic and preventive strategies for Parkinson’s disease.
Full article
(This article belongs to the Special Issue Intelligent Health Management, Nursing and Rehabilitation Technology)
Open AccessArticle
Bioprinting of Perfusable, Biocompatible Vessel-like Channels with dECM-Based Bioinks and Living Cells
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Marta Klak, Michał Rachalewski, Anna Filip, Tomasz Dobrzański, Andrzej Berman and Michał Wszoła
Bioengineering 2024, 11(5), 439; https://doi.org/10.3390/bioengineering11050439 (registering DOI) - 29 Apr 2024
Abstract
There is a growing interest in the production of bioinks that on the one hand, are biocompatible and, on the other hand, have mechanical properties that allow for the production of stable constructs that can survive for a long time after transplantation. While
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There is a growing interest in the production of bioinks that on the one hand, are biocompatible and, on the other hand, have mechanical properties that allow for the production of stable constructs that can survive for a long time after transplantation. While the selection of the right material is crucial for bioprinting, there is another equally important issue that is currently being extensively researched—the incorporation of the vascular system into the fabricated scaffolds. Therefore, in the following manuscript, we present the results of research on bioink with unique physico-chemical and biological properties. In this article, two methods of seeding cells were tested using bioink B and seeding after bioprinting the whole model. After 2, 5, 8, or 24 h of incubation, the flow medium was used in the tested systems. At the end of the experimental trial, for each time variant, the canals were stored in formaldehyde, and immunohistochemical staining was performed to examine the presence of cells on the canal walls and roof. Cells adhered to both ways of fiber arrangement; however, a parallel bioprint with the 5 h incubation and the intermediate plating of cells resulted in better adhesion efficiency. For this test variant, the percentage of cells that adhered was at least 20% higher than in the other analyzed variants. In addition, it was for this variant that the lowest percentage of viable cells was found that were washed out of the tested model. Importantly, hematoxylin and eosin staining showed that after 8 days of culture, the cells were evenly distributed throughout the canal roof. Our study clearly shows that neovascularization-promoting cells effectively adhere to ECM-based pancreatic bioink. Summarizing the presented results, it was demonstrated that the proposed bioink compositions can be used for bioprinting bionic organs with a vascular system formed by endothelial cells and fibroblasts.
Full article
(This article belongs to the Special Issue 3D Bioprinting Advanced Vascularized Tissues and Organs)
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Open AccessArticle
Mendelian Randomization Reveals: Triglycerides and Sensorineural Hearing Loss
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Shun Ding, Yixuan Liu, Tingting Duan, Peng Fang, Qiling Tong, Huawei Li and Huiqian Yu
Bioengineering 2024, 11(5), 438; https://doi.org/10.3390/bioengineering11050438 (registering DOI) - 29 Apr 2024
Abstract
Background: Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR),
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Background: Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR), which offers a method to reduce confounding and reverse causality by using genetic variants as instrumental variables. Methods: Utilizing publicly available genome-wide association study (GWAS) data, we performed a two-sample MR analysis. The initial analysis unveiled a causal relationship between TG (GWAS ID: ebi-a-GCST90018975) and SNHL (GWAS ID: finn b-H8_HL_SEN-NAS). Subsequent analysis validated this through MR with a larger sample size for TG (GWAS ID: ieu-b-111) and SNHL. To conduct the MR analysis, we utilized several methods including inverse-variance weighted (IVW), MR Egger, weighted median, and weighted mode. We also employed Cochrane’s Q test to identify any heterogeneity in the MR results. To detect horizontal pleiotropy, we conducted the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. We performed a leave-one-out analysis to assess the sensitivity of this association. Finally, a meta-analysis of the MR results was undertaken. Results: Our study found a significant positive correlation between TG and SNHL, with OR values of 1.14 (95% CI: 1.07–1.23, p < 0.001) in the IVW analysis and 1.09 (95% CI: 1.03–1.16, p < 0.006) in the replicate analysis. We also found no evidence of horizontal pleiotropy or heterogeneity between the genetic variants (p > 0.05), and a leave-one-out test confirmed the stability and robustness of this association. The meta-analysis combining the initial and replicate analyses showed a significant causal effect with OR values of 1.11 (95% CI: 1.06–1.16, p = 0.01). Conclusion: These findings indicate TG as a risk factor for SNHL, suggesting potential pathways for prevention and intervention in populations at risk. This conclusion underscores the importance of managing TG levels as a strategy to mitigate the risk of developing SNHL.
Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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Open AccessArticle
Repair of Rat Calvarial Critical-Sized Defects Using Heparin-Conjugated Fibrin Hydrogel Containing BMP-2 and Adipose-Derived Pericytes
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Gulshakhar Kudaibergen, Sholpan Mukhlis, Ainur Mukhambetova, Assel Issabekova, Aliya Sekenova, Madina Sarsenova, Abay Temirzhan, Murat Baidarbekov, Baurzhan Umbayev and Vyacheslav Ogay
Bioengineering 2024, 11(5), 437; https://doi.org/10.3390/bioengineering11050437 (registering DOI) - 29 Apr 2024
Abstract
The repair of critical-sized calvarial defects is a challenging problem for orthopedic surgery. One of the promising strategies of bone bioengineering to enhance the efficacy of large bone defect regeneration is the combined delivery of stem cells with osteoinductive factors within polymer carriers.
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The repair of critical-sized calvarial defects is a challenging problem for orthopedic surgery. One of the promising strategies of bone bioengineering to enhance the efficacy of large bone defect regeneration is the combined delivery of stem cells with osteoinductive factors within polymer carriers. The purpose of the research was to study the regenerative effects of heparin-conjugated fibrin (HCF) hydrogel containing bone morphogenetic protein 2 (BMP-2) and adipose-derived pericytes (ADPs) in a rat critical-sized calvarial defect model. In vitro analysis revealed that the HCF hydrogel was able to control the BMP-2 release and induce alkaline phosphatase (ALP) activity in neonatal rat osteoblasts. In addition, it was found that eluted BMP-2 significantly induced the osteogenic differentiation of ADPs. It was characterized by the increased ALP activity, osteocalcin expression and calcium deposits in ADPs. In vivo studies have shown that both HCF hydrogel with BMP-2 and HCF hydrogel with pericytes are able to significantly increase the regeneration of critical-sized calvarial defects in comparison with the control group. Nevertheless, the greatest regenerative effect was found after the co-delivery of ADPs and BMP-2 into a critical-sized calvarial defect. Thus, our findings suggest that the combined delivery of ADPs and BMP-2 in HCF hydrogel holds promise to be applied as an alternative biopolymer for the critical-sized bone defect restoration.
Full article
(This article belongs to the Special Issue Bone Tissue Engineering and Translational Research)
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Open AccessArticle
Hybrid Materials for Vascular Applications: A Preliminary In Vitro Assessment
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Martina Todesco, Martina Casarin, Deborah Sandrin, Laura Astolfi, Filippo Romanato, Germana Giuggioli, Fabio Conte, Gino Gerosa, Chiara Giulia Fontanella and Andrea Bagno
Bioengineering 2024, 11(5), 436; https://doi.org/10.3390/bioengineering11050436 (registering DOI) - 28 Apr 2024
Abstract
The production of biomedical devices able to appropriately interact with the biological environment is still a great challenge. Synthetic materials are often employed, but they fail to replicate the biological and functional properties of native tissues, leading to a variety of adverse effects.
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The production of biomedical devices able to appropriately interact with the biological environment is still a great challenge. Synthetic materials are often employed, but they fail to replicate the biological and functional properties of native tissues, leading to a variety of adverse effects. Several commercial products are based on chemically treated xenogeneic tissues: their principal drawback is due to weak mechanical stability and low durability. Recently, decellularization has been proposed to bypass the drawbacks of both synthetic and biological materials. Acellular materials can integrate with host tissues avoiding/mitigating any foreign body response, but they often lack sufficient patency and impermeability. The present paper investigates an innovative approach to the realization of hybrid materials that combine decellularized bovine pericardium with polycarbonate urethanes. These hybrid materials benefit from the superior biocompatibility of the biological tissue and the mechanical properties of the synthetic polymers. They were assessed from physicochemical, structural, mechanical, and biological points of view; their ability to promote cell growth was also investigated. The decellularized pericardium and the polymer appeared to well adhere to each other, and the two sides were distinguishable. The maximum elongation of hybrid materials was mainly affected by the pericardium, which allows for lower elongation than the polymer; this latter, in turn, influenced the maximum strength achieved. The results confirmed the promising features of hybrid materials for the production of vascular grafts able to be repopulated by circulating cells, thus, improving blood compatibility.
Full article
(This article belongs to the Special Issue Hybrid and Composite Biomaterials for Healthcare: Toward Innovative Approaches)
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Open AccessArticle
Evaluation of Skin Wound Healing with Biosheets Containing Somatic Stem Cells in a Dog Model: A Pilot Study
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Noritaka Maeta, Ryosuke Iwai, Hiroshi Takemitsu, Natsuki Akashi, Masahiro Miyabe, Marina Funayama-Iwai and Yasuhide Nakayama
Bioengineering 2024, 11(5), 435; https://doi.org/10.3390/bioengineering11050435 (registering DOI) - 28 Apr 2024
Abstract
The administration of mesenchymal stem cells (MSCs) has a positive effect on wound healing; however, the lack of adequate MSC engraftment at the wound site is a major limiting factor in current MSC-based therapies. In this study, a biosheet prepared using in-body tissue
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The administration of mesenchymal stem cells (MSCs) has a positive effect on wound healing; however, the lack of adequate MSC engraftment at the wound site is a major limiting factor in current MSC-based therapies. In this study, a biosheet prepared using in-body tissue architecture (iBTA) was used as a material to address these problems. This study aimed to assess and evaluate whether biosheets containing somatic stem cells would affect the wound healing process in dogs. Biosheets were prepared by subcutaneously embedding molds in beagles. These were then evaluated grossly and histologically, and the mRNA expression of inflammatory cytokines, interleukins, and Nanog was examined in some biosheets. Skin defects were created on the skin of the beagles to which the biosheets were applied. The wound healing processes of the biosheet and control (no biosheet application) groups were compared for 8 weeks. Nanog mRNA was expressed in the biosheets, and SSEA4/CD105 positive cells were observed histologically. Although the wound contraction rates differed significantly in the first week, the biosheet group tended to heal faster than the control group. This study revealed that biosheets containing somatic stem cells may have a positive effect on wound healing.
Full article
(This article belongs to the Section Regenerative Engineering)
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Open AccessArticle
Synergizing Deep Learning-Enabled Preprocessing and Human–AI Integration for Efficient Automatic Ground Truth Generation
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Christopher Collazo, Ian Vargas, Brendon Cara, Carla J. Weinheimer, Ryan P. Grabau, Dmitry Goldgof, Lawrence Hall, Samuel A. Wickline and Hua Pan
Bioengineering 2024, 11(5), 434; https://doi.org/10.3390/bioengineering11050434 (registering DOI) - 28 Apr 2024
Abstract
The progress of incorporating deep learning in the field of medical image interpretation has been greatly hindered due to the tremendous cost and time associated with generating ground truth for supervised machine learning, alongside concerns about the inconsistent quality of images acquired. Active
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The progress of incorporating deep learning in the field of medical image interpretation has been greatly hindered due to the tremendous cost and time associated with generating ground truth for supervised machine learning, alongside concerns about the inconsistent quality of images acquired. Active learning offers a potential solution to these problems of expanding dataset ground truth by algorithmically choosing the most informative samples for ground truth labeling. Still, this effort incurs the costs of human labeling, which needs minimization. Furthermore, automatic labeling approaches employing active learning often exhibit overfitting tendencies while selecting samples closely aligned with the training set distribution and excluding out-of-distribution samples, which could potentially improve the model’s effectiveness. We propose that the majority of out-of-distribution instances can be attributed to inconsistent cross images. Since the FDA approved the first whole-slide image system for medical diagnosis in 2017, whole-slide images have provided enriched critical information to advance the field of automated histopathology. Here, we exemplify the benefits of a novel deep learning strategy that utilizes high-resolution whole-slide microscopic images. We quantitatively assess and visually highlight the inconsistencies within the whole-slide image dataset employed in this study. Accordingly, we introduce a deep learning-based preprocessing algorithm designed to normalize unknown samples to the training set distribution, effectively mitigating the overfitting issue. Consequently, our approach significantly increases the amount of automatic region-of-interest ground truth labeling on high-resolution whole-slide images using active deep learning. We accept 92% of the automatic labels generated for our unlabeled data cohort, expanding the labeled dataset by 845%. Additionally, we demonstrate expert time savings of 96% relative to manual expert ground-truth labeling.
Full article
(This article belongs to the Special Issue Machine Learning Technology in Biomedical Engineering—2nd Edition)
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Open AccessArticle
Impact of Polyethylene-Glycol-Induced Water Potential on Methane Yield and Microbial Consortium Dynamics in the Anaerobic Degradation of Glucose
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Jin Yeo and Yong-Woo Jeon
Bioengineering 2024, 11(5), 433; https://doi.org/10.3390/bioengineering11050433 (registering DOI) - 27 Apr 2024
Abstract
This study investigated the relationship between water potential (Ψ) and the cation-induced inhibition of methane production in anaerobic digesters. The Ψ around methanogens was manipulated using polyethylene glycol (PEG) in a batch anaerobic reactor, ranging from −0.92 to −5.10 MPa. The ultimate methane
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This study investigated the relationship between water potential (Ψ) and the cation-induced inhibition of methane production in anaerobic digesters. The Ψ around methanogens was manipulated using polyethylene glycol (PEG) in a batch anaerobic reactor, ranging from −0.92 to −5.10 MPa. The ultimate methane potential (Bu) decreased significantly from 0.293 to 0.002 Nm3 kg−1-VSadded as Ψ decreased. When Ψ lowered from −0.92 MPa to −1.48 MPa, the community distribution of acetoclastic Methanosarcina decreased from 59.62% to 40.44%, while those of hydrogenotrophic Methanoculleus and Methanobacterium increased from 17.70% and 1.30% to 36.30% and 18.07%, respectively. These results mirrored changes observed in methanogenic communities affected by cation inhibition with KCl. Our findings strongly indicate that the inhibitory effect of cations on methane production may stem more from the water stress induced by cations than from their direct toxic effects. This study highlights the importance of considering Ψ dynamics in understanding cation-mediated inhibition in anaerobic digesters, providing insights into optimizing microbial processes for enhanced methane production from organic substrates.
Full article
(This article belongs to the Section Biochemical Engineering)
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Open AccessReview
Recent Advances of MSCs in Renal IRI: From Injury to Renal Fibrosis
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Xinhao Niu, Xiaoqing Xu, Cuidi Xu, Yin Celeste Cheuk and Ruiming Rong
Bioengineering 2024, 11(5), 432; https://doi.org/10.3390/bioengineering11050432 (registering DOI) - 27 Apr 2024
Abstract
Renal fibrosis is a pathological endpoint of maladaptation after ischemia-reperfusion injury (IRI), and despite many attempts, no good treatment has been achieved so far. At the core of renal fibrosis is the differentiation of various types of cells into myofibroblasts. MSCs were once
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Renal fibrosis is a pathological endpoint of maladaptation after ischemia-reperfusion injury (IRI), and despite many attempts, no good treatment has been achieved so far. At the core of renal fibrosis is the differentiation of various types of cells into myofibroblasts. MSCs were once thought to play a protective role after renal IRI. However, growing evidence suggests that MSCs have a two-sided nature. In spite of their protective role, in maladaptive situations, MSCs start to differentiate towards myofibroblasts, increasing the myofibroblast pool and promoting renal fibrosis. Following renal IRI, it has been observed that Bone Marrow-Derived Mesenchymal Stem Cells (BM-MSCs) and Renal Resident Mesenchymal Stem Cells (RR-MSCs) play important roles. This review presents evidence supporting their involvement, discusses their potential mechanisms of action, and suggests several new targets for future research.
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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 AccessReview
Artificial Intelligence in Adult and Pediatric Dentistry: A Narrative Review
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Seyed Mohammadrasoul Naeimi, Shayan Darvish, Bahareh Nazemi Salman and Ionut Luchian
Bioengineering 2024, 11(5), 431; https://doi.org/10.3390/bioengineering11050431 (registering DOI) - 27 Apr 2024
Abstract
Artificial intelligence (AI) has been recently introduced into clinical dentistry, and it has assisted professionals in analyzing medical data with unprecedented speed and an accuracy level comparable to humans. With the help of AI, meaningful information can be extracted from dental databases, especially
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Artificial intelligence (AI) has been recently introduced into clinical dentistry, and it has assisted professionals in analyzing medical data with unprecedented speed and an accuracy level comparable to humans. With the help of AI, meaningful information can be extracted from dental databases, especially dental radiographs, to devise machine learning (a subset of AI) models. This study focuses on models that can diagnose and assist with clinical conditions such as oral cancers, early childhood caries, deciduous teeth numbering, periodontal bone loss, cysts, peri-implantitis, osteoporosis, locating minor apical foramen, orthodontic landmark identification, temporomandibular joint disorders, and more. The aim of the authors was to outline by means of a review the state-of-the-art applications of AI technologies in several dental subfields and to discuss the efficacy of machine learning algorithms, especially convolutional neural networks (CNNs), among different types of patients, such as pediatric cases, that were neglected by previous reviews. They performed an electronic search in PubMed, Google Scholar, Scopus, and Medline to locate relevant articles. They concluded that even though clinicians encounter challenges in implementing AI technologies, such as data management, limited processing capabilities, and biased outcomes, they have observed positive results, such as decreased diagnosis costs and time, as well as early cancer detection. Thus, further research and development should be considered to address the existing complications.
Full article
(This article belongs to the Special Issue Artificial Intelligence in Healthcare)
Open AccessReview
Advancements and Challenges in Non-Invasive Sensor Technologies for Swallowing Assessment: A Review
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Yuwen Wu, Kai Guo, Yuyi Chu, Zhisen Wang, Hongbo Yang and Juzhong Zhang
Bioengineering 2024, 11(5), 430; https://doi.org/10.3390/bioengineering11050430 (registering DOI) - 27 Apr 2024
Abstract
Dysphagia is a pervasive health issue that impacts diverse demographic groups worldwide, particularly the elderly, stroke survivors, and those suffering from neurological disorders. This condition poses substantial health risks, including malnutrition, respiratory complications, and increased mortality. Additionally, it exacerbates economic burdens by extending
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Dysphagia is a pervasive health issue that impacts diverse demographic groups worldwide, particularly the elderly, stroke survivors, and those suffering from neurological disorders. This condition poses substantial health risks, including malnutrition, respiratory complications, and increased mortality. Additionally, it exacerbates economic burdens by extending hospital stays and escalating healthcare costs. Given that this disorder is frequently underestimated in vulnerable populations, there is an urgent need for enhanced diagnostic and therapeutic strategies. Traditional diagnostic tools such as the videofluoroscopic swallowing study (VFSS) and flexible endoscopic evaluation of swallowing (FEES) require interpretation by clinical experts and may lead to complications. In contrast, non-invasive sensors offer a more comfortable and convenient approach for assessing swallowing function. This review systematically examines recent advancements in non-invasive swallowing function detection devices, focusing on the validation of the device designs and their implementation in clinical practice. Moreover, this review discusses the swallowing process and the associated biomechanics, providing a theoretical foundation for the technologies discussed. It is hoped that this comprehensive overview will facilitate a paradigm shift in swallowing assessments, steering the development of technologies towards more accessible and accurate diagnostic tools, thereby improving patient care and treatment outcomes.
Full article
(This article belongs to the Special Issue Intelligent Health Management, Nursing and Rehabilitation Technology)
Open AccessArticle
Diagnosis of Forme Fruste Keratoconus Using Corvis ST Sequences with Digital Image Correlation and Machine Learning
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Lanting Yang, Kehan Qi, Peipei Zhang, Jiaxuan Cheng, Hera Soha, Yun Jin, Haochen Ci, Xianling Zheng, Bo Wang, Yue Mei, Shihao Chen and Junjie Wang
Bioengineering 2024, 11(5), 429; https://doi.org/10.3390/bioengineering11050429 (registering DOI) - 26 Apr 2024
Abstract
Purpose: This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish
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Purpose: This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish forme fruste keratoconus (FFKC) from normal corneas. Methods: 100 subjects were categorized into normal (N = 50) and FFKC (N = 50) groups. Image sequences depicting the horizontal cross-section of the human cornea under air puff were captured using the Corvis ST tonometer. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed utilizing the incremental DIC approach. Maximum (max-) and average (ave-) values of full-field displacement V, shear strain γxy, velocity VR, and shear strain rate γxyR were determined over time, generating eight evolution curves denoting max-V, max-γxy, max-VR, max-γxyR, ave-V, ave-γxy, ave-VR, and ave-γxyR, respectively. These evolution data were inputted into two machine learning (ML) models, specifically Naïve Bayes (NB) and Random Forest (RF) models, which were subsequently employed to construct a voting classifier. The performance of the models in diagnosing FFKC from normal corneas was compared to existing CVS parameters. Results: The Normal group and the FFKC group each included 50 eyes. The FFKC group did not differ from healthy controls for age (p = 0.26) and gender (p = 0.36) at baseline, but they had significantly lower bIOP (p < 0.001) and thinner central cornea thickness (CCT) (p < 0.001). The results demonstrated that the proposed voting ensemble model yielded the highest performance with an AUC of 1.00, followed by the RF model with an AUC of 0.99. Radius and A2 Time emerged as the best-performing CVS parameters with AUC values of 0.948 and 0.938, respectively. Nonetheless, no existing Corvis ST parameters outperformed the ML models. A progressive enhancement in performance of the ML models was observed with incremental time points during the corneal deformation. Conclusion: This study represents the first instance where displacement and strain data following incremental DIC analysis of Corvis ST images were integrated with machine learning models to effectively differentiate FFKC corneas from normal ones, achieving superior accuracy compared to existing CVS parameters. Considering biomechanical responses of the inner cornea and their temporal pattern changes may significantly improve the early detection of keratoconus.
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(This article belongs to the Special Issue Ophthalmic Engineering 2.0)
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Open AccessArticle
Automatic Estimation of the Interference Subspace Dimension Threshold in the Subspace Projection Algorithms of Magnetoencephalography Based on Evoked State Data
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Ruochen Zhao, Ruonan Wang, Yang Gao and Xiaolin Ning
Bioengineering 2024, 11(5), 428; https://doi.org/10.3390/bioengineering11050428 - 26 Apr 2024
Abstract
A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal
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A class of algorithms based on subspace projection is widely used in the denoising of magnetoencephalography (MEG) signals. Setting the dimension of the interference (external) subspace matrix of these algorithms is the key to balancing the denoising effect and the degree of signal distortion. However, most current methods for estimating the dimension threshold rely on experience, such as observing the signal waveforms and spectrum, which may render the results too subjective and lacking in quantitative accuracy. Therefore, this study proposes a method to automatically estimate a suitable threshold. Time–frequency transformations are performed on the evoked state data to obtain the neural signal of interest and the noise signal in a specific time–frequency band, which are then used to construct the objective function describing the degree of noise suppression and signal distortion. The optimal value of the threshold in the selected range is obtained using the weighted-sum method. Our method was tested on two classical subspace projection algorithms using simulation and two sensory stimulation experiments. The thresholds estimated by the proposed method enabled the algorithms to achieve the best waveform recovery and source location error. Therefore, the threshold selected in this method enables subspace projection algorithms to achieve the best balance between noise removal and neural signal preservation in subsequent MEG analyses.
Full article
(This article belongs to the Special Issue 10th Anniversary of Bioengineering: Biosignal Processing)
Open AccessArticle
A Novel Mis-Seg-Focus Loss Function Based on a Two-Stage nnU-Net Framework for Accurate Brain Tissue Segmentation
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Keyi He, Bo Peng, Weibo Yu, Yan Liu, Surui Liu, Jian Cheng and Yakang Dai
Bioengineering 2024, 11(5), 427; https://doi.org/10.3390/bioengineering11050427 - 26 Apr 2024
Abstract
Brain tissue segmentation plays a critical role in the diagnosis, treatment, and study of brain diseases. Accurately identifying these boundaries is essential for improving segmentation accuracy. However, distinguishing boundaries between different brain tissues can be challenging, as they often overlap. Existing deep learning
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Brain tissue segmentation plays a critical role in the diagnosis, treatment, and study of brain diseases. Accurately identifying these boundaries is essential for improving segmentation accuracy. However, distinguishing boundaries between different brain tissues can be challenging, as they often overlap. Existing deep learning methods primarily calculate the overall segmentation results without adequately addressing local regions, leading to error propagation and mis-segmentation along boundaries. In this study, we propose a novel mis-segmentation-focused loss function based on a two-stage nnU-Net framework. Our approach aims to enhance the model’s ability to handle ambiguous boundaries and overlapping anatomical structures, thereby achieving more accurate brain tissue segmentation results. Specifically, the first stage targets the identification of mis-segmentation regions using a global loss function, while the second stage involves defining a mis-segmentation loss function to adaptively adjust the model, thus improving its capability to handle ambiguous boundaries and overlapping anatomical structures. Experimental evaluations on two datasets demonstrate that our proposed method outperforms existing approaches both quantitatively and qualitatively.
Full article
(This article belongs to the Special Issue Novel MRI Techniques and Biomedical Image Processing)
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Open AccessArticle
A Novel Recombinant Human Filaggrin Segment (rhFLA-10) Alleviated a Skin Lesion of Atopic Dermatitis
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Jiawen Zhu, Xinhua Zhong, Hui Liao, Jianhang Cong, Qiqi Wu, Shuang Liang and Qi Xiang
Bioengineering 2024, 11(5), 426; https://doi.org/10.3390/bioengineering11050426 - 26 Apr 2024
Abstract
Atopic dermatitis (AD), a prevalent chronic inflammatory skin disorder, is marked by impaired skin barrier function and persistent pruritus. It significantly deteriorates patients’ quality of life, making it one of the most burdensome non-lethal skin disorders. Filaggrin plays a crucial role in the
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Atopic dermatitis (AD), a prevalent chronic inflammatory skin disorder, is marked by impaired skin barrier function and persistent pruritus. It significantly deteriorates patients’ quality of life, making it one of the most burdensome non-lethal skin disorders. Filaggrin plays a crucial role in the pathophysiology of barrier disruption in AD, interacting with inflammatory mediators. It is an integral part of the extracellular matrix architecture, serving to protect the skin barrier and attenuate the inflammatory cascade. In this study, we engineered a novel recombinant human filaggrin (rhFLA-10) expression vector, which was subsequently synthesized and purified. In vitro and ex vivo efficacy experiments were conducted for AD. rhFLA-10, at low concentrations (5 to 20 μg/mL), was non-toxic to HACaT cells, significantly inhibited the degranulation of P815 mast cells, and was readily absorbed by cells, thereby exerting a soothing therapeutic effect. Furthermore, rhFLA-10 demonstrated anti-inflammatory properties (p < 0.05). In vivo, efficacy experiments further substantiated that rhFLA-10 could effectively ameliorate AD in mice and facilitate the repair of damaged skin (p < 0.001). These findings underscore the considerable potential of rhFLA-10 in the treatment of AD.
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(This article belongs to the Section Biochemical Engineering)
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Open AccessReview
Modern In Vitro Techniques for Modeling Hearing Loss
by
Jamie J. Shah, Couger A. Jimenez-Jaramillo, Zane R. Lybrand, Tony T. Yuan and Isaac D. Erbele
Bioengineering 2024, 11(5), 425; https://doi.org/10.3390/bioengineering11050425 - 26 Apr 2024
Abstract
Sensorineural hearing loss (SNHL) is a prevalent and growing global health concern, especially within operational medicine, with limited therapeutic options available. This review article explores the emerging field of in vitro otic organoids as a promising platform for modeling hearing loss and developing
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Sensorineural hearing loss (SNHL) is a prevalent and growing global health concern, especially within operational medicine, with limited therapeutic options available. This review article explores the emerging field of in vitro otic organoids as a promising platform for modeling hearing loss and developing novel therapeutic strategies. SNHL primarily results from the irreversible loss or dysfunction of cochlear mechanosensory hair cells (HCs) and spiral ganglion neurons (SGNs), emphasizing the need for innovative solutions. Current interventions offer symptomatic relief but do not address the root causes. Otic organoids, three-dimensional multicellular constructs that mimic the inner ear’s architecture, have shown immense potential in several critical areas. They enable the testing of gene therapies, drug discovery for sensory cell regeneration, and the study of inner ear development and pathology. Unlike traditional animal models, otic organoids closely replicate human inner ear pathophysiology, making them invaluable for translational research. This review discusses methodological advances in otic organoid generation, emphasizing the use of human pluripotent stem cells (hPSCs) to replicate inner ear development. Cellular and molecular characterization efforts have identified key markers and pathways essential for otic organoid development, shedding light on their potential in modeling inner ear disorders. Technological innovations, such as 3D bioprinting and microfluidics, have further enhanced the fidelity of these models. Despite challenges and limitations, including the need for standardized protocols and ethical considerations, otic organoids offer a transformative approach to understanding and treating auditory dysfunctions. As this field matures, it holds the potential to revolutionize the treatment landscape for hearing and balance disorders, moving us closer to personalized medicine for inner ear conditions.
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(This article belongs to the Special Issue Operational Medicine Applications of Bioengineering)
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Open AccessCorrection
Correction: Reiter, J.; Beier, M. Deammonification Potential of Pig Slurries and Vapor Condensates from Sewage Sludge Drying—Substrate Quality and Inhibition. Bioengineering 2023, 10, 826
by
Johannes Reiter and Maike Beier
Bioengineering 2024, 11(5), 424; https://doi.org/10.3390/bioengineering11050424 - 25 Apr 2024
Abstract
In the original publication [...]
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Open AccessArticle
Glycosaminoglycans Modulate the Angiogenic Ability of Type I Collagen-Based Scaffolds by Acting on Vascular Network Remodeling and Maturation
by
Enrica Raffaella Grazia Salvante, Anca Voichita Popoiu, Amulya K. Saxena, Tudor Alexandru Popoiu, Eugen Sorin Boia, Anca Maria Cimpean, Florina Stefania Rus, Florica Ramona Dorobantu and Monica Chis
Bioengineering 2024, 11(5), 423; https://doi.org/10.3390/bioengineering11050423 - 25 Apr 2024
Abstract
Type I collagen, prevalent in the extracellular matrix, is biocompatible and crucial for tissue engineering and wound healing, including angiogenesis and vascular maturation/stabilization as required processes of newly formed tissue constructs or regeneration. Sometimes, improper vascularization causes unexpected outcomes. Vascularization failure may be
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Type I collagen, prevalent in the extracellular matrix, is biocompatible and crucial for tissue engineering and wound healing, including angiogenesis and vascular maturation/stabilization as required processes of newly formed tissue constructs or regeneration. Sometimes, improper vascularization causes unexpected outcomes. Vascularization failure may be caused by extracellular matrix collagen and non-collagen components heterogeneously. This study compares the angiogenic potential of collagen type I-based scaffolds and collagen type I/glycosaminoglycans scaffolds by using the chick embryo chorioallantoic membrane (CAM) model and IKOSA digital image analysis. Two clinically used biomaterials, Xenoderm (containing type I collagen derived from decellularized porcine extracellular matrix) and a dual-layer collagen sponge (DLC, with a biphasic composition of type I collagen combined with glycosaminoglycans) were tested for their ability to induce new vascular network formation. The AI-based IKOSA app enhanced the research by calculating from stereomicroscopic images angiogenic parameters such as total vascular area, branching sites, vessel length, and vascular thickness. The study confirmed that Xenoderm caused a fast angiogenic response and substantial vascular growth, but was unable to mature the vascular network. DLC scaffold, in turn, produced a slower angiogenic response, but a more steady and organic vascular maturation and stabilization. This research can improve collagen-based knowledge by better assessing angiogenesis processes. DLC may be preferable to Xenoderm or other materials for functional neovascularization, according to the findings.
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(This article belongs to the Special Issue Biomaterials for Angiogenesis)
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Decellularized Human Dermis for Orthoplastic Extremity Reconstruction
by
Christopher Bibbo and K. Ümit Yüksel
Bioengineering 2024, 11(5), 422; https://doi.org/10.3390/bioengineering11050422 - 25 Apr 2024
Abstract
The reconstruction of patients who possess multi morbid medical histories remains a challenge. With the ever-increasing number of patients with diabetes, infections, and trauma, there is a consistent need for promotion of soft tissue healing and a reliable substrate to assist with every
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The reconstruction of patients who possess multi morbid medical histories remains a challenge. With the ever-increasing number of patients with diabetes, infections, and trauma, there is a consistent need for promotion of soft tissue healing and a reliable substrate to assist with every aspect of soft tissue reconstruction, as well as the loss of fascial domain. Several proprietary products filled some of these needs but have failed to fulfill the needs of the clinician when faced with reconstructing multiple soft tissue systems, such as the integument and the musculoskeletal system. In this paper we discuss the use of decellularized human dermis (DermaPure®, Tissue Regenix, Universal City, TX, USA) through which a unique human tissue processing technique (dCELL® technology, Tissue Regenix, Universal City, TX, USA) and the creation of multiple product forms have proven to exhibit versatility in a wide range of clinical needs for successful soft tissue reconstruction. The background of human tissue processing, basic science, and early clinical studies are detailed, which has translated to the rationale for the success of this unique soft tissue substrate in orthoplastic reconstruction, which is also provided here in detail.
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(This article belongs to the Special Issue Foot and Ankle Surgery: Current Progresses and Emerging Technologies in Orthoplastic Reconstruction)
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