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Bioengineering
Volume 10
Issue 6
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Bioengineering, Volume 10, Issue 6 (June 2023) – 118 articles

Cover Story (view full-size image): The market for human therapeutic and diagnostic agents is increasingly dominated by monoclonal antibodies (mAb) produced by Chinese hamster ovary (CHO) cells. Innovative monitoring technologies and process optimization have enabled a shift to continuous cultivation strategies and stable operations at high space–time yields. Due to challenges associated with product recovery and cell retention efficiency of membrane-based systems in high-cell density processes, however, there is also a rising demand for alternative devices. We present a 3D-printed microfluidic spiral separator as a “plug and play” cell-retention device capable of increasing mAb yield in a CHO cell perfusion process. Additionally, we detail the implementation of a web-based flow control mechanism to ensure process stability. View this paper
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23 pages, 2506 KiB  
Review
From Spatial-Temporal Multiscale Modeling to Application: Bridging the Valley of Death in Industrial Biotechnology
by Xueting Wang, Ali Mohsin, Yifei Sun, Chao Li, Yingping Zhuang and Guan Wang
Bioengineering 2023, 10(6), 744; https://doi.org/10.3390/bioengineering10060744 - 20 Jun 2023
Cited by 2 | Viewed by 2666
Abstract
The Valley of Death confronts industrial biotechnology with a significant challenge to the commercialization of products. Fortunately, with the integration of computation, automation and artificial intelligence (AI) technology, the industrial biotechnology accelerates to cross the Valley of Death. The Fourth Industrial Revolution (Industry [...] Read more.
The Valley of Death confronts industrial biotechnology with a significant challenge to the commercialization of products. Fortunately, with the integration of computation, automation and artificial intelligence (AI) technology, the industrial biotechnology accelerates to cross the Valley of Death. The Fourth Industrial Revolution (Industry 4.0) has spurred advanced development of intelligent biomanufacturing, which has evolved the industrial structures in line with the worldwide trend. To achieve this, intelligent biomanufacturing can be structured into three main parts that comprise digitalization, modeling and intellectualization, with modeling forming a crucial link between the other two components. This paper provides an overview of mechanistic models, data-driven models and their applications in bioprocess development. We provide a detailed elaboration of the hybrid model and its applications in bioprocess engineering, including strain design, process control and optimization, as well as bioreactor scale-up. Finally, the challenges and opportunities of biomanufacturing towards Industry 4.0 are also discussed. Full article
(This article belongs to the Special Issue Design, Optimization and Scale-Up of Industrial Bioprocess)
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16 pages, 5679 KiB  
Article
Investigation of Stent Prototypes for the Eustachian Tube in Human Donor Bodies
by Lena Rosenbusch, Robert Schuon, Tamara Wilfling, Philipp Krüger, Kerstin Lebahn, Samuel John, Olga Sahmel, Niels Grabow, Marko Schulze, Andreas Wree, Klaus-Peter Schmitz, Tobias Stein, Thomas Lenarz and Gerrit Paasche
Bioengineering 2023, 10(6), 743; https://doi.org/10.3390/bioengineering10060743 - 20 Jun 2023
Cited by 3 | Viewed by 1517
Abstract
Chronic otitis media is often connected to Eustachian tube dysfunction. As successful treatment cannot be guaranteed with the currently available options, the aim is to develop a stent for the Eustachian tube (ET). Over the course of this development, different prototypes were generated [...] Read more.
Chronic otitis media is often connected to Eustachian tube dysfunction. As successful treatment cannot be guaranteed with the currently available options, the aim is to develop a stent for the Eustachian tube (ET). Over the course of this development, different prototypes were generated and tested in ex vivo experiments. Four different prototypes of an ET stent and one commercially available coronary stent were implanted in the ET of seven human donor bodies. The position of the stents was verified by cone beam CT. The implanted ETs were harvested, embedded in resin and ground at 200 µm steps. Resulting images of the single steps were used to generate 3D models. The 3D models were then evaluated regarding position of the stent in the ET, its diameters, amount of squeezing, orientation of the axes and other parameters. Virtual reconstruction of the implanted ET was successful in all cases and revealed one incorrect stent placement. The cross-section increased for all metal stents in direction from the isthmus towards the pharyngeal orifice of the ET. Depending on the individual design of the metal stents (open or closed design), the shape varied also between different positions along a single stent. In contrast, the cross-section area and shape remained constant along the polymeric prototype. With the current investigation, insight into the behavior of different prototypes of ET stents was gained, which can help in defining the specifications for the intended ET stent. Full article
(This article belongs to the Special Issue Feature Papers in Biomedical Engineering and Biomaterials)
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13 pages, 616 KiB  
Review
Deconstructing Fat to Reverse Radiation Induced Soft Tissue Fibrosis
by Hannes Prescher, Jill R. Froimson and Summer E. Hanson
Bioengineering 2023, 10(6), 742; https://doi.org/10.3390/bioengineering10060742 - 20 Jun 2023
Cited by 2 | Viewed by 2150
Abstract
Adipose tissue is composed of a collection of cells with valuable structural and regenerative function. Taken as an autologous graft, these cells can be used to address soft tissue defects and irregularities, while also providing a reparative effect on the surrounding tissues. Adipose-derived [...] Read more.
Adipose tissue is composed of a collection of cells with valuable structural and regenerative function. Taken as an autologous graft, these cells can be used to address soft tissue defects and irregularities, while also providing a reparative effect on the surrounding tissues. Adipose-derived stem or stromal cells are primarily responsible for this regenerative effect through direct differentiation into native cells and via secretion of numerous growth factors and cytokines that stimulate angiogenesis and disrupt pro-inflammatory pathways. Separating adipose tissue into its component parts, i.e., cells, scaffolds and proteins, has provided new regenerative therapies for skin and soft tissue pathology, including that resulting from radiation. Recent studies in both animal models and clinical trials have demonstrated the ability of autologous fat grafting to reverse radiation induced skin fibrosis. An improved understanding of the complex pathologic mechanism of RIF has allowed researchers to harness the specific function of the ASCs to engineer enriched fat graft constructs to improve the therapeutic effect of AFG. Full article
(This article belongs to the Special Issue Bioengineered Strategies for Surgical Innovation)
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17 pages, 1322 KiB  
Review
Suppressing Chondrocyte Hypertrophy to Build Better Cartilage
by Christian Shigley, Jay Trivedi, Ozair Meghani, Brett D. Owens and Chathuraka T. Jayasuriya
Bioengineering 2023, 10(6), 741; https://doi.org/10.3390/bioengineering10060741 - 20 Jun 2023
Cited by 4 | Viewed by 2340
Abstract
Current clinical strategies for restoring cartilage defects do not adequately consider taking the necessary steps to prevent the formation of hypertrophic tissue at injury sites. Chondrocyte hypertrophy inevitably causes both macroscopic and microscopic level changes in cartilage, resulting in adverse long-term outcomes following [...] Read more.
Current clinical strategies for restoring cartilage defects do not adequately consider taking the necessary steps to prevent the formation of hypertrophic tissue at injury sites. Chondrocyte hypertrophy inevitably causes both macroscopic and microscopic level changes in cartilage, resulting in adverse long-term outcomes following attempted restoration. Repairing/restoring articular cartilage while minimizing the risk of hypertrophic neo tissue formation represents an unmet clinical challenge. Previous investigations have extensively identified and characterized the biological mechanisms that regulate cartilage hypertrophy with preclinical studies now beginning to leverage this knowledge to help build better cartilage. In this comprehensive article, we will provide a summary of these biological mechanisms and systematically review the most cutting-edge strategies for circumventing this pathological hallmark of osteoarthritis. Full article
(This article belongs to the Special Issue Precision Medicine and Emerging Technologies for Osteoarthritis)
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12 pages, 1693 KiB  
Article
Quantification of Analgesic and Anti-Inflammatory Lipid Mediators in Long-Term Cryopreserved and Freeze-Dried Preserved Human Amniotic Membrane
by Vladimir Vrkoslav, Ingrida Smeringaiova, Natalia Smorodinova, Alzbeta Svobodova, Stepan Strnad, Catherine Joan Jackson, Jan Burkert and Katerina Jirsova
Bioengineering 2023, 10(6), 740; https://doi.org/10.3390/bioengineering10060740 - 20 Jun 2023
Cited by 3 | Viewed by 1527
Abstract
The aim of this study was to compare concentrations of endogenous N-acylethanolamine (NAE) lipid mediators—palmitoylethanolamide (PEA), oleoylethanolamide (OEA), and anandamide (AEA)—in fresh, decontaminated, cryopreserved, and freeze-dried amniotic membrane (AM) allografts, thereby determining whether AM’s analgesic and anti-inflammatory efficiency related to NAEs persists during [...] Read more.
The aim of this study was to compare concentrations of endogenous N-acylethanolamine (NAE) lipid mediators—palmitoylethanolamide (PEA), oleoylethanolamide (OEA), and anandamide (AEA)—in fresh, decontaminated, cryopreserved, and freeze-dried amniotic membrane (AM) allografts, thereby determining whether AM’s analgesic and anti-inflammatory efficiency related to NAEs persists during storage. The concentrations of NAEs were measured using ultra-high-performance liquid chromatography–tandem mass spectrometry. Indirect fluorescent immunohistochemistry was used to detect the PEA PPAR-α receptor. The concentrations of PEA, OEA, and AEA were significantly higher after decontamination. A significant decrease was found in cryopreserved AM compared to decontaminated tissue for PEA but not for OEA and AEA. However, significantly higher values for all NAEs were detected in cryopreserved samples compared to fresh tissue before decontamination. The freeze-dried AM had similar values to decontaminated AM with no statistically significant difference. The nuclear staining of the PPAR-α receptor was clearly visible in all specimens. The stability of NAEs in AM after cryopreservation was demonstrated under tissue bank storage conditions. However, a significant decrease, but still higher concentration of PEA compared to fresh not decontaminated tissue, was found in cryopreserved, but not freeze-dried, AM. Results indicate that NAEs persist during storage in levels sufficient for the analgesic and anti-inflammatory effects. This means that cryopreserved AM allografts released for transplant purposes before the expected expiration (usually 3–5 years) will still show a strong analgesic effect. The same situation was confirmed for AM lyophilized after one year of storage. This work thus contributed to the clarification of the analgesic effect of NAEs in AM allografts. Full article
(This article belongs to the Section Nanobiotechnology and Biofabrication)
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11 pages, 2361 KiB  
Communication
Rationally Improving Doramectin Production in Industrial Streptomyces avermitilis Strains
by Fujun Dang, Qingyu Xu, Zhongjun Qin and Haiyang Xia
Bioengineering 2023, 10(6), 739; https://doi.org/10.3390/bioengineering10060739 - 20 Jun 2023
Cited by 2 | Viewed by 1841
Abstract
Avermectins (AVMs), a family of 16-membered macrocyclic macrolides produced by Streptomyces avermitilis, have been the most successful microbial natural antiparasitic agents in recent decades. Doramectin, an AVM derivative produced by S. avermitilis bkd− mutants through cyclohexanecarboxylic acid (CHC) feeding, was commercialized [...] Read more.
Avermectins (AVMs), a family of 16-membered macrocyclic macrolides produced by Streptomyces avermitilis, have been the most successful microbial natural antiparasitic agents in recent decades. Doramectin, an AVM derivative produced by S. avermitilis bkd− mutants through cyclohexanecarboxylic acid (CHC) feeding, was commercialized as a veterinary antiparasitic drug by Pfizer Inc. Our previous results show that the production of avermectin and actinorhodin was affected by several other polyketide biosynthetic gene clusters in S. avermitilis and Streptomyces coelicolor, respectively. Thus, here, we propose a rational strategy to improve doramectin production via the termination of competing polyketide biosynthetic pathways combined with the overexpression of CoA ligase, providing precursors for polyketide biosynthesis. fadD17, an annotated putative cyclohex-1-ene-1-carboxylate:CoA ligase-encoding gene, was proven to be involved in the biosynthesis of doramectin. By sequentially removing three PKS (polyketide synthase) gene clusters and overexpressing FadD17 in the strain DM203, the resulting strain DM223 produced approximately 723 mg/L of doramectin in flasks, which was approximately 260% that of the original strain DM203 (approximately 280 mg/L). To summarize, our work demonstrates a novel viable approach to engineer doramectin overproducers, which might contribute to the reduction in the cost of this valuable compound in the future. Full article
(This article belongs to the Section Biochemical Engineering)
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36 pages, 13076 KiB  
Article
EnsemDeepCADx: Empowering Colorectal Cancer Diagnosis with Mixed-Dataset Features and Ensemble Fusion CNNs on Evidence-Based CKHK-22 Dataset
by Akella Subrahmanya Narasimha Raju and Kaliyamurthy Venkatesh
Bioengineering 2023, 10(6), 738; https://doi.org/10.3390/bioengineering10060738 - 19 Jun 2023
Cited by 1 | Viewed by 1778
Abstract
Colorectal cancer is associated with a high mortality rate and significant patient risk. Images obtained during a colonoscopy are used to make a diagnosis, highlighting the importance of timely diagnosis and treatment. Using techniques of deep learning could enhance the diagnostic accuracy of [...] Read more.
Colorectal cancer is associated with a high mortality rate and significant patient risk. Images obtained during a colonoscopy are used to make a diagnosis, highlighting the importance of timely diagnosis and treatment. Using techniques of deep learning could enhance the diagnostic accuracy of existing systems. Using the most advanced deep learning techniques, a brand-new EnsemDeepCADx system for accurate colorectal cancer diagnosis has been developed. The optimal accuracy is achieved by combining Convolutional Neural Networks (CNNs) with transfer learning via bidirectional long short-term memory (BILSTM) and support vector machines (SVM). Four pre-trained CNN models comprise the ADaDR-22, ADaR-22, and DaRD-22 ensemble CNNs: AlexNet, DarkNet-19, DenseNet-201, and ResNet-50. In each of its stages, the CADx system is thoroughly evaluated. From the CKHK-22 mixed dataset, colour, greyscale, and local binary pattern (LBP) image datasets and features are utilised. In the second stage, the returned features are compared to a new feature fusion dataset using three distinct CNN ensembles. Next, they incorporate ensemble CNNs with SVM-based transfer learning by comparing raw features to feature fusion datasets. In the final stage of transfer learning, BILSTM and SVM are combined with a CNN ensemble. The testing accuracy for the ensemble fusion CNN DarD-22 using BILSTM and SVM on the original, grey, LBP, and feature fusion datasets was optimal (95.96%, 88.79%, 73.54%, and 97.89%). Comparing the outputs of all four feature datasets with those of the three ensemble CNNs at each stage enables the EnsemDeepCADx system to attain its highest level of accuracy. Full article
(This article belongs to the Special Issue Machine Learning and Artificial Intelligence for Biomedical Applications)
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22 pages, 10751 KiB  
Article
Novel Baseline Facial Muscle Database Using Statistical Shape Modeling and In Silico Trials toward Decision Support for Facial Rehabilitation
by Vi-Do Tran, Tan-Nhu Nguyen, Abbass Ballit and Tien-Tuan Dao
Bioengineering 2023, 10(6), 737; https://doi.org/10.3390/bioengineering10060737 - 19 Jun 2023
Cited by 1 | Viewed by 2246
Abstract
Backgrounds and Objective: Facial palsy is a complex pathophysiological condition affecting the personal and professional lives of the involved patients. Sudden muscle weakness or paralysis needs to be rehabilitated to recover a symmetric and expressive face. Computer-aided decision support systems for facial [...] Read more.
Backgrounds and Objective: Facial palsy is a complex pathophysiological condition affecting the personal and professional lives of the involved patients. Sudden muscle weakness or paralysis needs to be rehabilitated to recover a symmetric and expressive face. Computer-aided decision support systems for facial rehabilitation have been developed. However, there is a lack of facial muscle baseline data to evaluate the patient states and guide as well as optimize the rehabilitation strategy. In this present study, we aimed to develop a novel baseline facial muscle database (static and dynamic behaviors) using the coupling between statistical shape modeling and in-silico trial approaches. Methods: 10,000 virtual subjects (5000 males and 5000 females) were generated from a statistical shape modeling (SSM) head model. Skull and muscle networks were defined so that they statistically fit with the head shapes. Two standard mimics: smiling and kissing were generated. The muscle strains of the lengths in neutral and mimic positions were computed and recorded thanks to the muscle insertion and attachment points on the animated head and skull meshes. For validation, five head and skull meshes were reconstructed from the five computed tomography (CT) image sets. Skull and muscle networks were then predicted from the reconstructed head meshes. The predicted skull meshes were compared with the reconstructed skull meshes based on the mesh-to-mesh distance metrics. The predicted muscle lengths were also compared with those manually defined on the reconstructed head and skull meshes. Moreover, the computed muscle lengths and strains were compared with those in our previous studies and the literature. Results: The skull prediction’s median deviations from the CT-based models were 2.2236 mm, 2.1371 mm, and 2.1277 mm for the skull shape, skull mesh, and muscle attachment point regions, respectively. The median deviation of the muscle lengths was 4.8940 mm. The computed muscle strains were compatible with the reported values in our previous Kinect-based method and the literature. Conclusions: The development of our novel facial muscle database opens new avenues to accurately evaluate the facial muscle states of facial palsy patients. Based on the evaluated results, specific types of facial mimic rehabilitation exercises can also be selected optimally to train the target muscles. In perspective, the database of the computed muscle lengths and strains will be integrated into our available clinical decision support system for automatically detecting malfunctioning muscles and proposing patient-specific rehabilitation serious games. Full article
(This article belongs to the Special Issue Multiscale Modeling in Computational Biomechanics)
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16 pages, 5002 KiB  
Article
An Integrated Method of Biomechanics Modeling for Pelvic Bone and Surrounding Soft Tissues
by Wei Kou, Yefeng Liang, Zhixing Wang, Qingxi Liang, Lining Sun and Shaolong Kuang
Bioengineering 2023, 10(6), 736; https://doi.org/10.3390/bioengineering10060736 - 19 Jun 2023
Cited by 1 | Viewed by 1911
Abstract
The pelvis and its surrounding soft tissues create a complicated mechanical environment that greatly affects the success of fixing broken pelvic bones with surgical navigation systems and/or surgical robots. However, the modeling of the pelvic structure with the more complex surrounding soft tissues [...] Read more.
The pelvis and its surrounding soft tissues create a complicated mechanical environment that greatly affects the success of fixing broken pelvic bones with surgical navigation systems and/or surgical robots. However, the modeling of the pelvic structure with the more complex surrounding soft tissues has not been considered in the current literature. The study developed an integrated finite element model of the pelvis, which includes bone and surrounding soft tissues, and verified it through experiments. Results from the experiments showed that including soft tissue in the model reduced stress and strain on the pelvis compared to when it was not included. The stress and strain distribution during pelvic loading was similar to what is typically seen in research studies and more accurate in modeling the pelvis. Additionally, the correlation with the experimental results from the predecessor’s study was strong (R2 = 0.9627). The results suggest that the integrated model established in this study, which includes surrounding soft tissues, can enhance the comprehension of the complex biomechanics of the pelvis and potentially advance clinical interventions and treatments for pelvic injuries. Full article
(This article belongs to the Section Biomechanics and Sports Medicine)
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12 pages, 1625 KiB  
Article
The Application of Design Thinking in Developing a Deep Learning Algorithm for Hip Fracture Detection
by Chun-Hsiang Ouyang, Chih-Chi Chen, Yu-San Tee, Wei-Cheng Lin, Ling-Wei Kuo, Chien-An Liao, Chi-Tung Cheng and Chien-Hung Liao
Bioengineering 2023, 10(6), 735; https://doi.org/10.3390/bioengineering10060735 - 19 Jun 2023
Cited by 5 | Viewed by 2012
Abstract
(1) Background: Design thinking is a problem-solving approach that has been applied in various sectors, including healthcare and medical education. While deep learning (DL) algorithms can assist in clinical practice, integrating them into clinical scenarios can be challenging. This study aimed to use [...] Read more.
(1) Background: Design thinking is a problem-solving approach that has been applied in various sectors, including healthcare and medical education. While deep learning (DL) algorithms can assist in clinical practice, integrating them into clinical scenarios can be challenging. This study aimed to use design thinking steps to develop a DL algorithm that accelerates deployment in clinical practice and improves its performance to meet clinical requirements. (2) Methods: We applied the design thinking process to interview clinical doctors and gain insights to develop and modify the DL algorithm to meet clinical scenarios. We also compared the DL performance of the algorithm before and after the integration of design thinking. (3) Results: After empathizing with clinical doctors and defining their needs, we identified the unmet need of five trauma surgeons as “how to reduce the misdiagnosis of femoral fracture by pelvic plain film (PXR) at initial emergency visiting”. We collected 4235 PXRs from our hospital, of which 2146 had a hip fracture (51%) from 2008 to 2016. We developed hip fracture DL detection models based on the Xception convolutional neural network by using these images. By incorporating design thinking, we improved the diagnostic accuracy from 0.91 (0.84–0.96) to 0.95 (0.93–0.97), the sensitivity from 0.97 (0.89–1.00) to 0.97 (0.94–0.99), and the specificity from 0.84 (0.71–0.93) to 0.93(0.990–0.97). (4) Conclusions: In summary, this study demonstrates that design thinking can ensure that DL solutions developed for trauma care are user-centered and meet the needs of patients and healthcare providers. Full article
(This article belongs to the Special Issue Deep Learning and Medical Innovation in Minimally Invasive Surgery)
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21 pages, 7460 KiB  
Article
Biocompatible MgFeCO3 Layered Double Hydroxide (LDH) for Bone Regeneration—Low-Temperature Processing through Cold Sintering and Freeze-Casting
by Hyoung-Jun Kim, Prescillia Lagarrigue, Jae-Min Oh, Jérémy Soulié, Fabrice Salles, Sophie Cazalbou and Christophe Drouet
Bioengineering 2023, 10(6), 734; https://doi.org/10.3390/bioengineering10060734 - 19 Jun 2023
Cited by 3 | Viewed by 1989
Abstract
Layered Double Hydroxides (LDHs) are inorganic compounds of relevance to various domains, where their surface reactivity and/or intercalation capacities can be advantageously exploited for the retention/release of ionic and molecular species. In this study, we have explored specifically the applicability in the field [...] Read more.
Layered Double Hydroxides (LDHs) are inorganic compounds of relevance to various domains, where their surface reactivity and/or intercalation capacities can be advantageously exploited for the retention/release of ionic and molecular species. In this study, we have explored specifically the applicability in the field of bone regeneration of one LDH composition, denoted “MgFeCO3”, of which components are already present in vivo, so as to convey a biocompatibility character. The propensity to be used as a bone substitute depends, however, on their ability to allow the fabrication of 3D constructs able to be implanted in bone sites. In this work, we display two appealing approaches for the processing of MgFeCO3 LDH particles to prepare (i) porous 3D scaffolds by freeze-casting, involving an alginate biopolymeric matrix, and (ii) pure MgFeCO3 LDH monoliths by Spark Plasma Sintering (SPS) at low temperature. We then explored the capacity of such LDH particles or monoliths to interact quantitatively with molecular moieties/drugs in view of their local release. The experimental data were complemented by computational chemistry calculations (Monte Carlo) to examine in more detail the mineral–organic interactions at play. Finally, preliminary in vitro tests on osteoblastic MG63 cells confirmed the high biocompatible character of this LDH composition. It was confirmed that (i) thermodynamically metastable LDH could be successfully consolidated into a monolith through SPS, (ii) the LDH particles could be incorporated into a polymer matrix through freeze casting, and (iii) the LDH in the consolidated monolith could incorporate and release drug molecules in a controlled manner. In other words, our results indicate that the MgFeCO3 LDH (pyroaurite structure) may be seen as a new promising compound for the setup of bone substitute biomaterials with tailorable drug delivery capacity, including for personalized medicine. Full article
(This article belongs to the Special Issue Biomaterials for Bone Repair and Regeneration)
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27 pages, 13791 KiB  
Review
Recent Advances in Metal–Organic Frameworks (MOFs) and Their Composites for Non-Enzymatic Electrochemical Glucose Sensors
by Panpan Li, Yi Peng, Jinpeng Cai, Yang Bai, Qing Li and Huan Pang
Bioengineering 2023, 10(6), 733; https://doi.org/10.3390/bioengineering10060733 - 19 Jun 2023
Cited by 6 | Viewed by 2452
Abstract
In recent years, with pressing needs such as diabetes management, the detection of glucose in various substrates has attracted unprecedented interest from researchers in academia and industry. As a relatively new glucose sensor, non-enzymatic target detection has the characteristics of high sensitivity, good [...] Read more.
In recent years, with pressing needs such as diabetes management, the detection of glucose in various substrates has attracted unprecedented interest from researchers in academia and industry. As a relatively new glucose sensor, non-enzymatic target detection has the characteristics of high sensitivity, good stability and simple manufacturing process. However, it is urgent to explore novel materials with low cost, high stability and excellent performance to modify electrodes. Metal–organic frameworks (MOFs) and their composites have the advantages of large surface area, high porosity and high catalytic efficiency, which can be utilized as excellent materials for electrode modification of non-enzymatic electrochemical glucose sensors. However, MOFs and their composites still face various challenges and difficulties that limit their further commercialization. This review introduces the applications and the challenges of MOFs and their composites in non-enzymatic electrochemical glucose sensors. Finally, an outlook on the development of MOFs and their composites is also presented. Full article
(This article belongs to the Section Nanobiotechnology and Biofabrication)
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15 pages, 2517 KiB  
Article
An Actinic Keratosis Auxiliary Diagnosis Method Based on an Enhanced MobileNet Model
by Shiyang Li, Chengquan Li, Qicai Liu, Yilin Pei, Liyang Wang and Zhu Shen
Bioengineering 2023, 10(6), 732; https://doi.org/10.3390/bioengineering10060732 - 19 Jun 2023
Cited by 3 | Viewed by 2242
Abstract
Actinic keratosis (AK) is a common precancerous skin lesion with significant harm, and it is often confused with non-actinic keratoses (NAK). At present, the diagnosis of AK mainly depends on clinical experience and histopathology. Due to the high difficulty of diagnosis and easy [...] Read more.
Actinic keratosis (AK) is a common precancerous skin lesion with significant harm, and it is often confused with non-actinic keratoses (NAK). At present, the diagnosis of AK mainly depends on clinical experience and histopathology. Due to the high difficulty of diagnosis and easy confusion with other diseases, this article aims to develop a convolutional neural network that can efficiently, accurately, and automatically diagnose AK. This article improves the MobileNet model and uses the AK and NAK images in the HAM10000 dataset for training and testing after data preprocessing, and we performed external independent testing using a separate dataset to validate our preprocessing approach and to demonstrate the performance and generalization capability of our model. It further compares common deep learning models in the field of skin diseases (including the original MobileNet, ResNet, GoogleNet, EfficientNet, and Xception). The results show that the improved MobileNet has achieved 0.9265 in accuracy and 0.97 in Area Under the ROC Curve (AUC), which is the best among the comparison models. At the same time, it has the shortest training time, and the total time of five-fold cross-validation on local devices only takes 821.7 s. Local experiments show that the method proposed in this article has high accuracy and stability in diagnosing AK. Our method will help doctors diagnose AK more efficiently and accurately, allowing patients to receive timely diagnosis and treatment. Full article
(This article belongs to the Special Issue Recent Advance of Machine Learning in Biomedical Image Analysis)
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13 pages, 2685 KiB  
Review
Bioactive Restorative Materials Applied over Coronal Dentine—A Bibliometric and Critical Review
by Paula Maciel Pires, Thamirys da Costa Rosa, Mariana Batista Ribeiro-Lages, Maysa Lannes Duarte, Lucianne Cople Maia, Aline de Almeida Neves and Salvatore Sauro
Bioengineering 2023, 10(6), 731; https://doi.org/10.3390/bioengineering10060731 - 19 Jun 2023
Cited by 4 | Viewed by 2367
Abstract
The objective of the research was to examine the scientific literature concerning restorative materials with bioactive properties for the purpose of covering dentin. Searches were performed in various databases including MEDLINE, Scopus, Web of Science, Cochrane Library, Lilacs/BBO, and Embase. Inclusion criteria involved [...] Read more.
The objective of the research was to examine the scientific literature concerning restorative materials with bioactive properties for the purpose of covering dentin. Searches were performed in various databases including MEDLINE, Scopus, Web of Science, Cochrane Library, Lilacs/BBO, and Embase. Inclusion criteria involved studies that utilized the terms “dentin” and “bioactive”, along with “ion-releasing”, “smart materials”, “biomimetic materials” and “smart replacement for dentin”. The information extracted included the title, authors, publication year, journal and the country of affiliation of the corresponding author. The studies were categorized based on their study design, type of material, substrate, analytical method, and bioactivity. A total of 7161 records were recovered and 159 were included for data extraction. Most of the publications were in vitro studies (n = 149), testing different types of materials in sound dentine (n = 115). Most studies were published in Dental Materials (n = 29), and an increase in publications could be observed after the year 2000. Most of the articles were from the USA (n = 34), followed by Brazil (n = 28). Interfacial analysis was the most investigated (n = 105), followed by bond strength (n = 86). Bioactivity potential was demonstrated for most tested materials (n = 148). This review presents insights into the current trends of bioactive materials development, clearly showing a severe lack of clinical studies. Full article
(This article belongs to the Special Issue Recent Advances in Dental Diseases: Diagnosis, Treatment and Prognosis)
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17 pages, 2837 KiB  
Article
Multimodal Deep Learning for Predicting Adverse Birth Outcomes Based on Early Labour Data
by Daniel Asfaw, Ivan Jordanov, Lawrence Impey, Ana Namburete, Raymond Lee and Antoniya Georgieva
Bioengineering 2023, 10(6), 730; https://doi.org/10.3390/bioengineering10060730 - 19 Jun 2023
Cited by 5 | Viewed by 2353
Abstract
Cardiotocography (CTG) is a widely used technique to monitor fetal heart rate (FHR) during labour and assess the health of the baby. However, visual interpretation of CTG signals is subjective and prone to error. Automated methods that mimic clinical guidelines have been developed, [...] Read more.
Cardiotocography (CTG) is a widely used technique to monitor fetal heart rate (FHR) during labour and assess the health of the baby. However, visual interpretation of CTG signals is subjective and prone to error. Automated methods that mimic clinical guidelines have been developed, but they failed to improve detection of abnormal traces. This study aims to classify CTGs with and without severe compromise at birth using routinely collected CTGs from 51,449 births at term from the first 20 min of FHR recordings. Three 1D-CNN and LSTM based architectures are compared. We also transform the FHR signal into 2D images using time-frequency representation with a spectrogram and scalogram analysis, and subsequently, the 2D images are analysed using a 2D-CNNs. In the proposed multi-modal architecture, the 2D-CNN and the 1D-CNN-LSTM are connected in parallel. The models are evaluated in terms of partial area under the curve (PAUC) between 0–10% false-positive rate; and sensitivity at 95% specificity. The 1D-CNN-LSTM parallel architecture outperformed the other models, achieving a PAUC of 0.20 and sensitivity of 20% at 95% specificity. Our future work will focus on improving the classification performance by employing a larger dataset, analysing longer FHR traces, and incorporating clinical risk factors. Full article
(This article belongs to the Special Issue Fetal-Maternal Monitoring during Pregnancy and Labor: Trends and Opportunities)
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10 pages, 1135 KiB  
Article
Infrared Thermography Imaging for Assessment of Peripheral Perfusion in Patients with Septic Shock
by Sigita Kazune, Edgars Vasiljevs, Anastasija Caica-Rinca, Zbignevs Marcinkevics and Andris Grabovskis
Bioengineering 2023, 10(6), 729; https://doi.org/10.3390/bioengineering10060729 - 18 Jun 2023
Cited by 3 | Viewed by 1663
Abstract
Skin temperature changes can be used to assess peripheral perfusion in circulatory shock patients. However, research has been limited to point measurements from acral parts of the body. Infrared thermography allows non-invasive evaluation of temperature distribution over a larger surface. Our study aimed [...] Read more.
Skin temperature changes can be used to assess peripheral perfusion in circulatory shock patients. However, research has been limited to point measurements from acral parts of the body. Infrared thermography allows non-invasive evaluation of temperature distribution over a larger surface. Our study aimed to map thermographic patterns in the knee and upper thigh of 81 septic shock patients within 24 h of admission and determine the relationship between skin temperature patterns, mottling, and 28-day mortality. We extracted skin temperature measurements from zones corresponding to mottling scores and used a linear mixed model to analyze the distribution of skin temperature in patients with different mottling scores. Our results showed that the distribution of skin temperature in the anterior thigh and knee is physiologically heterogeneous and has no significant association with mottling or survival at 28 days. However, overall skin temperature of the anterior thigh and knee is significantly lower in non-survivors when modified by mottling score. No differences were found in skin temperature between the survivor and non-survivor groups. Our study shows the potential usefulness of infrared thermography in evaluating skin temperature patterns in resuscitated septic shock patients. Overall skin temperature of the anterior thigh and knee may be an important indicator of survival status when modified by mottling score. Full article
(This article belongs to the Special Issue Contactless Technologies for Human Vital Signs Monitoring)
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13 pages, 1457 KiB  
Review
Mesenchymal Stromal Cell Therapy in Lung Transplantation
by Antti I. Nykänen, Mingyao Liu and Shaf Keshavjee
Bioengineering 2023, 10(6), 728; https://doi.org/10.3390/bioengineering10060728 - 17 Jun 2023
Cited by 5 | Viewed by 3155
Abstract
Lung transplantation is often the only viable treatment option for a patient with end-stage lung disease. Lung transplant results have improved substantially over time, but ischemia-reperfusion injury, primary graft dysfunction, acute rejection, and chronic lung allograft dysfunction (CLAD) continue to be significant problems. [...] Read more.
Lung transplantation is often the only viable treatment option for a patient with end-stage lung disease. Lung transplant results have improved substantially over time, but ischemia-reperfusion injury, primary graft dysfunction, acute rejection, and chronic lung allograft dysfunction (CLAD) continue to be significant problems. Mesenchymal stromal cells (MSC) are pluripotent cells that have anti-inflammatory and protective paracrine effects and may be beneficial in solid organ transplantation. Here, we review the experimental studies where MSCs have been used to protect the donor lung against ischemia-reperfusion injury and alloimmune responses, as well as the experimental and clinical studies using MSCs to prevent or treat CLAD. In addition, we outline ex vivo lung perfusion (EVLP) as an optimal platform for donor lung MSC delivery, as well as how the therapeutic potential of MSCs could be further leveraged with genetic engineering. Full article
(This article belongs to the Special Issue Mesenchymal Stem Cells in Regenerative Medicine)
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13 pages, 1636 KiB  
Perspective
Engineering Ferroptosis Inhibitors as Inhalable Nanomedicines for the Highly Efficient Treatment of Idiopathic Pulmonary Fibrosis
by Mengqin Guo, Tingting Peng, Chuanbin Wu, Xin Pan and Zhengwei Huang
Bioengineering 2023, 10(6), 727; https://doi.org/10.3390/bioengineering10060727 - 17 Jun 2023
Cited by 7 | Viewed by 1998
Abstract
Idiopathic pulmonary fibrosis (IPF) refers to chronic progressive fibrotic interstitial pneumonia. It is called a “tumor-like disease” and cannot be cured using existing clinical drugs. Therefore, new treatment options are urgently needed. Studies have proven that ferroptosis is closely related to the development [...] Read more.
Idiopathic pulmonary fibrosis (IPF) refers to chronic progressive fibrotic interstitial pneumonia. It is called a “tumor-like disease” and cannot be cured using existing clinical drugs. Therefore, new treatment options are urgently needed. Studies have proven that ferroptosis is closely related to the development of IPF, and ferroptosis inhibitors can slow down the occurrence of IPF by chelating iron or reducing lipid peroxidation. For example, the ferroptosis inhibitor deferoxamine (DFO) was used to treat a mouse model of pulmonary fibrosis, and DFO successfully reversed the IPF phenotype and increased the survival rate of mice from 50% to 90%. Given this, we perceive that the treatment of IPF by delivering ferroptosis inhibitors is a promising option. However, the delivery of ferroptosis inhibitors faces two bottlenecks: low solubility and targeting. For one thing, we consider preparing ferroptosis inhibitors into nanomedicines to improve solubility. For another thing, we propose to deliver nanomedicines through pulmonary drug-delivery system (PDDS) to improve targeting. Compared with oral or injection administration, PDDS can achieve better delivery and accumulation in the lung, while reducing the systemic exposure of the drug, and is an efficient and safe drug-delivery method. In this paper, three possible nanomedicines for PDDS and the preparation methods thereof are proposed to deliver ferroptosis inhibitors for the treatment of IPF. Proper administration devices and challenges in future applications are also discussed. In general, this perspective proposes a promising strategy for the treatment of IPF based on inhalable nanomedicines carrying ferroptosis inhibitors, which can inspire new ideas in the field of drug development and therapy of IPF. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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18 pages, 4944 KiB  
Article
Near-Infrared Blood Vessel Image Segmentation Using Background Subtraction and Improved Mathematical Morphology
by Ling Li, Haoting Liu, Qing Li, Zhen Tian, Yajie Li, Wenjia Geng and Song Wang
Bioengineering 2023, 10(6), 726; https://doi.org/10.3390/bioengineering10060726 - 15 Jun 2023
Cited by 3 | Viewed by 2017
Abstract
The precise display of blood vessel information for doctors is crucial. This is not only true for facilitating intravenous injections, but also for the diagnosis and analysis of diseases. Currently, infrared cameras can be used to capture images of superficial blood vessels. However, [...] Read more.
The precise display of blood vessel information for doctors is crucial. This is not only true for facilitating intravenous injections, but also for the diagnosis and analysis of diseases. Currently, infrared cameras can be used to capture images of superficial blood vessels. However, their imaging quality always has the problems of noises, breaks, and uneven vascular information. In order to overcome these problems, this paper proposes an image segmentation algorithm based on the background subtraction and improved mathematical morphology. The algorithm regards the image as a superposition of blood vessels into the background, removes the noise by calculating the size of connected domains, achieves uniform blood vessel width, and smooths edges that reflect the actual blood vessel state. The algorithm is evaluated subjectively and objectively in this paper to provide a basis for vascular image quality assessment. Extensive experimental results demonstrate that the proposed method can effectively extract accurate and clear vascular information. Full article
(This article belongs to the Special Issue Recent Advances in Biomedical Imaging)
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15 pages, 2100 KiB  
Article
Using Micro-Electrode-Array Recordings and Retinal Disease Models to Elucidate Visual Functions: Simultaneous Recording of Local Electroretinograms and Ganglion Cell Action Potentials Reveals the Origin of Retinal Oscillatory Potentials
by Wadood Haq, Eberhart Zrenner, Marius Ueffing and François Paquet-Durand
Bioengineering 2023, 10(6), 725; https://doi.org/10.3390/bioengineering10060725 - 15 Jun 2023
Cited by 5 | Viewed by 2704
Abstract
Background: The electroretinogram (ERG) is an essential diagnostic tool for visual function, both in clinical and research settings. Here, we establish an advanced in vitro approach to assess cell-type-specific ERG signal components. Methods: Retinal explant cultures, maintained under entirely controlled conditions, were derived [...] Read more.
Background: The electroretinogram (ERG) is an essential diagnostic tool for visual function, both in clinical and research settings. Here, we establish an advanced in vitro approach to assess cell-type-specific ERG signal components. Methods: Retinal explant cultures, maintained under entirely controlled conditions, were derived from wild-type mice and rd10 rod- and cpfl1 cone-degeneration mouse models. Local micro-ERG (µERG) and simultaneous ganglion cell (GC) recordings were obtained from the retinal explants using multi-electrode arrays. Band-pass filtering was employed to distinguish photoreceptor, bipolar cell, amacrine cell (AC), and GC responses. Results: Scotopic and photopic stimulation discriminated between rod and cone responses in wild-type and mutant retina. The 25 kHz sampling rate allowed the visualization of oscillatory potentials (OPs) in extraordinary detail, revealing temporal correlations between OPs and GC responses. Pharmacological isolation of different retinal circuits found that OPs are generated by inner retinal AC electrical synapses. Importantly, this AC activity helped synchronise GC activity. Conclusion: Our µERG protocol simultaneously records the light-dependent activities of the first-, second-, and third-order neurons within the native neuronal circuitry, providing unprecedented insights into retinal physiology and pathophysiology. This method now also enables complete in vitro retinal function testing of therapeutic interventions, providing critical guidance for later in vivo investigations. Full article
(This article belongs to the Special Issue Pathophysiology and Translational Research of Retinal Diseases)
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17 pages, 576 KiB  
Article
Automatic Levothyroxine Dosing Algorithm for Patients Suffering from Hashimoto’s Thyroiditis
by Ravi Sharma, Verena Theiler-Schwetz, Christian Trummer, Stefan Pilz and Markus Reichhartinger
Bioengineering 2023, 10(6), 724; https://doi.org/10.3390/bioengineering10060724 - 14 Jun 2023
Cited by 1 | Viewed by 1829
Abstract
Hypothyroidism is a condition where the patient’s thyroid gland cannot produce sufficient thyroid hormones (mainly triiodothyronine and thyroxine). The primary cause of hypothyroidism is autoimmune-mediated destruction of the thyroid gland, referred to as Hashimoto’s thyroiditis. A patient’s desired thyroid hormone concentration is achieved [...] Read more.
Hypothyroidism is a condition where the patient’s thyroid gland cannot produce sufficient thyroid hormones (mainly triiodothyronine and thyroxine). The primary cause of hypothyroidism is autoimmune-mediated destruction of the thyroid gland, referred to as Hashimoto’s thyroiditis. A patient’s desired thyroid hormone concentration is achieved by oral administration of thyroid hormone, usually levothyroxine. Establishing individual levothyroxine doses to achieve desired thyroid hormone concentrations requires several patient visits. Additionally, clear guidance for the dosing regimen is lacking, and significant inter-individual differences exist. This study aims to design a digital automatic dosing algorithm for patients suffering from Hashimoto’s thyroiditis. The dynamic behaviour of the relevant thyroid function is mathematically modelled. Methods of automatic control are exploited for the design of the proposed robust model-based levothyroxine dosing algorithm. Numerical simulations are performed to evaluate the mathematical model and the dosing algorithm. With the help of the developed controller thyroid hormone concentrations of patients, emulated using Thyrosim, have been regulated under the euthyroid state. The proposed concept demonstrates reliable responses amidst varying patient parameters. Our developed model provides a useful basis for the design of automatic levothyroxine dosing algorithms. The proposed robust feedback loop contributes to the first results for computer-assisted thyroid dosing algorithms. Full article
(This article belongs to the Section Biosignal Processing)
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44 pages, 29600 KiB  
Article
Holistic Approach to Process Design and Scale-Up for Itaconic Acid Production from Crude Substrates
by Katharina Maria Saur, Robert Kiefel, Paul-Joachim Niehoff, Jordy Hofstede, Philipp Ernst, Johannes Brockkötter, Jochem Gätgens, Jörn Viell, Stephan Noack, Nick Wierckx, Jochen Büchs and Andreas Jupke
Bioengineering 2023, 10(6), 723; https://doi.org/10.3390/bioengineering10060723 - 14 Jun 2023
Cited by 9 | Viewed by 3602
Abstract
Bio-based bulk chemicals such as carboxylic acids continue to struggle to compete with their fossil counterparts on an economic basis. One possibility to improve the economic feasibility is the use of crude substrates in biorefineries. However, impurities in these substrates pose challenges in [...] Read more.
Bio-based bulk chemicals such as carboxylic acids continue to struggle to compete with their fossil counterparts on an economic basis. One possibility to improve the economic feasibility is the use of crude substrates in biorefineries. However, impurities in these substrates pose challenges in fermentation and purification, requiring interdisciplinary research. This work demonstrates a holistic approach to biorefinery process development, using itaconic acid production on thick juice based on sugar beets with Ustilago sp. as an example. A conceptual process design with data from artificially prepared solutions and literature data from fermentation on glucose guides the simultaneous development of the upstream and downstream processes up to a 100 L scale. Techno-economic analysis reveals substrate consumption as the main constituent of production costs and therefore, the product yield is the driver of process economics. Aligning pH-adjusting agents in the fermentation and the downstream process is a central lever for product recovery. Experiments show that fermentation can be transferred from glucose to thick juice by changing the feeding profile. In downstream processing, an additional decolorization step is necessary to remove impurities accompanying the crude substrate. Moreover, we observe an increased use of pH-adjusting agents compared to process simulations. Full article
(This article belongs to the Special Issue Design, Optimization and Scale-Up of Industrial Bioprocess)
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16 pages, 1901 KiB  
Article
Retinal Vascular Image Segmentation Using Improved UNet Based on Residual Module
by Ko-Wei Huang, Yao-Ren Yang, Zih-Hao Huang, Yi-Yang Liu and Shih-Hsiung Lee
Bioengineering 2023, 10(6), 722; https://doi.org/10.3390/bioengineering10060722 - 14 Jun 2023
Cited by 3 | Viewed by 3473
Abstract
In recent years, deep learning technology for clinical diagnosis has progressed considerably, and the value of medical imaging continues to increase. In the past, clinicians evaluated medical images according to their individual expertise. In contrast, the application of artificial intelligence technology for automatic [...] Read more.
In recent years, deep learning technology for clinical diagnosis has progressed considerably, and the value of medical imaging continues to increase. In the past, clinicians evaluated medical images according to their individual expertise. In contrast, the application of artificial intelligence technology for automatic analysis and diagnostic assistance to support clinicians in evaluating medical information more efficiently has become an important trend. In this study, we propose a machine learning architecture designed to segment images of retinal blood vessels based on an improved U-Net neural network model. The proposed model incorporates a residual module to extract features more effectively, and includes a full-scale skip connection to combine low level details with high-level features at different scales. The results of an experimental evaluation show that the model was able to segment images of retinal vessels accurately. The proposed method also outperformed several existing models on the benchmark datasets DRIVE and ROSE, including U-Net, ResUNet, U-Net3+, ResUNet++, and CaraNet. Full article
(This article belongs to the Special Issue Artificial Intelligence-Based Diagnostics and Biomedical Analytics)
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17 pages, 2996 KiB  
Article
High-Definition Transcranial Direct Current Stimulation in the Right Ventrolateral Prefrontal Cortex Lengthens Sustained Attention in Virtual Reality
by Shan Yang, Ganbold Enkhzaya, Bao-Hua Zhu, Jian Chen, Zhi-Ji Wang, Eun-Seong Kim and Nam-Young Kim
Bioengineering 2023, 10(6), 721; https://doi.org/10.3390/bioengineering10060721 - 14 Jun 2023
Cited by 1 | Viewed by 3058
Abstract
Due to the current limitations of three-dimensional (3D) simulation graphics technology, mind wandering commonly occurs in virtual reality tasks, which has impeded it being applied more extensively. The right ventrolateral prefrontal cortex (rVLPFC) plays a vital role in executing continuous two-dimensional (2D) mental [...] Read more.
Due to the current limitations of three-dimensional (3D) simulation graphics technology, mind wandering commonly occurs in virtual reality tasks, which has impeded it being applied more extensively. The right ventrolateral prefrontal cortex (rVLPFC) plays a vital role in executing continuous two-dimensional (2D) mental paradigms, and transcranial direct current stimulation (tDCS) over this cortical region has been shown to successfully modulate sustained 2D attention. Accordingly, we further explored the effects of electrical activation of the rVLPFC on 3D attentional tasks using anodal high-definition (HD)-tDCS. A 3D Go/No-go (GNG) task was developed to compare the after effects of real and sham brain stimulation. Specifically, GNG tasks were periodically interrupted to assess the subjective perception of attentional level, behavioral reactions were tracked and decomposed into an underlying decision cognition process, and electroencephalography data were recorded to calculate event-related potentials (ERPs) in rVLPFC. The p-values statistically indicated that HD-tDCS improved the subjective mentality, led to more cautious decisions, and enhanced neuronal discharging in rVLPFC. Additionally, the neurophysiological P300 ERP component and stimulation being active or sham could effectively predict several objective outcomes. These findings indicate that the comprehensive approach including brain stimulation, 3D mental paradigm, and cross-examined performance could significantly lengthen and robustly compare sustained 3D attention. Full article
(This article belongs to the Special Issue VR/AR Applications in Biomedical Imaging)
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14 pages, 2395 KiB  
Article
Chemical Shift-Encoded Sequence (IDEAL-IQ) and Amide Proton Transfer (APT) MRI for Prediction of Histopathological Factors of Rectal Cancer
by Yang Peng, Xianlun Zou, Gen Chen, Xuemei Hu, Yaqi Shen, Daoyu Hu and Zhen Li
Bioengineering 2023, 10(6), 720; https://doi.org/10.3390/bioengineering10060720 - 14 Jun 2023
Cited by 4 | Viewed by 1636
Abstract
To investigate whether parameters from IDEAL-IQ/amide proton transfer MRI (APTWI) could help predict histopathological factors of rectal cancer. Preoperative IDEAL-IQ and APTWI sequences of 67 patients with rectal cancer were retrospectively analyzed. The intra-tumoral proton density fat fraction (PDFF), R2* and magnetization transfer [...] Read more.
To investigate whether parameters from IDEAL-IQ/amide proton transfer MRI (APTWI) could help predict histopathological factors of rectal cancer. Preoperative IDEAL-IQ and APTWI sequences of 67 patients with rectal cancer were retrospectively analyzed. The intra-tumoral proton density fat fraction (PDFF), R2* and magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)) were measured according to the histopathological factors of rectal cancer. The relationship between MR parameters and histopathological factors were analyzed, along with diagnostic performance of MR parameters. PDFF, R2* and MTRasym (3.5 ppm) were statistically different between T1+T2/T3+T4 stages, non-metastatic/metastatic lymph nodes, lower/higher tumor grade and negative/positive status of MRF and EMVI (p < 0.001 for PDFF, p = 0.000–0.015 for R2* and p = 0.000–0.006 for MTRasym (3.5 ppm)). There were positive correlations between the above parameters and the histopathological features of rectal cancer (r = 0.464–0.723 for PDFF (p < 0.001), 0.299–0.651 for R2* (p = 0.000–0.014), and 0.337–0.667 for MTRasym (3.5 ppm) (p = 0.000–0.005)). MTRasym (3.5 ppm) correlated moderately and mildly with PDFF (r = 0.563, p < 0.001) and R2* (r = 0.335, p = 0.006), respectively. PDFF provided a significantly higher diagnostic ability than MTRasym (3.5 ppm) for distinguishing metastatic from non-metastatic lymph nodes (z = 2.407, p = 0.0161). No significant differences were found in MR parameters for distinguishing other histopathological features (p > 0.05). IDEAL-IQ and APTWI were associated with histopathological factors of rectal cancer, and might serve as non-invasive biomarkers for characterizing rectal cancer. Full article
(This article belongs to the Section Biomedical Engineering and Biomaterials)
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16 pages, 3478 KiB  
Article
Robust Removal of Slow Artifactual Dynamics Induced by Deep Brain Stimulation in Local Field Potential Recordings Using SVD-Based Adaptive Filtering
by Nooshin Bahador, Josh Saha, Mohammad R. Rezaei, Saha Utpal, Ayda Ghahremani, Robert Chen and Milad Lankarany
Bioengineering 2023, 10(6), 719; https://doi.org/10.3390/bioengineering10060719 - 14 Jun 2023
Viewed by 1801
Abstract
Deep brain stimulation (DBS) is widely used as a treatment option for patients with movement disorders. In addition to its clinical impact, DBS has been utilized in the field of cognitive neuroscience, wherein the answers to several fundamental questions underpinning the mechanisms of [...] Read more.
Deep brain stimulation (DBS) is widely used as a treatment option for patients with movement disorders. In addition to its clinical impact, DBS has been utilized in the field of cognitive neuroscience, wherein the answers to several fundamental questions underpinning the mechanisms of neuromodulation in decision making rely on the ways in which a burst of DBS pulses, usually delivered at a clinical frequency, i.e., 130 Hz, perturb participants’ choices. It was observed that neural activities recorded during DBS were contaminated with large artifacts, which lasts for a few milliseconds, as well as a low-frequency (slow) signal (~1–2 Hz) that can persist for hundreds of milliseconds. While the focus of most of methods for removing DBS artifacts was on the former, the artifact removal capabilities of the slow signal have not been addressed. In this work, we propose a new method based on combining singular value decomposition (SVD) and normalized adaptive filtering to remove both large (fast) and slow artifacts in local field potentials, recorded during a cognitive task in which bursts of DBS were utilized. Using synthetic data, we show that our proposed algorithm outperforms four commonly used techniques in the literature, namely, (1) normalized least mean square adaptive filtering, (2) optimal FIR Wiener filtering, (3) Gaussian model matching, and (4) moving average. The algorithm’s capabilities are further demonstrated by its ability to effectively remove DBS artifacts in local field potentials recorded from the subthalamic nucleus during a verbal Stroop task, highlighting its utility in real-world applications. Full article
(This article belongs to the Special Issue Advances of Biomedical Signal Processing)
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13 pages, 1983 KiB  
Article
Targeted c-Myc Inhibition and Systemic Temozolomide Therapy Extend Survival in Glioblastoma Xenografts
by Laxmi Dhungel, Cayla Harris, Lauren Romine, Jan Sarkaria and Drazen Raucher
Bioengineering 2023, 10(6), 718; https://doi.org/10.3390/bioengineering10060718 - 14 Jun 2023
Cited by 2 | Viewed by 2041
Abstract
Glioblastoma is a highly aggressive disease with poor patient outcomes despite current treatment options, which consist of surgery, radiation, and chemotherapy. However, these strategies present challenges such as resistance development, damage to healthy tissue, and complications due to the blood–brain barrier. There is [...] Read more.
Glioblastoma is a highly aggressive disease with poor patient outcomes despite current treatment options, which consist of surgery, radiation, and chemotherapy. However, these strategies present challenges such as resistance development, damage to healthy tissue, and complications due to the blood–brain barrier. There is therefore a critical need for new treatment modalities that can selectively target tumor cells, minimize resistance development, and improve patient survival. Temozolomide is the current standard chemotherapeutic agent for glioblastoma, yet its use is hindered by drug resistance and severe side effects. Combination therapy using multiple drugs acting synergistically to kill cancer cells and with multiple targets can provide increased efficacy at lower drug concentrations and reduce side effects. In our previous work, we designed a therapeutic peptide (Bac-ELP1-H1) targeting the c-myc oncogene and demonstrated its ability to reduce tumor size, delay neurological deficits, and improve survival in a rat glioblastoma model. In this study, we expanded our research to the U87 glioblastoma cell line and investigated the efficacy of Bac-ELP1-H1/hyperthermia treatment, as well as the combination treatment of temozolomide and Bac-ELP1-H1, in suppressing tumor growth and extending survival in athymic mice. Our experiments revealed that the combination treatment of Bac-ELP1-H1 and temozolomide acted synergistically to enhance survival in mice and was more effective in reducing tumor progression than the single components. Additionally, our study demonstrated the effectiveness of hyperthermia in facilitating the accumulation of the Bac-ELP1-H1 protein at the tumor site. Our findings suggest that the combination of targeted c-myc inhibitory biopolymer with systemic temozolomide therapy may represent a promising alternative treatment option for glioblastoma patients. Full article
(This article belongs to the Special Issue Drug Delivery Systems, What's New?)
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13 pages, 1781 KiB  
Article
Performance of Nuclear Magnetic Resonance-Based Estimated Glomerular Filtration Rate in a Real-World Setting
by Amauri Schwäble Santamaria, Marcello Grassi, Jeffrey W. Meeusen, John C. Lieske, Renee Scott, Andrew Robertson and Eric Schiffer
Bioengineering 2023, 10(6), 717; https://doi.org/10.3390/bioengineering10060717 - 13 Jun 2023
Viewed by 1563
Abstract
An accurate estimate of glomerular filtration rate (eGFR) is essential for proper clinical management, especially in patients with kidney dysfunction. This prospective observational study evaluated the real-world performance of the nuclear magnetic resonance (NMR)-based GFRNMR equation, which combines creatinine, cystatin C, valine, [...] Read more.
An accurate estimate of glomerular filtration rate (eGFR) is essential for proper clinical management, especially in patients with kidney dysfunction. This prospective observational study evaluated the real-world performance of the nuclear magnetic resonance (NMR)-based GFRNMR equation, which combines creatinine, cystatin C, valine, and myo-inositol with age and sex. We compared GFRNMR performance to that of the 2021 CKD-EPI creatinine and creatinine-cystatin C equations (CKD-EPI2021Cr and CKD-EPI2021CrCys), using 115 fresh routine samples of patients scheduled for urinary iothalamate clearance measurement (mGFR). Median bias to mGFR of the three eGFR equations was comparably low, ranging from 0.4 to 2.0 mL/min/1.73 m2. GFRNMR outperformed the 2021 CKD-EPI equations in terms of precision (interquartile range to mGFR of 10.5 vs. 17.9 mL/min/1.73 m2 for GFRNMR vs. CKD-EPI2021CrCys; p = 0.01) and accuracy (P15, P20, and P30 of 66.1% vs. 48.7% [p = 0.007], 80.0% vs. 60.0% [p < 0.001] and 95.7% vs. 86.1% [p = 0.006], respectively, for GFRNMR vs. CKD-EPI2021CrCys). Clinical parameters such as etiology, comorbidities, or medications did not significantly alter the performance of the three eGFR equations. Altogether, this study confirmed the utility of GFRNMR for accurate GFR estimation, and its potential value in routine clinical practice for improved medical care. Full article
(This article belongs to the Special Issue Chronic Kidney Disease: Diagnosis and Treatment)
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23 pages, 10657 KiB  
Article
Exploring the Possibility of Measuring Vertebrae Bone Structure Metrics Using MDCT Images: An Unpaired Image-to-Image Translation Method
by Dan Jin, Han Zheng and Huishu Yuan
Bioengineering 2023, 10(6), 716; https://doi.org/10.3390/bioengineering10060716 - 12 Jun 2023
Viewed by 1379
Abstract
Bone structure metrics are vital for the evaluation of vertebral bone strength. However, the gold standard for measuring bone structure metrics, micro-Computed Tomography (micro-CT), cannot be used in vivo, which hinders the early diagnosis of fragility fractures. This paper used an unpaired image-to-image [...] Read more.
Bone structure metrics are vital for the evaluation of vertebral bone strength. However, the gold standard for measuring bone structure metrics, micro-Computed Tomography (micro-CT), cannot be used in vivo, which hinders the early diagnosis of fragility fractures. This paper used an unpaired image-to-image translation method to capture the mapping between clinical multidetector computed tomography (MDCT) and micro-CT images and then generated micro-CT-like images to measure bone structure metrics. MDCT and micro-CT images were scanned from 75 human lumbar spine specimens and formed training and testing sets. The generator in the model focused on learning both the structure and detailed pattern of bone trabeculae and generating micro-CT-like images, and the discriminator determined whether the generated images were micro-CT images or not. Based on similarity metrics (i.e., SSIM and FID) and bone structure metrics (i.e., bone volume fraction, trabecular separation and trabecular thickness), a set of comparisons were performed. The results show that the proposed method can perform better in terms of both similarity metrics and bone structure metrics and the improvement is statistically significant. In particular, we compared the proposed method with the paired image-to-image method and analyzed the pros and cons of the method used. Full article
(This article belongs to the Special Issue Biomedical Application of Big Data and Artificial Intelligence)
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13 pages, 4696 KiB  
Article
Multiphysics Interaction Analysis of the Therapeutic Effects of the Sigmoid Sinus Wall Reconstruction in Patients with Venous Pulsatile Tinnitus
by Zhenxia Mu, Lihui Zhuang, Pengfei Zhao, Bin Gao, Youjun Liu, Zhenchang Wang, Shifeng Yang and Ximing Wang
Bioengineering 2023, 10(6), 715; https://doi.org/10.3390/bioengineering10060715 - 12 Jun 2023
Cited by 3 | Viewed by 1556
Abstract
Sigmoid sinus wall dehiscence (SSWD) is an important etiology of venous pulsatile tinnitus (VPT) and is treated by sigmoid sinus wall reconstruction (SSWR). This study aimed to investigate the therapeutic effects of the different degrees of SSWR and the prognostic effect in patients [...] Read more.
Sigmoid sinus wall dehiscence (SSWD) is an important etiology of venous pulsatile tinnitus (VPT) and is treated by sigmoid sinus wall reconstruction (SSWR). This study aimed to investigate the therapeutic effects of the different degrees of SSWR and the prognostic effect in patients with VPT. Personalized models of three patients with SSWD (control), 3/4SSWD, 1/2SSWD, 1/4SSWD, and 0SSWD were reconstructed. A multiphysics interaction approach was applied to elucidate the biomechanical and acoustic changes. Results revealed that after SSWR, the average pressure of venous vessel on the SSWD region reduced by 33.70 ± 12.53%, 35.86 ± 12.39%, and 39.70 ± 12.45% (mean ± SD) in three patients with 3/4SSWD, 1/2SSWD, and 1/4SSWD. The maximum displacement of the SSWR region reduced by 25.91 ± 30.20%, 37.20 ± 31.47%, 52.60 ± 34.66%, and 79.35 ± 18.13% (mean ± SD) in three patients with 3/4SSWD, 1/2SSWD, 1/4SSWD, and 0SSWD, with a magnitude approximately 10−3 times that of the venous vessel in the SSWD region. The sound pressure level at the tympanum reduced by 23.72 ± 1.91%, 31.03 ± 14.40%, 45.62 ± 19.11%, and 128.46 ± 15.46% (mean ± SD). The SSWR region was still loaded with high stress in comparison to the surrounding region. The SSWR region of the temporal bone effectively shielded the high wall pressure and blocked the transmission of venous vessel vibration to the inner ear. Patients with inadequate SSWR still had residual VPT symptoms despite the remission of VPT symptoms. Complete SSWR could completely solve VPT issues. High-stress distribution of the SSWR region may be the cause of the recurrence of VPT symptoms. Full article
(This article belongs to the Special Issue Computational Biomechanics, Volume II)
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