AIMS Bioengineering最新文献

{"title":"Advanced platelet rich fibrin in periodontal regeneration","authors":"Aishwarya Rathod, Priyanka Jaiswal, D. Masurkar","doi":"10.3934/bioeng.2023012","DOIUrl":"https://doi.org/10.3934/bioeng.2023012","url":null,"abstract":"Regenerating periodontal tissue is the main goal of periodontal therapy. Periodontal tissue regeneration involves the development of new bone, cement, and periodontal ligaments on damaged tooth root surfaces in order to restore anatomy and function. In order to further enhance PRF (Platelet rich fibrin) and develop advanced platelet-rich fibrin, a slower rotating speed is proposed (A-PRFs). Cell dispersion is affected by centrifugation rate. The majority of the leukocytes in the PRF are concentrated near the bottom of the tube due to centrifugation rate. By switching the centrifugation process to 1,500 rpm for 14 minutes, granulocyte neutrophils and the fibrin matrix are more evenly distributed in the A-PRF created. Hence, a periodontal evaluation of this subject is required.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"71 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83838987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust QRS complex detection in noisy electrocardiogram based on underdamped periodic stochastic resonance","authors":"Zheng Guo, Siqi Li, Kaicong Chen, Xuehui Zang","doi":"10.3934/bioeng.2023018","DOIUrl":"https://doi.org/10.3934/bioeng.2023018","url":null,"abstract":"<abstract> <p>Robust QRS detection is crucial for accurate diagnosis and monitoring of cardiovascular diseases. During the detection process, various types of noise and artifacts in the electrocardiogram (ECG) can degrade the accuracy of algorithm. Previous QRS detectors have employed various filtering methods to minimize the negative impact of noise. However, their performance still significantly deteriorates in large-noise environments. To further enhance the robustness of QRS detectors on noisy electrocardiograms (ECGs), we proposed a QRS detection algorithm based on an underdamped. This method utilizes the period nonlinearity-induced stochastic resonance to enhance QRS complexes while suppressing noise and non-QRS components in the ECG. In contrast to neural network-based algorithms, our proposed algorithm does not rely on large datasets or prior knowledge. Through testing on three widely used ECG datasets, we demonstrated that the proposed algorithm achieves state-of-the-art detection performance. Furthermore, compared to traditional stochastic resonance-based method, our algorithm has increased noise robustness by 25% to 100% across various real-world environments. This enables the proposed method to maintain its optimal performance within a certain range even in the presence of additional injected noise, thus providing an excellent approach for robust QRS detection in noisy ECGs.</p> </abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135495427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing biomedical engineering through a multi-modal sensor fusion system for enhanced physical training","authors":"Yi Deng, Zhiguo Wang, Xiaohui Li, Yu Lei, Owen Omalley","doi":"10.3934/bioeng.2023022","DOIUrl":"https://doi.org/10.3934/bioeng.2023022","url":null,"abstract":"<abstract> <p>In this paper, we introduce a multi-modal sensor fusion system designed for biomedical engineering, specifically geared toward optimizing physical training by collecting detailed body movement data. This system employs inertial measurement units, flex sensors, electromyography sensors, and Microsoft's Kinect V2 to generate an in-depth analysis of an individual's physical performance. We incorporate a gated recurrent unit- recurrent neural network algorithm to achieve highly accurate body and hand motion estimation, thus surpassing the performance of traditional machine learning algorithms in terms of accuracy, precision, recall, and F1 score. The system's integration with the PICO 4 VR environment creates a rich, interactive experience for physical training. Unlike conventional motion capture systems, our sensor fusion system is not limited to a fixed workspace, allowing users to engage in exercise within a flexible, free-form environment.</p> </abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135007694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and validation of aging-related genes and their classification models based on myelodysplastic syndromes","authors":"Xiao-Li Gu, Li Yu, Yu Du, Xiu-Peng Yang, Yong-Gang Xu","doi":"10.3934/bioeng.2023026","DOIUrl":"https://doi.org/10.3934/bioeng.2023026","url":null,"abstract":"<abstract><sec> <title>Background</title> <p>Myelodysplastic syndrome is a malignant clonal disorder of hematopoietic stem cells (HSC) with both myelodysplastic problems and hematopoietic disorders. The greatest risk factor for the development of MDS is advanced age, and aging causes dysregulation and decreased function of the immune and hematopoietic systems. However, the mechanisms by which this occurs remain to be explored. Therefore, we explore the association between MDS and aging genes through a classification model and use bioinformatics analysis tools to explore the relationship between MDS aging subtypes and the immune microenvironment.</p> </sec><sec> <title>Methods</title> <p>The dataset of MDS in the paper was obtained from the GEO database, and aging-related genes were taken from HAGR. Specific genes were screened by three machine learning algorithms. Then, artificial neural network (ANN) models and Nomogram models were developed to validate the effectiveness of the methods. Finally, aging subtypes were established, and the correlation between MDS and the immune microenvironment was analyzed using bioinformatics analysis tools. Weighted correlation network analysis (WGCNA) and single cell analysis were also added to validate the consistency of the result analysis.</p> </sec><sec> <title>Results</title> <p>Seven core genes associated with ARG were screened by differential analysis, enrichment analysis and machine learning algorithms for accurate diagnosis of MDS. Subsequently, two subtypes of senescent expressions were identified based on ARG, illustrating that different subtypes have different biological and immune functions. The cell clustering results obtained from manual annotation were validated using single cell analysis, and the expression of 7 pivotal genes in MDS was verified by flow cytometry and RT-PCR.</p> </sec><sec> <title>Discussion</title> <p>The findings demonstrate a key role of senescence in the immunological milieu of MDS, giving new insights into MDS pathogenesis and potential treatments. The findings also show that aging plays an important function in the immunological microenvironment of MDS, giving new insights into the pathogenesis of MDS and possible immunotherapy.</p> </sec></abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135711566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic expansion of mesenchymal stem/stromal cells in a stirred tank bioreactor promotes the release of potent extracellular vesicles","authors":"J. Barekzai, Jonas Friedrich, Maduwuike Okpara, Laura Refflinghaus, Dustin Eckhardt, P. Czermak, D. Salzig","doi":"10.3934/bioeng.2023016","DOIUrl":"https://doi.org/10.3934/bioeng.2023016","url":null,"abstract":"Mesenchymal stem/stromal cell-derived extracellular vesicles (MSC-EVs) are considered a promising therapeutic tool in cell therapy due to their immunomodulatory, regenerative and angiogenic capabilities. However, there is a lack of process knowledge, particularly for a large-scale production of MSC-EV using fully controlled stirred tank bioreactor (STR) systems. For the establishment of a STR-based process, we investigated dynamic process set-ups in spinner flasks, using three different microcarriers, as well as in shaking flasks, using microcarrier-free spheroids. An immortalized cell line (hMSC-TERT) and a particle-free chemically defined medium was used for all approaches. Cell characteristics (e.g., growth, metabolism, cell-specific particle production rates), MSC-EV epitope markers and MSC-EV potency in migration assays were analyzed. We showed that the transfer to a dynamic system (non-porous microcarrier, spinner flask) significantly increased the cell-specific particle production rate (6-fold) and the expression of EV-specific markers. Moreover, MSC proliferation and, most importantly, the therapeutic potency of MSC-derived particles including EVs was maintained. We demonstrated that high cell-specific particle production rates were associated with an increased glucose consumption rate rather than cell growth, which can be utilized for future process development. Furthermore, we showed that dynamic conditions of a controlled 1 L STR significantly increased the cell-specific particle production rate (24-fold) as well as the final concentration (3-fold) of potent MSC-derived particles including EVs. This indicates that fully controlled STRs are an efficient production system for MSC-derived particles including EVs that may open and facilitate the path for clinical applications.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"29 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80529214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New biomaterials for bone augmentation in complicated cases","authors":"José Luis Calvo-Guirado","doi":"10.3934/bioeng.2023021","DOIUrl":"https://doi.org/10.3934/bioeng.2023021","url":null,"abstract":"<jats:p xml:lang=\"fr\" />","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136367819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19","authors":"Houssem Ben Khalfallah, M. Jelassi, J. Demongeot, Narjès Bellamine Ben Saoud","doi":"10.3934/bioeng.2023004","DOIUrl":"https://doi.org/10.3934/bioeng.2023004","url":null,"abstract":"<abstract><sec> <title>Objective</title> <p>The objective of this study was to provide an overview of Decision Support Systems (DSS) applied in healthcare used for diagnosis, monitoring, prediction and recommendation in medicine.</p> </sec><sec> <title>Methods</title> <p>We conducted a systematic review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines of articles published until September 2022 from PubMed, Cochrane, Scopus and web of science databases. We used KH coder to analyze included research. Then we categorized decision support systems based on their types and medical applications.</p> </sec><sec> <title>Results</title> <p>The search strategy provided a total of 1605 articles in the studied period. Of these, 231 articles were included in this qualitative review. This research was classified into 4 categories based on the DSS type used in healthcare: Alert Systems, Monitoring Systems, Recommendation Systems and Prediction Systems. Under each category, domain applications were specified according to the disease the system was applied to.</p> </sec><sec> <title>Conclusion</title> <p>In this systematic review, we collected CDSS studies that use ML techniques to provide insights into different CDSS types. We highlighted the importance of ML to support physicians in clinical decision-making and improving healthcare according to their purposes.</p> </sec></abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72819969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cardiovascular disease prediction using hyperparameters-tuned LSTM considering COVID-19 with experimental validation","authors":"Kuna Dhananjay Rao, Mudunuru Satya Dev Kumar, Paidi Pavani, Darapureddy Akshitha, Kagitha Nagamaleswara Rao, Hafiz Tayyab Rauf, Mohamed Sharaf","doi":"10.3934/bioeng.2023017","DOIUrl":"https://doi.org/10.3934/bioeng.2023017","url":null,"abstract":"<abstract> <p>Heart disease, globally recognized as a leading cause of death, has seen its impact magnified by the emergence of COVID-19. The heightened demand for early detection and diagnosis of heart disease has forced the development of innovative, intelligent systems. This research offers a novel approach by leveraging extended short-term memory networks (LSTM) and including COVID-19 as a significant parameter in cardiac arrest analysis. A comparative study is conducted between LSTM and other prevalent techniques, such as support vector machines (SVM), linear regression (LR), and artificial neural networks (ANN), focusing on accuracy and other prognostic criteria for heart disease. We aim to develop an intelligent system powered by LSTM to predict heart disease, thereby assisting healthcare professionals in making well-informed decisions about heart disease management, stroke prevention, and patient monitoring. Additionally, hyperparameter tuning has been performed to optimize the LSTM model's performance in cardiac arrest prediction. The results underscore that LSTM, especially when trained with COVID-19 as an input parameter, surpasses other established techniques in prediction accuracy. The proposed model underwent experimental testing, showcasing its proficiency in predicting cardiovascular disease.</p> </abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135495426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Micro-CT evaluation of bone grow concept of an implant with microstructured backtaper crestally and sub-crestally placed. Preliminary study in New Zealand rabbits tibia at one month","authors":"José Luis Calvo-Guirado, Marta Belén Cabo-Pastor, Félix de Carlos-Villafranca, Nuria García-Carrillo, Manuel Fernández-Domínguez, Francisco Martínez Martínez","doi":"10.3934/bioeng.2023024","DOIUrl":"https://doi.org/10.3934/bioeng.2023024","url":null,"abstract":"<abstract> <p>The primary purpose of this study was to determine the accuracy of micro-computed tomography (micro-CT) as a novel tool for the 3D analysis of bone density around dental implants in tibia rabbits. Six male New Zealand rabbits were used in our evaluation. One Copa SKY® (Bredent Medical GmbH &amp;amp; Co. K.G.) with a 3.5 mm diameter by 8.0 mm in length was placed within 12 tibia rabbits divided into two experimental groups: Group A (crestal placement) and Group B (sub-crestal placement). The animals were sacrificed at four weeks. Micro-CT evaluations showed a high amount of bone around all implants in the tibia rabbit bone. There was an increased formation of bone around the Copa SKY implants, mainly in the implants that were placed crestally. The most frequent density found in most implants was a medullary bone formation surrounding the implant; the density three (D3) was the most common type in all implants. The 3D model analysis revealed a mean bone volume (B.V.) of 31.24 ± 1.24% in crestal implants compared with the 43.12 ± 0.43% in sub-crestal implants. The mean actual contact implant to bone (B.I.C.) in the sub-crestal group was 51.76 ± 0.86%, compared to the 42.63 ± 0.75% in the crestal group. Compared to crestal implants, the Copa Sky implant placed sub-crestally allows for the formation of bone on top of the neck, thereby stimulating bone growth in tibia rabbits.</p> </abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135659481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming lung cancer care: Synergizing artificial intelligence and clinical expertise for precision diagnosis and treatment","authors":"Meiling Sun, Changlei Cui","doi":"10.3934/bioeng.2023020","DOIUrl":"https://doi.org/10.3934/bioeng.2023020","url":null,"abstract":"<abstract> <p>Lung cancer is a predominant cause of global cancer-related mortality, highlighting the urgent need for enhanced diagnostic and therapeutic modalities. With the integration of artificial intelligence (AI) into clinical practice, a new horizon in lung cancer care has emerged, characterized by precision in both diagnosis and treatment. This review delves into AI's transformative role in this domain. We elucidate AI's significant contributions to imaging, pathology, and genomic diagnostics, underscoring its potential to revolutionize early detection and accurate categorization of the disease. Shifting the focus to treatment, we spotlight AI's synergistic role in tailoring patient-centric therapies, predicting therapeutic outcomes, and propelling drug research and development. By harnessing the combined prowess of AI and clinical expertise, there's potential for a seismic shift in the lung cancer care paradigm, promising more precise, individualized interventions, and ultimately, improved survival rates for patients.</p> </abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135699575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}