Bioengineering最新文献

{"title":"A Lightweight Breast Cancer Mass Classification Model Utilizing Simplified Swarm Optimization and Knowledge Distillation.","authors":"Wei-Chang Yeh, Wei-Chung Shia, Yun-Ting Hsu, Chun-Hui Huang, Yong-Shiuan Lee","doi":"10.3390/bioengineering12060640","DOIUrl":"10.3390/bioengineering12060640","url":null,"abstract":"<p><p>In recent years, an increasing number of women worldwide have been affected by breast cancer. Early detection is crucial, as it is the only way to identify abnormalities at an early stage. However, most deep learning models developed for classifying breast cancer abnormalities tend to be large-scale and computationally intensive, often overlooking the constraints of cost and limited computational resources. This research addresses these challenges by utilizing the CBIS-DDSM dataset and introducing a novel concatenated classification architecture and a two-stage strategy to develop an optimized, lightweight model for breast mass abnormality classification. Through data augmentation and image preprocessing, the proposed model demonstrates a superior performance compared to standalone CNN and DNN models. The two-stage strategy involves first constructing a compact model using knowledge distillation and then refining its structure with a heuristic approach known as Simplified Swarm Optimization (SSO). The experimental results confirm that knowledge distillation significantly enhances the model's performance. Furthermore, by applying SSO's full-variable update mechanism, the final model-SSO-Concatenated NASNetMobile (SSO-CNNM)-achieves outstanding performance metrics. It attains a compression rate of 96.17%, along with accuracy, precision, recall, and AUC scores of 96.47%, 97.4%, 94.94%, and 98.23%, respectively, outperforming other existing methods.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electric Potential of <i>Chlorella</i> sp. Microalgae Biomass in Microbial Fuel Cells (MFCs).","authors":"Rickelmi Agüero-Quiñones, Magaly De La Cruz-Noriega, Walter Rojas-Villacorta","doi":"10.3390/bioengineering12060635","DOIUrl":"10.3390/bioengineering12060635","url":null,"abstract":"<p><p>The projected global energy demand for 2050 drives the imperative search for alternative and environmentally friendly energy sources. An emerging and promising alternative is microbial fuel cells assisted with microalgae. This research evaluated the potential of <i>Chlorella</i> sp. biomass in electricity production using microbial fuel cells (MFCs) with a single chamber and activated carbon and zinc electrodes at the laboratory scale over 20 days of operation. Maximum values of voltage (1271 ± 2.52 mV), current (4.77 ± 0.02 mA), power density (247.514 mW/cm²), current density (0.551 mA/cm²), and internal resistance (200.83 ± 0.327 Ω) were obtained. The biomass-maintained pH values of 7.32 ± 0.03-7.74 ± 0.02 and peaks of electrical conductivity of 2450 ± 17.1 µS/cm and oxidation-reduction potential of 952 ± 20 mV were reached. Meanwhile, cell density and absorbance increased to average values of 2.2933 × 10⁷ ± 1.15 × 10⁶ cells/mL and 3.471 ± 0.195 absorbance units (AU), respectively. Scanning electron microscopy micrographs allowed the observation of filamentous structures of the formed biofilm attached to carbon particles, and energy-dispersive X-ray spectroscopy spectra of the anodes determined the predominance of oxygen, carbon, silicon, aluminum, and iron. Finally, this research demonstrates the great potential of <i>Chlorella</i> sp. biomass for sustainable bioelectricity generation in MFCs.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Possibility of Using Ultrasound Imaging in Treatment of Stress Urinary Incontinence in Women-Preliminary Study.","authors":"Gabriela Kołodyńska, Maciej Zalewski, Aleksandra Piątek, Anna Mucha, Krystyna Rożek-Piechura, Waldemar Andrzejewski","doi":"10.3390/bioengineering12060633","DOIUrl":"10.3390/bioengineering12060633","url":null,"abstract":"<p><p>The number of people suffering from urinary incontinence increases every year. Along this trend, the knowledge of society increases regarding the various methods available for treating this ailment. Both patients and researchers are constantly looking for new treatments for urinary incontinence. One of the new solutions is sonofeedback of the pelvic floor muscles, which may help to strengthen them and thus reduce the problem. The aim of this study was to evaluate the effectiveness of sonofeedback and transvaginal electrostimulation in increasing the bioelectrical activity of pelvic floor muscles in postmenopausal women with stress urinary incontinence. Sixty women with stress urinary incontinence were enrolled in the study. The patients were divided into two groups: A, where sonofeedback was used, and B, where electrostimulation of the pelvic floor muscles was performed with biofeedback training. In patients, the resting bioelectrical activity of the pelvic floor muscles was assessed using an electromyograph. The assessment of the resting bioelectrical activity of the pelvic floor muscles was performed before the therapy, after the 5th training, and after the therapy. It was observed that after the end of the therapy, the average bioelectrical potential increased by 1.1 µV compared with the baseline in group A. It can be suggested that the sonofeedback method is comparatively effective in reducing symptoms that are associated with urinary incontinence as an electrostimulation method with biofeedback training.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189424/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in Wearable Technologies for the In-Field Assessment of Biomechanical Risk.","authors":"Micaela Porta, Massimiliano Pau","doi":"10.3390/bioengineering12060632","DOIUrl":"10.3390/bioengineering12060632","url":null,"abstract":"<p><p>The exceptional improvements that have characterized the technology of wearable devices for biomedical applications in recent decades have made it possible for researchers and practitioners to provide advanced solutions for the assessment of biomechanical and physiological variables in the present day, exploiting miniaturized, lightweight, and low-power-consumption devices at affordable costs [...].</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large Language Models in Healthcare and Medical Applications: A Review.","authors":"Subhankar Maity, Manob Jyoti Saikia","doi":"10.3390/bioengineering12060631","DOIUrl":"10.3390/bioengineering12060631","url":null,"abstract":"<p><p>This paper provides a systematic and in-depth examination of large language models (LLMs) in the healthcare domain, addressing their significant potential to transform medical practice through advanced natural language processing capabilities. Current implementations demonstrate LLMs' promising applications across clinical decision support, medical education, diagnostics, and patient care, while highlighting critical challenges in privacy, ethical deployment, and factual accuracy that require resolution for responsible integration into healthcare systems. This paper provides a comprehensive understanding of the background of healthcare LLMs, the evolution and architectural foundation, and the multimodal capabilities. Key methodological aspects-such as domain-specific data acquisition, large-scale pre-training, supervised fine-tuning, prompt engineering, and in-context learning-are explored in the context of healthcare use cases. The paper highlights the trends and categorizes prominent application areas in medicine. Additionally, it critically examines the prevailing technical and social challenges of healthcare LLMs, including issues of model bias, interpretability, ethics, governance, fairness, equity, data privacy, and regulatory compliance. The survey concludes with an outlook on emerging research directions and strategic recommendations for the development and deployment of healthcare LLMs.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189880/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Colony Binary Classification Based on Persistent Homology Feature Extraction and Improved EfficientNet.","authors":"Zumin Wang, Ke Yang, Jie Tang, Jun Gao, Yuhao Zhang, Wei Xu, Chun-Ming Huang","doi":"10.3390/bioengineering12060625","DOIUrl":"10.3390/bioengineering12060625","url":null,"abstract":"<p><p>Classifying newly formed colonies is instrumental in uncovering sources of infection and enabling precision medicine, holding significant clinical value. However, due to the ambiguous features of early-stage colony images in culture dishes, conventional computer vision (CV) classification algorithms are often ineffective. To achieve accurate and efficient colony classification, this paper proposes a high-precision method based on Persistent Homology (PH) and an improved EfficientNet. Specifically, (1) a PH feature extraction algorithm is applied to Candida albicans (CA) and Staphylococcus epidermidis (SE) colonies cultured for 18 h in Petri dishes to capture their topological information. (2) The Mobile Inverted Bottleneck Convolution (MBConv) module in EfficientNet is modified, enhancing the attention mechanism to better handle local small targets. (3) A novel self-attention mechanism named the Spatial and Contextual Transformer (SCoT), which is introduced to process information at multiple scales, increasing the resolution in orthogonal directions of the image and the aggregation capability of feature maps. The proposed approach achieves a high accuracy of 98.64%, a 10.29% improvement over the original classification model. The research findings indicate that this method can effectively classify colonies with high efficiency.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190165/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active and Inactive Tuberculosis Classification Using Convolutional Neural Networks with MLP-Mixer.","authors":"Beanbonyka Rim, Hyeonung Jang, Hongchang Lee, Wangsu Jeon","doi":"10.3390/bioengineering12060630","DOIUrl":"10.3390/bioengineering12060630","url":null,"abstract":"<p><p>Early detection of tuberculosis plays a critical role in effective treatment management. Like active tuberculosis, early identification of inactive forms such as latent or healed tuberculosis is essential to prevent future reactivation. In this study, we developed a deep-learning-based binary classification model to distinguish between active and inactive tuberculosis cases. Our model architecture incorporated an EfficientNet backbone with an MLP-Mixer classification head and was fine-tuned on a dataset annotated by Cheonan Soonchunhyang Hospital. To enhance predictive performance, we applied transfer learning using weights pre-trained on the JFT-300M dataset via the Noisy Student training method. Unlike conventional models, our approach achieved competitive results, with an accuracy of 96.3%, a sensitivity of 95.9%, and a specificity of 96.6% on the test set. These promising outcomes suggest that our model could serve as a valuable asset to support clinical decision-making and streamline early screening workflows for latent tuberculosis.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189041/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing MRI Scheduling in High-Complexity Hospitals: A Digital Twin and Reinforcement Learning Approach.","authors":"Fabián Silva-Aravena, Jenny Morales, Manoj Jayabalan, Paula Sáez","doi":"10.3390/bioengineering12060626","DOIUrl":"10.3390/bioengineering12060626","url":null,"abstract":"<p><p>Magnetic Resonance Imaging (MRI) services in high-complexity hospitals often suffer from operational inefficiencies, including suboptimal MRI machine utilization, prolonged patient waiting times, and inequitable service delivery across clinical priority levels. Addressing these challenges requires intelligent scheduling strategies capable of dynamically managing patient waitlists based on clinical urgency while optimizing resource allocation. In this study, we propose a novel framework that integrates a digital twin (DT) of the MRI operational environment with a reinforcement learning (RL) agent trained via Deep Q-Networks (DQN). The digital twin simulates realistic hospital dynamics using parameters extracted from a MRI publicly available dataset, modeling patient arrivals, examination durations, MRI machine reliability, and clinical priority stratifications. Our strategy learns policies that maximize MRI machine utilization, minimize average waiting times, and ensure fairness by prioritizing urgent cases in the patient waitlist. Our approach outperforms traditional baselines, achieving a 14.5% increase in MRI machine utilization, a 44.8% reduction in average patient waiting time, and substantial improvements in priority-weighted fairness compared to First-Come-First-Served (FCFS) and static priority heuristics. Our strategy is designed to support hospital deployment, offering scalability, adaptability to dynamic operational conditions, and seamless integration with existing healthcare information systems. By advancing the use of digital twins and reinforcement learning in healthcare operations, our work provides a promising pathway toward optimizing MRI services, improving patient satisfaction, and enhancing clinical outcomes in complex hospital environments.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189641/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Aerosol Containment Performance of a Negative Pressure Hood with an Aerodynamic Cap Design: Multi-Method Validation Using CFD, PAO Particles, and Microbial Testing.","authors":"Seungcheol Ko, Kisub Sung, Min Jae Oh, Yoonjic Kim, Min Ji Kim, Jung Woo Lee, Yoo Seok Park, Yong Hyun Kim, Ju Young Hong, Joon Sang Lee","doi":"10.3390/bioengineering12060624","DOIUrl":"10.3390/bioengineering12060624","url":null,"abstract":"<p><p>Healthcare providers performing aerosol-generating procedures (AGPs) face significant infection risks, emphasizing the critical need for effective aerosol containment systems. In this study, we developed and validated a negative pressure chamber enhanced with an innovative aerodynamic cap structure designed to optimize aerosol containment. Initially, computational fluid dynamics (CFD) simulations were performed to evaluate multiple structural improvement ideas, including air curtains, bidirectional suction, and aerodynamic cap structures. Among these, the aerodynamic cap was selected due to its superior predicted containment performance, practical feasibility, and cost-effectiveness. The CFD analyses employed realistic transient boundary conditions, precise turbulence modeling using the shear stress transport (SST) k-ω model, and detailed droplet evaporation dynamics under realistic humidity conditions. A full-scale prototype incorporating the selected aerodynamic cap was fabricated and evaluated using physical polyalphaolefin (PAO) particle leakage tests and biological aerosol validation with aerosolized <i>Bacillus subtilis</i>. For the physical leakage tests, the chamber opening was divided into nine sections, and the aerosol dispersion was tested in three distinct directions: ceiling-directed, toward the suction hole, and opposite the suction hole. These tests demonstrated significantly stabilized airflow and substantial reductions in aerosol leakage, consistently maintaining containment levels below the critical threshold of 0.3%, especially under transient coughing conditions. The biological aerosol experiments, conducted in a simulated emergency department environment, involved aerosolizing bacteria continuously for one hour. The results confirmed the effectiveness of the aerodynamic cap structure in achieving at least a one millionth (10^-6) reduction in the aerosolized bacterial leakage compared to the control conditions. These findings highlight the importance and effectiveness of advanced CFD modeling methodologies in accurately predicting aerosol dispersion and improving containment strategies. Although further studies assessing the structural durability, long-term operational ease, and effectiveness against pathogenic microorganisms are required, the aerodynamic cap structure presents a promising, clinically practical infection control solution for widespread implementation during aerosol-generating medical procedures.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189663/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functionally Isolated Sarcoplasmic Reticulum in Cardiomyocytes: Experimental and Mathematical Models.","authors":"Diogo C Soriano, Rosana A Bassani, José W M Bassani","doi":"10.3390/bioengineering12060627","DOIUrl":"10.3390/bioengineering12060627","url":null,"abstract":"<p><p>The interaction among the various Ca²⁺ transporters complicates the assessment of isolated systems in an intact cell. This article proposes the functionally isolated SR model (FISRM), a hybrid (experimental and mathematical) approach to study Ca²⁺ cycling between the cytosol and the sarcoplasmic reticulum (SR), the main source of Ca²⁺ for contraction in mammalian cardiomyocytes. In FISRM, the main transmembrane Ca²⁺ transport pathways are eliminated by using a Na⁺, Ca²⁺-free extracellular medium, and SR Ca²⁺ release is elicited by a train of brief caffeine pulses. Two compounds that exert opposite effects on the SR Ca²⁺ uptake were characterized by this approach in isolated rat ventricular cardiomyocytes. The experimental FISRM was simulated with a simple mathematical model of Ca²⁺ fluxes across the SR membrane, based on a previous model adapted to the present conditions. To a fair extent, the theoretical model could reproduce the experimental results, and confirm the main assumption of the experimental model: that the only relevant Ca²⁺ fluxes occur across the SR membrane. Thus, the FISRM seems to be a valuable framework to investigate the SR Ca²⁺ transport in intact cardiomyocytes under physiological and pathophysiological conditions, and to test therapeutic approaches targeting SR proteins.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}