Annals of Biomedical Engineering最新文献

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StrokeENDPredictor-19: Setting New Prediction Model in Neurological Prognosis in Acute Ischemic Stroke. StrokeENDPredictor-19:建立急性缺血性脑卒中神经预后预测新模型。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-23 DOI: 10.1007/s10439-025-03838-4
Lingli Li, Hongxiao Li, Miaowen Jiang, Jing Fang, Ning Ma, Jianzhuo Yan, Chen Zhou
{"title":"StrokeENDPredictor-19: Setting New Prediction Model in Neurological Prognosis in Acute Ischemic Stroke.","authors":"Lingli Li, Hongxiao Li, Miaowen Jiang, Jing Fang, Ning Ma, Jianzhuo Yan, Chen Zhou","doi":"10.1007/s10439-025-03838-4","DOIUrl":"https://doi.org/10.1007/s10439-025-03838-4","url":null,"abstract":"<p><strong>Background and purpose: </strong>Early Neurological Deterioration (END) following intravenous thrombolysis (IVT) highlights potential risks in current management strategies for acute ischemic stroke. Early identification of at-risk patients could enhance treatment efficacy. This study aims to develop an advanced AI predictive model that improves accuracy in forecasting END while ensuring interpretability for clinical application.</p><p><strong>Methods: </strong>This prospective cohort study included 970 patients with acute ischemic stroke who underwent IVT. Data from 365 patients were used for model development and internal validation, while data from 605 patients were utilized for external validation. Five machine learning models were developed and compared using evaluation metrics such as accuracy and AUC. Feature selection and model optimization were performed using the XGBoost algorithm and SHapley Additive exPlanations (SHAP) method, resulting in the StrokeENDPredictor-19 model.</p><p><strong>Results: </strong>Among the five models, XGBoost demonstrated superior performance with an internal validation accuracy of 91% (AUC = 0.96) and external validation accuracy of 90% (AUC = 0.95). Notably, this study established cutoff values for critical clinical features, providing quantifiable reference standards for practical applications.</p><p><strong>Conclusion: </strong>The StrokeENDPredictor-19 model offers neurologists a valuable tool for forecasting the likelihood of END in patients receiving IVT therapy, thereby supporting more precise clinical decision-making.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Prediction of Clinically Significant Improvements During the Interdisciplinary Intensive Outpatient Program for Traumatic Brain Injury Using Machine Learning. 使用机器学习预测创伤性脑损伤跨学科强化门诊项目的临床显著改善。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-23 DOI: 10.1007/s10439-025-03853-5
Rujirutana Srikanchana, David Samuel, Jacob Powell, Treven Pickett, Thomas DeGraba, Chandler Sours Rhodes
{"title":"Prediction of Clinically Significant Improvements During the Interdisciplinary Intensive Outpatient Program for Traumatic Brain Injury Using Machine Learning.","authors":"Rujirutana Srikanchana, David Samuel, Jacob Powell, Treven Pickett, Thomas DeGraba, Chandler Sours Rhodes","doi":"10.1007/s10439-025-03853-5","DOIUrl":"https://doi.org/10.1007/s10439-025-03853-5","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this research was to assess the potential for machine learning to predict clinically significant patient improvement during a four-week interdisciplinary Intensive Outpatient Program (IOP) for traumatic brain injury (TBI) at the National Intrepid Center of Excellence (NICoE).</p><p><strong>Methods: </strong>Assessment of brain injury characterization and outcomes were measured in 790 active duty service members at the NICoE, Walter Reed National Military Medical Center Bethesda Maryland. Demographic and self-reported measures of posttraumatic stress, depression, anxiety, post-concussion symptoms, and sleep were assessed upon admission. Total scores and symptom cluster scores for self-report measures were calculated. Clinically significant improvement from pre- to post NICoE IOP was operationally defined as clinically significant changes in posttraumatic stress and post-concussion symptoms. Two datasets were created: one including demographics and total scores on self-report measures and one including demographics, total scores, and symptom cluster scores for relevant self-report measures. Extreme gradient boosting (XGBoost) models were trained to predict group identification (clinically significant improvement vs. not significant improvement), where a binary logistic objective function is used to minimize the log loss between the predicted probabilities. Model performance and feature ranking were then evaluated on test datasets.</p><p><strong>Results: </strong>The performance and feature importance of two models to predict group identification were evaluated, where the model including only demographics and total self-report measures performed with an AUC of 75% with the accuracy of 68%, compared to the model incorporating demographics and symptom cluster measures improved the AUC to 79% with 72% accuracy. The top five features contributing to the model with symptom clusters included the posttraumatic stress arousal, avoidance, and reexperiencing sub-scores, education, and postconcussive symptoms cognitive sub-score.</p><p><strong>Conclusion: </strong>Utilization of the XGBoost models demonstrated acceptable discrimination for determining key factors associated with clinically significant improvement for SMs following participation in an interdisciplinary IOP using demographics and self-report measures. Severity of posttraumatic stress symptoms upon admission was the greatest predictors of clinically significant improvement in this model of care. Incorporating ML algorithms into clinical care is a precision medicine approach that may accurately predict treatment efficacy leading to improved healthcare resource allocation and patient outcomes.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Innovative Approaches in Microtia Treatment: Advancements in Tissue Engineering and Scaffold Design. 微创治疗的创新方法:组织工程和支架设计的进展。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-23 DOI: 10.1007/s10439-025-03851-7
Jael Adrián Vergara-Lope Núñez, Juan Moisés Ocampo-Godínez, Febe Carolina Vàzquez-Vàzquez, Armando Apellaniz-Campo, Edgar Oliver Lopez Villegas, Marco Antonio Álvarez-Pérez
{"title":"Innovative Approaches in Microtia Treatment: Advancements in Tissue Engineering and Scaffold Design.","authors":"Jael Adrián Vergara-Lope Núñez, Juan Moisés Ocampo-Godínez, Febe Carolina Vàzquez-Vàzquez, Armando Apellaniz-Campo, Edgar Oliver Lopez Villegas, Marco Antonio Álvarez-Pérez","doi":"10.1007/s10439-025-03851-7","DOIUrl":"https://doi.org/10.1007/s10439-025-03851-7","url":null,"abstract":"<p><p>Facial symmetry is paramount in societal perceptions of attractiveness, with symmetric faces receiving higher ratings. This is particularly relevant for individuals with microtia, a congenital condition affecting external ear formation, who often experience psychosocial challenges such as anxiety and depression. Auricular prostheses and High-density porous polyethylene (MEDPOR<sup>®</sup>) offer an aesthetic solution. However, they are related to disadvantages like color mismatches, periodic replacement, and skin infections. Currently, the Nagata technique, regarded as the \"gold standard\" for microtia treatment, involves a two-step surgical procedure using autologous rib cartilage to reconstruct the auricle. Despite its widespread use, this method is highly invasive and associated with significant risks, including chronic pain, skin necrosis, and variable aesthetic outcomes dependent on the surgeon's skill. Tissue engineering presents a novel approach to microtia treatment, focusing on three core principles: creating a temporary scaffold for cellular support, selecting appropriate cells for seeding, and optimizing the regeneration process through molecular enhancements. This review discusses a novel perspective for microtia treatment with innovative methodologies that seek to improve aesthetic and functional outcomes, mainly through advancements in tissue engineering and scaffold fabrication techniques.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Dual-Camera Markerless Motion Capture System for Precise Lower-Limb Kinematic Analysis in Osteoarthritis. 用于骨关节炎下肢精确运动分析的双摄像头无标记运动捕捉系统。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-22 DOI: 10.1007/s10439-025-03859-z
Bo Hu, Junqing Wang, Wei Xu, Tengfei Li, Yong Nie, Kang Li
{"title":"Dual-Camera Markerless Motion Capture System for Precise Lower-Limb Kinematic Analysis in Osteoarthritis.","authors":"Bo Hu, Junqing Wang, Wei Xu, Tengfei Li, Yong Nie, Kang Li","doi":"10.1007/s10439-025-03859-z","DOIUrl":"https://doi.org/10.1007/s10439-025-03859-z","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to develop a dual-camera markerless system based on data from patients with osteoarthritis (OA) and validate its agreement with a marker-based motion capture system for measuring lower-limb kinematics.</p><p><strong>Methods: </strong>A total of 152 OA patients were divided into a training set (n = 120) and a test set (n = 32). Kinematic data during gait were collected simultaneously via both markerless and marker-based systems. The dual-camera markerless system consists of a 2D pose extractor based on a neural network and 3D triangulation, and the kinematic differences between the two systems were evaluated via the root mean square distance (RMSD) and root mean square error (RMSE) and intraclass correlation coefficient (ICC).</p><p><strong>Results: </strong>The markerless system demonstrated great performance, achieving a grand mean RMSD of 11.0 mm and an ICC of 0.95 for keypoints. Joint angle analysis revealed a mean RMSE of 4.25°, with ICC values for joint angle waveforms reaching 0.90 in the sagittal plane, 0.48 in the frontal plane, and 0.24 in the transverse plane compared with the marker-based system.</p><p><strong>Conclusion: </strong>These results indicate that the dual-camera markerless system provides accurate lower-limb kinematic measurements for patient populations while offering significant advantages in terms of cost-effectiveness, installation simplicity, and reduced operational expertise requirements, facilitating efficient biomechanical assessment in clinical use.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145111764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A CNN Autoencoder for Learning Latent Disc Geometry from Segmented Lumbar Spine MRI. 一种CNN自编码器用于学习分段腰椎MRI的潜在椎间盘几何。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-22 DOI: 10.1007/s10439-025-03840-w
Mattia Perrone, D'Mar M Moore, Daisuke Ukeba, John T Martin
{"title":"A CNN Autoencoder for Learning Latent Disc Geometry from Segmented Lumbar Spine MRI.","authors":"Mattia Perrone, D'Mar M Moore, Daisuke Ukeba, John T Martin","doi":"10.1007/s10439-025-03840-w","DOIUrl":"10.1007/s10439-025-03840-w","url":null,"abstract":"<p><strong>Purpose: </strong>Low back pain is the world's leading cause of disability and pathology of the lumbar intervertebral discs is frequently considered a driver of pain. The geometric characteristics of intervertebral discs offer valuable insights into their mechanical behavior and pathological conditions. In this study, we present a convolutional neural network (CNN) autoencoder to extract latent features from segmented disc MRI. Additionally, we interpret these latent features and demonstrate their utility in identifying disc pathology, providing a complementary perspective to standard geometric measures.</p><p><strong>Methods: </strong>We examined 195 sagittal T1-weighted MRI of the lumbar spine from a publicly available multi-institutional dataset. The proposed pipeline includes five main steps: (1) segmenting MRI, (2) training the CNN autoencoder and extracting latent geometric features, (3) measuring standard geometric features, (4) predicting disc narrowing with latent and/or standard geometric features and (5) determining the relationship between latent and standard geometric features.</p><p><strong>Results: </strong>Our segmentation model achieved an intersection over union (IoU) of 0.82 (95% CI 0.80-0.84) and dice similarity coefficient (DSC) of 0.90 (95% CI 0.89-0.91). The minimum bottleneck size for which the CNN autoencoder converged was 4 × 1 after 350 epochs (IoU of 0.9984-95% CI 0.9979-0.9989). Combining latent and geometric features improved predictions of disc narrowing compared to use either feature set alone. Latent geometric features encoded for disc shape and angular orientation.</p><p><strong>Conclusions: </strong>This study presents a CNN autoencoder to extract latent features from segmented lumbar disc MRI, enhancing disc narrowing prediction and feature interpretability. Future work will integrate disc voxel intensity to analyze composition.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Rotator Cuff Tear-induced Changes in Tendon Structure and Mechanics Measured by Quantitative Magnetic Resonance Imaging. 定量磁共振成像测量肩袖撕裂引起的肌腱结构和力学变化。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-20 DOI: 10.1007/s10439-025-03849-1
Mason J Garcia, Giovanni Intermesoli, Alberto Lalli, Gabriel Landi, Dev R Mehrotra, Erik E Ersland, Arun J Ramappa, Joseph P DeAngelis, Aaron Grant, Michael B Albro, Umile Giuseppe Longo, Ara Nazarian
{"title":"Rotator Cuff Tear-induced Changes in Tendon Structure and Mechanics Measured by Quantitative Magnetic Resonance Imaging.","authors":"Mason J Garcia, Giovanni Intermesoli, Alberto Lalli, Gabriel Landi, Dev R Mehrotra, Erik E Ersland, Arun J Ramappa, Joseph P DeAngelis, Aaron Grant, Michael B Albro, Umile Giuseppe Longo, Ara Nazarian","doi":"10.1007/s10439-025-03849-1","DOIUrl":"https://doi.org/10.1007/s10439-025-03849-1","url":null,"abstract":"<p><strong>Introduction: </strong>Rotator cuff (RC) tears are prevalent degenerative injuries associated with progressive loss of shoulder function. Although MRI is routinely used for diagnosing RC tears, the relationship between imaging biomarkers and tendon mechanical function remains poorly understood. This study investigates whether quantitative MRI (qMRI), particularly T2 relaxation time, reflects structural and mechanical changes in supraspinatus tendons with RC tears.</p><p><strong>Methods: </strong>Twenty-four human cadaveric supraspinatus tendons (10 intact, 14 torn) were analyzed. Mechanical testing was performed to assess structural and material properties. T2 mapping using a 9.4T MRI scanner was employed to determine relaxation times. Raman spectroscopy and multiphoton imaging were used to assess biochemical composition and collagen organization.</p><p><strong>Results: </strong>Torn tendons showed significantly reduced stiffness (p = 0.035) and failure force (p = 0.015) compared to intact tendons. T2 relaxation times were significantly elevated in the torn group (23.7 ± 3.5 ms vs. 20.6 ± 3.3 ms; p = 0.035), with higher heterogeneity and 90th percentile values. T2 metrics correlated strongly with mechanical properties (stiffness: r<sub>s</sub> = - 0.84, p = 0.002; failure force: r<sub>s</sub> = - 0.86, p = 0.002) and tear area (r<sub>s</sub> = - 0.79, p = 0.004). Raman spectroscopy showed reduced proline and hydroxyproline spectral biomarkers in torn tendons (p < 0.02), which correlated with mechanical weakening. Multiphoton imaging revealed significant collagen disorganization and damage in torn tendons.</p><p><strong>Discussion: </strong>This study demonstrates that T2 relaxation time is a sensitive non-invasive biomarker of tendon mechanical health and collagen structure in RC tears. These findings support the clinical utility of qMRI in assessing tendon pathology and guiding treatment strategies.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Determination of Patient-Specific Blood Coagulation Kinetic Parameters via Neural Networks: Toward Thrombosis Prediction in Personalized Medicine. 通过神经网络确定患者特异性凝血动力学参数:用于个体化医疗血栓预测。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-18 DOI: 10.1007/s10439-025-03837-5
Mohamad Al Bannoud, Tiago Dias Martins, Silmara Aparecida de Lima Montalvão, Joyce Maria Annichino-Bizzacchi, Rubens Maciel Filho, Maria Regina Wolf Maciel
{"title":"Determination of Patient-Specific Blood Coagulation Kinetic Parameters via Neural Networks: Toward Thrombosis Prediction in Personalized Medicine.","authors":"Mohamad Al Bannoud, Tiago Dias Martins, Silmara Aparecida de Lima Montalvão, Joyce Maria Annichino-Bizzacchi, Rubens Maciel Filho, Maria Regina Wolf Maciel","doi":"10.1007/s10439-025-03837-5","DOIUrl":"https://doi.org/10.1007/s10439-025-03837-5","url":null,"abstract":"<p><strong>Purpose: </strong>The solution of the system of equations that model the coagulation cascade enables the determination of thrombin production, which is related to blood clot formation and thrombosis. However, traditional models often overlook clinical and hematological variables due to modeling challenges or incomplete understanding. Mathematical models of blood coagulation cascade are typically generalist, presenting limited accuracy. This study aimed to incorporate patient-specific and hematological data into the kinetic parameters of the coagulation cascade to generate individualized thrombin curves and predict the recurrence of venous thromboembolism.</p><p><strong>Methods: </strong>A sensitivity analysis identified the most influential kinetic parameters for thrombin production. These parameters were adjusted using a model hybrid combining an artificial neural network with a system of ordinary differential equations optimized via a genetic algorithm. The dataset is split into two subsets to prevent data leakage.</p><p><strong>Results: </strong>Eight kinetic rates were identified as the most sensitive, particularly those related to factor V activation and thrombin-antithrombin III complex formation. Factors such as anticoagulant use, smoking, pulmonary embolism, and factor V Leiden mutation significantly impacted the kinetic parameters. The model presented an AUC of 0.9941 and an accuracy of 0.9872.</p><p><strong>Conclusion: </strong>The influence of these input variables on the kinetic parameters and thrombin production aligned with their known effects as risk factors reported in the literature. Adjusting the kinetic parameters individualized the model response, providing a clear cutoff point for thrombosis classification based on thrombin production. With further validation, this model could assist in diagnosing and prognosticating thrombosis and identifying new therapeutic targets to regulate thrombin production.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Correction: Locally Reprogramming Tumor-Associated Macrophages with Cytokine-Loaded Injectable Cryogels for Breast Cancer. 校正:局部重编程肿瘤相关巨噬细胞与装载细胞因子的可注射冷冻细胞用于乳腺癌。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-17 DOI: 10.1007/s10439-025-03844-6
Sydney R Henriques, Evan B Glass, Kristen L Hoek, Ori Z Chalom, Abigail E Manning, Sohini Roy, Diana K Graves, Sarah M Goldstein, Benjamin C Hacker, Renjie Jin, Marjan Rafat, Paula J Hurley, Laura C Kennedy, Young J Kim, Andrew J Wilson, Fiona E Yull, Todd D Giorgio
{"title":"Correction: Locally Reprogramming Tumor-Associated Macrophages with Cytokine-Loaded Injectable Cryogels for Breast Cancer.","authors":"Sydney R Henriques, Evan B Glass, Kristen L Hoek, Ori Z Chalom, Abigail E Manning, Sohini Roy, Diana K Graves, Sarah M Goldstein, Benjamin C Hacker, Renjie Jin, Marjan Rafat, Paula J Hurley, Laura C Kennedy, Young J Kim, Andrew J Wilson, Fiona E Yull, Todd D Giorgio","doi":"10.1007/s10439-025-03844-6","DOIUrl":"https://doi.org/10.1007/s10439-025-03844-6","url":null,"abstract":"","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Cholesterol Depletion with U18666A and Methyl-β Cyclodextrin Increased Small Molecule Permeability Across Brain Microvascular Endothelial Cells. U18666A和甲基β环糊精降低胆固醇可增加脑微血管内皮细胞的小分子通透性。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-17 DOI: 10.1007/s10439-025-03841-9
Bilal Moiz, Viviana Alpizar Vargas, Ken D Brandon, Gurneet Sangha, Callie Weber, Andrew Li, Tristan Pepper, Matthew Walls, Anthony Qin, Sara Hart, Cristin Davidson, Kimberly Stroka, Forbes D Porter, Alisa Morss Clyne
{"title":"Cholesterol Depletion with U18666A and Methyl-β Cyclodextrin Increased Small Molecule Permeability Across Brain Microvascular Endothelial Cells.","authors":"Bilal Moiz, Viviana Alpizar Vargas, Ken D Brandon, Gurneet Sangha, Callie Weber, Andrew Li, Tristan Pepper, Matthew Walls, Anthony Qin, Sara Hart, Cristin Davidson, Kimberly Stroka, Forbes D Porter, Alisa Morss Clyne","doi":"10.1007/s10439-025-03841-9","DOIUrl":"https://doi.org/10.1007/s10439-025-03841-9","url":null,"abstract":"<p><p>Cholesterol is a vital component of the cell membrane and plays an essential role in mediating integral membrane protein function. Altered cholesterol regulation has been implicated in neurological diseases that are associated with blood-brain barrier breakdown. However, the role of brain barrier function in inherited disorders of cholesterol metabolism, such as Niemann-Pick disease C1 (NP-C1), remains unclear. In this study, we determined how cholesterol depletion with U18666A, a chemical inhibitor of NPC1 protein, as well as with the cholesterol-depleting agent methyl-β cyclodextrin (MβCD), impacted brain endothelial cell barrier function. We hypothesized that cholesterol depletion would decrease barrier integrity by disrupting tight junction protein continuity. To test this hypothesis, we differentiated human-induced pluripotent stem cells into brain microvascular endothelial cells (hiBMECs). We then assessed barrier integrity by quantifying trans-endothelial electrical resistance (TEER), small fluorescent molecule permeability, and tight junction continuity and protein levels. We now show that U18666A-treated hiBMECs demonstrated a 75% decrease in TEER and 9-fold increase in sodium fluorescein permeability. Similar trends were observed for hiBMECs treated with MβCD, which showed significantly lowered TEER (93% decrease) and increased sodium fluorescein permeability (20-fold higher). We also observed decreased continuity of the tight junction proteins occludin (13% lower) and claudin-5 (8% lower) as well as a 53% decrease in claudin-5 protein with U18666A treatment. Co-treating U18666A-treated hiBMECs with hydroxypropyl-β cyclodextrin (HPβCD), which releases lysosomal cholesterol, prevented these changes. Together, our results demonstrate that cholesterol is vital for hiBMEC barrier function and tight junction continuity. This study highlights the potential of therapeutics targeted to brain endothelium in NP-C1 and other cholesterol metabolism disorders.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ChatGPT in Nursing: Applications, Advantages, and Challenges in Education, Research, and Clinical Practice. ChatGPT在护理中的应用:教育、研究和临床实践中的应用、优势和挑战。
IF 5.4 2区 医学
Annals of Biomedical Engineering Pub Date : 2025-09-09 DOI: 10.1007/s10439-025-03832-w
Abdullah Gerçek, Necmettin Çiftci, Mustafa Durmuş, Abdullah Sarman, Ömer Taşcı, Metin Yıldız
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