Current Opinion in Biomedical Engineering最新文献

英文中文

Recent advances in facilitating the translation of bioelectronic medicine therapies 促进生物电子医学疗法翻译的最新进展。

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2025-03-01 Epub Date: 2024-12-20 DOI: 10.1016/j.cobme.2024.100575

Alex Baldwin , Gregory States , Victor Pikov , Pallavi Gunalan , Sahar Elyahoodayan , Kevin Kilgore , Ellis Meng

Bioelectronic medicine is a growing field which involves directly interfacing with the vagus, sacral, enteric, and other autonomic nerves to treat conditions. Therapies based on bioelectronic medicine could address previously intractable diseases and provide an alternative to pharmaceuticals. However, translating a bioelectronic medicine therapy to the clinic requires overcoming several challenges, including titrating stimulation parameters to an individual's physiology, selectively stimulating target nerves without inducing off-target activation or block, and improving accessibility to clinically approved devices. This review describes recent progress towards solving these problems, including advances in mapping and characterizing the human autonomic nervous system, new sensor technology and signal processing techniques to enable closed-loop therapies, new methods for selectively stimulating autonomic nerves without inducing off-target effects, and efforts to develop open-source implantable devices. Recent commercial successes in bringing bioelectronic medicine therapies to the clinic are highlighted showing how addressing these challenges can lead to novel therapies.

生物电子医学是一个正在发展的领域，它涉及直接与迷走神经、骶神经、肠神经和其他自主神经相结合来治疗疾病。基于生物电子医学的治疗方法可以解决以前难以治愈的疾病，并提供药物的替代方案。然而，将生物电子医学疗法转化为临床需要克服几个挑战，包括根据个体生理学滴定刺激参数，有选择地刺激目标神经而不引起脱靶激活或阻滞，以及提高临床批准设备的可及性。本文介绍了解决这些问题的最新进展，包括绘制和表征人类自主神经系统的进展，实现闭环治疗的新传感器技术和信号处理技术，选择性刺激自主神经而不引起脱靶效应的新方法，以及开发开源植入式设备的努力。最近在将生物电子医学疗法引入临床方面的商业成功突出显示了如何解决这些挑战可以导致新的疗法。

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引用次数: 0

Beyond static models: Mechanically dynamic matrices reveal new insights into cancer and fibrosis progression 超越静态模型：机械动态矩阵揭示了癌症和纤维化进展的新见解

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2025-03-01 Epub Date: 2024-11-29 DOI: 10.1016/j.cobme.2024.100570

M. Walker , D. Gourdon , M. Cantini

The dynamic mechanical nature of extracellular matrices (ECMs) is crucial for the mechanosensitive regulation of cell fate. This is evident in pathological conditions such as cancer and fibrosis, which are characterised by highly fibrotic tissue developing over time. This fibrotic progression not only alters tissue mechanics, but also coincides with the reprogramming of resident cells, promoting their differentiation into aberrant phenotypes and increasing drug resistance. Hydrogels, with their tuneable mechanical and biochemical properties, emerge as powerful ECM mimetics to model and study these abnormal, mechanically-driven cell differentiation phenomena. In this review, after establishing how conventional, mechanically static hydrogels contribute to our understanding of the role of altered mechanosensing in cell differentiation during cancer and fibrosis, we explore the research opportunities given by advanced dynamic matrices. Models employing hydrogels that are fast relaxing, plastic or even with temporally switchable mechanics reveal the otherwise hidden role of time-dependent phenomena during disease development.

细胞外基质（ecm）的动态力学性质对细胞命运的机械敏感调节至关重要。这在癌症和纤维化等病理条件下是明显的，其特征是随着时间的推移高度纤维化组织的发展。这种纤维化进展不仅改变了组织力学，而且与常驻细胞的重编程相吻合，促进其分化为异常表型并增加耐药性。水凝胶具有可调节的机械和生化特性，成为强大的ECM模拟物，可以模拟和研究这些异常的、机械驱动的细胞分化现象。在这篇综述中，在确定了传统的机械静态水凝胶如何有助于我们理解在癌症和纤维化期间改变的机械传感在细胞分化中的作用之后，我们探索了先进的动态基质提供的研究机会。采用快速放松、可塑或甚至具有时间可切换力学的水凝胶的模型揭示了疾病发展过程中时间依赖现象的隐藏作用。

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引用次数: 0

What lies beyond—Insights into elastic microscaffolds with metamaterial properties for cell studies 什么是超越-洞察弹性微支架与超材料性质的细胞研究

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2025-03-01 Epub Date: 2024-11-22 DOI: 10.1016/j.cobme.2024.100568

Magdalena Fladung , Alexander Berkes , Tim Alletzhaeusser , Yi Chen , Natalie Munding , Motomu Tanaka , Martin Wegener , Martin Bastmeyer

Recent advances in additive manufacturing have opened up new possibilities to print almost arbitrary structures with submicrometer resolution. An intriguing application is the fabrication of metamaterial-based scaffolds with unprecedented precision and with defined effective elastic properties for mechanobiological research. This field of study has already led to promising results but remains wide open. The vast possibilities, together with the high interdisciplinary character and current lack of established protocols or literature on the subject, are intriguing on the one hand but might discourage researchers who are new to this field. In this review, we aim to provide insights into the work with such microstructured bio-metamaterials, mainly based on our own experience with 2D systems, hoping to encourage further mechanobiological studies. Finally, we present some considerations for expanding to the third dimension to more closely resemble the in vivo situation.

增材制造的最新进展开辟了以亚微米分辨率打印几乎任意结构的新可能性。一个有趣的应用是制造基于超材料的支架，具有前所未有的精度和定义的有效弹性特性，用于机械生物学研究。这一领域的研究已经取得了可喜的成果，但仍处于开放状态。巨大的可能性，加上高度跨学科的特点，以及目前缺乏关于该主题的既定协议或文献，一方面很吸引人，但可能会使这个领域的新研究人员感到沮丧。在这篇综述中，我们的目标是根据我们自己在二维系统上的经验，对这种微结构生物超材料的工作提供见解，希望能鼓励进一步的机械生物学研究。最后，我们提出了扩展到第三维度以更接近于体内情况的一些考虑。

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引用次数: 0

3M engineering approaches to combat high-shear thrombosis: Integrating modeling, microfluidics, and mechanobiology 对抗高剪切血栓形成的3M工程方法：集成建模、微流体和机械生物学

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2025-03-01 Epub Date: 2025-01-08 DOI: 10.1016/j.cobme.2025.100576

Allan Sun , Arian Nasser , Nicole Alexis Yap , Rui Gao , Lining Arnold Ju

Arterial thrombosis remains a significant global health concern, with shear-induced platelet aggregation (SIPA) playing a crucial role. This review focuses on the integration of three key engineering approaches—Computational Modeling Microfluidics and Mechanobiology (3 M)—in understanding and combating high-shear thrombosis. We discuss the biomechanical mechanisms of SIPA, highlighting how platelet mechanoreceptors and von Willebrand factor interactions drive thrombosis under pathological flow conditions. Through computational fluid dynamics (CFD), key hemodynamic metrics including time-averaged wall shear stress, oscillatory shear index, and relative residence time have been developed to predict thrombosis risk. Microfluidic platforms, ranging from straight channels to stenotic geometries, provide insights into platelet behavior under various shear conditions while enabling rapid screening of antithrombotic therapies. The integration of these experimental approaches with CFD analysis offers powerful tools for predicting thrombosis risk and optimizing device designs, particularly in mechanical circulatory support devices (MCSDs). Recent advances in mechanobiology have revealed how mechanical forces trigger cellular responses through membrane damage and mechanosensitive channels, offering new therapeutic targets. This review underscores how the synergy between these 3 M engineering approaches advances our understanding of the complex interplay between hemodynamics and thrombosis, paving the way for improved antithrombotic therapies and medical device designs essential to optimizing MCSDs, such as left ventricular assist devices and extracorporeal membrane oxygenators.

动脉血栓形成仍然是一个重要的全球健康问题，剪切诱导血小板聚集（SIPA）起着至关重要的作用。这篇综述的重点是整合三个关键的工程方法-计算建模微流体和力学生物学(3m) -在理解和对抗高剪切血栓形成。我们讨论了SIPA的生物力学机制，强调血小板机械受体和血管性血友病因子的相互作用如何在病理血流条件下驱动血栓形成。通过计算流体动力学（CFD），开发了包括时间平均壁面剪切应力、振荡剪切指数和相对停留时间在内的关键血流动力学指标来预测血栓形成风险。微流体平台，从直通道到狭窄的几何形状，提供了在各种剪切条件下血小板行为的见解，同时实现了抗血栓治疗的快速筛选。将这些实验方法与CFD分析相结合，为预测血栓形成风险和优化设备设计提供了强大的工具，特别是在机械循环支持设备（mcsd）中。机械生物学的最新进展揭示了机械力如何通过膜损伤和机械敏感通道触发细胞反应，提供了新的治疗靶点。这篇综述强调了这3种M工程方法之间的协同作用如何促进了我们对血流动力学和血栓形成之间复杂相互作用的理解，为改进抗血栓治疗和优化mcsd必不可少的医疗设备设计铺平了道路，如左心室辅助装置和体外膜氧合器。

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引用次数: 0

Analysis of wireless powering modes for nanotransducer-mediated neuromodulation 纳米传感器介导的神经调节无线供电模式分析

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2025-03-01 Epub Date: 2024-11-09 DOI: 10.1016/j.cobme.2024.100562

Prachi Kumari , Aleksandra Milojkovic , Kristen Kozielski

Nanomaterials offer a promising approach for precise and minimally invasive modulation of neural activity versus traditional implants. This review explores recent advances in various nanotransducer systems that are powered by a remotely deliverable carrier signal (optical, mechanical, or magnetic) and output a neuromodulatory signal (optical, thermal, mechanical, or electrical). Key advantages of individual transduction methods have been highlighted, such as penetration to deeper brain regions, and potential for cell-specific targeting with or without genetic modification of the target tissue. Current challenges and advances are discussed in the context of considerations for clinical translation, which include optimizing transduction efficiency, reducing power requirements, and spatiotemporal stimulation control.

与传统植入物相比，纳米材料为精确和微创调节神经活动提供了一种很有前途的方法。本综述探讨了各种纳米换能器系统的最新进展，这些系统由可远程传递的载体信号（光学、机械或磁性）驱动，并输出神经调节信号（光学、热、机械或电）。个体转导方法的主要优势已经被强调，例如渗透到更深的大脑区域，以及有或没有对目标组织进行基因修饰的细胞特异性靶向的潜力。当前的挑战和进展在临床翻译考虑的背景下进行了讨论，包括优化转导效率，降低功率需求和时空刺激控制。

引用次数: 0

Generalizable and explainable deep learning for medical image computing: An overview 医学图像计算的可概括和可解释的深度学习：概述

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2025-03-01 Epub Date: 2024-11-14 DOI: 10.1016/j.cobme.2024.100567

Ahmad Chaddad , Yan Hu , Yihang Wu , Binbin Wen , Reem Kateb

Objective

This paper presents an overview of generalizable and explainable artificial intelligence (XAI) in deep learning (DL) for medical imaging, with the aim of addressing the urgent need for transparency and explainability in clinical applications.

Methodology

We propose to use four CNNs in three medical datasets (brain tumor, skin cancer, and chest x-ray) for medical image classification tasks. Furthermore, we combine ResNet50 with five common XAI techniques to obtain explainable results for model prediction, in order to improve model transparency. We also involve a quantitative metric (confidence increase) to evaluate the usefulness of XAI techniques.

Key findings

The experimental results indicate that ResNet50 can achieve feasible accuracy and F1 score in all datasets (e.g., 86.31 % accuracy in skin cancer). Furthermore, the findings show that while certain XAI methods, such as eXplanation with Gradient-weighted Class activation mapping (XgradCAM), effectively highlight relevant abnormal regions in medical images, others, such as EigenGradCAM, may perform less effectively in specific scenarios. In addition, XgradCAM indicates higher confidence increase (e.g., 0.12 in glioma tumor) compared to GradCAM++ (0.09) and LayerCAM (0.08).

Implications

Based on the experimental results and recent advancements, we outline future research directions to enhance the generalizability of DL models in the field of biomedical imaging.

目的综述了医学影像深度学习（DL）中可推广和可解释的人工智能（XAI），旨在解决临床应用中对透明度和可解释性的迫切需求。我们建议在三个医学数据集（脑肿瘤、皮肤癌和胸部x射线）中使用四个cnn进行医学图像分类任务。此外，我们将ResNet50与五种常见的XAI技术相结合，以获得可解释的模型预测结果，以提高模型透明度。我们还涉及定量度量（置信度增加）来评估XAI技术的有用性。实验结果表明，ResNet50在所有数据集上都能达到可行的准确率和F1评分（例如，在皮肤癌上的准确率为86.31%）。此外，研究结果表明，虽然某些XAI方法，如带有梯度加权类激活映射的解释（XgradCAM），可以有效地突出医学图像中的相关异常区域，但其他方法，如EigenGradCAM，在特定场景下的效果可能不太好。此外，与GradCAM++(0.09)和LayerCAM（0.08）相比，XgradCAM显示更高的置信度增加（如胶质瘤肿瘤为0.12）。基于实验结果和最新进展，我们概述了未来的研究方向，以提高深度学习模型在生物医学成像领域的通用性。

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引用次数: 0

Immune cell and engineering for the therapeutics 免疫细胞和治疗工程

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2025-03-01 Epub Date: 2024-11-25 DOI: 10.1016/j.cobme.2024.100569

Jin Hyuck Jeong , Miseol Kim , Hui-Shan Li

Reprogrammed immune cell therapies show great promise as “living drugs”, a concept successfully demonstrated in clinical settings with engineered chimeric antigen receptor (CAR) T cells. Beyond CAR-T therapies, immune cells possess unique characteristics that can be leveraged to enhance the body's immune response against specific diseases. This review first highlights recent clinical advancements in immune cell therapies, focusing on the use of different immune cell types across various disease settings. It then explores current engineering approaches aimed at addressing the specific challenges in cancer treatment. Additionally, the review examines the role of emerging technologies such as synthetic circuits, CRISPR, and induced pluripotent stem cells (iPSCs) in expanding the potential of immune cell therapies to treat a broad range of conditions.

重编程免疫细胞疗法作为“活的药物”显示出巨大的前景，这是一种利用工程嵌合抗原受体（CAR） T细胞在临床环境中成功证明的概念。除了CAR-T疗法，免疫细胞还具有独特的特性，可以用来增强人体对特定疾病的免疫反应。这篇综述首先强调了免疫细胞疗法的最新临床进展，重点是在各种疾病环境中使用不同的免疫细胞类型。然后探讨了当前的工程方法，旨在解决癌症治疗中的具体挑战。此外，该综述还探讨了合成电路、CRISPR和诱导多能干细胞（iPSCs）等新兴技术在扩大免疫细胞疗法治疗多种疾病的潜力方面的作用。

引用次数: 0

Enhancing resilience against adversarial attacks in medical imaging using advanced feature transformation training 利用高级特征变换训练增强医学成像对对抗性攻击的复原力

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2024-12-01 Epub Date: 2024-10-22 DOI: 10.1016/j.cobme.2024.100561

Danish Vasan , Mohammad Hammoudeh

This study presents a machine learning-driven defense mechanism against adversarial attacks, specifically tailored for medical imaging applications. This mechanism utilizes feature transformation through transfer learning, leveraging a fine-tuned ResNet152V2 network trained on original medical images. To enhance the model's robustness, we apply efficient adversarial training on transformed features extracted from both original and adversarial images. Additionally, we integrate Principal Component Analysis (PCA) to reduce feature dimensionality, optimizing the adversarial training process. When evaluated on Chest X-ray datasets, focusing on pneumonia and normal cases, the proposed mechanism demonstrated strong resilience against imperceptible attacks while maintaining a performance retention rate above 90 %. These results show the potential of the proposed mechanism to enhance the reliability and security of CNN-based medical imaging systems in practical, real-world settings.

本研究提出了一种机器学习驱动的防御机制，专门针对医学影像应用来抵御对抗性攻击。该机制通过迁移学习，利用在原始医学图像上训练的微调 ResNet152V2 网络进行特征转换。为了增强模型的鲁棒性，我们对从原始图像和对抗图像中提取的转换特征进行了有效的对抗训练。此外，我们还整合了主成分分析（PCA）来降低特征维度，从而优化对抗训练过程。在以肺炎和正常病例为重点的胸部 X 光数据集上进行评估时，所提出的机制对不可察觉的攻击表现出了很强的抵御能力，同时保持了 90% 以上的性能保持率。这些结果表明，所提出的机制有潜力在实际的真实世界环境中提高基于 CNN 的医学成像系统的可靠性和安全性。

引用次数: 0

The prospect of electroceutical intervention and its implementation toward intractable neuromuscular diseases 电疗干预的前景及其在难治性神经肌肉疾病中的应用

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2024-12-01 Epub Date: 2024-10-19 DOI: 10.1016/j.cobme.2024.100563

Aseer Intisar , Minseok S. Kim

The treatment of intractable neuromuscular diseases (INMDs) via biochemical interventions has remained challenging. Treatments using electrical stimulation (ES), or electroceuticals, can potentially shift the paradigm in the treatment of INMDs, since (1) their localized nature minimizes the risks for systemic side effects and (2) they conform with the innate neuromuscular communication. In addition, the recent developments in electrical interfaces for the neuromuscular system can advance the possibility of the clinical adoption of electroceuticals. In this review, we first introduce the studies that have explored the potential of ES in the treatment or management of INMDs. We then highlight the recent advancements in interfaces to deliver ES to the neuromuscular system, focusing on their miniaturization, flexibility, and non-invasive implantation. This review sheds light on the therapeutic benefits and implementation of electroceuticals toward INMDs and will hopefully encourage further in-depth research that can transform their treatment landscape.

通过生化干预治疗难治性神经肌肉疾病（INMDs）仍然具有挑战性。使用电刺激（ES）或电药物进行治疗有可能改变治疗 INMDs 的模式，因为（1）电刺激的局部性将全身副作用的风险降至最低，（2）电刺激符合神经肌肉的先天交流。此外，神经肌肉系统电接口的最新发展也为电疗法的临床应用提供了可能。在本综述中，我们首先介绍了探索 ES 在治疗或管理 INMDs 方面潜力的研究。然后，我们着重介绍了将 ES 输送到神经肌肉系统的接口的最新进展，重点关注其微型化、灵活性和无创植入。这篇综述揭示了电疗法对 INMDs 的治疗益处和实施情况，希望能鼓励进一步的深入研究，从而改变其治疗格局。

引用次数: 0

Neuromodulation for the treatment of sexual dysfunction: An opportunity for the field 治疗性功能障碍的神经调节疗法：这一领域的机遇

IF 4.7 3区工程技术 Q2 ENGINEERING, BIOMEDICAL

Current Opinion in Biomedical Engineering

Pub Date : 2024-12-01 Epub Date: 2024-10-24 DOI: 10.1016/j.cobme.2024.100564

Tim M. Bruns , Lauren Zimmerman Hershey

Sexual dysfunction affects a substantial number of women and men. Currently there are no commercially available neuromodulation therapies for sexual dysfunction. Neuromodulation has long been used as a third-line therapy for bladder and bowel dysfunction, with frequent reports of utility for sexual dysfunction. Sacral neuromodulation has a robust literature showing benefits in sexual function for implant recipients. Tibial nerve stimulation (TNS) has seen a recent growth in studies for sexual dysfunction. Transcutaneous TNS provides a lower-barrier neuromodulation approach with potential efficacy for male and female sexual dysfunction. Other neuromodulation approaches, including spinal cord stimulation and dorsal genital nerve stimulation also have potential as therapies for sexual dysfunction. There is a considerable opportunity for one or more neuromodulation therapies to enter an open market space.

性功能障碍影响着大量女性和男性。目前，市场上还没有治疗性功能障碍的神经调节疗法。长期以来，神经调控疗法一直被用作治疗膀胱和肠道功能障碍的三线疗法，经常有报告称这种疗法可用于治疗性功能障碍。有大量文献显示，骶神经调节对植入者的性功能有益。胫神经刺激（TNS）治疗性功能障碍的研究最近有所增加。经皮 TNS 提供了一种屏障较低的神经调控方法，对男性和女性性功能障碍具有潜在疗效。其他神经调节方法，包括脊髓刺激和生殖器背神经刺激，也具有治疗性功能障碍的潜力。一种或多种神经调节疗法有很大的机会进入开放的市场空间。

引用次数: 0

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