Bioengineering最新文献_第6页

Intratumoral Chemotherapy: The Effects of Drug Concentration and Dose Apportioning on Tumor Cell Injury 瘤内化疗：药物浓度和剂量分配对肿瘤细胞损伤的影响

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-09 DOI: 10.3390/bioengineering11080809

J.S. Warner, C. Kinsey, J. Bates, Vitor Mori

The addition of intravenous (i.v.) chemotherapy to i.v. immunotherapy for patients with lung cancer results in improved overall survival but is limited by synergistic side effects and an unknown, highly variable final cytotoxic dose within the tumor. The synergy between i.v. chemo- and immunotherapies is hypothesized to occur as a result of cell injury caused by chemotherapy, a mechanism demonstrated to drive antigen presentation within the tumor microenvironment. Intratumoral delivery of chemotherapy may thus be optimized to maximize tumor cell injury. To assess the balance between the damage versus the death of tumor cells, we developed a computational model of intratumoral dynamics within a lung cancer tumor for three different chemotherapy agents following direct injection as a function of location and number of injection sites. We based the model on the morphology of a lung tumor obtained from a thoracic CT scan. We found no meaningful difference in the extent of tumor cell damage between a centrally injected versus peripherally injected agent, but there were significant differences between a single injection versus when the total dose was apportioned between multiple injection sites. Importantly, we also found that the standard chemotherapeutic concentrations used for intravenous administration were effective at causing cell death but were too high to generate significant cell injury. This suggests that to induce maximal tumor cell injury, the optimal concentration should be several orders of magnitude lower than those typically used for intravenous therapy.

在对肺癌患者进行静脉注射免疫疗法的同时进行静脉注射化疗，可以提高患者的总生存率，但却受到协同副作用和肿瘤内最终细胞毒性剂量未知且变化较大的限制。据推测，静脉化疗与免疫疗法之间的协同作用是化疗造成细胞损伤的结果，而化疗的机制已被证实可推动肿瘤微环境中的抗原呈递。因此，可以优化瘤内化疗给药，使肿瘤细胞损伤最大化。为了评估肿瘤细胞损伤与死亡之间的平衡，我们建立了一个肺癌肿瘤瘤内动力学计算模型，将三种不同化疗药物直接注射后的瘤内动力学作为注射点位置和数量的函数。我们根据胸部 CT 扫描获得的肺部肿瘤形态建立了该模型。我们发现，集中注射与外周注射化疗剂对肿瘤细胞的损伤程度并无明显差异，但单次注射与在多个注射点之间分配总剂量则存在显著差异。重要的是，我们还发现，用于静脉注射的标准化疗浓度能有效导致细胞死亡，但浓度过高则无法产生明显的细胞损伤。这表明，要诱导最大程度的肿瘤细胞损伤，最佳浓度应比通常用于静脉注射的浓度低几个数量级。

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引用次数: 0

Enhancing Forensic Diagnostics: Structured Reporting of Post-Mortem CT versus Autopsy for Laryngohyoid Complex Fractures in Strangulation 加强法医诊断：死后 CT 与尸检的结构化报告：扼杀性喉头复合体骨折

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-09 DOI: 10.3390/bioengineering11080807

A. M. Bucher, Adrian Koppold, Mattias Kettner, Sarah Kölzer, Julia Dietz, Eric Frodl, Alexey Surov, Daniel Pinto dos Santos, Thomas J. Vogl, M. A. Verhoff, M. Beeres, Constantin Lux, Sara Heinbuch

Background: The purpose of this study was to establish a standardized structured workflow to compare findings from high-resolution, optimized reconstructions from post-mortem computed tomography (pmCT) with autopsy results in the detection of fractures of the laryngohyoid complex in strangulation victims. Method: Forty-two strangulation cases were selected, and pmCT scans of the laryngohyoid complex were obtained. Both pmCT scans and autopsy reports were analyzed using a structured template and compared using Cohen’s kappa coefficient (κ) and the McNemar test. The study also compared the prevalence of ossa sesamoidea and non-fusion of the major and minor horns of the hyoid bone between both diagnostic methods. Results: The detection of fractures showed a very good correlation between autopsy and pmCT results (κ = 0.905), with the McNemar test showing no statistically significant difference between the two methods. PmCT identified 28 sesamoid bones, 45 non-fusions of the major horns, and 47 non-fusions of the minor horns of the hyoid bone, compared to four, six, and zero, respectively, identified by autopsy (p < 0.0001). Conclusions: Autopsy and pmCT findings correlate well and can be used in a complementary manner. PmCT is superior to autopsy in identifying dislocations and detecting anatomical variations in the laryngohyoid complex, which can lead to misinterpretations during autopsy. Therefore, we do not advocate replacing autopsy with pmCT but propose using a structured workflow, including our standardized reporting template, for evaluating lesions in the laryngohyoid complex.

背景：本研究的目的是建立一个标准化的结构化工作流程，将死后计算机断层扫描（pmCT）的高分辨率优化重建结果与尸检结果进行比较，以检测勒颈受害者的咽喉复合体骨折情况。方法：选取 42 例扼死病例，并获取喉咽喉复合体的 pmCT 扫描图像。使用结构化模板对 pmCT 扫描和尸检报告进行分析，并使用 Cohen's kappa coefficient (κ) 和 McNemar 检验进行比较。该研究还比较了两种诊断方法中的芝麻状骨和舌骨大角与小角不融合的发生率。结果显示骨折的检测结果表明，尸检和 pmCT 的结果之间具有很好的相关性（κ = 0.905），McNemar 检验显示两种方法之间没有显著的统计学差异。PmCT 发现了 28 处芝麻状骨、45 处舌骨大角不融合和 47 处舌骨小角不融合，而尸检发现的芝麻状骨、大角不融合和小角不融合分别为 4 处、6 处和 0 处（P < 0.0001）。结论：尸检和 pmCT 的结果有很好的相关性，可以互补使用。PmCT 在识别喉头脱位和检测喉头复合体解剖变异方面优于尸检，而尸检可能会导致误解。因此，我们并不主张用 pmCT 代替尸检，而是建议使用结构化的工作流程（包括我们的标准化报告模板）来评估喉返神经复合体的病变。

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引用次数: 0

Enhancing Fermentation Process Monitoring through Data-Driven Modeling and Synthetic Time Series Generation 通过数据驱动建模和合成时间序列生成加强发酵过程监控

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-08 DOI: 10.3390/bioengineering11080803

Hyun J. Kwon, Joseph H. Shiu, C. K. Yamakawa, Elmer C. Rivera

Soft sensors based on deep learning regression models are promising approaches to predict real-time fermentation process quality measurements. However, experimental datasets are generally sparse and may contain outliers or corrupted data. This leads to insufficient model prediction performance. Therefore, datasets with a fully distributed solution space are required that enable effective exploration during model training. In this study, the robustness and predictive capability of the underlying model of a soft sensor was improved by generating synthetic datasets for training. The monitoring of intensified ethanol fermentation is used as a case study. Variational autoencoders were employed to create synthetic datasets, which were then combined with original datasets (experimental) to train neural network regression models. These models were tested on original versus augmented datasets to assess prediction improvements. Using the augmented datasets, the soft sensor predictive capability improved by 34%, and variability was reduced by 82%, based on R2 scores. The proposed method offers significant time and cost savings for dataset generation for the deep learning modeling of ethanol fermentation and can be easily adapted to other fermentation processes. This work contributes to the advancement of soft sensor technology, providing practical solutions for enhancing reliability and robustness in large-scale production.

基于深度学习回归模型的软传感器是预测实时发酵过程质量测量的有前途的方法。然而，实验数据集通常比较稀疏，可能包含异常值或损坏数据。这导致模型预测性能不足。因此，需要具有完全分布式解空间的数据集，以便在模型训练过程中进行有效探索。在本研究中，通过生成合成数据集进行训练，提高了软传感器底层模型的鲁棒性和预测能力。本研究以强化乙醇发酵监测为案例。利用变异自动编码器创建合成数据集，然后将其与原始数据集（实验）相结合，训练神经网络回归模型。在原始数据集和增强数据集上对这些模型进行了测试，以评估预测的改进情况。根据 R2 分数，使用增强数据集后，软传感器的预测能力提高了 34%，可变性降低了 82%。所提出的方法为乙醇发酵深度学习建模的数据集生成节省了大量时间和成本，并可轻松适用于其他发酵过程。这项工作为软传感器技术的发展做出了贡献，为提高大规模生产的可靠性和稳健性提供了实用的解决方案。

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引用次数: 0

Adaptive Detection in Real-Time Gait Analysis through the Dynamic Gait Event Identifier 通过动态步态事件识别器在实时步态分析中进行自适应检测

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-08 DOI: 10.3390/bioengineering11080806

Yifan Liu, Xing Liu, Qianhui Zhu, Yuan Chen, Yifei Yang, Haoyu Xie, Yichen Wang, Xingjun Wang

The Dynamic Gait Event Identifier (DGEI) introduces a pioneering approach for real-time gait event detection that seamlessly aligns with the needs of embedded system design and optimization. DGEI creates a new standard for gait analysis by combining software and hardware co-design with real-time data analysis, using a combination of first-order difference functions and sliding window techniques. The method is specifically designed to accurately separate and analyze key gait events such as heel strike (HS), toe-off (TO), walking start (WS), and walking pause (WP) from a continuous stream of inertial measurement unit (IMU) signals. The core innovation of DGEI is the application of its dynamic feature extraction strategies, including first-order differential integration with positive/negative windows, weighted sleep time analysis, and adaptive thresholding, which together improve its accuracy in gait segmentation. The experimental results show that the accuracy rate of HS event detection is 97.82%, and the accuracy rate of TO event detection is 99.03%, which is suitable for embedded systems. Validation on a comprehensive dataset of 1550 gait instances shows that DGEI achieves near-perfect alignment with human annotations, with a difference of less than one frame in pulse onset times in 99.2% of the cases.

动态步态事件识别器 (DGEI) 引入了一种用于实时步态事件检测的开创性方法，该方法与嵌入式系统设计和优化的需求实现了无缝对接。DGEI 采用一阶差分函数和滑动窗口技术，将软件和硬件协同设计与实时数据分析相结合，为步态分析创建了一个新标准。该方法专门用于从连续的惯性测量单元（IMU）信号流中准确分离和分析关键步态事件，如脚跟着地（HS）、脚尖离开（TO）、步行开始（WS）和步行暂停（WP）。DGEI 的核心创新在于其动态特征提取策略的应用，包括正/负窗口一阶微分积分、加权睡眠时间分析和自适应阈值，这些策略共同提高了步态分割的准确性。实验结果表明，HS 事件检测的准确率为 97.82%，TO 事件检测的准确率为 99.03%，适用于嵌入式系统。在一个包含 1550 个步态实例的综合数据集上进行的验证表明，DGEI 与人类注释实现了近乎完美的对齐，在 99.2% 的情况下脉冲发生时间的差异小于一帧。

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引用次数: 0

An Exosome-Laden Hydrogel Wound Dressing That Can Be Point-of-Need Manufactured in Austere and Operational Environments 可在恶劣环境和作战环境中按需生产的含外泌体的水凝胶伤口敷料

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-08 DOI: 10.3390/bioengineering11080804

E. C. Wisdom, Andrew Lamont, Hannah Martinez, Michael Rockovich, Woojin Lee, Kristin H. Gilchrist, Vincent B. Ho, G. Klarmann

Skin wounds often form scar tissue during healing. Early intervention with tissue-engineered materials and cell therapies may promote scar-free healing. Exosomes and extracellular vesicles (EV) secreted by mesenchymal stromal cells (MSC) are believed to have high regenerative capacity. EV bioactivity is preserved after lyophilization and storage to enable use in remote and typically resource-constrained environments. We developed a bioprinted bandage containing reconstituted EVs that can be fabricated at the point-of-need. An alginate/carboxymethyl cellulose (CMC) biomaterial ink was prepared, and printability and mechanical properties were assessed with rheology and compression testing. Three-dimensional printed constructs were evaluated for Young’s modulus relative to infill density and crosslinking to yield material with stiffness suitable for use as a wound dressing. We purified EVs from human MSC-conditioned media and characterized them with nanoparticle tracking analysis and mass spectroscopy, which gave a peak size of 118 nm and identification of known EV proteins. Fluorescently labeled EVs were mixed to form bio-ink and bioprinted to characterize EV release. EV bandages were bioprinted on both a commercial laboratory bioprinter and a custom ruggedized 3D printer with bioprinting capabilities, and lyophilized EVs, biomaterial ink, and thermoplastic filament were deployed to an austere Arctic environment and bioprinted. This work demonstrates that EVs can be bioprinted with an alginate/CMC hydrogel and released over time when in contact with a skin-like substitute. The technology is suitable for operational medical applications, notably in resource-limited locations, including large-scale natural disasters, humanitarian crises, and combat zones.

皮肤伤口在愈合过程中往往会形成疤痕组织。使用组织工程材料和细胞疗法进行早期干预可促进无疤痕愈合。间充质基质细胞（MSC）分泌的外泌体和细胞外囊泡（EV）被认为具有很强的再生能力。EV的生物活性在冻干和储存后得以保留，因此可在偏远和资源有限的环境中使用。我们开发了一种生物打印绷带，其中含有可在需要时制造的重组 EV。我们制备了一种藻酸盐/羧甲基纤维素（CMC）生物材料墨水，并通过流变学和压缩测试评估了其可印刷性和机械性能。我们评估了三维打印结构的杨氏模量与填充密度和交联度的关系，以确定材料的硬度是否适合用作伤口敷料。我们从人类间充质干细胞调节培养基中纯化了EVs，并通过纳米颗粒跟踪分析和质谱分析对其进行了表征。荧光标记的EV被混合成生物墨水并进行生物打印，以表征EV的释放。在商用实验室生物打印机和具有生物打印功能的定制加固型 3D 打印机上对 EV 绷带进行了生物打印，并将冻干 EV、生物材料墨水和热塑性长丝部署到严酷的北极环境中进行生物打印。这项工作表明，EV 可与藻酸盐/CMC 水凝胶一起进行生物打印，并在与类肤替代物接触后随时间释放。该技术适用于实际医疗应用，尤其是在资源有限的地区，包括大规模自然灾害、人道主义危机和战区。

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引用次数: 0

Synthesizing High b-Value Diffusion-Weighted Imaging of Gastric Cancer Using an Improved Vision Transformer CycleGAN 利用改进的视觉变换器循环广域网合成胃癌的高 b 值扩散加权成像

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-08 DOI: 10.3390/bioengineering11080805

Can Hu, Congchao Bian, Ning Cao, Han Zhou, Bin Guo

Background: Diffusion-weighted imaging (DWI), a pivotal component of multiparametric magnetic resonance imaging (mpMRI), plays a pivotal role in the detection, diagnosis, and evaluation of gastric cancer. Despite its potential, DWI is often marred by substantial anatomical distortions and sensitivity artifacts, which can hinder its practical utility. Presently, enhancing DWI’s image quality necessitates reliance on cutting-edge hardware and extended scanning durations. The development of a rapid technique that optimally balances shortened acquisition time with improved image quality would have substantial clinical relevance. Objectives: This study aims to construct and evaluate the unsupervised learning framework called attention dual contrast vision transformer cyclegan (ADCVCGAN) for enhancing image quality and reducing scanning time in gastric DWI. Methods: The ADCVCGAN framework, proposed in this study, employs high b-value DWI (b = 1200 s/mm2) as a reference for generating synthetic b-value DWI (s-DWI) from acquired lower b-value DWI (a-DWI, b = 800 s/mm2). Specifically, ADCVCGAN incorporates an attention mechanism CBAM module into the CycleGAN generator to enhance feature extraction from the input a-DWI in both the channel and spatial dimensions. Subsequently, a vision transformer module, based on the U-net framework, is introduced to refine detailed features, aiming to produce s-DWI with image quality comparable to that of b-DWI. Finally, images from the source domain are added as negative samples to the discriminator, encouraging the discriminator to steer the generator towards synthesizing images distant from the source domain in the latent space, with the goal of generating more realistic s-DWI. The image quality of the s-DWI is quantitatively assessed using metrics such as the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), feature similarity index (FSIM), mean squared error (MSE), weighted peak signal-to-noise ratio (WPSNR), and weighted mean squared error (WMSE). Subjective evaluations of different DWI images were conducted using the Wilcoxon signed-rank test. The reproducibility and consistency of b-ADC and s-ADC, calculated from b-DWI and s-DWI, respectively, were assessed using the intraclass correlation coefficient (ICC). A statistical significance level of p < 0.05 was considered. Results: The s-DWI generated by the unsupervised learning framework ADCVCGAN scored significantly higher than a-DWI in quantitative metrics such as PSNR, SSIM, FSIM, MSE, WPSNR, and WMSE, with statistical significance (p < 0.001). This performance is comparable to the optimal level achieved by the latest synthetic algorithms. Subjective scores for lesion visibility, image anatomical details, image distortion, and overall image quality were significantly higher for s-DWI and b-DWI compared to a-DWI (p < 0.001). At the same time, there was no significant difference between the scores of s-DWI and b-DWI (p > 0.05). The consistency o

背景：扩散加权成像（DWI）是多参数磁共振成像（mpMRI）的重要组成部分，在胃癌的检测、诊断和评估中发挥着关键作用。尽管 DWI 具有很大的潜力，但它经常受到严重的解剖学扭曲和灵敏度伪影的影响，这可能会妨碍它的实际应用。目前，要提高 DWI 的图像质量，必须依靠最先进的硬件和延长扫描时间。开发一种快速技术，在缩短采集时间和提高图像质量之间取得最佳平衡，将具有重大的临床意义。研究目标本研究旨在构建并评估一种名为注意力双对比度视觉转换器循环（ADCVCGAN）的无监督学习框架，以提高胃部 DWI 的图像质量并缩短扫描时间。方法：本研究提出的 ADCVCGAN 框架采用高 b 值 DWI（b = 1200 s/mm2）作为参考，从获取的低 b 值 DWI（a-DWI，b = 800 s/mm2）生成合成 b 值 DWI（s-DWI）。具体来说，ADCVCGAN 将注意力机制 CBAM 模块纳入 CycleGAN 生成器，以增强输入 a-DWI 在通道和空间维度上的特征提取。随后，引入基于 U-net 框架的视觉转换器模块，以完善细节特征，从而生成图像质量与 b-DWI 相当的 s-DWI。最后，将源域的图像作为负样本添加到判别器中，鼓励判别器引导生成器在潜空间中合成远离源域的图像，从而生成更逼真的 s-DWI。s-DWI 的图像质量通过峰值信噪比 (PSNR)、结构相似性指数 (SSIM)、特征相似性指数 (FSIM)、均方误差 (MSE)、加权峰值信噪比 (WPSNR) 和加权均方误差 (WMSE) 等指标进行量化评估。不同 DWI 图像的主观评价采用 Wilcoxon 符号秩检验。根据 b-DWI 和 s-DWI 分别计算出的 b-ADC 和 s-ADC 的再现性和一致性采用类内相关系数（ICC）进行评估。统计学显著性水平为 p < 0.05。结果无监督学习框架 ADCVCGAN 生成的 s-DWI 在 PSNR、SSIM、FSIM、MSE、WPSNR 和 WMSE 等定量指标上的得分明显高于 a-DWI，且具有统计学意义（p < 0.001）。这一性能与最新合成算法达到的最佳水平相当。与 a-DWI 相比，s-DWI 和 b-DWI 在病灶可见度、图像解剖细节、图像失真和整体图像质量方面的主观评分明显更高（p < 0.001）。同时，s-DWI 和 b-DWI 的评分没有明显差异（p > 0.05）。不同读者对 b-ADC 和 s-ADC 读数的一致性相当（ICC：b-ADC 分别为 0.87-0.90；s-ADC 为 0.88-0.89）。同一阅读器读取的 b-ADC 和 s-ADC 读数的重复性也相当（阅读器 1 ICC：b-ADC 0.85-0.86，s-ADC 0.85-0.93；阅读器 2 ICC：b-ADC 0.86-0.87，s-ADC 0.89-0.92）。结论ADCVCGAN 在生成胃癌 DWI 图像方面显示出良好的前景。它能有效缩短扫描时间，提高图像质量，确保 s-DWI 图像及其 s-ADC 值的真实性，从而为辅助临床决策提供依据。

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引用次数: 0

Wavelet Coherence Analysis of Post-Stroke Intermuscular Coupling Modulated by Myoelectric-Controlled Interfaces 由肌电控制界面调制的卒中后肌间耦合的小波相干分析

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-08 DOI: 10.3390/bioengineering11080802

Xinyi He, Wenbo Sun, Rong Song, Weiling Xu

Intermuscular coupling reflects the corticospinal interaction associated with the control of muscles. Nevertheless, the deterioration of intermuscular coupling caused by stroke has not received much attention. The purpose of this study was to investigate the effect of myoelectric-controlled interface (MCI) dimensionality on the intermuscular coupling after stroke. In total, ten age-matched controls and eight stroke patients were recruited and executed elbow tracking tasks within 1D or 2D MCI. Movement performance was quantified using the root mean square error (RMSE). Wavelet coherence was used to analyze the intermuscular coupling in alpha band (8–12 Hz) and beta band (15–35 Hz). The results found that smaller RMSE of antagonist muscles was observed in both groups within 2D MCI compared to 1D MCI. The alpha-band wavelet coherence was significantly lower in the patients compared to the controls during elbow extension. Furthermore, a decreased alpha-band and beta-band wavelet coherence was observed in the controls and stroke patients, as the dimensionality of MCI increased. These results may suggest that stroke-related neural impairments deteriorate the motor performance and intermuscular coordination pattern, and, further, that MCI holds promise as a novel effective tool for rehabilitation through the direct modulation of muscle activation pattern.

肌间耦合反映了与肌肉控制相关的皮质脊髓相互作用。然而，中风导致的肌间耦合恶化尚未引起人们的重视。本研究旨在探讨肌电控制界面（MCI）的维度对中风后肌间耦合的影响。共招募了 10 名年龄匹配的对照组和 8 名中风患者，在一维或二维 MCI 中执行肘部追踪任务。运动表现用均方根误差（RMSE）进行量化。小波相干性用于分析α波段（8-12赫兹）和β波段（15-35赫兹）的肌间耦合。结果发现，与一维 MCI 相比，二维 MCI 两组中拮抗肌的 RMSE 均较小。与对照组相比，患者在伸肘时的α波段小波相干性明显降低。此外，随着 MCI 维度的增加，在对照组和脑卒中患者中观察到α-带和β-带小波相干性降低。这些结果可能表明，与中风相关的神经损伤会恶化运动表现和肌肉间协调模式，而且，通过直接调节肌肉激活模式，MCI有望成为一种新型有效的康复工具。

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引用次数: 0

Novel Hybrid Quantum Architecture-Based Lung Cancer Detection Using Chest Radiograph and Computerized Tomography Images. 利用胸片和计算机断层扫描图像进行基于混合量子架构的新型肺癌检测。

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-07 DOI: 10.3390/bioengineering11080799

Jason Elroy Martis, Sannidhan M S, Balasubramani R, A M Mutawa, M Murugappan

Lung cancer, the second most common type of cancer worldwide, presents significant health challenges. Detecting this disease early is essential for improving patient outcomes and simplifying treatment. In this study, we propose a hybrid framework that combines deep learning (DL) with quantum computing to enhance the accuracy of lung cancer detection using chest radiographs (CXR) and computerized tomography (CT) images. Our system utilizes pre-trained models for feature extraction and quantum circuits for classification, achieving state-of-the-art performance in various metrics. Not only does our system achieve an overall accuracy of 92.12%, it also excels in other crucial performance measures, such as sensitivity (94%), specificity (90%), F1-score (93%), and precision (92%). These results demonstrate that our hybrid approach can more accurately identify lung cancer signatures compared to traditional methods. Moreover, the incorporation of quantum computing enhances processing speed and scalability, making our system a promising tool for early lung cancer screening and diagnosis. By leveraging the strengths of quantum computing, our approach surpasses traditional methods in terms of speed, accuracy, and efficiency. This study highlights the potential of hybrid computational technologies to transform early cancer detection, paving the way for wider clinical applications and improved patient care outcomes.

肺癌是全球第二大常见癌症，给人们的健康带来了巨大挑战。早期检测这种疾病对于改善患者预后和简化治疗至关重要。在这项研究中，我们提出了一种将深度学习（DL）与量子计算相结合的混合框架，以提高利用胸片（CXR）和计算机断层扫描（CT）图像检测肺癌的准确性。我们的系统利用预训练模型进行特征提取，利用量子电路进行分类，在各种指标上都达到了最先进的性能。我们的系统不仅达到了 92.12% 的总体准确率，而且在灵敏度（94%）、特异度（90%）、F1 分数（93%）和精确度（92%）等其他关键性能指标方面也表现出色。这些结果表明，与传统方法相比，我们的混合方法能更准确地识别肺癌特征。此外，量子计算的加入提高了处理速度和可扩展性，使我们的系统成为一种有前途的早期肺癌筛查和诊断工具。通过利用量子计算的优势，我们的方法在速度、准确性和效率方面都超越了传统方法。这项研究凸显了混合计算技术改变早期癌症检测的潜力，为更广泛的临床应用和改善患者护理效果铺平了道路。

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引用次数: 0

Genetic and Modifiable Risk Factors for Postoperative Complications of Total Joint Arthroplasty: A Genome-Wide Association and Mendelian Randomization Study. 全关节置换术术后并发症的遗传和可改变风险因素：全基因组关联和孟德尔随机化研究

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-07 DOI: 10.3390/bioengineering11080797

Sijia Guo, Jiping Zhang, Huiwu Li, Cheng-Kung Cheng, Jingwei Zhang

Background: Total joint arthroplasty (TJA) is an orthopedic procedure commonly used to treat damaged joints. Despite the efficacy of TJA, postoperative complications, including aseptic prosthesis loosening and infections, are common. Moreover, the effects of individual genetic susceptibility and modifiable risk factors on these complications are unclear. This study analyzed these effects to enhance patient prognosis and postoperative management. Methods: We conducted an extensive genome-wide association study (GWAS) and Mendelian randomization (MR) study using UK Biobank data. The cohort included 2964 patients with mechanical complications post-TJA, 957 with periprosthetic joint infection (PJI), and a control group of 398,708 individuals. Genetic loci associated with postoperative complications were identified by a GWAS analysis, and the causal relationships of 11 modifiable risk factors with complications were assessed using MR. Results: The GWAS analysis identified nine loci associated with post-TJA complications. Two loci near the PPP1R3B and RBM26 genes were significantly linked to mechanical complications and PJI, respectively. The MR analysis demonstrated that body mass index was positively associated with the risk of mechanical complications (odds ratio [OR]: 1.42; p < 0.001). Higher educational attainment was associated with a decreased risk of mechanical complications (OR: 0.55; p < 0.001) and PJI (OR: 0.43; p = 0.001). Type 2 diabetes was suggestively associated with mechanical complications (OR, 1.18, p = 0.02), and hypertension was suggestively associated with PJI (OR, 1.41, p = 0.008). Other lifestyle factors, including smoking and alcohol consumption, were not causally related to postoperative complications. Conclusions: The genetic loci near PPP1R3B and RBM26 influenced the risk of post-TJA mechanical complications and infections, respectively. The effects of genetic and modifiable risk factors, including body mass index and educational attainment, underscore the need to perform personalized preoperative assessments and the postoperative management of surgical patients. These results indicate that integrating genetic screening and lifestyle interventions into patient care can improve the outcomes of TJA and patient quality of life.

背景：全关节成形术（TJA）是一种常用于治疗受损关节的骨科手术。尽管 TJA 疗效显著，但术后并发症（包括无菌性假体松动和感染）却很常见。此外，个体遗传易感性和可改变的风险因素对这些并发症的影响尚不清楚。本研究分析了这些影响，以改善患者的预后和术后管理。方法：我们利用英国生物库数据进行了广泛的全基因组关联研究（GWAS）和孟德尔随机化研究（MR）。研究对象包括 2964 名 TJA 术后机械并发症患者、957 名假体周围关节感染（PJI）患者以及 398708 名对照组个体。通过 GWAS 分析确定了与术后并发症相关的基因位点，并使用 MR 评估了 11 个可改变的风险因素与并发症的因果关系。结果：GWAS 分析确定了 9 个与 TJA 术后并发症相关的基因位点。PPP1R3B和RBM26基因附近的两个位点分别与机械并发症和PJI有显著关联。MR分析表明，体重指数与机械并发症的风险呈正相关（几率比[OR]：1.42；P < 0.001）。教育程度越高，机械并发症（OR：0.55；P < 0.001）和 PJI（OR：0.43；P = 0.001）的风险越低。2型糖尿病与机械并发症呈提示性相关（OR：1.18，p = 0.02），高血压与PJI呈提示性相关（OR：1.41，p = 0.008）。其他生活方式因素，包括吸烟和饮酒，与术后并发症没有因果关系。结论PPP1R3B和RBM26附近的遗传位点分别影响了TJA术后机械并发症和感染的风险。遗传因素和可改变的风险因素（包括体重指数和教育程度）的影响强调了对手术患者进行个性化术前评估和术后管理的必要性。这些结果表明，将基因筛查和生活方式干预纳入患者护理可改善 TJA 的疗效和患者的生活质量。

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引用次数: 0

αvβ3 Integrin and Folate-Targeted pH-Sensitive Liposomes with Dual Ligand Modification for Metastatic Breast Cancer Treatment. 双配体修饰的αvβ3整合素和叶酸靶向pH敏感脂质体用于转移性乳腺癌治疗

IF 3.8 3区医学 Q2 ENGINEERING, BIOMEDICAL

Bioengineering

Pub Date : 2024-08-07 DOI: 10.3390/bioengineering11080800

Prashant Pandey, Dilip Kumar Arya, Payal Deepak, Daoud Ali, Saud Alarifi, Saurabh Srivastava, Afsaneh Lavasanifar, Paruvathanahalli Siddalingam Rajinikanth

The advent of pH-sensitive liposomes (pHLips) has opened new opportunities for the improved and targeted delivery of antitumor drugs as well as gene therapeutics. Comprising fusogenic dioleylphosphatidylethanolamine (DOPE) and cholesteryl hemisuccinate (CHEMS), these nanosystems harness the acidification in the tumor microenvironment and endosomes to deliver drugs effectively. pH-responsive liposomes that are internalized through endocytosis encounter mildly acidic pH in the endosomes and thereafter fuse or destabilize the endosomal membrane, leading to subsequent cargo release into the cytoplasm. The extracellular tumor matrix also presents a slightly acidic environment that can lead to the enhanced drug release and improved targeting capabilities of the nano-delivery system. Recent studies have shown that folic acid (FA) and iRGD-coated nanocarriers, including pH-sensitive liposomes, can preferentially accumulate and deliver drugs to breast tumors that overexpress folate receptors and αvβ3 and αvβ5 integrins. This study focuses on the development and characterization of 5-Fluorouracil (5-FU)-loaded FA and iRGD surface-modified pHLips (FA-iRGD-5-FU-pHLips). The novelty of this research lies in the dual targeting mechanism utilizing FA and iRGD peptides, combined with the pH-sensitive properties of the liposomes, to enhance selective targeting and uptake by cancer cells and effective drug release in the acidic tumor environment. The prepared liposomes were small, with an average diameter of 152 ± 3.27 nm, uniform, and unilamellar, demonstrating efficient 5-FU encapsulation (93.1 ± 2.58%). Despite surface functionalization, the liposomes maintained their pH sensitivity and a neutral zeta potential, which also conferred stability and reduced aggregation. Effective pH responsiveness was demonstrated by the observation of enhanced drug release at pH 5.5 compared to physiological pH 7.4. (84.47% versus 46.41% release at pH 5.5 versus pH 7.4, respectively, in 72 h). The formulations exhibited stability for six months and were stable when subjected to simulated biological settings. Blood compatibility and cytotoxicity studies on MDA-MB-231 and SK-BR3 breast cancer cell lines revealed an enhanced cytotoxicity of the liposomal formulation that was modified with FA and iRGD compared to free 5-FU and minimal hemolysis. Collectively, these findings support the potential of FA and iRGD surface-camouflaged, pH-sensitive liposomes as a promising drug delivery strategy for breast cancer treatment.

对 pH 值敏感的脂质体（pHLips）的出现为改善抗肿瘤药物和基因疗法的靶向递送提供了新的机遇。pH敏感脂质体通过内吞作用内化，在内质体中遇到微酸性pH值，然后融合或破坏内质体膜的稳定性，导致随后的货物释放到细胞质中。细胞外的肿瘤基质也呈现微酸性环境，这也会导致纳米递送系统的药物释放和靶向能力增强。最近的研究表明，叶酸（FA）和 iRGD 包被的纳米载体（包括 pH 敏感脂质体）可优先积聚药物并将药物输送到叶酸受体、αvβ3 和 αvβ5 整合素过度表达的乳腺肿瘤。本研究的重点是5-氟尿嘧啶（5-FU）负载的FA和iRGD表面修饰的pHLips（FA-iRGD-5-FU-pHLips）的开发和表征。这项研究的创新之处在于利用FA和iRGD肽的双重靶向机制，结合脂质体的pH敏感特性，增强了癌细胞的选择性靶向和吸收，并在酸性肿瘤环境中有效释放药物。制备的脂质体体积小，平均直径为 152 ± 3.27 nm，均匀且为单线粒体，能有效包封 5-FU (93.1 ± 2.58%)。尽管进行了表面官能化，但脂质体仍保持了对 pH 值的敏感性和中性 ZETA 电位，这也赋予了脂质体稳定性并减少了聚集。与生理 pH 值 7.4 相比，pH 值为 5.5 时的药物释放量增加（72 小时内，pH 值为 5.5 时的释放量为 84.47%，pH 值为 7.4 时的释放量为 46.41%）。制剂的稳定性可维持 6 个月，在模拟生物环境下也很稳定。对 MDA-MB-231 和 SK-BR3 乳腺癌细胞系进行的血液相容性和细胞毒性研究表明，与游离 5-FU 相比，用 FA 和 iRGD 修饰的脂质体制剂的细胞毒性更强，溶血现象极少。总之，这些研究结果支持了 FA 和 iRGD 表面掩蔽、pH 值敏感的脂质体作为乳腺癌治疗药物递送策略的潜力。

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