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[The research development of programmed cell death in rheumatoid arthritis]. [类风湿性关节炎中程序性细胞死亡的研究进展]。
Q3 Medicine Pub Date : 2024-10-25
Ke Han, Zi-Xia Ding, Xiao-Yu He, Tian-Yu Wu, Yu-Hang Meng, Bang Du, Xiao-Nan Zhang

The etiology of rheumatoid arthritis (RA), a chronic inflammatory systemic disease, remains unclear. It is characterized by symmetrical and invasive joint inflammation, primarily affecting distal small joints such as those in the hands and feet. This inflammation can lead to joint deformity and loss of function, and often accompanied by involvement of extra-articular organs like the lungs and heart. Currently, anti-rheumatic drugs only provide symptom improvement but have toxic side effects that require optimization. Therefore, it is crucial to thoroughly analyze the mechanisms underlying RA development for the identification of new drug targets. Programmed cell death (PCD) has been extensively studied in recent years and proved to be one of the key pathogenic factors in RA. Dysregulation of PCD is particularly evident in synoviocytes, immune cells, and osteocytes. This review summarizes various forms of PCD including apoptosis, NETosis, autophagy, pyroptosis, necroptosis, ferroptosis, cuproptosis, as well as their regulatory roles in fibroblast synoviocytes, immune cells and osteocytes. These findings hold significant theoretical implications for optimizing clinical treatment options for RA and developing new target drugs.

类风湿性关节炎(RA)是一种慢性全身性炎症性疾病,其病因至今仍不清楚。其特点是对称性和侵袭性关节炎症,主要影响远端小关节,如手部和足部关节。这种炎症可导致关节畸形和功能丧失,通常还伴有肺和心脏等关节外器官的受累。目前,抗风湿药物只能改善症状,但其毒副作用需要优化。因此,透彻分析 RA 的发病机制以确定新的药物靶点至关重要。近年来,人们对程序性细胞死亡(PCD)进行了广泛研究,并证明它是RA的关键致病因素之一。PCD失调在滑膜细胞、免疫细胞和骨细胞中尤为明显。本综述总结了PCD的各种形式,包括凋亡、NETosis、自噬、热凋亡、坏死凋亡、铁凋亡、杯状凋亡,以及它们在成纤维滑膜细胞、免疫细胞和骨细胞中的调控作用。这些发现对优化RA的临床治疗方案和开发新的靶向药物具有重要的理论意义。
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引用次数: 0
[Research progress of breast pathology image diagnosis based on deep learning]. [基于深度学习的乳腺病理图像诊断研究进展]。
Q4 Medicine Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202311061
Liang Jiang, Cheng Zhang, Hui Cao, Baihao Jiang

Breast cancer is a malignancy caused by the abnormal proliferation of breast epithelial cells, predominantly affecting female patients, and it is commonly diagnosed using histopathological images. Currently, deep learning techniques have made significant breakthroughs in medical image processing, outperforming traditional detection methods in breast cancer pathology classification tasks. This paper first reviewed the advances in applying deep learning to breast pathology images, focusing on three key areas: multi-scale feature extraction, cellular feature analysis, and classification. Next, it summarized the advantages of multimodal data fusion methods for breast pathology images. Finally, the study discussed the challenges and future prospects of deep learning in breast cancer pathology image diagnosis, providing important guidance for advancing the use of deep learning in breast diagnosis.

乳腺癌是一种由乳腺上皮细胞异常增生引起的恶性肿瘤,主要影响女性患者,通常使用组织病理学图像进行诊断。目前,深度学习技术在医学图像处理领域取得了重大突破,在乳腺癌病理分类任务中的表现优于传统检测方法。本文首先回顾了将深度学习应用于乳腺病理图像的进展,重点关注三个关键领域:多尺度特征提取、细胞特征分析和分类。接着,它总结了乳腺病理图像多模态数据融合方法的优势。最后,研究探讨了深度学习在乳腺癌病理图像诊断中面临的挑战和未来前景,为推进深度学习在乳腺诊断中的应用提供了重要指导。
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引用次数: 0
[m6A RNA methylation is a potential biological target for neuropathic pain]. [m6A RNA 甲基化是治疗神经性疼痛的潜在生物靶点]
Q3 Medicine Pub Date : 2024-10-25
Yu-Ting Zhang, Li-Cai Zhang

N6-methyladenosine (m6A) is the most common type of RNA modification in eukaryotes, which affects intracellular RNA metabolism and controls gene expression of related pathophysiological processes through dynamic reversible regulation of methyltransferases, demethylases and m6A-binding proteins. In recent years, the involvement of m6A methylation in the study of neuropathic pain has become a hot topic, some new understandings have been emerging, and m6A methylation has become a potential biological target for the treatment of neuropathic pain. Therefore, this article reviews the role and regulation of m6A methylation in neuropathic pain, in order to provide new enlightenment for the drug development and treatment of neuropathic pain.

N6-甲基腺苷(m6A)是真核生物中最常见的一种RNA修饰,通过甲基转移酶、去甲基化酶和m6A结合蛋白的动态可逆调控,影响细胞内RNA代谢,控制相关病理生理过程的基因表达。近年来,m6A 甲基化参与神经病理性疼痛的研究已成为一个热门话题,一些新的认识不断涌现,m6A 甲基化已成为治疗神经病理性疼痛的潜在生物学靶点。因此,本文综述了m6A甲基化在神经病理性疼痛中的作用和调控,以期为神经病理性疼痛的药物研发和治疗提供新的启示。
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引用次数: 0
[Research progress in the regulation of functional homeostasis of adipose tissue by exosomal miRNA]. [外泌体 miRNA 调控脂肪组织功能平衡的研究进展]。
Q3 Medicine Pub Date : 2024-10-25
Jun-Qing Xu, Meng-Xin Jiang, Ying-Jiang Xu, Sheng-Jun Dong

Adipose tissue holds a pivotal position in maintaining systemic energy homeostasis. Brown adipose tissue (BAT) expresses uncoupling protein 1 (UCP1), which is specialized in dissipating chemical energy as heat to maintain euthermia, a process called non-shivering thermogenesis. Conversely, white adipocyte (WAT) predominantly serves as the primary reservoir for energy storage, while also exhibiting endocrine activity by secreting various adipokines, thereby modulating systemic metabolism. Under the stimulation of cold exposure, physical activity and pharmacological intervention, WAT can occur as "browning" or "beiging", and transform into beige adipose tissue. The morphology and function of beige adipocyte are similar to brown adipocyte, both of which express higher levels of UCP1 and also have the function of thermogenesis. Thus, exploring methods to regulate the functional homeostasis of adipose tissue and its underlying molecular mechanisms hold promise for advancing preventative and therapeutic approaches against metabolic diseases. Exosomes, a subtype of extracellular vesicles (EVs) with a diameter of 40-100 nm, facilitate intercellular communication in obese individuals and exert significant influence on insulin resistance and impaired glucose tolerance within adipose tissue. These effects are primarily mediated by microRNA (miRNA) transported by exosomes. MiRNA, originating from various cellular sources, traverses between different cell types via EVs, thereby orchestrating reciprocal functional modulation among diverse tissues and organs. This review systematically summarized the research progress in exosomal miRNA-mediated regulation of adipose tissue functional homeostasis, with the aim of offering novel insights into the diagnosis and treatment of obesity and associated metabolic diseases.

脂肪组织在维持全身能量平衡方面具有举足轻重的地位。棕色脂肪组织(BAT)表达解偶联蛋白 1(UCP1),专门将化学能转化为热能,以维持体温,这一过程被称为非颤抖性产热。相反,白色脂肪细胞(WAT)主要作为能量储存库,同时还通过分泌各种脂肪因子表现出内分泌活性,从而调节全身代谢。在寒冷暴露、体力活动和药物干预的刺激下,白脂肪组织会发生 "褐变 "或 "米色化",转变为米色脂肪组织。米色脂肪细胞的形态和功能与棕色脂肪细胞相似,都表达较高水平的 UCP1,同样具有产热功能。因此,探索调节脂肪组织功能平衡的方法及其潜在的分子机制有望推进代谢性疾病的预防和治疗方法。外泌体是细胞外囊泡的一种亚型,直径为 40-100 nm,可促进肥胖者细胞间的交流,并对脂肪组织内的胰岛素抵抗和糖耐量受损产生显著影响。这些影响主要是由外泌体运输的微核糖核酸(miRNA)介导的。miRNA来自不同的细胞来源,通过外泌体在不同类型的细胞之间穿行,从而协调不同组织和器官之间的相互功能调节。这篇综述系统地总结了外泌体miRNA介导的脂肪组织功能平衡调控的研究进展,旨在为肥胖症及相关代谢性疾病的诊断和治疗提供新的见解。
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引用次数: 0
[Research on motion impedance cardiography de-noising method based on two-step spectral ensemble empirical mode decomposition and canonical correlation analysis]. [基于两步谱集合经验模式分解和典型相关分析的运动阻抗心动图去噪方法研究]。
Q4 Medicine Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202210059
Yao Xie, Dong Yang, Honglong Yu, Qilian Xie

Impedance cardiography (ICG) is essential in evaluating cardiac function in patients with cardiovascular diseases. Aiming at the problem that the measurement of ICG signal is easily disturbed by motion artifacts, this paper introduces a de-noising method based on two-step spectral ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA). Firstly, the first spectral EEMD-CCA was performed between ICG and motion signals, and electrocardiogram (ECG) and motion signals, respectively. The component with the strongest correlation coefficient was set to zero to suppress the main motion artifacts. Secondly, the obtained ECG and ICG signals were subjected to a second spectral EEMD-CCA for further denoising. Lastly, the ICG signal is reconstructed using these share components. The experiment was tested on 30 subjects, and the results showed that the quality of the ICG signal is greatly improved after using the proposed denoising method, which could support the subsequent diagnosis and analysis of cardiovascular diseases.

阻抗心动图(ICG)对评估心血管疾病患者的心脏功能至关重要。针对 ICG 信号的测量容易受到运动伪影干扰的问题,本文介绍了一种基于两步频谱集合经验模式分解(EEMD)和卡农相关分析(CCA)的去噪方法。首先,分别在 ICG 和运动信号、心电图(ECG)和运动信号之间进行第一次频谱 EEMD-CCA。将相关系数最大的分量设为零,以抑制主要的运动伪影。其次,对获得的心电图和 ICG 信号进行第二次频谱 EEMD-CCA 以进一步去噪。最后,利用这些共享分量重建 ICG 信号。实验在 30 名受试者身上进行了测试,结果表明,在使用了所提出的去噪方法后,ICG 信号的质量得到了极大的改善,可以为后续的心血管疾病诊断和分析提供支持。
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引用次数: 0
[Reinforcement learning-based method for type B aortic dissection localization]. [基于强化学习的 B 型主动脉夹层定位方法]。
Q4 Medicine Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202309047
An Zeng, Xianyang Lin, Jingliang Zhao, Dan Pan, Baoyao Yang, Xin Liu

In the segmentation of aortic dissection, there are issues such as low contrast between the aortic dissection and surrounding organs and vessels, significant differences in dissection morphology, and high background noise. To address these issues, this paper proposed a reinforcement learning-based method for type B aortic dissection localization. With the assistance of a two-stage segmentation model, the deep reinforcement learning was utilized to perform the first-stage aortic dissection localization task, ensuring the integrity of the localization target. In the second stage, the coarse segmentation results from the first stage were used as input to obtain refined segmentation results. To improve the recall rate of the first-stage segmentation results and include the segmentation target more completely in the localization results, this paper designed a reinforcement learning reward function based on the direction of recall changes. Additionally, the localization window was separated from the field of view window to reduce the occurrence of segmentation target loss. Unet, TransUnet, SwinUnet, and MT-Unet were selected as benchmark segmentation models. Through experiments, it was verified that the majority of the metrics in the two-stage segmentation process of this paper performed better than the benchmark results. Specifically, the Dice index improved by 1.34%, 0.89%, 27.66%, and 7.37% for each respective model. In conclusion, by incorporating the type B aortic dissection localization method proposed in this paper into the segmentation process, the overall segmentation accuracy is improved compared to the benchmark models. The improvement is particularly significant for models with poorer segmentation performance.

在主动脉夹层的分割中,存在主动脉夹层与周围器官和血管对比度低、夹层形态差异大、背景噪声高等问题。针对这些问题,本文提出了一种基于强化学习的 B 型主动脉夹层定位方法。在两阶段分割模型的辅助下,利用深度强化学习完成第一阶段主动脉夹层定位任务,确保定位目标的完整性。在第二阶段,将第一阶段的粗分割结果作为输入,获得精细分割结果。为了提高第一阶段分割结果的召回率,并将分割目标更完整地纳入定位结果,本文设计了基于召回率变化方向的强化学习奖励函数。此外,还将定位窗口与视场窗口分开,以减少分割目标丢失的发生。本文选择 Unet、TransUnet、SwinUnet 和 MTUnet 作为基准分割模型。通过实验验证,本文两阶段分割过程中的大多数指标都优于基准结果。具体来说,每个模型的 Dice 指数分别提高了 1.34%、0.89%、27.66% 和 7.37%。总之,通过将本文提出的 B 型主动脉夹层定位方法纳入分割过程,与基准模型相比,整体分割准确性得到了提高。对于分割性能较差的模型,这种改进尤为明显。
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引用次数: 0
[Enhancement algorithm for surface electromyographic-based gesture recognition based on real-time fusion of muscle fatigue features]. [基于肌肉疲劳特征实时融合的表面肌电图手势识别增强算法]。
Q4 Medicine Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202312023
Shijia Yan, Ye Yang, Peng Yi

This study aims to optimize surface electromyography-based gesture recognition technique, focusing on the impact of muscle fatigue on the recognition performance. An innovative real-time analysis algorithm is proposed in the paper, which can extract muscle fatigue features in real time and fuse them into the hand gesture recognition process. Based on self-collected data, this paper applies algorithms such as convolutional neural networks and long short-term memory networks to provide an in-depth analysis of the feature extraction method of muscle fatigue, and compares the impact of muscle fatigue features on the performance of surface electromyography-based gesture recognition tasks. The results show that by fusing the muscle fatigue features in real time, the algorithm proposed in this paper improves the accuracy of hand gesture recognition at different fatigue levels, and the average recognition accuracy for different subjects is also improved. In summary, the algorithm in this paper not only improves the adaptability and robustness of the hand gesture recognition system, but its research process can also provide new insights into the development of gesture recognition technology in the field of biomedical engineering.

本研究旨在优化基于表面肌电图的手势识别技术,重点关注肌肉疲劳对识别性能的影响。本文提出了一种创新的实时分析算法,可实时提取肌肉疲劳特征并将其融合到手势识别过程中。基于自收集的数据,本文应用卷积神经网络和长短期记忆网络等算法深入分析了肌肉疲劳的特征提取方法,并比较了肌肉疲劳特征对基于表面肌电图的手势识别任务性能的影响。结果表明,通过实时融合肌肉疲劳特征,本文提出的算法提高了不同疲劳程度下的手势识别准确率,不同受试者的平均识别准确率也有所提高。总之,本文的算法不仅提高了手势识别系统的适应性和鲁棒性,而且其研究过程也能为生物医学工程领域手势识别技术的发展提供新的启示。
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引用次数: 0
[Colon polyp detection based on multi-scale and multi-level feature fusion and lightweight convolutional neural network]. [基于多尺度、多层次特征融合和轻量级卷积神经网络的结肠息肉检测]。
Q4 Medicine Pub Date : 2024-10-25 DOI: 10.7507/1001-5515.202312014
Yiyang Li, Jiayi Zhao, Ruoyi Yu, Huixiang Liu, Shuang Liang, Yu Gu

Early diagnosis and treatment of colorectal polyps are crucial for preventing colorectal cancer. This paper proposes a lightweight convolutional neural network for the automatic detection and auxiliary diagnosis of colorectal polyps. Initially, a 53-layer convolutional backbone network is used, incorporating a spatial pyramid pooling module to achieve feature extraction with different receptive field sizes. Subsequently, a feature pyramid network is employed to perform cross-scale fusion of feature maps from the backbone network. A spatial attention module is utilized to enhance the perception of polyp image boundaries and details. Further, a positional pattern attention module is used to automatically mine and integrate key features across different levels of feature maps, achieving rapid, efficient, and accurate automatic detection of colorectal polyps. The proposed model is evaluated on a clinical dataset, achieving an accuracy of 0.9982, recall of 0.9988, F1 score of 0.9984, and mean average precision (mAP) of 0.9953 at an intersection over union (IOU) threshold of 0.5, with a frame rate of 74 frames per second and a parameter count of 9.08 M. Compared to existing mainstream methods, the proposed method is lightweight, has low operating configuration requirements, high detection speed, and high accuracy, making it a feasible technical method and important tool for the early detection and diagnosis of colorectal cancer.

大肠息肉的早期诊断和治疗对预防大肠癌至关重要。本文提出了一种用于大肠息肉自动检测和辅助诊断的轻量级卷积神经网络。首先,使用 53 层卷积主干网络,结合空间金字塔池化模块,实现不同感受野大小的特征提取。随后,利用特征金字塔网络对骨干网络的特征图进行跨尺度融合。空间注意力模块用于增强对息肉图像边界和细节的感知。此外,位置模式注意模块用于自动挖掘和整合不同层次特征图的关键特征,从而实现快速、高效、准确的大肠息肉自动检测。该模型在临床数据集上进行了评估,在每秒 74 帧的帧率和 9 个参数的情况下,在交集大于联合(IOU)阈值为 0.5 时,准确率达到 0.9982,召回率达到 0.9988,F1 分数达到 0.9984,平均精度(mAP)达到 0.9953。08 M。与现有的主流方法相比,所提出的方法具有轻便、操作配置要求低、检测速度快、精确度高等特点,是一种可行的技术方法,也是结直肠癌早期检测和诊断的重要工具。
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引用次数: 0
Next-Generation Tumor Targeting with Genetically Engineered Cell Membrane-Coated Nanoparticles. 利用基因工程细胞膜包裹的纳米粒子进行下一代肿瘤靶向治疗。
Q2 Agricultural and Biological Sciences Pub Date : 2024-10-25 eCollection Date: 2024-01-01 DOI: 10.34133/bdr.0055
Quazi T H Shubhra, Xiaojun Cai, Qiang Cai
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引用次数: 0
[Research progress on the effects of mitochondrial-associated endoplasmic reticulum membranes tethering proteins interaction on cerebral ischemia/reperfusion]. [线粒体相关内质网膜系链蛋白相互作用对脑缺血再灌注影响的研究进展]。
Q3 Medicine Pub Date : 2024-10-25
Meng-Ling Huang, Li-Hong Zhang, Chang-Yu Gu, Jing-Jing Li, Rui-Qing Li, Xiao-Dong Feng, Jing Gao, Jian Guo

Cerebral ischemia/reperfusion injury (CIRI) refers to secondary damage caused by reperfusion of blood flow following ischemic stroke. Its mechanism is complex, involving mitochondrial energy metabolism disorders, Ca2+ overload, oxidative stress, apoptosis, inflammatory responses, excitatory amino acid toxicity, blood-brain barrier disruption, excessive NO synthesis, and cell necrosis etc. Mitochondrial-associated endoplasmic reticulum membranes (MAMs) are specialized regions of the endoplasmic reticulum that play crucial roles in various cellular processes, including regulation of mitochondrial morphology and activity, lipid metabolism, Ca2+ homeostasis, and cell viability. Existing research has confirmed that mitochondrial homeostasis, cell apoptosis, and endoplasmic reticulum stress are closely related to MAMs. This article summarizes the research progress on MAMs in recent years, reviews the biological functions of MAMs and the localization of tethering proteins, analyzes the signaling between mitochondria and the endoplasmic reticulum, explores the impact of MAMs tethering proteins interaction on Ca2+ signaling and cell viability during the pathophysiological process of CIRI, aiming to provide a theoretical basis for the treatment of CIRI.

脑缺血再灌注损伤(CIRI)是指缺血性脑卒中后血流再灌注引起的继发性损伤。其机制复杂,涉及线粒体能量代谢紊乱、Ca2+ 超载、氧化应激、细胞凋亡、炎症反应、兴奋性氨基酸毒性、血脑屏障破坏、NO 过度合成和细胞坏死等。线粒体相关内质网膜(MAMs)是内质网的特殊区域,在各种细胞过程中发挥着至关重要的作用,包括线粒体形态和活性、脂质代谢、钙离子平衡和细胞活力的调节。现有研究证实,线粒体稳态、细胞凋亡和内质网应激与 MAMs 密切相关。本文总结了近年来MAMs的研究进展,综述了MAMs的生物学功能和系链蛋白的定位,分析了线粒体与内质网之间的信号传导,探讨了CIRI病理生理过程中MAMs系链蛋白相互作用对Ca2+信号传导和细胞活力的影响,旨在为CIRI的治疗提供理论依据。
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引用次数: 0
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