Fundamental Research最新文献

Unsupervised and supervised machine learning to identify variability of tumor-educated platelets and association with pan-cancer: A cross-national study 一项跨国研究：无监督和有监督机器学习识别肿瘤血小板变异性及其与泛癌的关系

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2023.09.004

Xiong Chen , Runnan Shen , Lin Lv , Dongxi Zhu , Guochang You , Zhenluan Tian , Jinwei Chen , Shen Lin , Jiatang Xu , Guibin Hong , Hu Li , Mingli Luo , Lin Cao , Shaoxu Wu , Kai Huang

Cancer can educate platelets by altering transcriptome profiles. However, the exact education mechanism remains unclear, and the variability of tumor-educated platelet (TEP) transcriptome has not been investigated. In this study, we aimed to build a stratification system for TEP based on machine learning (ML) data-driven patterns and platelet transcriptome profiles. This study included platelet samples from 1,628 cancer participants from European and United States populations, including 18 different and most prevalent types of cancer. Gaussian mixture model (GMM) was used to identify robust clusters and similar education pattern. While extreme gradient boosting (XGBoost) was used to precisely predict the clusters. Three clusters were eventually identified. The cluster results showed robustness and generality, reflected by comparable patterns of important gene expression, cancer type prevalence, and biological annotation across derivation, evaluation and validation cohorts. Cluster 1 (n = 346), mainly participated in drug metabolism cytochrome P450, metabolism of xenobiotics by cytochrome P450, and glutathione metabolism. Cluster 2 (n = 538) mainly participated in ribosome, spliceosome, and primary immunodeficiency. Cluster 3 (n = 744) mainly participated in gap junction and focal adhesion. Based on this novel cluster system, further observational study can investigate the association between these clusters and cancer progression, prognosis, cancer associated thrombosis, treatment resistance (both chemotherapy and immunotherapy), and immune cell infiltration. Overall, in this study, we built the first pan-cancer TEP stratification system based on data-driven patterns of ML and platelet transcriptional profiles. These clusters could help us better understand the variability of the pan-cancer education mechanism.

癌症可以通过改变转录组谱来教育血小板。然而，确切的教育机制尚不清楚，并且尚未研究肿瘤教育血小板（TEP）转录组的变异性。在这项研究中，我们旨在建立一个基于机器学习（ML）数据驱动模式和血小板转录组谱的TEP分层系统。这项研究包括来自欧洲和美国人群的1628名癌症参与者的血小板样本，包括18种不同的和最常见的癌症类型。采用高斯混合模型（GMM）识别稳健聚类和相似教育模式。而极端梯度增强（XGBoost）则用于精确预测聚类。最终确定了三组。聚类结果显示出稳健性和通用性，反映在重要基因表达、癌症类型患病率和跨推导、评估和验证队列的生物注释的可比模式上。集群1 (n = 346)，主要参与药物代谢细胞色素P450、细胞色素P450对外源药物的代谢和谷胱甘肽的代谢。集群2 （n = 538）主要参与核糖体、剪接体和原发性免疫缺陷。簇3 （n = 744）主要参与间隙连接和局灶粘连。基于这一新的簇簇系统，进一步的观察研究可以探讨这些簇簇与癌症进展、预后、癌症相关血栓形成、治疗抵抗（化疗和免疫治疗）以及免疫细胞浸润之间的关系。总的来说，在这项研究中，我们基于ML和血小板转录谱的数据驱动模式建立了第一个泛癌症TEP分层系统。这些集群可以帮助我们更好地理解泛癌症教育机制的可变性。

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引用次数: 0

Metasurface-tuned light-matter interactions for high-performance photodetectors 用于高性能光电探测器的元表面调谐光物质相互作用

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2024.01.002

Guanyu Zhang , Chang Xu , Dong Sun , Qinsheng Wang , Guowei Lu , Qihuang Gong

Photodetection, the conversion of optical signals to electrical signals, plays a pivotal role in optical communication, sensing, and computing. However, with the advent of novel applications such as quantum computing, intelligent driving, high-speed communication, and augmented reality, traditional photodetectors encounter challenges associated with miniaturization, the assurance of high performance, and the need for multifunctionality. These demands have prompted the development of novel photodetectors. One particularly promising avenue involves integrating conventional photodetection with metasurfaces. Metasurfaces facilitate highly localized field manipulation and versatile modes control at the subwavelength scale via plasmon resonance or Mie scattering, thereby enabling superior performance and multifunctionality detection. Consequently, metasurface-enhanced photodetectors have garnered significant attention in recent years. This review provides an overview of the unique roles played by metasurfaces in photodetection and summarizes notable breakthroughs in recent years.

光探测是光信号到电信号的转换，在光通信、传感和计算中起着举足轻重的作用。然而，随着量子计算、智能驾驶、高速通信和增强现实等新应用的出现，传统光电探测器面临着小型化、高性能保证和多功能需求等挑战。这些需求促使了新型光电探测器的发展。一个特别有前途的途径是将传统的光探测与超表面相结合。超表面通过等离子体共振或米氏散射促进高度局域场操作和亚波长尺度上的通用模式控制，从而实现卓越的性能和多功能检测。因此，近年来，超表面增强光电探测器获得了极大的关注。本文综述了超表面在光探测中的独特作用，并总结了近年来的重大突破。

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引用次数: 0

Coordination of genome stability: Novel communication pathways between chloroplasts and other compartments in plant cells 协调基因组的稳定性：叶绿体与植物细胞其他区室之间的新型交流途径

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2024.03.027

Sujuan Duan , Yajun Zeng , Hong-Bin Wang , Hong-Lei Jin

Chloroplasts have their own genomes, as do the nucleus and mitochondria. Coordination between these genomic compartments in plant cells is crucial for plant development and adaptation to the environment. However, little attention has been paid to the coordination of genome stability in the chloroplast and other genomic compartments. Several recent studies have shed light on the regulatory mechanisms governing this coordination, demonstrating the importance of communication between the different genomes to maintain genome stability. Here we review the communication of genome stability between chloroplasts and other compartments in plant cells. We also discuss the challenges and opportunities in this exciting research area.

叶绿体有自己的基因组，细胞核和线粒体也是如此。植物细胞中这些基因组区室之间的协调对植物的发育和对环境的适应至关重要。然而，叶绿体和其他基因组区室中基因组稳定性的协调却很少受到关注。最近的几项研究揭示了控制这种协调的调控机制，证明了不同基因组之间的交流对于维持基因组稳定性的重要性。本文综述了植物细胞中叶绿体与其他区室之间基因组稳定性的通讯。我们还讨论了这个令人兴奋的研究领域的挑战和机遇。

引用次数: 0

Enhancement of antibacterial and wound healing capabilities of cotton fabric through the covalent bonding of antibiotic-loaded hydrophobized mesoporous silica nanoparticles 通过共价键合抗生素负载的疏水介孔二氧化硅纳米粒子，增强棉织物的抗菌和伤口愈合能力

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2023.08.012

Ruiqi Zhang , Chao Yao , Atif Saleem , Yumei Qian , Pengfei Wang , Rui Zhang , Shengcai Qi , Yuezhou Zhang

Wound dressings are highly desirable for mitigating pathogenic bacterial infections. Sterilized cotton fabric is a widely used medical dressing, facilitating wound healing, mitigating pathogenic infections, and reducing treatment expenses. Nevertheless, untreated cotton fabric lacks intrinsic antibacterial properties. In this study, we introduced antibiotics-loaded aminopropyl and octadecyl grafted mesoporous silica nanoparticles onto the surface of hydrophobized cotton fabric. The obtained wound dressing exhibited remarkable antibacterial efficacy against Escherichia coli and Staphylococcus aureus through sustained antibiotic release. In vivo assessments verified that this intelligent cotton fabric dressing accelerates wound healing and prevents adhesion to skin tissues. Additionally, the reusability, hydrophobic nature, and straightforward synthesis methodology collectively provide an alternative solution to smart wound dressings for biomedical applications.

伤口敷料对于减轻致病性细菌感染是非常可取的。无菌棉织物是一种广泛使用的医用敷料，促进伤口愈合，减轻病原感染，降低治疗费用。然而，未经处理的棉织物缺乏固有的抗菌性能。在这项研究中，我们将抗生素负载的氨基丙基和十八烷基接枝的介孔二氧化硅纳米颗粒引入到疏水性棉织物表面。所得创面敷料对大肠杆菌和金黄色葡萄球菌具有明显的抑菌效果，并能持续释放抗生素。体内评估证实，这种智能棉织物敷料加速伤口愈合，防止粘连到皮肤组织。此外，可重用性、疏水性和直接的合成方法共同为生物医学应用的智能伤口敷料提供了另一种解决方案。

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引用次数: 0

Augmented reality navigation for precise implantation of LC2 pelvic tunnel screws in minimally invasive surgery 增强现实导航在微创手术中精确植入LC2骨盆隧道螺钉

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2024.05.010

Jie Zang , Zhipeng Lin , Chaowei Ding , DongXiao Bian , Junjun Pan , Xiaodong Tang

Background

Due to the considerable risk of trauma, traditional open surgery has been gradually replaced by minimally invasive surgery using tunnel screws. However, during minimally invasive pelvic surgery, surgical navigation can be improved by effectively using the augmented reality technique. This can further improve the accuracy of the surgery and reduce risks.

Methods

This study adopts a registration approach based on the patient coordinate system and uses a specific manual setting comparison method to select the suitable 3D corner detection parameters.

Results

After experiments, this strategy can effectively improve the accuracy of positioning during surgery. It achieves a balance in detection time and accuracy, which further reduces risks and injuries during surgery.

Conclusions

Our technique can achieve more precise and safer results during minimally invasive pelvic surgery, which shows its great value and potential in the clinic.

由于存在较大的创伤风险，传统的开放手术已逐渐被采用隧道螺钉的微创手术所取代。然而，在微创盆腔手术中，通过有效地使用增强现实技术可以改善手术导航。这可以进一步提高手术的准确性，降低风险。方法本研究采用基于患者坐标系的配准方法，并采用特定的人工设定对比方法选择合适的三维角点检测参数。结果经实验，该策略能有效提高术中定位的准确性。它达到了检测时间和准确性的平衡，进一步降低了手术中的风险和伤害。结论在微创盆腔手术中，sour技术可以获得更精确、更安全的结果，显示出其巨大的临床价值和潜力。

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引用次数: 0

Research progress and perspectives on ecological processes and carbon feedback in permafrost wetlands under changing climate conditions 气候变化条件下永冻土湿地生态过程和碳反馈的研究进展与展望

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2024.05.002

Changchun Song , Alain N. Rousseau , Yanyu Song , Yang Ou , Ning Chen , Xianwei Wang , Li Sun , Yuedong Guo , Hao Zhang , Zhengang Zhang , Zhuohang Xin

Permafrost wetlands are closely related to potential greenhouse gas emissions under climate warming. In recent decades, climate change and human activities have induced extensive permafrost degradation, severely influencing the stability of wetlands in permafrost regions. The widely observed significant changes in vegetation cover, hydrological conditions, and soil carbon stability are strongly affecting the carbon cycle and the carbon sources/sinks of permafrost wetlands. In this review, research progress on the response and feedback mechanisms of wetland ecological processes to permafrost degradation under the influences of climate change is first explored, including the impacts of permafrost degradation on the vegetation dynamics, hydrological processes, soil carbon decomposition, greenhouse gas emissions, and carbon feedback. In addition, several questions regarding recent advances are raised and some suggestions are provided for future related research pertaining to the following issues: (i) linkages and response relationships between permafrost degradation and the vegetation-hydrology-carbon cycle in permafrost wetlands, (ii) stabilization mechanisms of their carbon sink function, (iii) accurate estimation of the carbon sequestration rate and sink potential, and (iv) carbon feedback in permafrost wetlands under future climate change scenarios. The findings will provide critical scientific evidence and data support for protecting wetland ecosystems in permafrost regions under changing climate conditions and the implementation of carbon peaking and carbon neutrality strategies.

在气候变暖的背景下，冻土湿地与潜在的温室气体排放密切相关。近几十年来，气候变化和人类活动导致多年冻土大面积退化，严重影响了多年冻土区湿地的稳定性。植被覆盖、水文条件和土壤碳稳定性的显著变化强烈影响着多年冻土湿地的碳循环和碳源/汇。本文首先探讨了气候变化影响下湿地生态过程对多年冻土退化的响应和反馈机制的研究进展，包括多年冻土退化对植被动态、水文过程、土壤碳分解、温室气体排放和碳反馈的影响。此外，对近年来的研究进展提出了几个问题，并就以下问题对今后的相关研究提出了一些建议：(1)多年冻土退化与多年冻土湿地植被-水文-碳循环的联系与响应关系；(2)多年冻土湿地碳汇功能的稳定机制；(3)未来气候变化情景下多年冻土湿地固碳速率和汇潜力的精确估算；(4)多年冻土湿地碳反馈。研究结果将为气候变化条件下保护多年冻土区湿地生态系统以及实施碳峰值和碳中和战略提供重要的科学证据和数据支持。

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引用次数: 0

Jumping in the human brain: A review on somatic transposition 人脑中的跳跃：体细胞转位的研究进展

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2025.03.001

Yufei Zhang , Yanyan Guo , Hangxing Jia , Huijing Ma , Shengjun Tan , Yong E. Zhang

As a Nobel Prize-winning discovery, transposable elements, or “jumping genes”, have attracted significant interest due to their roles in providing functional coding and regulatory sequences. A longstanding hypothesis suggests that somatic transposition may preferentially occur in the mammalian brain, contributing to neuronal diversity. Here, we aim to provide the latest overview of somatic transposition studies in the human brain. We first introduce the historical context and the limited studies on the functionality of somatic transposition, indicating its pathogenic role. We then highlight the wide variability in somatic transposition rate estimates across studies, discussing the complexities—such as artificial chimeras and the multicopy nature—that contribute to false positive and negative results. We also review the evolving experimental and computational methods designed to mitigate these challenges and briefly cover studies estimating germline transposition rate. Finally, we suggest that advances in single-cell genome amplification methods, coupled with deep learning-based software, could pave the way for more definitive studies on the prevalence and functional role of somatic transposition in the human brain.

作为一项获得诺贝尔奖的发现，转座因子或“跳跃基因”由于其提供功能编码和调控序列的作用而引起了极大的兴趣。一个长期存在的假设表明，体细胞转位可能优先发生在哺乳动物的大脑中，有助于神经元的多样性。在这里，我们的目的是提供在人类大脑的体细胞转位研究的最新概述。我们首先介绍了体细胞转位的历史背景和有限的功能研究，表明其致病作用。然后，我们强调了研究中体细胞转位率估计的广泛差异，讨论了复杂性-例如人工嵌合体和多拷贝性质-导致假阳性和阴性结果。我们还回顾了旨在缓解这些挑战的不断发展的实验和计算方法，并简要介绍了估计种系转位率的研究。最后，我们建议单细胞基因组扩增方法的进步，加上基于深度学习的软件，可以为更明确地研究人类大脑中体细胞转位的患病率和功能作用铺平道路。

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引用次数: 0

Data tells the truth: A Knowledge distillation method for genomic survival analysis by handling censoring 数据告诉真相：一种处理审查的基因组生存分析的知识蒸馏方法

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2024.06.016

Xiu-Shen Wei , He-Yang Xu , Ye Wu , Xiaoming Liu , Ruru Gao , Jiacheng Liu , Bowen Du

Survival analysis is a critical tool for cancer research, yet handling censored data remains challenging due to supervision bias and inaccurate hazard estimates. To address these issues, we propose a simple but effective method termed KD, which employs knowledge distillation using uncensored data to rectify the supervision bias in censored data. This approach leverages the combined power of both rectified censored data and uncensored data to improve survival prediction accuracy. Remarkably, our KD method not only effectively harnesses censored data but also better reflects clinical reality, demonstrating its immense value in survival analysis. We applied our KD method to 19 target cancer sites using The Cancer Genome Atlas (TCGA) dataset. Our results consistently outperform traditional machine learning and deep learning-based methods across both target cancer sites and independent cancer cohorts. More importantly, our data-driven approach enables the model to extract hidden information from censored data, leading to conclusions that align more closely with clinical knowledge and scenarios. This validation of our KD method’s effectiveness highlights the substantial value of rational censored data usage, providing valuable insights for cancer research and clinical decisions. All data and codes are freely available at: https://datatellstruth.github.io/.

生存分析是癌症研究的重要工具，但由于监管偏见和不准确的危害估计，处理审查数据仍然具有挑战性。为了解决这些问题，我们提出了一种简单而有效的方法，称为KD，它使用未经审查的数据进行知识蒸馏，以纠正审查数据中的监督偏差。这种方法利用经过修正的审查数据和未经审查的数据的综合能力来提高生存预测的准确性。值得注意的是，我们的KD方法不仅有效地利用了审查数据，而且更好地反映了临床现实，证明了其在生存分析中的巨大价值。我们使用癌症基因组图谱（TCGA）数据集将KD方法应用于19个目标癌症位点。我们的结果在目标癌症部位和独立癌症队列中始终优于传统的机器学习和基于深度学习的方法。更重要的是，我们的数据驱动方法使模型能够从删除的数据中提取隐藏信息，从而得出更符合临床知识和场景的结论。对我们的KD方法有效性的验证突出了合理审查数据使用的巨大价值，为癌症研究和临床决策提供了有价值的见解。所有数据和代码可在https://datatellstruth.github.io/免费获得。

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引用次数: 0

Virtual physical framework reveals vortex-induced vibration “Soar” and “Death” for a bluff body at high Reynolds numbers 虚拟物理框架揭示了高雷诺数下钝体涡激振动的“飙升”和“死亡”

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2024.05.011

Haojie Ren , Shixiao Fu , Mengmeng Zhang , Yuwang Xu , Hao Ren

Vortex-induced vibration (VIV) of a bluff body is well known as a canonical phenomenon in complex fluid–structure interactions (FSI). However, our understanding and physical theories of this phenomenon are still restricted to a lower Reynolds number (Re) range owing to the limitations of experimental fluid mechanics. Herein, we describe a virtual physical framework (VPF) capable of editing and controlling the physical parameters of an actual physical system with high fidelity by combining numerical disciplinary and mechanical actuators. We demonstrated the effectiveness of applying a VPF to address the experimental fluid mechanical challenges of VIV for a bluff body at a high Re by virtualizing a large, flexibly mounted rigid cylindrical system. We observed the VIV evolution of the bluff body at different Re values. Notably, the VIV appears in its “soar” stages with unexpected amplitudes of 2.4 D, nearly 200% higher than the traditionally acknowledged value at approximately Re = 2.0E5, while suddenly entering into its “death” stages with no vibrations over the critical Re region. The dissynchrony changes in the energy dissipation and input with Re caused by drag and excitation forces in the fluid system were further found to result in these VIV phenomena. This discovery upsets previous perceptions of VIVs and raises profound questions regarding related engineering projects. The VPF also opens a promising paradigm in experimental research for accelerating scientific discovery and investigating unaddressed classical physical phenomena.

钝体的涡激振动（VIV）是复杂流固耦合（FSI）中的典型现象。然而，由于实验流体力学的限制，我们对这一现象的理解和物理理论仍然局限于较低的雷诺数（Re）范围。在此，我们描述了一个虚拟物理框架（VPF）能够编辑和高保真地控制实际物理系统的物理参数，结合数值学科和机械执行器。通过虚拟一个大型、灵活安装的刚性圆柱形系统，我们证明了应用VPF来解决高Re钝体VIV实验流体力学挑战的有效性。我们观察了不同Re值下钝体的涡激振动演化。值得注意的是，VIV在其“飙升”阶段出现了意想不到的2.4 D振幅，比传统上公认的Re = 2.0E5的值高出近200%，而突然进入其“死亡”阶段，在临界Re区域没有振动。进一步发现了流体系统中阻力和激励力引起的能量耗散和输入随Re的不同步变化是造成这些涡激现象的原因。这一发现颠覆了以前对viv的看法，并提出了有关相关工程项目的深刻问题。VPF还为加速科学发现和研究未解决的经典物理现象开辟了一个有前途的实验研究范式。

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引用次数: 0

Molecule generation for drug design: A graph learning perspective 药物设计的分子生成：图学习视角

IF 6.3 3区综合性期刊 Q1 Multidisciplinary

Fundamental Research

Pub Date : 2026-01-01 DOI: 10.1016/j.fmre.2024.11.027

Nianzu Yang , Huaijin Wu , Kaipeng Zeng , Yang Li , Siyuan Bao , Junchi Yan

Machine learning, particularly graph learning, is gaining increasing recognition for its transformative impact across various fields. One such promising application is in the realm of molecule design and discovery, notably within the pharmaceutical industry. Our survey offers a comprehensive overview of state-of-the-art methods in molecule design, particularly focusing on de novo drug design, which incorporates (deep) graph learning techniques. We categorize these methods into three distinct groups: i) all-at-once, ii) fragment-based, and iii) node-by-node. Additionally, we introduce some key public datasets and outline the commonly used evaluation metrics for both the generation and optimization of molecules. In the end, we discuss the existing challenges in this field and suggest potential directions for future research.

机器学习，特别是图学习，因其在各个领域的变革性影响而获得越来越多的认可。其中一个很有前途的应用是在分子设计和发现领域，特别是在制药行业。我们的调查提供了分子设计中最先进的方法的全面概述，特别是专注于新药物设计，它结合了（深度）图学习技术。我们将这些方法分为三个不同的组：i)一次性，ii)基于片段的，和iii)逐个节点。此外，我们还介绍了一些关键的公共数据集，并概述了用于分子生成和优化的常用评估指标。最后，讨论了该领域存在的挑战，并提出了未来的研究方向。

引用次数: 0