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Biophysical approaches to cancer diagnostics: Collagen biomarkers in colorectal cancer. 癌症诊断的生物物理方法:结直肠癌中的胶原生物标志物。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-01-29 DOI: 10.1016/j.plrev.2026.01.009
Shimul Biswas, Krishna Kishore Mahato

Collagen remodeling in the extracellular matrix drives alterations in the physical, mechanical, and optical properties of tissues, representing a fundamental biophysical hallmark of colorectal cancer (CRC) progression. These changes, reflected in variations in collagen composition, molecular orientation, and cross-linking density, transform tissue stiffness, elasticity, and anisotropy, directly influencing cancer cell behavior and mechanotransduction. Understanding these structural and physical transitions requires analytical methods capable of probing the molecular origins of biomechanical alteration in situ. Spectroscopic and optical methodologies provide high-resolution, label-free detection of the vibrational, optical, and mechanical alteration associated with collagen remodeling. These techniques capture the shifts in molecular vibrational modes, nonlinear optical responses, and scattering anisotropy that arise from collagen fibril alignment, structural disorder, and cross-link formation, thereby connecting molecular architecture to measurable macroscale biomechanics. The integration of multimodal spectroscopy and incorporation of machine learning algorithms further enhance diagnostic performance by resolving complex tissue heterogeneity and improving tumor margin detection. Overall, this review demonstrates how spectroscopic techniques can be applied in the biomedical field for cancer detection by analyzing collagen remodeling and structural alterations.

细胞外基质中的胶原重塑驱动组织的物理、机械和光学特性的改变,代表了结直肠癌(CRC)进展的基本生物物理标志。这些变化反映在胶原组成、分子取向和交联密度的变化上,改变了组织的刚度、弹性和各向异性,直接影响癌细胞的行为和机械转导。理解这些结构和物理转变需要能够探测生物力学变化原位分子起源的分析方法。光谱和光学方法提供高分辨率,无标记检测与胶原蛋白重塑相关的振动,光学和机械改变。这些技术捕获了由胶原纤维排列、结构紊乱和交联形成引起的分子振动模式、非线性光学响应和散射各向异性的变化,从而将分子结构与可测量的宏观生物力学联系起来。多模态光谱的集成和机器学习算法的结合通过解决复杂的组织异质性和改进肿瘤边缘检测进一步提高了诊断性能。总之,本文综述了光谱技术如何应用于生物医学领域,通过分析胶原重塑和结构改变来检测癌症。
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引用次数: 0
Illuminating brain’s “dark energy”: a living lens of spontaneous slow oscillations. reply to comments on ‘dark brain energy: toward an integrative model of spontaneous slow oscillations’ 照亮大脑的“暗能量”:一个自发缓慢振荡的活透镜。回复“暗脑能量:走向自发慢振荡的综合模型”评论
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-01-21 DOI: 10.1016/j.plrev.2026.01.007
Zhu-Qing Gong , Xi-Nian Zuo
In our target article “Dark Brain Energy: Toward an Integrative Model of Spontaneous Slow Oscillations”, we proposed a three-layer hierarchical framework to model the spontaneous slow oscillations (SSOs) across six frequency bands to delineate their spectral architecture, functional roles, and neurocognitive basis. We are grateful for the seven insightful commentary articles from colleagues across neuroscience, physics, mathematics, psychology and clinics, which collectively enrich our framework. In this review, we address five key themes emerging from and inspired by these commentaries: (1) the relationship between SSOs and consciousness, (2) the geometric foundations of SSOs, (3) evolutionary, developmental, and metabolic mechanisms of SSOs, (4) mathematical modeling of traveling waves underlying SSOs, and (5) neuroscientific implications for brain-inspired intelligence. We finally integrate these perspectives to refine our original model and outline future research directions.
在我们的目标文章“暗脑能量:走向自发慢振荡的综合模型”中,我们提出了一个三层分层框架来模拟六个频段的自发慢振荡(sso),以描绘它们的频谱结构、功能角色和神经认知基础。我们感谢来自神经科学、物理、数学、心理学和临床等领域的同事们发表的七篇富有洞察力的评论文章,它们共同丰富了我们的框架。在这篇综述中,我们将讨论从这些评论中产生并受到启发的五个关键主题:(1)SSOs与意识之间的关系,(2)SSOs的几何基础,(3)SSOs的进化、发育和代谢机制,(4)SSOs背后的行波的数学建模,以及(5)脑启发智能的神经科学意义。最后,我们整合这些观点来完善我们的原始模型,并概述未来的研究方向。
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引用次数: 0
Mnemonics, optimization, and leveraging what we already have: Comment on “To enhance or not to enhance: A debate about cognitive enhancement from a psychological and neuroscientific perspective” by Grinschgl, S., Ninaus, M., Wood, G., & Neubauer, A. C 助记法、优化和利用我们已有的东西:评论“增强还是不增强:从心理学和神经科学的角度讨论认知增强”,作者:Grinschgl, S.、Ninaus, M.、Wood, G.和Neubauer, A. C .
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-01-21 DOI: 10.1016/j.plrev.2026.01.008
Nicco Reggente , Theo Tobel , Michael Lifshitz
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引用次数: 0
Sirtuins as modulators of infection outcomes in host-pathogen dynamics, comment on "Sirtuins as modulators of infection outcomes in the battle of host-pathogen dynamics" Sirtuins作为宿主-病原体动力学感染结果的调节剂,评论“Sirtuins作为宿主-病原体动力学战斗中感染结果的调节剂”
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-01-20 DOI: 10.1016/j.plrev.2026.01.005
Yongzheng Han , Zunwen Zheng , Xinxiu Ren , Guangzhen Wu
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引用次数: 0
General integration theory of cognitive emergent: Comment on "Brain dynamics shape cognition–spatiotemporal neuroscience" by Georg Northoff, Angelika Wolman and Jianfeng Zhang 认知涌现的一般整合理论:评Georg Northoff、Angelika Wolman和张剑锋的“脑动力学塑造认知-时空神经科学”。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-01-20 DOI: 10.1016/j.plrev.2026.01.004
Feiyan Chen , Fan Liu , Jingcheng Wang , Rengqin Sun , Hongjian He , Xi-Nian Zuo
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引用次数: 0
Protein post-translational modifications in tumor immunity: a multi-layered regulatory network deserving systematic decoding Comment on “Protein post-translational modifications and tumor immunity: A pan-cancer perspective” 蛋白质翻译后修饰与肿瘤免疫:一个值得系统解码的多层调控网络
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-01-11 DOI: 10.1016/j.plrev.2026.01.001
Xiuluan Du , Yuansheng Lin
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引用次数: 0
Comment on " Protein post-translational modifications and tumor immunity: A pan-cancer perspective" “蛋白质翻译后修饰与肿瘤免疫:泛癌症视角”评论
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2026-01-07 DOI: 10.1016/j.plrev.2026.01.002
Yongzheng Han , Chengming Li , Yuanhua Qin , Guangzhen Wu
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引用次数: 0
Toward embodied and action-oriented studies and models of peripersonal space: Comment on “Computational models of peripersonal space representations” by Bertoni et al. 面向具体化和行动导向的周围个人空间研究和模型:评Bertoni等人的“周围个人空间表征的计算模型”。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2025-12-30 DOI: 10.1016/j.plrev.2025.12.009
Matej Hoffmann, Zdenek Straka
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引用次数: 0
On implementation of nonlocal terms in models in ecology and evolution. Comment on ‘Nonlocal models in biology and life sciences: Sources, developments, and applications’ by S. Pal & R. Melnick 生态学和进化中模型中非局部项的实现。对S. Pal和R. Melnick著的《生物学和生命科学中的非局部模型:来源、发展和应用》的评论
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2025-12-26 DOI: 10.1016/j.plrev.2025.12.013
Andrew Yu Morozov
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引用次数: 0
From Hierarchical Decoding to State Dependent Computation: “Comment on Neural decoding in brain computer interfaces Hierarchical representations, complexity measures, and dynamical perspectives” by Li et al. 从层次解码到状态依赖计算:《脑机接口中的神经解码评论》,作者:Li等。
IF 14.3 1区 生物学 Q1 BIOLOGY Pub Date : 2025-12-22 DOI: 10.1016/j.plrev.2025.12.014
Han Zhang , Jincan Che
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引用次数: 0
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Physics of Life Reviews
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