Journal of microscopy最新文献

Focus on the methods reproducibility of bioimage analysis. 重点介绍生物图像分析方法的再现性。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-19 DOI: 10.1111/jmi.70188

Kota Miura, Christa Walther, Elnaz Fazeli, Agustin Corbat, Paula Sampaio, Rocco D'Antuono

引用次数: 0

Introduction to the Festschrift for Guy Christopher Cox. 盖伊·克里斯托弗·考克斯的节日简介。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-15 DOI: 10.1111/jmi.70189

Louise Cole, Colin Sheppard

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Pushing the limits of atomic force microscopy: Emerging methods for speed, resolution, and quantitative analysis. 推动原子力显微镜的极限：速度、分辨率和定量分析的新兴方法。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-15 DOI: 10.1111/jmi.70191

Yueqi Wang, Daniel E Rollins, Varun Gupta, Maya Tekchandani, Bashra A Mahamed, George R Heath

{"title":"Pushing the limits of atomic force microscopy: Emerging methods for speed, resolution, and quantitative analysis.","authors":"Yueqi Wang, Daniel E Rollins, Varun Gupta, Maya Tekchandani, Bashra A Mahamed, George R Heath","doi":"10.1111/jmi.70191","DOIUrl":"https://doi.org/10.1111/jmi.70191","url":null,"abstract":"Since its introduction 40 years ago, atomic force microscopy (AFM) has transformed nanoscale imaging across the physical and life sciences. In biology, AFM has provided unprecedented insights into nanoscale biomolecular organisation under near-physiological conditions, revealing structures and interactions inaccessible to many conventional approaches. However, biological function is inherently dynamic, and understanding molecular mechanisms requires moving beyond static structural snapshots towards direct observation of processes across multiple spatial and temporal scales. In this review, we discuss emerging approaches that are extending the capabilities of AFM beyond traditional imaging, pushing the limits of temporal resolution, spatial precision, quantitative measurement, and data analysis. We highlight advances in speed that enable direct visualisation of molecular dynamics, approaches for sub-millisecond measurements, methods that overcome conventional resolution limits, and computational approaches that enhance image analysis, automation, and information extraction from complex datasets. Together, these developments are transforming AFM from a technique focused primarily on high-resolution structural imaging into a platform for dynamic, quantitative, and high-throughput investigation of biological systems. Finally, we consider how these advances may shape the next 40 years of AFM, enable autonomous measurements and reveal biological mechanisms across previously inaccessible spatial and temporal scales.","PeriodicalId":16484,"journal":{"name":"Journal of microscopy","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149194393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reviewing reproducibility and replicability in 'Deconstructing gastrulation at single-cell resolution' by Stern et al. (2022). 回顾Stern等人（2022）在“以单细胞分辨率解构原肠胚”中的再现性和可复制性。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-13 DOI: 10.1111/jmi.70132

Gabriel G Martins, Haydee O Hernández, Lachlan Whitehead, Pradeep Rajasekhar

{"title":"Reviewing reproducibility and replicability in 'Deconstructing gastrulation at single-cell resolution' by Stern et al. (2022).","authors":"Gabriel G Martins, Haydee O Hernández, Lachlan Whitehead, Pradeep Rajasekhar","doi":"10.1111/jmi.70132","DOIUrl":"https://doi.org/10.1111/jmi.70132","url":null,"abstract":"Quantitative analysis of embryonic morphogenesis often requires handling terabyte-scale 4D microscopy datasets, posing major computational and methodological challenges. Such analyses involve complex workflows for image restoration, segmentation, and tracking of thousands of cells in 3D, sometimes assembled from multiple generic tools and custom scripts. In their study 'Deconstructing gastrulation at single-cell resolution,' the authors present an integrated computational framework for cell segmentation, tracking and modelling of cell-cell interactions during Drosophila gastrulation. Their approach combines both generic tools such as ilastik, FIJI, Cellpose, MATLAB code and tools such as ImSAnE to reconstruct whole-embryo, single-cell morphogenetic atlas with unprecedented detail. While the methodology is transparent and well-documented, its implementation relies on multiple software environments and some non-open-source components, limiting full reproducibility and generalisability. Nevertheless, their 'computational framework' exemplifies rigorous data sharing, clear documentation, and methodological transparency aligned with several community guidelines for reproducible image analysis. We discuss this work in the context of reproducibility, replicability, generalisability, transparency, validity, and robustness, emphasising how emerging open-source and popular solutions could improve accessibility and replicability of similar large-scale bioimage analysis workflows in developmental biology.","PeriodicalId":16484,"journal":{"name":"Journal of microscopy","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149182548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electron spin resonance in scanning probe microscopy: From single-spin spectroscopy to atomically engineered quantum operations. 扫描探针显微镜中的电子自旋共振：从单自旋光谱学到原子工程量子操作。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-10 DOI: 10.1111/jmi.70187

Deung-Jang Choi

{"title":"Electron spin resonance in scanning probe microscopy: From single-spin spectroscopy to atomically engineered quantum operations.","authors":"Deung-Jang Choi","doi":"10.1111/jmi.70187","DOIUrl":"https://doi.org/10.1111/jmi.70187","url":null,"abstract":"Electron spin resonance (ESR) is one of the most powerful spectroscopic methods for probing systems with unpaired electronic spins. Conventional ESR has usually relied on the detection of large spin ensembles, thereby averaging over local environments and suppressing microscopic information that is central to surface science, molecular magnetism, and quantum nanoscience. Scanning probe microscopy (SPM) changes this situation. By combining magnetic resonance with the spatial resolution and manipulation capabilities of scanning tunnelling microscopy (STM) and atomic force microscopy (AFM), ESR can now be performed on individual atoms and molecules on surfaces. This short perspective discusses three connected developments. First, ESR-STM has enabled all-electrical detection and coherent control of individual spins with atomic precision. Second, ESR-AFM has recently provided a complementary route to single-molecule spin resonance based on force-detected pump-probe protocols. Third, these advances are turning surface spins into atomically engineered quantum systems in which spin Hamiltonians, interactions, sensing architectures, and elementary quantum operations can be designed locally. The resulting field does not merely miniaturise conventional ESR; it transforms magnetic resonance into a local quantum tool for spectroscopy, sensing, and coherent manipulation at the atomic scale.","PeriodicalId":16484,"journal":{"name":"Journal of microscopy","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149167456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiscale mechanical analysis of live breast cancer spheroids by micro-compression and Brillouin imaging. 微压缩和布里渊成像技术对乳腺癌活体球体的多尺度力学分析。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-10 DOI: 10.1111/jmi.70185

Ashutosh Khaswal, Hadi Mahmodi, Ellie Mok, Thomas R Cox, Irina Kabakova

引用次数: 0

AFM-based nanomechanical mapping and mechanobiology, two unforeseen fields that have lifted each other up. 基于原子力显微镜的纳米机械制图和机械生物学，这两个不可预见的领域相互提升。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-09 DOI: 10.1111/jmi.70183

Núria Gavara

引用次数: 0

Quantum optical properties of solid-state defects using stage scanning confocal microscopy 利用级扫描共聚焦显微镜研究固态缺陷的量子光学特性。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-07 Epub Date: 2026-09-16 DOI: 10.1111/jmi.70172

Nitesh Singh, Rajesh V. Nair

{"title":"Quantum optical properties of solid-state defects using stage scanning confocal microscopy","authors":"Nitesh Singh, Rajesh V. Nair","doi":"10.1111/jmi.70172","DOIUrl":"10.1111/jmi.70172","url":null,"abstract":"Solid-state quantum emitters (QEs) at room temperature are central to emerging technologies in quantum computing, communication, and sensing. These atomic-scale defects require high-resolution spatial and spectral characterisation to study their photophysical behaviour. To address this, we developed a stage-scanning confocal microscopy system optimised for nanoscale mapping and single photon level investigations of QEs in diverse host materials, fully automated and controlled via custom LabVIEW software. The system features high-precision three-axis translation stages with nanometre resolution, enabling accurate spatial scanning. A high numerical aperture (NA) objective lens ensures diffraction-limited optical resolution, while integrated photon-counting modules allow for sensitive detection of photoluminescence signals. The platform supports various spectroscopic measurements, including frequency-resolved and time-resolved photoluminescence. The system incorporates a Hanbury Brown and Twiss (HBT) interferometer for second-order temporal autocorrelation measurements to verify single photon emission. Designed for versatility, the system can accommodate a broad range of QE materials, including organic dye molecules, perovskites, and inorganic semiconductors. Furthermore, the setup enables the study of emission engineering through the manipulation of the local density of optical states, supported by the ability to collect large-scale statistical datasets. Overall, the flexibility and robustness of the platform make it ideal for quantum photonic, supporting fundamental studies and practical device development.","PeriodicalId":16484,"journal":{"name":"Journal of microscopy","volume":"304 1","pages":"51-64"},"PeriodicalIF":1.9,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148977056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modular training resources for bioimage analysis 生物图像分析的模块化培训资源。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-07 Epub Date: 2026-06-18 DOI: 10.1111/jmi.70133

Christian Tischer, Antonio Zaccaria Politi, Tim-Oliver Buchholz, Elnaz Fazeli, Nicola Gritti, Aliaksandr Halavatyi, Sebastián González-Tirado, Julian Hennies, Toby Hodges, Arif Khan, Dominik Kutra, Stefania Marcotti, Bugra Oezdemir, Felix Schneider, Martin Schorb, Anniek Stokkermans, Yi Sun, Nima Vakili

{"title":"Modular training resources for bioimage analysis","authors":"Christian Tischer, Antonio Zaccaria Politi, Tim-Oliver Buchholz, Elnaz Fazeli, Nicola Gritti, Aliaksandr Halavatyi, Sebastián González-Tirado, Julian Hennies, Toby Hodges, Arif Khan, Dominik Kutra, Stefania Marcotti, Bugra Oezdemir, Felix Schneider, Martin Schorb, Anniek Stokkermans, Yi Sun, Nima Vakili","doi":"10.1111/jmi.70133","DOIUrl":"10.1111/jmi.70133","url":null,"abstract":"Modern microscopy enables us to measure structural and dynamical properties of many biological processes and is therefore an indispensable research tool. However, the amount and complexity of the produced imaging data is steadily increasing. Thus, handling the data as well as reproducibly and automatically extracting accurate scientific information require dedicated ‘bioimage analysis’ expertise. To facilitate the dissemination of this ubiquitously required expertise we developed an open-access bioimage analysis training resource. The resource is designed to help trainers to design and run courses on bioimage analysis for life scientists. The material is modular where each module covers one concise topic and provides corresponding activities using microscopy images from biological samples. The activities can be executed using various popular software packages (e.g. ImageJ, Python). The material is hosted on a public software repository allowing the bioimaging community to readily contribute new training modules or improve existing modules. Within the last 3 years, the material has been used by several trainers in numerous courses and continuously improved.","PeriodicalId":16484,"journal":{"name":"Journal of microscopy","volume":"304 1","pages":"3-14"},"PeriodicalIF":1.9,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jmi.70133","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148271935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Microscopy image segmentation using a fine-tuned machine learning model with limited training dataset 显微镜图像分割使用微调机器学习模型与有限的训练数据集。

IF 1.9 4区工程技术

Journal of microscopy Pub Date : 2026-10-07 Epub Date: 2026-08-31 DOI: 10.1111/jmi.70162

Sooyong Chae, Dani Giammattei, Ajmal Ajmal, Junzhu Pei, Amanda Sanchez, Tananant Boonya-ananta, Andres Rodriguez, Jessica C. Ramella-Roman, Tatiana Novikova

引用次数: 0