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Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches 1 – 6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations 7 – 14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems. The authors introduce a single-molecule DNA-barcoding method, resolution enhancement by sequential imaging, that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents.

This Review introduces the fundamental considerations for building a light sheet microscope, describes the pros and cons associated with available implementations, and offers practical advice for users. The impact of light-sheet fluorescence microscopy (LSFM) is visible in fields as diverse as developmental and cell biology, anatomical science, biophysics and neuroscience. Although adoption among biologists has been steady, LSFM has not displaced more traditional imaging methods despite its often-superior performance. One reason for this is that the field has largely conformed to a do-it-yourself ethic, although the challenges of big image data cannot be overstated. With the most powerful implementations of LSFM available to only a few groups worldwide, the scope of this technique is unnecessarily limited. Here we elucidate the key developments and define a simple set of underlying principles governing LSFM. In doing so, we aim to clarify the decisions to be made for those who wish to develop and use bespoke light-sheet systems and to assist in identifying the best approaches to apply this powerful technique to myriad biological questions.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

More fields should, like particle physics, adopt blind analysis to thwart bias, urge Robert MacCoun and Saul Perlmutter.

Recent developments within micro-computed tomography (μCT) imaging have combined to extend our capacity to image tissue in three (3D) and four (4D) dimensions at micron and sub-micron spatial resolutions, opening the way for virtual histology, live cell imaging, subcellular imaging and correlative microscopy. Pivotal to this has been the development of methods to extend the contrast achievable for soft tissue. Herein, we review the new capabilities within the field of life sciences imaging, and consider how future developments in this field could further benefit the life sciences community.

The reliability of experimental findings depends on the rigour of experimental design. Here we show limited reporting of measures to reduce the risk of bias in a random sample of life sciences publications, significantly lower reporting of randomisation in work published in journals of high impact, and very limited reporting of measures to reduce the risk of bias in publications from leading United Kingdom institutions. Ascertainment of differences between institutions might serve both as a measure of research quality and as a tool for institutional efforts to improve research quality.

We develop a model describing how false paradigms may persist, hindering scientific progress. The model features two paradigms, one describing reality better than the other. Tenured scientists display homophily: They favor tenure candidates who adhere to their paradigm. As in statistics, power is the probability (absent any bias) of denying tenure to scientists adhering to the false paradigm. The model shows that because of homophily, when power is low, the false paradigm may prevail. Then, only an increase in power can ignite convergence to the true paradigm. Historical case studies suggest that low power comes either from lack of empirical evidence or from reluctance to base tenure decisions on available evidence.

Multiphoton microscopy (MPM) has found a niche in the world of biological imaging as the best noninvasive means of fluorescence microscopy in tissue explants and living animals. Coupled with transgenic mouse models of disease and 'smart' genetically encoded fluorescent indicators, its use is now increasing exponentially. Properly applied, it is capable of measuring calcium transients 500 μm deep in a mouse brain, or quantifying blood flow by imaging shadows of blood cells as they race through capillaries. With the multitude of possibilities afforded by variations of nonlinear optics and localized photochemistry, it is possible to image collagen fibrils directly within tissue through nonlinear scattering, or release caged compounds in sub-femtoliter volumes.

The increasing complexity of life science research requires laboratory tools that combine precision, automation, and accessibility. Conventional liquid handling and imaging systems are either separated or integrated at high cost, limiting their adoption in small-scale laboratories. Here we show that G-Bot, a compact five-axis platform, integrates automated liquid handling, live-cell imaging, and real-time data processing into a single system. G-Bot performs complex workflows, e.g., including cell seeding, drug dosing, media exchange, and long-term live-cell imaging, while maintaining stable culture conditions through integrated incubator and stage-top regulation modules. Its imaging capabilities span cells, organoids, and small organisms such as zebrafish larvae, providing high-content, physiologically relevant data. Unlike pipette-based systems, G-Bot employs a tubing-based dispensing mechanism for precise reagent delivery with minimal waste. By unifying liquid handling, imaging, and analysis, G-Bot streamlines laboratory-scale workflows, improves reproducibility, and bridges the gap between manual methods and costly industrial automation, offering broad utility in research and drug discovery. Avci and colleagues present G-Bot, a compact and affordable technology that combines automated liquid handling, incubator control, and real-time imaging, enabling precise and user-friendly biological experiments for small-scale laboratories.