ReviewCurrent opinion in structural biology2025
Advances in automation for cryo-electron tomography data collection.
Review in Current opinion in structural biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
2 authors.
Funding
Abstract
Cryo-electron microscopy has become the preferred method for determining structures of macromolecular complexes both in isolation, using single particle analysis, and in their cellular contexts, using cryo-electron tomography (Cryo-ET) combined with subvolume averaging (SVA). Collection of tilt series for Cryo-ET introduces challenges such as low signal-to-noise ratios, sample radiation sensitivity, and mechanical imprecision of the microscope stage - particularly at high magnifications. Strategies to improve throughput and resolution include continuous tilt and beam-image-shift parallel acquisition, real-time predictive adjustments, and machine learning-driven targeting. Additionally, montage tomography has increased the observable cellular area, while innovations like rectangular condenser apertures promise improved dose efficiency. Web-based and machine learning-enhanced solutions for automated and remote microscope operation are improving the user experience. Collectively, these advancements represent a critical step towards robust, high-resolution, and user-friendly Cryo-ET, facilitating the visualization of macromolecular assemblies within their authentic biological environments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.