Evidence map›Paper›PMID 41648511›Full record

ArticlebioRxiv : the preprint server for biology2026

Gradient based refinement of CryoET tilt series alignment improves tomogram contrast and structure resolution.

Muyuan Chen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Muyuan ChenDivision of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA 94025, USA.

Funding

Comprehensive analysis of macromolecule structural variability in CryoEM/CryoETR01GM150905 · NIGMS · STANFORD UNIVERSITY · PI Muyuan Chen · 2023 to 2026
$1.5M
NIGMS NIH HHS R01 GM150905
6 · The paper itself

Abstract

Cryogenic electron tomography (CryoET) provides 3D views of vitrified cellular samples, and protein structures can be determined from the tomograms by averaging many copies of the same protein computationally. However, the resolution of these averaged structures, particularly for smaller proteins, is often constrained by the precision of tilt-series alignment. In this study, we introduce a gradient descent-based approach to refine alignment parameters, enhancing the contrast in tomograms of the sample regions. This refinement not only improves contrast but also yields higher-resolution protein structures derived from the same particle populations.

Identifiers

PMID41648511
PMCPMC12871777

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Registered trials

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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.