Evidence map›Paper›PMID 41889909›Full record

ArticlebioRxiv : the preprint server for biology2026

Automated Cyclic Super-Resolution Microscopy for Nanoscale Protein Mapping.

Hongqiang Ma, Chaojie Zhang, Shuyuan Zheng, Shengwei Chen, Yang Liu

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

5 authors.

Hongqiang MaDepartment of Bioengineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.ORCID 0000-0003-1967-3777
Chaojie ZhangDepartment of Bioengineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
Shuyuan ZhengDepartment of Bioengineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
Shengwei ChenDepartment of Bioengineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
Yang LiuDepartment of Bioengineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.

Funding

The Center for Label-free Imagingand Multiscale Biophotonics (CLIMB)P41EB031772 · NIBIB · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Stephen A Boppart · 2022 to 2026
$7.6M
Imaging nanoscale chromatin folding in early carcinogenesisR01CA254112 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LIU, YANG · 2020 to 2025
$2.2M
Ultrahigh-throughput imaging of 3D tumor microenvironment at nanoscaleR01CA301488 · NCI · CARNEGIE-MELLON UNIVERSITY · PI Yang Liu, Hongqiang Ma · 2025 to 2026
$1.2M
NCI NIH HHS R01 CA254112NCI NIH HHS R01 CA301488NIBIB NIH HHS P41 EB031772
6 · The paper itself

Abstract

Nanoscale mapping of multiple molecular targets is essential for decoding cellular architecture, but current approaches are limited by low throughput, intensive manual intervention, and signal variability across imaging cycles. Here, we introduce CycSTORM, an integrated super-resolution imaging platform for automated cyclic (d)STORM that enables multiplexed nanoscale protein mapping in single cells. To overcome the instability inherent in multi-day imaging, CycSTORM combines automated fluidic exchange, active 3D drift correction, and an oxygen-excluded imaging environment to stabilize fluorophore blinking and enables sub-5 nm registration across day-long experiments. Furthermore, CycSTORM incorporates a rapid chemical inactivation step using meta-chloroperoxybenzoic acid (mCPBA), eliminating >99.9% residual fluorescence within 10 minutes and minimizing inter-cycle crosstalk while preserving sample integrity. By standardizing labeling to Alexa Fluor 647, a fluorophore with stable and well-characterized blinking behavior, CycSTORM minimizes fluorophore-dependent variation and provides a robust platform for consistent localization precision across cycles, enabling reliable mapping of protein organization in single cells. Using CycSTORM, we simultaneously map multiple protein targets within the same cells with nanometer precision. Together, these advances transform cyclic super-resolution imaging into a scalable approach for quantitative nanoscale mapping of molecular organization in single cells.

Identifiers

PMID41889909
PMCPMC13015466

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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.