Evidence map›Paper›PMID 38781327›Full record

ArticleScience advances2024

Toward drift-free high-throughput nanoscopy through adaptive intersection maximization.

Hongqiang Ma, Maomao Chen, Phuong Nguyen, Yang Liu

Abstract read
In one paragraph

Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. A Versatile Drift-Free Super-Resolution Imaging Method via Oblique Bright-Field Correlation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  15. Article
  16. Article
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

4 authors.

Hongqiang MaDepartment of Medicine, Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.ORCID 0000-0003-1967-3777
Maomao ChenDepartment of Medicine, Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.ORCID 0000-0003-3692-1138
Phuong NguyenDepartment of Medicine, Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.ORCID 0000-0001-9170-9303
Yang LiuDepartment of Medicine, Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.ORCID 0000-0002-6388-9674

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
Three dimensional nanoscale nuclear architecture mapping based taxonomy of precursor lesions for predicting colorectal cancer riskR01CA232593 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LIU, YANG, UTTAM, SHIKHAR · 2019 to 2023
$2.1M
Super-Resolution Imaging of Higher-Order Heterochromatin Structure for Early Detection of Lung CarcinogenesisR21CA259787 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI STABILE, LAURA P. · 2022 to 2023
$404k
NCI NIH HHS R01 CA232593NCI NIH HHS R01 CA254112NCI NIH HHS R21 CA259787NIBIB NIH HHS P41 EB031772
6 · The paper itself

Abstract

Single-molecule localization microscopy (SMLM) often suffers from suboptimal resolution due to imperfect drift correction. Existing marker-free drift correction algorithms often struggle to reliably track high-frequency drift and lack the computational efficiency to manage large, high-throughput localization datasets. We present an adaptive intersection maximization-based method (AIM) that leverages the entire dataset's information content to minimize drift correction errors, particularly addressing high-frequency drift, thereby enhancing the resolution of existing SMLM systems. We demonstrate that AIM can robustly and efficiently achieve an angstrom-level tracking precision for high-throughput SMLM datasets under various imaging conditions, resulting in an optimal resolution in simulated and biological experimental datasets. We offer AIM as one simple, model-free software for instant resolution enhancement with standard CPU devices.

Identifiers

PMID38781327
PMCPMC11114195

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.