Evidence map›Paper›PMID 37426747›Full record

ArticleCell reports methods2023

A computational suite for the structural and functional characterization of amyloid aggregates.

Zengjie Xia, Yunzhao Wu, Jeff Yui Long Lam, Ziwei Zhang, Melanie Burke, Emre Fertan, Rohan T Ranasinghe, Eric Hidari, John S H Danial, David Klenerman

Abstract read
In one paragraph

Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
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  4. Lecanemab preferentially binds to smaller aggregates present at early Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  5. Article
  6. Article
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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

10 authors.

Zengjie XiaYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Yunzhao WuYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Jeff Yui Long LamYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Ziwei ZhangYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Melanie BurkeYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Emre FertanYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Rohan T RanasingheYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Eric HidariYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
John S H DanialYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
David KlenermanYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.

Funding

Medical Research Council
6 · The paper itself

Abstract

We developed the aggregate characterization toolkit (ACT), a fully automated computational suite based on existing and widely used core algorithms to measure the number, size, and permeabilizing activity of recombinant and human-derived aggregates imaged with diffraction-limited and super-resolution microscopy methods at high throughput. We have validated ACT on simulated ground-truth images of aggregates mimicking those from diffraction-limited and super-resolution microscopies and showcased its use in characterizing protein aggregates from Alzheimer's disease. ACT is developed for high-throughput batch processing of images collected from multiple samples and is available as an open-source code. Given its accuracy, speed, and accessibility, ACT is expected to be a fundamental tool in studying human and non-human amyloid intermediates, developing early disease stage diagnostics, and screening for antibodies that bind toxic and heterogeneous human amyloid aggregates.

Indexed as

Alzheimer DiseaseProtein AggregatesAlgorithmsAmyloidAmyloidogenic ProteinsHumansAmyloidAmyloidogenic ProteinsProtein Aggregatesanalysis automationfluorescence microscopyImage processingneurodegenerative diseaseprotein aggregate characterisationsuper-resolution imaging

Identifiers

PMID37426747
PMCPMC10326375

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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.