Evidence map›Paper›PMID 41229410›Full record

ArticlePNAS nexus2025

Single-fibril Förster resonance energy transfer imaging and deep learning reveal concentration dependence of amyloid β 42 aggregation pathways.

Sara H Sohail, Janghyun Yoo, Hoi Sung Chung

Abstract read
In one paragraph

Article in PNAS nexus, 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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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

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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

3 authors.

Sara H SohailLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, USA.ORCID https://orcid.org/0000-0003-2640-1745
Janghyun YooLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, USA.ORCID https://orcid.org/0000-0002-2330-4053
Hoi Sung ChungLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, USA.ORCID https://orcid.org/0000-0001-6897-4969

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyloid fibril formation is a highly heterogeneous process as evidenced by polymorphism in fibril structure. It has been suggested that different polymorphs are associated with different diseases or disease subtypes. Detailed characterization of this heterogeneity is a key to understanding the aggregation mechanism and, possibly, the disease mechanism. In this work, we develop Förster resonance energy transfer (FRET) imaging of amyloid fibril formation in real time and investigate the concentration-dependent heterogeneous fibril formation of amyloid β 42 (Aβ42). We incubated a mixture of unlabeled and labeled (5% donor and 5% acceptor) Aβ42, followed aggregation, and characterized individual fibrils in terms of FRET efficiency, acceptor fluorescence lifetime, and stoichiometry of the donor- and acceptor-labeled monomers incorporated into the fibrils. By FRET efficiency, we found that there are two distinct species at a relatively low concentration, 2 μM. The high FRET species appears first, but the low FRET species becomes dominant at later times. On the other hand, the high FRET species dominates throughout aggregation at 4 μM. The broad FRET efficiency distributions are consistent with those calculated from various known fibril structures. In addition to the FRET efficiencies, different acceptor lifetimes at the two concentrations and broad acceptor density distributions indicate at least three structurally distinct fibril species exist at each concentration, which also differ between the two different concentrations. The distinct heterogeneity in fibril formation pathways depending on the monomer concentration highlights the importance of understanding heterogeneity in the context of the biologically relevant aggregation environment.

Indexed as

amyloid βfibril polymorphprotein aggregationsingle-molecule fluorescence imaging

Identifiers

PMID41229410
PMCPMC12604471

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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.