Evidence map›Paper›PMID 26774039›Full record

ArticleMathematical biosciences2016

Determination of critical nucleation number for a single nucleation amyloid-β aggregation model.

Preetam Ghosh, Ashwin Vaidya, Amit Kumar, Vijayaraghavan Rangachari

Abstract read
In one paragraph

Article in Mathematical biosciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

15 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Molecular Mechanism and Kinetics of Amyloid-βACS chemical neuroscience · 2019
    Article
  12. Article
  13. Amyloidogenesis of Tau protein.Protein science : a publication of the Protein Society · 2017
    Review
  14. Article
  15. 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 at 4 institutions in 2 countries.

Preetam GhoshDepartment of Computer Science, Virginia Commonwealth University, Richmond, Virginia, USA.
Ashwin VaidyaDepartment of Mathematical Science, Montclair State University, Montclair, New Jersey, USA.
Amit KumarDepartment of Chemistry and Biochemistry, University of Southern Mississippi, Hattiesburg, Mississippi, USA ; Department of Protein Evolution, Max Planck Institute for Developmental Biology, D-72076 Tübingen, Germany.
Vijayaraghavan RangachariDepartment of Chemistry and Biochemistry, University of Southern Mississippi, Hattiesburg, Mississippi, USA . Electronic address: Vijay.rangachari@usm.edu.
Max Planck Institute for Developmental Biology · DEMontclair State University · USUniversity of Southern Mississippi · USVirginia Commonwealth University · US

Funding

Training and Mentoring Core P20GM103476 · NIGMS · UNIVERSITY OF SOUTHERN MISSISSIPPI · PI Vijay Rangachari · 2012 to 2026
$60.2M
TOUGALOO PROTEOMICSP20RR016476 · NCRR · UNIVERSITY OF SOUTHERN MISSISSIPPI · PI KRAMER, WOLFGANG · 2001 to 2011
$30.4M
NCRR NIH HHS 5P20RR016476-11NCRR NIH HHS P20 RR016476NIGMS NIH HHS 8P20GM103476-11NIGMS NIH HHS P20 GM103476
6 · The paper itself

Abstract

Aggregates of amyloid-β (Aβ) peptide are known to be the key pathological agents in Alzheimer disease (AD). Aβ aggregates to form large, insoluble fibrils that deposit as senile plaques in AD brains. The process of aggregation is nucleation-dependent in which the formation of a nucleus is the rate-limiting step, and controls the physiochemical fate of the aggregates formed. Therefore, understanding the properties of nucleus and pre-nucleation events will be significant in reducing the existing knowledge-gap in AD pathogenesis. In this report, we have determined the plausible range of critical nucleation number (n(*)), the number of monomers associated within the nucleus for a homogenous aggregation model with single unique nucleation event, by two independent methods: A reduced-order stability analysis and ordinary differential equation based numerical analysis, supported by experimental biophysics. The results establish that the most likely range of n(*) is between 7 and 14 and within, this range, n(*) = 12 closely supports the experimental data. These numbers are in agreement with those previously reported, and importantly, the report establishes a new modeling framework using two independent approaches towards a convergent solution in modeling complex aggregation reactions. Our model also suggests that the formation of large protofibrils is dependent on the nature of n(*), further supporting the idea that pre-nucleation events are significant in controlling the fate of larger aggregates formed. This report has re-opened an old problem with a new perspective and holds promise towards revealing the molecular events in amyloid pathologies in the future.

Indexed as

Models, MolecularAlzheimer DiseaseAmyloid beta-PeptidesBrainComputer SimulationHumansMathematical ConceptsProtein AggregatesProtein Aggregation, PathologicalProtein StabilityAmyloid beta-PeptidesProtein AggregatesAggregationAmyloid-βNucleationOligomersSimulationStability analysis

Identifiers

PMID26774039
PMCPMC4822416
OpenAlexW2231120016

What OpenQuestion holds

Textmetadata
LicenceTDM
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.