Evidence map›Paper›PMID 23811936›Full record

ReviewCellular and molecular life sciences : CMLS2014

Joining S100 proteins and migration: for better or for worse, in sickness and in health.

Stephane R Gross, Connie Goh Then Sin, Roger Barraclough, Philip S Rudland

Open access · greenAbstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
6.3field-weighted citation impact, top 3% 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

114 citing papers in PubMed, 185 citations in OpenAlex.

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  13. Single-cell transcriptomics identifies anFrontiers in molecular biosciences · 2025
    Article
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  16. Translational cancer research · 2024
    Article
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54 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Stephane R GrossSchool of Life and Health Sciences, Aston University, Aston Triangle, Birmingham, B4 7ET, UK, s.r.gross@aston.ac.uk.
Connie Goh Then Sin
Roger Barraclough
Philip S Rudland
Aston University · GBUniversity of Liverpool · GB

Funding

Medical Research Council G0801447
6 · The paper itself

Abstract

The vast diversity of S100 proteins has demonstrated a multitude of biological correlations with cell growth, cell differentiation and cell survival in numerous physiological and pathological conditions in all cells of the body. This review summarises some of the reported regulatory functions of S100 proteins (namely S100A1, S100A2, S100A4, S100A6, S100A7, S100A8/S100A9, S100A10, S100A11, S100A12, S100B and S100P) on cellular migration and invasion, established in both culture and animal model systems and the possible mechanisms that have been proposed to be responsible. These mechanisms involve intracellular events and components of the cytoskeletal organisation (actin/myosin filaments, intermediate filaments and microtubules) as well as extracellular signalling at different cell surface receptors (RAGE and integrins). Finally, we shall attempt to demonstrate how aberrant expression of the S100 proteins may lead to pathological events and human disorders and furthermore provide a rationale to possibly explain why the expression of some of the S100 proteins (mainly S100A4 and S100P) has led to conflicting results on motility, depending on the cells used.

Indexed as

AnimalsCell DifferentiationCell MovementCell ProliferationHumansIntegrinsMicroRNAsMitogen-Activated Protein KinasesS100 ProteinsIntegrinsMicroRNAsMitogen-Activated Protein KinasesS100 Proteins

Identifiers

PMID23811936
PMCPMC11113901
OpenAlexW2066749848

What OpenQuestion holds

Textmetadata
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.