The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
IGF-I receptor signalling in transformation and differentiation
Open accessAbstract
The type 1 insulin-like growth factor receptor (IGF-IR) sends several signals, some of which are contradictory. When the concentrations of insulin receptor substrate 1 (IRS-1), a major substrate of the IGF-IR, are high, the signal is mitogenic, anti-apoptotic, and can even cause malignant transformation. However, in the absence of IRS-1, the IGF-IR sends a differentiation signal, which leads to granulocytic differentiation in haemopoietic cells. The mitogenic signal of the IGF-IR/IRS-1 combination depends largely, but not exclusively, on the activation of the phosphatidylinositol-3 kinase (PI3K).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ribosomal S6 Kinase Signaling and the Control of Translation
Dufner, A., & Thomas, G. (1999) · Experimental Cell Research · doi:10.1006/excr.1999.4683 · Cited by 676
Cited by
Insulin-like growth factors and cancer
Fürstenberger, G., & Senn, H.-J. (2002) · The Lancet Oncology · doi:10.1016/s1470-2045(02)00731-3 · Cited by 536
Al-Nasiry, S., Geusens, N., Hanssens, M., Luyten, C., & Pijnenborg, R. (2007) · Human Reproduction · doi:10.1093/humrep/dem011 · Cited by 486
Prieur, A., Tirode, F., Cohen, P., & Delattre, O. (2004) · Molecular and Cellular Biology · doi:10.1128/mcb.24.16.7275-7283.2004 · Cited by 420
Targeting of the protein interaction site between FAK and IGF-1R
Zheng, D., Kurenova, E., Ucar, D., Golubovskaya, V., Magis, A., Ostrov, D., Cance, W. G., & Hochwald, S. N. (2009) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2009.07.156 · Cited by 30
Metadata
- Authors
- Valentinis, B., & Baserga, R.
- Venue
- Molecular Pathology
- Publisher
- BMJ
- Published
- 2001-06
- Volume
- 54
- Issue
- 3
- Pages
- 133-137
- ISSN
- 1366-8714 (ISSN-L)
- 1472-4154
- OpenAlex
- W2018697055
- Cited by
- 323
- References
- 1
- FWCI
- 14.31
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: IGF-I receptor signalling in transformation and differentiation. https://app.cochat.ai/papers/10.1136/mp.54.3.133
- The paper
- Valentinis, B., & Baserga, R. (2001). IGF-I receptor signalling in transformation and differentiation. Molecular Pathology. https://doi.org/10.1136/mp.54.3.133
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
