Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 985

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

PTEN deletion enhances the regenerative ability of adult corticospinal neurons

Open access
Liu, Kai, Lu, Yi, Lee, Jae K, Samara, Ramsey, Willenberg, Rafer, Sears-Kraxberger, Ilse, Tedeschi, Andrea, Park, Kevin Kyungsuk, Jin, Duo, Cai, Bin, Xu, Bengang, Connolly, Lauren, Steward, Oswald, Zheng, Binhai, He, Zhigang·2010·Nature Neuroscience

Abstract

Despite the essential role of the corticospinal tract (CST) in controlling voluntary movements, successful regeneration of large numbers of injured CST axons beyond a spinal cord lesion has never been achieved. We found that PTEN/mTOR are critical for controlling the regenerative capacity of mouse corticospinal neurons. After development, the regrowth potential of CST axons was lost and this was accompanied by a downregulation of mTOR activity in corticospinal neurons. Axonal injury further diminished neuronal mTOR activity in these neurons. Forced upregulation of mTOR activity in corticospinal neurons by conditional deletion of Pten, a negative regulator of mTOR, enhanced compensatory sprouting of uninjured CST axons and enabled successful regeneration of a cohort of injured CST axons past a spinal cord lesion. Furthermore, these regenerating CST axons possessed the ability to reform synapses in spinal segments distal to the injury. Thus, modulating neuronal intrinsic PTEN/mTOR activity represents a potential therapeutic strategy for promoting axon regeneration and functional repair after adult spinal cord injury.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nn.2603

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 1 references

Cited by

Metadata

Authors
Liu, K., Lu, Y., Lee, J. K., Samara, R., Willenberg, R., Sears-Kraxberger, I., Tedeschi, A., Park, K. K., Jin, D., Cai, B., Xu, B., Connolly, L., Steward, O., Zheng, B., & He, Z.
Venue
Nature Neuroscience
Published
2010-08-08
Volume
13
Issue
9
Pages
1075-1081
ISSN
  • 1097-6256 (ISSN-L)
  • 1546-1726
OpenAlex
W2094215712
Cited by
985
References
1
FWCI
19.08
Type
journal article
Language
en
Open access
green

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

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.