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Record W2078500394 · doi:10.1126/sageke.2002.19.nw65

Unnerved: Molecule that pumps neurons up also keeps them down (Neurodegeneration)

2002· article· en· W2078500394 on OpenAlexaboutno aff
Kendall Morgan

Bibliographic record

VenueScience of Aging Knowledge Environment · 2002
Typearticle
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsnot available
Fundersnot available
KeywordsLow-affinity nerve growth factor receptorNeurotrophinNeuroscienceReceptorRegeneration (biology)Nerve growth factorCell biologyBiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Like a tree that has been chopped down to its roots, damaged nerves often refuse to grow back. Earlier work identified a molecule, myelin-associated glycoprotein (MAG), that impedes a nerve's comeback. MAG's method of delivering the nerve-stunting message--which might keep normal cells from growing out of control--has remained a mystery, however. Now, researchers have pinpointed a cell surface molecule called p75 as the transmitter of MAG's signal. The finding suggests a way to foster nerve regeneration after injury. Although its collaboration with MAG eluded researchers until now, p75 earned fame previously for an opposite role: spurring nerve cell growth. It acts as a receptor, sensing signals outside cells and conveying their messages to the inside. Neurons are covered with the receptor during embryonic development when they begin to reach out to other nerve cells; chemicals called neurotrophins encourage nerves to sprout by goading p75 into action. Three years ago, researchers found that nerve cells doused with neurotrophins overcame MAG's power to squelch growth. To Yamashita and colleagues, the finding hinted at a connection between p75 and MAG. Perhaps MAG has nowhere to go when neurotrophins occupy p75, they reasoned. To learn whether the receptor might be playing both sides--as a growth stimulant and suppressor--the team tested whether MAG requires p75 to relay its message. The researchers examined MAG's effect on nerve elongation in normal mice and in animals lacking the receptor. Without p75, MAG's clout in blocking nerve extension withered. "They demonstrate quite convincingly that p75 has a physiological role in inhibiting nerve growth," says Philip Barker, a molecular neurobiologist at the Montreal Neurological Institute and Hospital in Canada. Next, the researchers looked for conspirators in the molecules' ability to suppress nerve cell extension. They knew that p75's talent for eliciting nerve growth relies on a protein called Rho. When p75 binds neurotrophins, Rho shuts down and nerves branch out. Perhaps p75's nerve-constraining alter ego also relies on Rho, they reasoned. To test the idea, they crippled Rho's function in cells and found that MAG susceptibility vanished. Then they exposed normal and p75-deficient cells to MAG and measured the amount of active Rho. MAG charged up Rho only in the presence of the receptor, verifying p75's part in the game. Further analysis showed that p75 doesn't bind MAG alone. Instead, p75 hooks up with another molecule and the pair sends MAG's nerve-quelling message together. The results are intriguing, "but they raise more questions than they answer," says Marie Filbin, a neurobiologist at Hunter College of the City University of New York. For example, not all nerves produce p75, yet all respond to MAG, suggesting that other receptors might be important. But, Barker predicts that the findings "will have a major impact on the field of neurotrophins" because they uncover a complex role for p75 in neurons. And, he says, they might resolve earlier confusion. Some neurons are known to grow uncontrollably in p75-deficient mice. That observation "might be explained by a lack of MAG-mediated inhibitory signal," Barker adds. What's more, by tweaking p75, scientists might find their green thumb for cultivating degenerated nerves. --Kendall Morgan T. Yamashita, H. Higuchi, M. Tohyama, The p75 receptor transduces the signal from myelin-associated glycoprotein to Rho. J. Cell Biol. 157 , 565-570 (2002). [Abstract] [Full Text]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.086
GPT teacher head0.278
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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