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Record W2163232633 · doi:10.1042/0264-6021:3570881

Treatment of PC12 cells with nerve growth factor increases iron uptake

2001· article· en· W2163232633 on OpenAlexafffund
James Mwanjewe, Betsy King HUI, Michael D. Coughlin, Ashok K. Grover

Bibliographic record

VenueBiochemical Journal · 2001
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsMcMaster University
FundersMedical Research CouncilHeart and Stroke Foundation of Canada
KeywordsTransferrinThapsigarginNerve growth factorTransferrin receptorEndoplasmic reticulumChemistryBiochemistryCell biologyBiologyEndocrinologyInternal medicineBiophysicsMolecular biologyReceptorMedicine

Abstract

fetched live from OpenAlex

Phaeochromocytoma PC12 cells treated with nerve growth factor (NGF) differentiate into a neuronal phenotype. Here we compare the uptake of transferrin-bound and non-transferrin-bound iron in NGF-treated (neuronal phenotype) and control (proliferating) PC12 cells. The non-transferrin-bound iron uptake was greater in the NGF-treated cells than in the control, independently of the uptake time, the iron-chelating agents used, the oxidation state of iron (Fe(2+) or Fe(3+)) and the iron concentration tested. The NGF-treated cells expressed L-type and N-type voltage-operated Ca(2+) channels. Nitrendipine (an L-type inhibitor) and possibly omega-conotoxin (an N-type inhibitor) inhibited the iron uptake by 20%. Thapsigargin inhibits the endoplasmic reticulum Ca(2+) pump and allowed Mn(2+) entry into cells. Preincubating PC12 cells with thapsigargin increased the iron uptake. The rate of transferrin-bound iron uptake was less than 1% of the non-transferrin-bound iron uptake and the maximum transferrin-bound iron uptake was also very low. We conclude that an increase in the iron uptake by multiple pathways accompanies the transition of PC12 cells from the proliferating to the neuronal phenotype.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.248
Teacher spread0.234 · 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 teacher head, 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

Citations12
Published2001
Admission routes2
Has abstractyes

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