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Record W2155282698

Overexpression of acetylcholinesterase inhibited cell proliferation and promoted apoptosis in NRK cells.

2004· article· en· W2155282698 on OpenAlexaff
Qi Jin, Heng Yi He, Yufang Shi, Lu H, Xue Jun Zhang

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsTransfectionMolecular biologyAcetylcholinesteraseMTT assayCell growthApoptosisclone (Java method)BlotCell cultureViability assayBiologyChemistryGeneEnzymeBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

AIM: To study the potential function of acetylcholinesterase (AChE) in apoptosis through overexpression of AChE in Normal Rat Kidney (NRK) cells. METHODS: AChE activity was detected by the method of Karnovsky and Roots. Activated caspase-3 was analyzed by Western blotting and immunofluorescence with antibody special to activated caspase-3 fragment. The expression plasmids were constructed in pcDNA3.1 containing AChE gene or a fragment of AChE antisense that were got from RT-PCR. Stable expression cell lines were selected by G418 in cells transfected by lipofection. AChE expression was analyzed by RT-PCR and Western blotting. The proliferation rates of transfected cells were examined by the growth curve and cloning efficiency. MTT assay was used to analyze the cell viability. RESULTS: The proliferation rate of the cells transfected with AChE was retarded and the cloning efficiency was lower (28.2 %+/-3.1 % and 48.7 %+/-2.1 %) than cells transfected with vector (56.1 %+/-0.3 %) or AChE-antisense (77.7 %+/-2.2 %). After 2 d the various clone types were deprived of serum, the residue cell viability were 10.4 %+/-4.6 % and 12.6 %+/-6.7 % in the cells transfected with AChE, and 27.4 %+/-3.5 % in cells with vector, and 50.3 %+/-7.8 % in cells with AChE-antisense. CONCLUSION: During apoptosis, increase of AChE protein is to inhibit cell proliferation, and then to promote apoptosis in NRK cells.

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 score0.117
Threshold uncertainty score0.497

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 head0.019
GPT teacher head0.237
Teacher spread0.219 · 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

Citations74
Published2004
Admission routes1
Has abstractyes

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