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Record W1990307793 · doi:10.1007/s11670-011-0229-6

Src is dephosphorylated at tyrosine 530 in human colon carcinomas

2011· article· en· W1990307793 on OpenAlexaff
Shudong Zhu, Jeffrey D. Bjorge, Donald J. Fujita

Bibliographic record

VenueChinese Journal of Cancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProto-oncogene tyrosine-protein kinase SrcTyrosine kinaseCancer researchKinaseColorectal cancerPhosphorylationBiologyCancerMedicineInternal medicineSignal transductionCell biology

Abstract

fetched live from OpenAlex

OBJECTIVE: Src is a protein tyrosine kinase that plays important roles in cancer development, and Src kinase activity has been found to be elevated in several types of cancers. However, the cause of the elevation of Src kinase activity in the majority of human colon carcinomas is still largely unknown. We aim at finding the cause of elevated Src kinase activity in human colon carcinomas. METHODS: We employed normal colon epithelial FHC cells and examined Src activation in human colon carcinoma specimens from 8 patients. Protein expression levels were determined by Western blotting, and the activity of Src kinase by kinase assay. RESULTS: Actin levels were different between tumor and normal tissues, demonstrating the complexities and inhomogeneities of the tissue samples. Src kinase activities were increased in the majority of the colon carcinomas as compared with normal colon epithelial cells (range 13-29). Src protein levels were reduced in the colon carcinomas. Src Y530 phosphorylation levels were reduced to a higher extent than protein levels in the carcinomas. CONCLUSION: The results suggest that Src specific activities were highly increased in human colon carcinomas; phosphorylation at Src Y530 was reduced, contributing to the highly elevated Src specific activity and Src kinase activity.

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)0.001
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 score0.011
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.055
GPT teacher head0.374
Teacher spread0.319 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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