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Record W2731204293 · doi:10.5430/jst.v7n2p38

Salivary proline rich peptide decreases cell growth in HCC38 triple negative breast cancer cell line

2017· article· en· W2731204293 on OpenAlexvenueno aff
Charles F. Streckfus, Daniel D. Arreola, C. Guajardo Streckfus, Lenora Bigler

Bibliographic record

VenueJournal of Solid Tumors · 2017
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsnot available
Fundersnot available
KeywordsTriple-negative breast cancerCell cultureBreast cancerPeptideCancer cell linesCell growthReceptorCancer researchGrowth inhibitionCellInternal medicineMedicineCancerOncologyBiologyCancer cellEndocrinologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

Objective: The objective of this study is to determine the effects of p1978 on the growth rate of a triple receptor negative breast cancer cell line.Methods: Three cell lines, 185B5 normal tissue, HCC38, and AU585, were seeded with peptide p1978. Corresponding plates were seeded with PBS to serve as controls. Baseline line cell counts were taken at 30% confluence prior to seeding. Counts were again made 48 hours later.Results: The HCC38 cell line showed decreased growth when exposed to the low and high dose of p1978 peptide.Conclusion: The results suggest that p1978 may have potential in treating triple receptor negative breast cancer.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.017
GPT teacher head0.289
Teacher spread0.272 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

Explore more

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