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Record W1986160966 · doi:10.3389/fonc.2011.00040

Influence of pH on the cytotoxic activity of inositol hexakisphosphate (IP6) in prostate cancer

2011· article· en· W1986160966 on OpenAlexafffund
Blandine Betton

Bibliographic record

VenueFrontiers in Oncology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersInstitute of Cancer ResearchInstitut Du Cancer de MontréalUniversité de Montréal
KeywordsProstate cancerCytotoxic T cellCancerProstateInositolCancer researchChemistryInternal medicineMedicineOncologyBiochemistryIn vitroReceptor

Abstract

fetched live from OpenAlex

OBJECTIVES: In the present study, we investigated whether the pH of IP6 could influence its anti-tumoral activity in vitro. METHODS: PC-3 cells were exposed to IP6 at pH 5, pH 7, and pH 12 and we evaluated the metabolic activity (WST-1 assay), cell proliferation (cell count), cell cycle distribution (FACS), and mitochondrial depolarization (JC-1 staining) in vitro. RESULTS: Our results demonstrated that IP6 at pH 5 and pH 12 were more potent at lowering the metabolic activity of PC-3 cells than IP6 at pH 7. Treatment with IP6 at pH 12 also caused the greatest inhibition in cellular proliferation and accumulation of PC-3 cells in sub-G1. Finally, IP6 at pH 12 lead to a reduction in phospho-AKT and phospho-PDK1 and upregulated phospho-ERK. CONCLUSION: Together, our data strongly suggest that the pH of IP6 effectively modulates its anti-tumoral activity and should be reported in future studies.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.024
GPT teacher head0.258
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 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

Citations1
Published2011
Admission routes2
Has abstractyes

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