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Record W2140819381 · doi:10.3109/09553002.2014.927933

Carbon ion beam is more effective to induce cell death in sphere-type A172 human glioblastoma cells compared with X-rays

2014· article· en· W2140819381 on OpenAlexaff
Momoko Takahashi, Hirokazu Hirakawa, Hirohiko Yajima, Nakako Izumi‐Nakajima, Ryuichi Okayasu, Akira Fujimori

Bibliographic record

VenueInternational Journal of Radiation Biology · 2014
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsInstitute of Particle Physics
FundersChina Scholarship Council
KeywordsGlioblastomaCarbon fibersProgrammed cell deathIonIrradiationMaterials scienceRadiochemistryCancer researchChemistryBiophysicsBiologyApoptosisPhysicsBiochemistryNuclear physics

Abstract

fetched live from OpenAlex

PURPOSE: To obtain human glioblastoma cells A172 expressing stem cell-related protein and comparison of radiosensitivity in these cells with X-rays and carbon beam. METHODS: Human monolayer-type A172 glioblastoma cells were maintained in normal medium with 10% bovine serum. In order to obtain sphere-type A172 cells the medium was replaced with serum-free medium supplemented with growth factors. Both types of A172 cells were irradiated with either X-rays or carbon ion beams and their radiosensitivity was evaluated. RESULTS: Serum-free medium induced expression of stem cell-related proteins in A172 cells along with the neurosphere-like appearance. These sphere-type cells were found resistant to both X-rays and carbon ion beams. Phosphorylation of histone H2A family member X persisted for a longer period in the cells exposed to carbon ion beams than in those exposed to X-rays and it disappeared quicker in the sphere type than in the monolayer type. Relative radioresistance of the sphere type cells was smaller for carbon ion beams than for X-rays. CONCLUSIONS: We demonstrated that glioblastoma A172 cells with induced stem cell-related proteins turned resistant to irradiation. Accelerated heavy ion particles may have advantage over X-rays in overcoming the tumor resistance due to cell stemness.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.292
Teacher spread0.284 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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