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Record W2142288290 · doi:10.3892/ijo_00000537

Cryotreatment as a simple method for cell preparation in autologous tumor cell-based vaccination

2010· article· en· W2142288290 on OpenAlexaff
Lavigne

Bibliographic record

VenueInternational Journal of Oncology · 2010
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversité de Moncton
FundersInstitut National de la Santé et de la Recherche MédicaleCancer Research Institute
KeywordsBreast cancerCancerOncogeneCellImmune systemCancer researchCancer vaccineCancer cellImmunologyVaccinationIn vivoMolecular medicineCell cycleMedicineImmunotherapyBiologyInternal medicineBiotechnology

Abstract

fetched live from OpenAlex

Immunotherapies using autologous whole tumor cell vaccines have great potential in the treatment of cancer. Very few studies report the use of cryotreatment for the preparation of cells in cell-based vaccines. In this study, we demonstrated that a preparation containing cryotreated human breast cancer cells has the same capacity as a preparation containing irradiated human breast cancer cells to induce the activation of immune cells in vivo. The vaccine strategy proposed in this study may provide the experiment basis for the use of autologous or allogeneic breast cancer cells in the cell-based vaccine approach for the treatment of breast cancer and other types of cancer as well.

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 score0.279
Threshold uncertainty score0.887

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)0.0010.000

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 head0.011
GPT teacher head0.357
Teacher spread0.346 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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