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Establishment of Primary Cultures from Ovarian Tumor Tissue and Ascites Fluid

2013· article· en· W27844308 on OpenAlexaff
Brigitte L. Thériault, Lise Portelance, Anne‐Marie Mes‐Masson, Mark W. Nachtigal

Bibliographic record

VenueMethods in molecular biology · 2013
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of ManitobaUniversité de MontréalUniversity Health NetworkCancerCare ManitobaOntario Institute for Cancer Research
Fundersnot available
KeywordsTrypsinizationAscitesCryopreservationCell cultureTumor cellsPrimary cultureIsolation (microbiology)Tissue culturePathologyCancer researchBiologyChemistryCell biologyMedicineTrypsinInternal medicineIn vitroBioinformaticsEmbryoBiochemistry

Abstract

fetched live from OpenAlex

We have refined the technique for isolating and propagating cultures of primary epithelial ovarian cancer (EOC) cells derived from solid tumors and ascites. Both protocols involve a simple yet rapid method for the growth and propagation of EOC tumor and ascites cells in a basal culture medium without the addition of growth factors. Isolation of tumor EOC cells involves the mechanical disruption of the tumor tissue with the help of a cell scraper, while ascites-derived EOC cells are mixed with growth medium and placed directly into culture with very little manipulation. We further describe a partial trypsinization method to eliminate fibroblast contamination from primary EOC cells derived from solid tumors. These methods allow for the direct application of many molecular, cellular, and functional analyses within a few weeks of initial isolation, with the added potential of retrospective analyses of archived cells and tissues. Thus, we have included steps for long-term cryopreservation of early-passage EOC cells. Initial isolation of EOC cells can be completed within 1 h, and primary cells are further expanded in culture for several weeks.

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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.726
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.363
Teacher spread0.347 · 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
GenreMethods

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

Citations26
Published2013
Admission routes1
Has abstractyes

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