MétaCan
Menu
Back to cohort
Record W2028813771 · doi:10.1021/bp0000914

Effects of Insulin and LongR3 on Serum-Free Chinese Hamster Ovary Cell Cultures Expressing Two Recombinant Proteins

2000· article· en· W2028813771 on OpenAlexaff
Adrian Morris, Johannes A. Schmid

Bibliographic record

VenueBiotechnology Progress · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicViral Infectious Diseases and Gene Expression in Insects
Canadian institutionsResearch & Development Corporation
Fundersnot available
KeywordsChinese hamster ovary cellCell cultureGrowth factorBiologyViability assayRecombinant DNAInsulinInsulin-like growth factorCell growthCell biologyCellReceptorEndocrinologyInternal medicineBiochemistryMedicineGeneticsGene

Abstract

fetched live from OpenAlex

Insulin is the most commonly used growth factor for sustaining cell growth and viability in serum-free Chinese hamster ovary (CHO) cell cultures. In the present study insulin and IGF-1 analogue (LongR(3)) were compared for their ability to support growth, viability, and production of two serum-free CHO cell lines expressing recombinant protein. The first cell line, VA12, expresses protein B, and the second cell line, CL23, expresses protein C. Both molecules are recombinant cytokine receptors. VA12 will grow in serum-free media lacking growth factor, while CL23 requires either insulin or LongR(3) for cell growth. Both cell lines, however, require a growth factor for optimal performance under production conditions. In this study, LongR(3) was better able to sustain the viability of both cell lines under production conditions than insulin. These data indicate that while insulin and LongR(3) can both serve as growth and viability factors for CHO cells, LongR(3) is the preferred growth factor for cell lines VA12 and CL23.

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 score0.005

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 integrity0.0000.001
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 head0.003
GPT teacher head0.243
Teacher spread0.240 · 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

Citations38
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueBiotechnology ProgressSame topicViral Infectious Diseases and Gene Expression in InsectsFrench-language works237,207