MétaCan
Menu
Back to cohort
Record W104598464

Friend virus-induced erythroleukemias: a unique and well-defined mouse model for the development of leukemia.

2003· article· en· W104598464 on OpenAlexaff
Christina R. Lee, Dave Cervi, Amandine Truong, You Jun Li, Aloke Sarkar, Yaacov Ben‐David

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsBiologyFriend virusVirusGeneSuppressorMurine leukemia virusCancerLeukemiaTumor suppressor geneCancer researchOncovirusDiseaseVirologyGeneticsCarcinogenesisMedicinePathology
DOInot available

Abstract

fetched live from OpenAlex

Retroviruses lacking oncogenes have been known to induce various types of cancer when inoculated into animals. Among these, Friend virus, discovered by Charlotte Friend in 1957, is capable of inducing erythroleukemias when injected into susceptible strains of mice. Since its discovery, this murine model of leukemogenesis has been extensively used to study the multistage nature of cancer. In the past two decades, several oncogenes and tumour suppressor genes, which play critical roles in the induction and progression of Friend erythroleukemia, have been identified. Retroviral insertional activation of Fli-1 and Spi-1/PU.1, as well as loss of tumour suppressor genes such as p53 or p45 NFE2 have been shown to be critical for the induction and progression of Friend virus-induced erythroleukemias. The majority of these genetic changes have also been implicated in various types of human neoplastic transformations. In this review we will discuss the genetic changes associated with Friend Disease, the temporal order during induction and progression of disease, and the function of these genes in both normal erythroid development as well as malignant transformation.

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 score0.034
Threshold uncertainty score0.507

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)0.0000.000

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 head0.034
GPT teacher head0.266
Teacher spread0.232 · 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

Citations27
Published2003
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicVirus-based gene therapy researchFrench-language works237,207