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Record W4317401629 · doi:10.3390/ijms24031867

Characterization of IGF2R Molecular Expression in Canine Osteosarcoma as Part of a Novel Comparative Oncology Approach

2023· article· en· W4317401629 on OpenAlexafffund
Charles Boisclair, Ryan Dickinson, Sabeena Giri, Ekaterina Dadachova, Valerie MacDonald‐Dickinson

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsImmunohistochemistryInsulin-like growth factor 2 receptorOsteosarcomaClinical significanceOncologyBiopsyInternal medicineCancer researchMedicinePathologyBiologyReceptorGrowth factorInsulin-like growth factor 1 receptor

Abstract

fetched live from OpenAlex

Progress in prognostic factors, treatments, and outcome for both canine and human osteosarcoma (OS) has been minimal over the last three decades. Surface overexpression of the cation independent mannose-6-phosphate/insulin-like growth factor receptor type 2 (IGF2R) has been proven to occur in human OS cells. Subsequently, radioimmunotherapy (RIT) targeting IGF2R has demonstrated promising preliminary results. The main aims of this study were to investigate the expression of IGF2R in spontaneously occurring canine OS cells using immunohistochemistry (IHC) on archived biopsy samples and to assess its prognostic significance. Thirty-four dogs were included in the study. All cases showed that 80-100% of OS cells stained positive for IGF2R. IGF2R overexpression alone was not shown to have prognostic significance using both visual and quantitative methods of IHC staining intensity. This study has established for the first time the consistent expression of IGF2R in spontaneously occurring canine OS. This comparative oncology approach will allow further investigation into RIT as a novel treatment modality; first in canines and then in humans with OS. In addition, further studies should be performed to assess the true prognostic significance of IGF2R overexpression.

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 score0.073
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.109
GPT teacher head0.433
Teacher spread0.323 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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