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Record W4378640485 · doi:10.1139/bcb-2023-0025

Dysregulation of insulin-like growth factor-1 signaling in postnatal bone elongation

2023· review· en· W4378640485 on OpenAlexvenueno aff
Cassaundra A. White, Maria A. Serrat

Bibliographic record

VenueBiochemistry and Cell Biology · 2023
Typereview
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of General Medical Sciences
KeywordsGrowth factorInsulin-like growth factorSignal transductionEndocrinologyInsulin receptorBiologyInternal medicineBone growthMedicineCancer researchInsulinReceptorCell biologyInsulin resistance

Abstract

fetched live from OpenAlex

Insulin-like growth factor-1 (IGF-1) is a critical modulator of cell growth and survival, making it a central part of maintaining essentially every biological system in the body. Knowledge of the intricate mechanisms involved in activating IGF-1 signaling is not only key to understanding basic processes of growth and development, but also for addressing diseases, such as cancer and diabetes. This brief review explores how dysregulation of normal IGF-1 signaling can impact growth by examining its role in postnatal bone elongation. IGF-1 actions are dysregulated in autoimmune diseases, such as juvenile idiopathic arthritis and chronic kidney disease, which results in growth stunting. Conversely, childhood obesity results in growth acceleration, premature growth cessation, and ultimately, diminished bone quality, while systemic IGF-1 levels remain normal. Understanding the role of IGF-1 signaling in normal and dysregulated growth can add to other studies that address how this system regulates chronic diseases.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.033
GPT teacher head0.290
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

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