The Insulin-Like Growth Factor Family: Molecular Mechanisms, Redox Regulation, and Clinical Implications
Bibliographic record
Abstract
Insulin-like growth factor (IGF)-induced signaling networks are vital in modulating multiple fundamental cellular processes, such as cell growth, survival, proliferation, and differentiation. Aberrations in the generation or action of IGF have been suggested to play an important role in several pathological conditions, including metabolic disorders, neurodegenerative diseases, and multiple types of cancer. Yet the exact mechanism involved in the pathogenesis of these diseases by IGFs remains obscure. Redox pathways involving reactive oxygen species (ROS) and reactive nitrogen species (RNS) contribute to the pathogenetic mechanism of various diseases by modifying key signaling pathways involved in cell growth, proliferation, survival, and apoptosis. Furthermore, ROS and RNS have been demonstrated to alter IGF production and/or action, and vice versa, and thereby have the ability to modulate cellular functions, leading to clinical manifestations of diseases. In this review, we provide an overview on the IGF system and discuss the potential role of IGF-1/IGF-1 receptor and redox pathways in the pathophysiology of several diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".