Viruses exploit growth factor mechanisms to achieve augmented pathogenicity and promote tumorigenesis
Bibliographic record
Abstract
Cellular homeostasis is regulated by growth factors (GFs) which orchestrate various cellular processes including proliferation, survival, differentiation, motility, inflammation and angiogenesis. Dysregulation of GFs in microbial infections and malignancies have been reported previously. Viral pathogens exemplify the exploitation of host cell GFs and their signalling pathways contributing to viral entry, virulence, and evasion of anti-viral immune responses. Viruses can also perturb cellular metabolism and the cell cycle by manipulation of GF signaling. In some cases, this disturbance may promote oncogenesis. Viral pathogens can encode viral GF homologues and induce the endogenous biosynthesis of GFs and their corresponding receptors or manipulate their activity to infect the host cells. Close investigation of how viral strategies exploit and regulate GFs, a will shed light on how to improve anti-viral therapy and cancer treatment. In this review, we discuss and provide insights on how various viral pathogens exploit different GFs to promote viral survival and oncogenic transformation, and how this knowledge can be leveraged toward the design of more efficient therapeutics or novel drug delivery systems in the treatment of both viral infections and malignancies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".