Assessment of hypoxia and TNF-alpha nbsp response by a vector with HRE and NF-kappaB response elements
Bibliographic record
Abstract
Hypoxia and inflammatory cytokine activation (H&I) are common processes in many acute and chronic diseases. Thus, a single vector that responds to both hypoxia and inflammatory cytokines, such as TNF-α, is useful for assesing the severity of such diseases. Adaptation to hypoxia is regulated primarily by hypoxia inducible transcription factor (HIFα) nuclear proteins that engage genes containing a hypoxia response element (HRE). Inflammation activates a multitude of cytokines, including TNF-α, that invariably modulate activation of the nuclear factor kappa B (NF-kB) transcription factor. We constructed a vector that encompassed both a hypoxia response element (HRE), and a NF-kappaB responsive element. We show that this vector was functionally responsive to both hypoxia and TNF-α, in vitro and in vivo. Thus, this vector might be suitable for the detection and assessment of hypoxia or TNF-α.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".