Bibliographic record
Abstract
Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation and progressive joint destruction. Anti-TNF biologics have been developed to treat RA and although effective in the majority of patients, they require repeated administration and systemically inhibit TNF. This systemic inhibition leads to systemic immune suppression and can result in side-effects including opportunistic infections, serious infections and malignancy. To address these limitations, I developed a novel, local-acting biologic known as TNF sticky trap. This biologic was shown capable of inhibiting TNF while sticking or localizing to the extracellular matrix (ECM) where it is produced or administered. Next, cell lines inducibly expressing this local-acting biologic were generated, characterized and evaluated for their therapeutic efficacy in an animal model of RA. A single injection of cells expressing TNF sticky trap was sufficient to reduce arthritis and this local-acting biologic was undetectable in the serum of treated animals. Lastly, to help advance the translation of RA cell therapies into the clinic, a cell safety mechanism was developed and characterized. The development of a safe cell therapy inducibly expressing local-acting biologics could avoid the limitations associated with systemic therapies and improve the current treatment of RA.
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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".