Tacrolimus, a Calcineurin Inhibitor, Overcomes Treatment Unresponsiveness Mediated by P-glycoprotein on Lymphocytes in Refractory Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Tacrolimus, a calcineurin inhibitor, is used for treatment of rheumatoid arthritis (RA). It also inhibits functions of P-glycoprotein, which is involved in drug resistance. We examined the mechanisms of early response to 2-week tacrolimus treatment in patients with RA. METHODS: One hundred thirteen patients with refractory RA despite at least 3 antirheumatic agents, including methotrexate, were treated with tacrolimus (1.5-3 mg/day) and the response was assessed at 2 weeks. Expression of the multidrug resistance (MDR-1) gene and P-glycoprotein was assessed in peripheral blood mononuclear cells (PBMC) collected from 113 patients and 40 healthy subjects. The drug exclusion function by the P-glycoprotein was measured by the residual amount of intracellular tritium-labeled dexamethasone cell/medium ratio (C/M ratio). RESULTS: The disease activity of enrolled patients was 5.8 +/- 1.2 (mean +/- SD) by DAS28 erythrocyte sedimentation rate. A good response to tacrolimus was noted at 2 weeks in 22 of 113 patients. At baseline, PBMC of patients with RA showed upregulated expression of MDR-1 gene and P-glycoprotein and low C/M ratio. The response to tacrolimus correlated with P-glycoprotein expression and C/M ratio. A significant improvement in C/M ratio was noted after 2 weeks of treatment. The C/M ratio correlated significantly with P-glycoprotein expression on CD4+ lymphocytes. CONCLUSION: Early efficacy of tacrolimus treatment depended on its inhibitory effect on the drug exclusion function of P-glycoprotein, leading to restoration of intracellular therapeutic levels of corticosteroids and clinical improvement. Evaluation of P-glycoprotein expression on lymphocytes is potentially useful for predicting the response to RA treatment.
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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 | 0.001 |
| 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) | 0.001 | 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 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".