Kinin B1 Receptor Expression on Multiple Sclerosis Mononuclear Cells
Bibliographic record
Abstract
BACKGROUND: We have previously shown that the inducible kinin B(1) receptor is expressed on T lymphocytes during relapses and progression in multiple sclerosis. OBJECTIVE: To evaluate the correlation between the expression of B1 receptor on peripheral blood mononuclear cells derived from patients who have multiple sclerosis with serial, clinical magnetic resonance imaging and immunological study-derived measures. DESIGN: Using frozen samples obtained from a high-frequency magnetic resonance imaging-immunological study, we analyzed B1 receptor messenger RNA (mRNA) expression in peripheral blood-derived mononuclear cells serially collected from 6 patients with multiple sclerosis and 8 healthy control subjects by semiquantitative radioactive duplex reverse transcriptase-polymerase chain reaction amplification. Time-course kinin B1-actin mRNA ratios were subsequently compared with corresponding clinical magnetic resonance imaging and immune parameters. RESULTS: The time-course kinin B1-actin mRNA ratio correlated positively with the Expanded Disability Status Scale index (P<.001), occurrence of clinical relapse (P = .02), volume of lesion on T2-weighted images (P<.003) and interleukin 2 receptor and major histocompatibility complex class II expression on CD4+ lymphocytes, but not with gadolinium-enhancing lesions. The time-course kinin B1-actin mRNA ratios were 5 to 25 times lower in samples derived from healthy controls. CONCLUSION: The correlation of kinin B1 receptor mRNA levels with dynamic clinical and magnetic resonance imaging measures suggests that expression of this receptor can serve as an index of disease activity in multiple sclerosis.
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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) | 0.000 | 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) | 0.003 | 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".