Bibliographic record
Abstract
【目的】14-3-3ηは200以上の細胞内タンパクに関係する細胞内シャペロンである，関節リウマチ（RA）では関節液および血清中にも出現する．そこで14-3-3ηに注目し，RA治療開始後の臨床的アウトカムとの関係を検討した．【成績】当科で治療導入したRA患者99（adalimumab; ADA 49，tocilizumab; TCZ 50）例で，Baseline（BL）と1年後の血清14-3-3ηをELISA法で測定し，BLと1年後の種々の臨床的指標との関係を検討した．【結果】背景中央値は年齢63歳，罹病期間76ヶ月，DAS28ESR 5.3，RF陽性82％，ACPA陽性90％で，ADA群とTCZ群で罹病期間，MTX併用率，Sharp-vdH score（SHS）で差があった．BLにおける14-3-3η濃度は，BLの疾患活動性（DAS28, CDAI, SDAI），急性炎症反応（CRP, ESR），関節破壊（SHS），血清反応（RF濃度，ACPA濃度）のいずれとも有意に相関した．また治療によりBL 0.70 ng/mlから1年後0.37 ng/mlにに低下した（p < 0.0001）．1年後のDAS28-ESR寛解（η 2.6）に対するBL 14-3-3ηカットオフ値（0.32 ng/ml）をROC解析により設定し層別化すると，1年後の寛解達成率はADAではBL 14-3-3η低値群40％（8/12），高値群59％（12/29）であった（p = 0.20）が，TCZでは低値群77％（10/13），高値群37％（10/27）とBL14-3-3η低値群で有意（p = 0.0007）に高かった．【結論】BL 14-3-3η低値の場合，tocilizumabによる1年後の臨床的寛解を達成しやすいこと示された．
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.234 | 0.179 |
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".