INCREASED LEVELS OF GAL??1???4GLCNAC??2???6 SIALYLTRANSFERASE PRETRANSPLANT PREDICT DELAYED GRAFT FUNCTION IN KIDNEY TRANSPLANT RECIPIENTS1
Bibliographic record
Abstract
BACKGROUND: Galbeta1-4GlcNAcalpha2-6 sialyltransferase (ST6GalI) is an acute phase reactant whose release from cells can be induced by proinflammatory cytokines. Because patients with chronic renal failure have high circulating levels of proinflammatory cytokines, we hypothesized that patients on the renal transplant waiting list would have high circulating levels of ST6GalI, which might adversely affect post-transplant events. METHODS: Levels of ST6GalI were measured in the serum of 70 patients immediately before renal transplant; these were correlated with posttransplant events, such as delayed graft function and rejection. RESULTS: The mean serum level of ST6GalI was significantly higher in the patients (3162+/-97 U) than in 19 controls (2569 +/- 125 U; P<0.003). Patients who required dialysis posttransplant for treatment of delayed graft function (n=20) had significantly higher levels of ST6GalI pretransplant (3735+/-228 U) than patients (n=50) who did not require dialysis (2933+/-83 U; P<0.0001). In a multivariate analysis the ST6GalI level and cold ischemic time were found to be independent risk factors for the development of delayed graft function. CONCLUSIONS: ST6GalI levels are high in renal failure patients awaiting a renal transplant and may be a risk factor for the development of delayed graft function. The assessment and perhaps modulation of a potential transplant recipient's ST6GalI systemic level may be beneficial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".