Association of IgG co-deposition with serum levels of galactose-deficient IgA1 in pediatric IgA nephropathy
Bibliographic record
Abstract
OBJECTIVE: To determine whether the absence of mesangial IgG deposits is associated with the absence of elevated blood levels of galactose-deficient IgA1 (Gd-IgA1) in pediatric patients with IgA nephropathy (IgAN). DESIGN AND METHODS: Serum Gd-IgA1 levels were determined by ELISA using an N-acetylgalactosamine-specific lectin from Helix aspersa. Levels of Gd-IgA1 above the 90th percentile for healthy pediatric controls were considered to be elevated. Renal biopsy samples were examined by immunofluorescence for presence and intensity of staining for IgA, IgG, IgM, C3 and C1q and by light microscopy for histological changes. Findings were graded by a single pathologist (L. Gaber) at UTHSC until 2007 and by NephropathTM (Little Rock, AR, USA) thereafter. Staining for the mesangial deposits was considered negative when intensity was trace or less, and positive at greater intensity. Fisher's exact test was used to determine significance of 2 × 2 tables. RESULTS: Serum samples were obtained from 30 patients with IgAN diagnosed before age 18 years. Male:female ratio was 2.3:1. Twenty were Caucasian and 10 were African-American. Blood was obtained within 3 months of biopsy (incident cases) for 12, while 18 provided blood > 3 months after biopsy (prevalent cases). Serum Gd-IgA1 level was elevated in 23 (77%) of cases and 20 (67%) had a biopsy positive for IgG. Of those 20 patients, 18 (90%) had an elevated serum Gd-IgA1 level, whereas 5 (50%) of patients with biopsies without IgG had a normal serum Gd-IgA1 level (p = 0.026). SUMMARY: In this small study we found a weak association between the absence of IgG in the biopsy and normal serum Gd-IgA1 level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".