Reduced Incidence of Slowly Progressive Heymann Nephritis in Rats Immunized With a Modified Vaccination Technique
Bibliographic record
Abstract
A slowly progressive Heymann nephritis (SPHN) was induced in three groups of rats by weekly injections of a chemically modified renal tubular antigen in an aqueous medium. A control group of rats received the chemically unmodified version of the antigen in an aqueous solution. One group of SPHN rats were pre- and post-treated with weekly injections of IC made up of rKF3 and rarKF3 IgM antibody at antigen excess (MIC) (immune complexes [ICs] containing sonicated ultracentrifuged [u/c] rat kidney fraction 3 [rKF3] antigen and IgM antibodies specific against the antigen, at slight antigen excess). One group of SPHN rats were post-treated with MIC 3 weeks after the induction of the disease and one group of SPHN animals received no treatment. The control group of rats received pre- and post-treatment with sonicated u/c rKF3. The incidence of immune-complex glomerulonephritis (ICGN) in the untreated SPHN rats was 87%, in the pre- and post-treated animals 13%, and in the post-treated-only rats 20%. Rats receiving sonicated ultracentrifuged rKF3 antigen did not develop ICGN. The present experiment demonstrates that the development of SPHN can be not only prevented but also effectively terminated by our newly developed modified vaccination technique.
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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 | 0.001 |
| 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".