Seroreactivity against Streptococcal DRS (Distantly Related to SIC) Protein Is a Predictor for End-Stage Renal Failure
Bibliographic record
Abstract
We hypothesized that immunoreactivity against antigens from nephritic strains of Streptococcus pyogenes may be elevated in patients with end-stage renal failure (ESRF). Additionally, we investigated whether a difference in seroreactivity exists between nonindigenous and indigenous (Aboriginal/Torres Strait Islander) patients. To examine these possibilities, antibodies against potentially nephritogenic proteins, streptokinase (Ska1) (from M1), streptococcal pyrogenic exotoxin type B (SpeB) (from M1), the streptococcal inhibitor of complement-mediated cell lysis (SIC) (from M1) and its two variants, closely related to SIC (CRS) (from M57) and distantly related to SIC (DRS) (from M12) were determined in 66 patients and 31 healthy controls by enzyme-linked immunosorbent assays. A significantly higher proportion of patients compared to controls were seropositive to Ska1 (P = 0.004), DRS (P = 0.0003), CRS (P = 0.001), and SIC (P = 0.018). Regression analysis showed that seroreactivity to DRS (r(2) = 0.85, P = 0.001) predicted the development of ESRF and that being diabetic was positively associated with being an ESRF patient (r(2) = 0.37, P < 0.0001) and being indigenous (r(2) = 0.47, P < 0.0001). These results suggest that these ESRF patients were exposed to strains of S. pyogenes that secrete Ska1, DRS, CRS, and SIC and may have pathological significance. No significant difference was observed between the indigenous patients and nonindigenous patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".