Potentially antigenic <scp>RBC</scp> membrane proteins in dogs with primary immune‐mediated hemolytic anemia
Bibliographic record
Abstract
BACKGROUND: Primary immune-mediated hemolytic anemia (IMHA) is an important cause of morbidity and mortality in dogs. The mechanisms underlying autoimmune reactivity remain poorly understood. OBJECTIVE: The aim of this study was to identify membrane proteins of RBCs that could be antigenic in dogs with primary IMHA. METHODS: Antibodies were eluted with xylene from RBCs of 12 dogs with IMHA, 4 dogs with anemia due to causes other than IMHA, and 2 healthy dogs. Pooled RBC membrane proteins were prepared from blood of 17 healthy dogs. The eluted antibodies were then analyzed by immunoblotting for interactions with the pooled membrane proteins and autologous plasma. Bands present in the 12 dogs with IMHA but not in the 6 other dogs were considered potential autoantigens and were identified by liquid chromatography followed by tandem mass spectrometry. RESULTS: RBC eluates from all 18 dogs had reactivity against band 3 protein. Antibodies to 6 additional proteins were uniquely identified in dogs with IMHA. Reactivity to calpain, complement component 3, and peroxiredoxin 2 was identified in 8, 8, and 4 of the 12 samples, respectively, from dogs with IMHA, but in none of the samples from the 6 dogs without IMHA. CONCLUSIONS: Detection of universal immune reactivity against band 3 protein probably indicates recognition of senescent RBC. Proteins uniquely recognized by antibodies in dogs with IMHA are involved in oxidative stress and apoptosis (calpain), inflammation (complement), and scavenging of reactive oxygen species (peroxiredoxin 2). It remains to be determined if these proteins are important in initiating autoimmunity or if immunoglobulins targeting these proteins develop during IMHA.
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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 | 0.001 | 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 | 0.000 |
| 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".