Antibody convergence along a common idiotypic axis in immunodeficiency virus and hepatitis C virus infections
Bibliographic record
Abstract
The anti-idiotypic antibody 1F7 selectively binds antibodies against human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV) gag, pol, and env proteins. We tested anti-hepatitis C virus (HCV) antibodies to investigate selection of the 1F7 idiotype on antibodies against other chronic pathogens. Twelve of 15 HCV-seropositive individuals co-infected with HIV had detectable antibodies against recombinant HCV core, 4 against HCV NS4 protein, and 3 against HCV NS3 protein. All four HCV-seropositive, non-HIV-infected individuals had antibodies against HCV core and NS4, while 3 had antibodies against NS3. The 1F7 idiotype was frequently present on antibodies against each of the HCV antigens in the HIV co-infected and non-HIV-infected groups. Antibodies against HCV, including antibodies recognizing the putative principal neutralizing determinant of HCV E2 protein, displayed skewed kappa/lambda light chain usage consistent with clonal dominance. These observations extend the association between expression of the 1F7 idiotype and abnormal B cell clonal dominance in HIV and SIV infection to HCV infection and suggest that early establishment of an oligoclonal antibody response against HCV may freeze the B cell repertoire, impair adaptation to emergent HCV variants, and favor escape from neutralizing antibodies. We also demonstrated that expression of the 1F7 idiotype extends beyond antibodies against multiple antigens of AIDS-causing retroviruses to include antibodies against multiple antigens of an unrelated chronic hepatitis virus. Thus, distinct pathogens establishing chronic infection in the face of strong humoral immune responses select antibodies along a common idiotypic axis of the immune network.
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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 | 0.001 |
| 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 | 0.000 |
| 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".