Comparative Evaluation of Profiles of Antibodies to Mycobacterial Capsular Polysaccharides in Tuberculosis Patients and Controls Stratified by HIV Status
Bibliographic record
Abstract
Despite the complexity of tuberculosis (TB) serology, antibodies (Abs) remain attractive biomarkers for TB. Recent evidence of a mycobacterial capsule that consists mainly of the polysaccharides arabinomannan (AM) and glucan provides new options for serologic targets. For this study, Ab responses to AM and glucan for 47 U.S. TB patients (33 HIV negative [HIV(-)], 14 HIV positive [HIV(+)]), 42 healthy controls, and 38 asymptomatic HIV(+) controls were evaluated by enzyme-linked immunosorbent assays (ELISAs). The results were compared with Ab responses to the mycobacterial glycolipid cell wall antigen lipoarabinomannan (LAM) and to the proteins malate synthase (MS) and MPT51. We found that the main immunoglobulin (Ig) isotype response to polysaccharides was IgG, predominantly of subclass IgG2. IgG responses to AM were significantly higher for HIV(-) and HIV(+) TB cases than for controls (P, <0.0001 and <0.01, respectively); significantly higher for HIV(-) than for HIV(+) TB cases (P, <0.01); and significantly higher in sputum smear-positive than smear-negative patients in both HIV(-) and HIV(+) cases (P, 0.01 and 0.02, respectively). In both TB groups, titers of Ab to glucan were significantly lower than titers of Ab to AM (P, <0.0001). IgG responses to AM and MS or to AM and MPT51 did not correlate with each other in HIV(-) TB patients, while they correlated significantly in HIV(+) TB patients (P, 0.01 and 0.05, respectively). We conclude that Ab responses to AM could contribute to the serodiagnosis of TB, especially for HIV(-) TB patients. This study also provides new and important insights into the differences in the profiles of Abs to mycobacterial antigens between HIV(-) and HIV(+) TB 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 | 0.001 |
| 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 | 0.001 | 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".