Characterization of the Antigenic Heterogeneity of Lipoarabinomannan, the Major Surface Glycolipid of <i>Mycobacterium tuberculosis</i>, and Complexity of Antibody Specificities toward This Antigen
Bibliographic record
Abstract
, is an important immunodiagnostic target for detecting tuberculosis (TB) infection in HIV-1-coinfected patients, and is believed to mediate a number of functions that promote infection and disease development. To probe the human humoral response against LAM during TB infection, several novel LAM-specific human mAbs were molecularly cloned from memory B cells isolated from infected patients and grown in vitro. The fine epitope specificities of these Abs, along with those of a panel of previously described murine and phage-derived LAM-specific mAbs, were mapped using binding assays against LAM Ags from several mycobacterial species and a panel of synthetic glycans and glycoconjugates that represented diverse carbohydrate structures present in LAM. Multiple reactivity patterns were seen that differed in their specificity for LAM from different species, as well as in their dependence on arabinofuranoside branching and nature of capping at the nonreducing termini. Competition studies with mAbs and soluble glycans further defined these epitope specificities and guided the design of highly sensitive immunodetection assays capable of detecting LAM in urine of TB patients, even in the absence of HIV-1 coinfection. These results highlighted the complexity of the antigenic structure of LAM and the diversity of the natural Ab response against this target. The information and novel reagents described in this study will allow further optimization of diagnostic assays for LAM and may facilitate the development of potential immunotherapeutic approaches to inhibit the functional activities of specific structural motifs in LAM.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".