Structural Profiling of Short-Chain Lipopolysaccharides from Haemophilus influenzae
Bibliographic record
Abstract
Lipopolysaccharides (LPS) are a complex class of glycolipids that can trigger a cascade of immunological responses in mammals, including endotoxic effects and serum antibody production ( 1 ). LPS have been found to exhibit a common molecular architecture consisting of at least two distinct regions: a carbohydrate containing region and a lipid moiety referred to as lipid A ( 2 ). In enteric bacteria (e.g., Escherichia coli, Salmonella spp.), the carbohydrate containing region consists of a high-molecular-mass O-specific polysaccharide that is covalently linked to a low-molecular-mass core oligosaccharide ( 3 ). Haemophilus influenzae produces only short-chain LPS in which the carbohydrate region typically contains mixtures of low-molecular-mass but structurally diverse oligosaccharide components. This pathogen remains a major cause of disease worldwide. Six capsular serotypes and an indeterminate number of nontypeable (i.e., acapsular) strains of H. influenzae are recognized. In the developed world, non-typeable (NTHi) strains are the second major cause of otitis media infections in children, while serotype b capsular strains are associated with invasive diseases, including meningitis and pneumonia ( 4 ). The carbohydrate regions of H. influenzae LPS molecules provide targets for recognition by host immune responses, and expression of certain oligosaccharide epitopes is known to contribute to disease pathogenesis. Molecular structural studies of LPS from a number of different H. influenzae strains have resulted in a structural model in which a conserved l - glycero - d - manno -heptose (Hep)-containing inner-core trisaccharide moiety is attached via a phosphorylated 3-deoxy-D-manno-octulosonic acid (Kdo) residue to the lipid A component ( 5 – 16 ) ( see Structure 1 ). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.001 |
| 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".