Heptose Sounds the Alarm: Innate Sensing of a Bacterial Sugar Stimulates Immunity
Bibliographic record
Abstract
PAMPs Are Indicators of Microbial Identity and VirulenceThe first line of defense against infection, the innate immune system, identifies and responds to microbial threats.Central to this response is the discrimination of self from non-self.Pattern recognition receptors (PRRs) expressed by mammalian cells detect molecular signatures unique to microbes yet absent from the host.These molecules, termed pathogen-associated molecular patterns (PAMPs), are invariant structures broadly represented among microbial taxa and have essential roles in microbial physiology.Consequently, only an extremely select group of molecules have been found to function as PAMPs.It is becoming increasingly clear that rather than being redundant, PAMPs are interpreted by the innate immune system as a "pathogenic barcode" that informs the host to both the identity and infectious risk posed by a microorganism.The combination of PAMPs presented, the tissue type affected, and the subcellular compartment contaminated represent just some of the contextual signals used by the host to identify and assess the microbial threat.For example, PAMP contamination of the host cytosol is interpreted as an indicator of microbial virulence since direct cellular invasion or virulence factor-mediated translocation is a prerequisite for their presence in this normally sterile site [1].Such distinctions are critical to maintaining immune homeostasis since, despite their name, PAMPs are not unique to pathogens; instead, they can be found in virtually all microorganisms, including the commensal microflora that constitutively reside on body surfaces.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".