Antimicrobial peptides: key components of the innate immune system
Bibliographic record
Abstract
Life-threatening infectious diseases are on their way to cause a worldwide crisis, as treating them effectively is becoming increasingly difficult due to the emergence of antibiotic resistant strains. Antimicrobial peptides (AMPs) form an ancient type of innate immunity found universally in all living organisms, providing a principal first-line of defense against the invading pathogens. The unique diverse function and architecture of AMPs has attracted considerable attention by scientists, both in terms of understanding the basic biology of the innate immune system, and as a tool in the design of molecular templates for new anti-infective drugs. AMPs are gene-encoded short (<100 amino acids), amphipathic molecules with hydrophobic and cationic amino acids arranged spatially, which exhibit broad spectrum antimicrobial activity. AMPs have been the subject of natural evolution, as have the microbes, for hundreds of millions of years. Despite this long history of co-evolution, AMPs have not lost their ability to kill or inhibit the microbes totally, nor have the microbes learnt to avoid the lethal punch of AMPs. AMPs therefore have potential to provide an important breakthrough and form the basis for a new class of antibiotics. In this review, we would like to give an overview of cationic antimicrobial peptides, origin, structure, functions, and mode of action of AMPs, which are highly expressed and found in humans, as well as a brief discussion about widely abundant, well characterized AMPs in mammals, in addition to pharmaceutical aspects and the additional functions of AMPs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".