Host Defense (Antimicrobial) Peptides and Proteins
Bibliographic record
Abstract
Pathogen clearance is mediated by a complex set of strategies, ranging from the ingestion of microbes by phagocytes to the production of antimicrobial molecules, including reactive chemical species or lytic compounds. Another strategy is the production of cationic host defence proteins and peptides, compounds that play an important role in innate immunity, not only as antimicrobial agents, but also as immune regulators. Defensins members are categorized into three families based on their sizes and θ: the α-, β-, and θ-defensins. Defensins have generated a large amount of interest due to their modest in vitro antimicrobial activity against a wide range of microorganisms, including enveloped viruses, fungi, and bacteria. Host defense proteins include more than 700 structurally diverse members expressed extensively in both plants and animals. Lysozymes, also called muramidases, are small, abundant cationic enzymes that are widely distributed in plants and animals. Lactoferrin is an 80-kDa iron-binding plasma protein that belongs to the transferrin protein family, which includes serum transferrin, ovotransferrin, melanotransferrin, and the inhibitor of carbonic anhydrase. Chemokines are an extensive family of small chemotactic cytokine proteins of 7 to 10 kDa in size and include approximately 50 members in humans. Most chemokines are also cationic proteins and thus possess modest antibacterial properties in dilute medium. Host defense peptides and proteins are major components in the arsenal of our immune system.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.036 |
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".