Bibliographic record
Abstract
Chemokines are best known as signaling proteins in the immune system. Recently however, a large number of human chemokines have been shown to exert direct antimicrobial activity. This moonlighting activity appears to be related to the net high positive charge of these immune signaling proteins. Chemokines can be divided into distinct structural elements and some of these have been studied as isolated peptide fragments that can have their own antimicrobial activity. Such peptides often encompass the α-helical region found at the C-terminal end of the parent chemokines, which, similar to other antimicrobial peptides, adopt a well-defined membrane-bound amphipathic structure. Because of their relatively small size, intact chemokines can be studied effectively by NMR spectroscopy to examine their structures in solution. In addition, NMR relaxation experiments of intact chemokines can provide detailed information about the intrinsic dynamic behavior; such analyses have helped for example to understand the activity of TC-1, an antimicrobial variant of CXCL7/NAP-2. With chemokine dimerization and oligomerization influencing their functional properties, the use of NMR diffusion experiments can provide information about monomer-dimer equilibria in solution. Furthermore, NMR chemical shift perturbation experiments can be used to map out the interface between self-associating subunits. Moreover, the unusual case of XCL1/lymphotactin presents a chemokine that can interconvert between two distinct folds in solution, both of which have been elucidated. Finally, recent advances have allowed for the determination of the structures of chemokines in complex with glycosaminoglycans, a process that could interfere with their antimicrobial activity. Taken together, these studies highlight several different structural facets that contribute to the way in which chemokines exert their direct microbicidal actions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".