Exploring the development of endotoxin tolerance and anti-endotoxin activity of LL-37 in mammalian cells (134.55)
Bibliographic record
Abstract
Abstract The innate immune response is the first line of defense against microorganisms. However, its over-stimulation can result in excessive inflammation that can lead to deadly syndromes like sepsis. Initially, septic patients exhibit a high immune response, which later shifts towards an immunosuppressive state. This state may be related with a phenomenon called endotoxin tolerance, which is a reduced capacity to respond to antigens. Recent studies have demonstrated that cationic host defense peptides, such as LL-37, have broad immunomodulatory activities like diminishing inflammatory responses. Therefore, the purpose of these two phenomena may be to reduce the immune response and control excessive inflammation. Although much studied, mechanisms that lead to their development are not clear. In this work, time course analysis by RT-qPCR, western blot, and microarrays on human peripheral blood mononuclear cells and monocytic cell line, have shown similar patterns in the up- and down-regulation of important immune players like pro/anti-inflammatory mediators, and negative regulators during the development of endotoxin tolerance and anti-endotoxin activity of LL-37. Results from this work may not only help clarify how each of these phenomena occur, but also may find a link between them. This work has been supported by Genome British Columbia and Genome Prairie for the Pathogenomics of Innate Immunity Research Program, and by the Foundation for the National Institutes of Health and Canadian Institutes for Health Research through the Grand Challenges in Global Health Initiative.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".