IL-8 enhancement of amyloid-beta (Abeta 1-42)-induced expression and production of pro-inflammatory cytokines and COX-2 in cultured human microglia.
Bibliographic record
Abstract
Abstract The effects of the chemokine IL-8 on amyloid beta peptide (Aβ1-42)-induced responses in cultured human microglia were investigated using RT–PCR, ELISA and immunocytochemistry. Aβ1-42 (5 μM) applied for 8 h induced the expression and increased the production of the pro-inflammatory cytokines IL-6, IL-1β, TNF-α, the inducible enzyme COX-2 and chemokine IL-8. Microglial treatment with IL-8 added (at 100 ng/mL) with Aβ1-42 led to enhancement in both expression and production of all of these pro-inflammatory factors compared with peptide alone. Stimulation with IL-8 itself was effective in increasing microglial expression of pro-inflammatory cytokines, IL-8 and COX-2, however, had no effect on protein levels of all these factors. The expression of the anti-inflammatory cytokines IL-10 and TGFβ1 remained unchanged from basal levels with stimulation using either Aβ1-42, IL-8 or the peptide together with IL-8. The actions of IL-8 to potentiate Aβ1-42-induced inflammatory mediators may have particular relevance to Alzheimer disease brain which exhibits elevated levels of the chemokine.
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) | 0.002 | 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".