Human Astrocytes: Secretome Profiles of Cytokines and Chemokines
Bibliographic record
Abstract
Astrocytes play a key role in maintenance of neuronal functions in the central nervous system by producing various cytokines, chemokines, and growth factors, which act as a molecular coordinator of neuron-glia communication. At the site of neuroinflammation, astrocyte-derived cytokines and chemokines play both neuroprotective and neurotoxic roles in brain lesions of human neurological diseases. At present, the comprehensive profile of human astrocyte-derived cytokines and chemokines during inflammation remains to be fully characterized. We investigated the cytokine secretome profile of highly purified human astrocytes by using a protein microarray. Non-stimulated human astrocytes in culture expressed eight cytokines, including G-CSF, GM-CSF, GROα (CXCL1), IL-6, IL-8 (CXCL8), MCP-1 (CCL2), MIF and Serpin E1. Following stimulation with IL-1β and TNF-α, activated astrocytes newly produced IL-1β, IL-1ra, TNF-α, IP-10 (CXCL10), MIP-1α (CCL3) and RANTES (CCL5), in addition to the induction of sICAM-1 and complement component 5. Database search indicated that most of cytokines and chemokines produced by non-stimulated and activated astrocytes are direct targets of the transcription factor NF-kB. These results indicated that cultured human astrocytes express a distinct set of NF-kB-target cytokines and chemokines in resting and activated conditions, suggesting that the NF-kB signaling pathway differentially regulates gene expression of cytokines and chemokines in human astrocytes under physiological and inflammatory conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".