Identifying Early Inflammatory Changes in Monocyte-Derived Macrophages from a Population with IQ-Discrepant Episodic Memory
Bibliographic record
Abstract
BACKGROUND: Cells of the innate immune system including monocytes and macrophages are the first line of defence against infections and are critical regulators of the inflammatory response. These cells express toll-like receptors (TLRs), innate immune receptors which govern tailored inflammatory gene expression patterns. Monocytes, which produce pro-inflammatory mediators, are readily recruited to the central nervous system (CNS) in neurodegenerative diseases. METHODS: This study explored the expression of receptors (CD11b, TLR2 and TLR4) on circulating monocyte-derived macrophages (MDMs) and peripheral blood mononuclear cells (PBMCs) isolated from healthy elderly adults who we classified as either IQ memory-consistent (high-performing, HP) or IQ memory-discrepant (low-performing, LP). RESULTS: The expression of CD11b, TLR4 and TLR2 was increased in MDMs from the LP group when compared to HP cohort. MDMs from both groups responded robustly to treatment with the TLR4 activator, lipopolysaccharide (LPS), in terms of cytokine production. Significantly, MDMs from the LP group displayed hypersensitivity to LPS exposure. INTERPRETATION: Overall these findings define differential receptor expression and cytokine profiles that occur in MDMs derived from a cohort of IQ memory-discrepant individuals. These changes are indicative of inflammation and may be involved in the prodromal processes leading to the development of neurodegenerative disease.
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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 | 0.000 |
| 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".