[P3–129]: EARLY AND LATE NEUROINFLAMMATORY EVENTS AS ALZHEIMER's DISEASE PATHOLOGY EVOLVES IN DOWN SYNDROME INDIVIDUALS
Bibliographic record
Abstract
Cognitively normal individuals under long term anti-inflammatory treatment have a reduced risk of developing Alzheimer's Disease (AD). We have reported, in transgenic rodent models of AD-like pathology, that intraneuronal-Amyloid Beta (Aβ) accumulation unleashes an early disease-aggravating-neuroinflammation (Hanzel et al., 2014, Ferreti et al., 2012); explaining the efficacy of anti-inflammatories at preclinical stages. It is becoming more evident that pre-clinical AD-neuroinflammation can aggravate AD progression. Little is known about the early neuroinflammation in the human-AD pathology. Down syndrome (DS) individuals represent the largest population of genetically-predisposed AD. They gradually accumulate intraneuronal-Aβ pathology (Busciglio et al., 2012, Mori et al., 2002) that further develops into full-blown AD-neuropathology and, in most cases, leading to dementia. Recently, we have reported an upregulation of inflammatory factors in plasma from DS individuals, before clinical AD-manifestation (Iulita et al., 2016). We propose that intraneuronal-Aβ accumulation will unleash an early neuroinflammatory process at preclinical stages of AD in DS. Moreover, given the importance of inflammasome activation in AD-pathogenesis we are studying its activation throughout the lifespan of DS individuals. Expression of pro-inflammatory genes was analyzed via a qPCR array (QIAGEN) in postmortem frozen frontal cortex tissue of DS (3-weeks-9 months-old) and non-DS-infants (22-days- 13-months-old), DS-AD adults (43–63 years-old) and non-DS-AD (44–68 years-old). Individual qPCR was performed in DS-AD. Protein expression was analyzed via ELISA in the conditioned media of DS and non-DS fetal cortical cells. Pro-inflammatory qPCR-array analysis showed an upregulation of IL-1β, IL-33, IL-6, IL-12a, IL12b, MCP-1, TNFSF11, and a downregulation of IFN-β and CARD18 in DS-infants. Inflammasome-related genes: caspases-1 and 5, NLRP3, NLRP4, NLRP6 were upregulated in DS-infants. DS-AD showed an upregulation of IFN-B and CARD18, IL-6, IL-12, MCP-1; however, the overexpression of inflammatory markers is larger in the DS-infants. MCP-1 and IL-6 protein expression was elevated in the conditioned media of DS-fetal cells as compared to non-DS cell cultures. Our results suggest a differential neuroinflammatory process at early and late stages of AD pathology in DS.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".