A leaky blood–brain barrier, fibrinogen infiltration and microglial reactivity in inflamed Alzheimer’s disease brain
Bibliographic record
Abstract
This study has used immunohistochemical examination of tissue obtained from Alzheimer's disease (AD) brains and rat hippocampus injected with Abeta(1-42) peptide to determine effects of induced inflammatory reactivity on integrity of blood-brain barrier (BBB) and viability of neurons. Tissue from AD, but not non-demented, brains exhibited a diffuse pattern of staining for fibrinogen and immunoglobulin (IgG) indicative of BBB leakiness with considerable fibrinogen immunoreactivity (ir) appearing in association with Abeta deposits. Immunostaining for the endothelial cell specific glycoprotein, von Willebrand factor, showed morphological evidence for altered blood vessels in AD tissue. AD brains also demonstrated extensive areas of fibrinogen ir in association with microglial reactivity. In vivo, intra-hippocampal injection of Abeta(1-42) caused time-dependent (1-7 days after injection) increases in double staining of fibrinogen with areas of microgliosis. Two independent pharmacological strategies were employed to examine how Abeta(1-42) stimulation (7 days injection) may be linked to neurodegeneration. The defibrinogenating compound, ancrod, reduced inflammatory reactivity, levels of parenchymal fibrinogen and IgG, and was neuroprotective. These results prompted use of Abeta(1-42) plus fibrinogen as a novel in vivo inflammatory stimulus and this combination significantly enhanced inflammatory reactivity, vascular perturbations and neuronal damage compared to Abeta(1-42) alone. A second approach, using anti-Mac-1 (antibody for antigen CD11b) to block activation of microglia, was highly effective in attenuating effects of Abeta(1-42) plus fibrinogen amplification of inflammatory and vascular responses and conferred significant neuroprotection. The overall findings from study of AD tissue and in vivo in Abeta(1-42) and Abeta(1-42) plus fibrinogen stimulated rat hippocampus suggest microglial responses to promote increased extravasation of blood protein as a critical component in amplifying inflammatory reactivity and causing neuronal damage in inflamed AD brain.
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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 | 0.000 | 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".