Neuroinflammatory processes, A1 astrocyte activation and protein aggregation in the retina of Alzheimer’s and Parkinson's disease patients: Possible biomarkers for early diagnosis
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease (AD), a primary cause of dementia in the aging population, is characterized by extracellular amyloid‐beta peptides aggregation, intracellular deposits of hyperphosphorylated tau, neurodegeneration and glial activation in the brain. It is commonly thought that the lack of early diagnostic criteria is among the main causes of pharmacological therapy and clinical trials failure therefore, the actual challenge is to define new biomarkers and non‐invasive technologies to measure neuropathological changes in vivo at pre‐symptomatic stages. Recent evidences obtained from human samples and mouse models indicate the possibility to detect protein aggregates and other pathological features in the retina, paving the road for non‐invasive rapid detection of AD biomarkers. Method Human retinal slices from AD (n=20) and PD (n = 10) patients and age matched controls (n=20/10) were purchased from Human Eye Biobank for Research, St Michael Hospital, Toronto, Canada. Immunofluorescence analysis was perfomed using primary antibodies to detect protein aggregates, neurodegeneration and glial activation: anti‐βAmyloid; anti‐Cleaved‐Casapase3; anti‐PhosphoTau; anti‐Iba1; anti‐GFAP; anti‐C3d; anti‐IL‐1β; anti‐αsynuclein; anti‐TH, anti‐TuJ1. Result In all AD patients we detected retinal Aβ and pTau immunoreactivity and both in the inner and outer layers; Aβ plaques number, in a region of 400 mm 2 , was significantly higher in AD patients compared to controls (p<0.01). pTau immunoreactivity (AT100 clone) was significantly higher in the AD retina compared to age matched controls as quantified by fluorescence intensity in each field of view (p<0.005). Analysis GFAP staining showed a marked astrogliosis localized at the level of the ganglion cell layer both in AD and PD retinas. Astrogliosis may arise also as a consequence of aging however, the amount of astrocyte activation was more pronounced in the AD and PD retina compared to controls, as quantified by fluorescence intensity in each field of view. Similarly microglia cell density was increased in AD and PD patients retina compared to age matched controls. C3 and Il1β were enhanced in bot AD and PD retina, suggesting a detrimental glial activation. Conclusion These observations further support the possibility that ocular biomarkers could be used for early detection of AD associated neurodegeneration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".