Reduction in neurons immunoreactive for calcium-binding proteins in the anteroventral thalamic nuclei of individuals with Down syndrome
Bibliographic record
Abstract
The anterior thalamic nuclei are important for cognition, and memory in particular. However, little is known about how the anterior thalamic nuclei are affected in many neurological disorders partly due to difficulties in selective segmentation in in vivo scans, due to their size and location. Post-mortem studies, therefore, remain a valuable source of information about the status of the anterior thalamic nuclei. We used post-mortem tissue to assess the status of the anteroventral thalamic nucleus in Down syndrome using samples from males and females ranging from 22-65 years in age and comparing to tissue from age matched controls. As expected, there was increased beta-amyloid plaque expression in the Down syndrome group. While there was a significant increase in neuronal density in the Down syndrome group, the values showed more variation consistent with a heterogeneous population. The surface area of the anteroventral thalamic nucleus was smaller in the Down syndrome group suggesting the increased neuronal density was due to greater neuronal packing but likely fewer overall neurons. There was a marked reduction in the proportion of neurons immunoreactive for the calcium-binding proteins calbindin, calretinin, and parvalbumin in individuals with Down syndrome. These findings highlight the vulnerability of calcium-binding proteins in the anteroventral nucleus in Down syndrome, which could both be driven by, and exacerbate, Alzheimer-related pathology in this region.
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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 | 0.001 |
| 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".