On the nature of the Cu-rich aggregates in brain astrocytes
Bibliographic record
Abstract
Fulfilling a bevy of biological roles, copper is an essential metal for healthy brain function. Cu dyshomeostasis has been demonstrated to be involved in some neurological conditions including Menkes and Alzheimer's diseases. We have previously reported localized Cu-rich aggregates in astrocytes of the subventricular zone (SVZ) in rodent brains with Cu concentrations in the hundreds of millimolar. Metallothionein, a cysteine-rich protein critical to metal homeostasis and known to participate in a variety of neuroprotective and neuroregenerative processes, was proposed as a binding protein. Here, we present an analysis of metallothionein(1,2) knockout (MTKO) mice and age-matched controls using X-ray fluorescence microscopy. In large structures such as the corpus callosum, cortex, and striatum, there is no significant difference in Cu, Fe, or Zn concentrations in MTKO mice compared to age-matched controls. In the astrocyte-rich subventricular zone where Cu-rich aggregates reside, approximately 1/3 as many Cu-rich aggregates persist in MTKO mice resulting in a decrease in periventricular Cu concentration. Aggregates in both wild-type and MTKO mice show XANES spectra characteristic of Cu x S y multimetallic clusters and have similar [S]/[Cu] ratios. Consistent with assignment as a Cu x S y multimetallic cluster, the astrocyte-rich SVZ of both MTKO and wild-type mice exhibit autofluorescent bodies, though MTKO mice exhibit fewer. Furthermore, XRF imaging of Au-labeled lysosomes and ubiquitin demonstrates a lack of co-localization with Cu-rich aggregates suggesting they are not involved in a degradation pathway. Overall, these data suggest that Cu in aggregates is bound by either metallothionein-3 or a yet unknown protein similar to metallothionein.
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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) | 0.000 | 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 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".