Cerebrospinal fluid soluble insulin receptor levels in Alzheimer's disease
Bibliographic record
Abstract
INTRODUCTION: Brain insulin resistance and deficiency is a consistent feature of Alzheimer's disease (AD). Insulin resistance can be mediated by the surface expression of the insulin receptor (IR). Cleavage of the IR generates the soluble IR (sIR). METHODS: = 61). We further investigated the brain cellular contribution for sIR using human cell lines. RESULTS: CSF sIR levels were not statistically different in AD. CSF sIR and amyloid beta (Aβ)42 and Aβ40 levels significantly correlated as well as CSF sIR and cognition in the CIMA-Q cohort. Human neurons expressing the amyloid precursor protein "Swedish" mutation generated significantly greater sIR and human astrocytes were also able to release sIR in response to both an inflammatory and insulin stimulus. DISCUSSION: These data support further investigation into the generation and role of sIR in AD. Highlights: Cerebrospinal fluid (CSF) soluble insulin receptor (sIR) levels positively correlate with amyloid beta (Aβ)42 and Aβ40.CSF sIR levels negatively correlate with cognitive performance (Montreal Cognitive Assessment score).CSF sIR levels in humans remain similar across Alzheimer's disease diagnostic groups.Neurons derived from humans with the "Swedish" mutation in which Aβ42 is increased generate increased levels of sIR.Human astrocytes can also produce sIR and generation is stimulated by tumor necrosis factor α and insulin.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".