Calmodulin binding proteins and neuroinflammation in multiple neurodegenerative diseases
Why this work is in the frame
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Bibliographic record
Abstract
Calcium dysregulation ("Calcium Hypothesis") is an early and critical event in Alzheimer's and other neurodegenerative diseases. Calcium binds to and regulates the small regulatory protein calmodulin that in turn binds to and regulates several hundred calmodulin binding proteins. Initial and continued research has shown that many calmodulin binding proteins mediate multiple events during the onset and progression of Alzheimer's disease, thus establishing the "Calmodulin Hypothesis". To gain insight into the general applicability of this hypothesis, the involvement of calmodulin in neuroinflammation in Alzheimer's, amyotrophic lateral sclerosis, Huntington's disease, Parkinson's disease, frontotemporal dementia, and other dementias was explored. After a literature search for calmodulin binding, 11 different neuroinflammatory proteins (TREM2, CD33, PILRA, CR1, MS4A, CLU, ABCA7, EPHA1, ABCA1, CH3L1/YKL-40 and NLRP3) were scanned for calmodulin binding domains using the Calmodulin Target Database. This analysis revealed the presence of at least one binding domain within which visual scanning demonstrated the presence of valid binding motifs. Coupled with previous research that identified 13 other neuroinflammation linked proteins (BACE1, BIN1, CaMKII, PP2B, PMCA, NOS, NMDAR, AchR, Ado A2AR, Aβ, APOE, SNCA, TMEM175), this work shows that at least 24 critical proteins involved in neuroinflammation are putative or proven calmodulin binding proteins. Many of these proteins are linked to multiple neurodegenerative diseases indicating that calmodulin binding proteins lie at the heart of neuroinflammatory events associated with multiple neurodegenerative diseases. Since many calmodulin-based pharmaceuticals have been successfully used to treat Huntington's and other neurodegenerative diseases, these findings argue for their immediate therapeutic implementation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it