Kaempferol enhances ER-mitochondria coupling and protects motor neurons from mitochondrial dysfunction and ER stress in C9ORF72-ALS
Bibliographic record
Abstract
Repeat expansions in the C9ORF72 gene are a frequent cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. Considerable progress has been made in identifying C9ORF72-mediated disease and resolving its underlying etiopathogenesis. The contributions of intrinsic mitochondrial deficits as well as chronic endoplasmic reticulum stress to the development of the C9ORF72-linked pathology are well established. Nevertheless, to date, no cure or effective therapy is available, and thus attempts to find a potential drug target, have received increasing attention. Here, we investigated the mode of action and therapeutic effect of a naturally occurring dietary flavanol, kaempferol in preclinical rodent and human models of C9ORF72-ALS. Notably, kaempferol treatment of C9ORF72-ALS human patient-derived motor neurons/neurons, resolved mitochondrial deficits, promoted resiliency against severe ER stress, and conferred neuroprotection. Treatment of symptomatic C9ORF72 mice with kaempferol, normalized mitochondrial calcium uptake, restored mitochondria function, and diminished ER stress. Importantly, in vivo, chronic kaempferol administration ameliorated pathological motor dysfunction and inhibited motor neuron degeneration, highlighting the translational potential of kaempferol. Lastly, in silico modelling identified a novel kaempferol target and mechanistically the neuroprotective mechanism of kaempferol is through the iP3R-VDAC1 pathway via the modulation of GRP75 expression. Thus, kaempferol holds great promise for treating neurodegenerative diseases where both mitochondrial and ER dysfunction are causally linked to the pathophysiology.
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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 | 0.000 | 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 | 0.001 |
| 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".