Neuronal PTP1B hastens Alzheimer's disease in mice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Familial forms of Alzheimer's Disease (AD) are tied to mutations in the amyloid precursor protein, but the cellular mechanisms that cause AD remain unclear. Here, we used 2 mouse models: one with amyloid beta pathology (hAPP-J20) and another with tau pathology (PS19) and asked whether activation of a phosphatase PTP1B participates in the disease process. In hAPP-J20 mice, systemic inhibition of this phosphatase using a selective inhibitor (Trodusquemine) prevented cognitive decline, neuron loss in the hippocampus and attenuated inflammation. Importantly, neuron-targeted ablation of PTP1B also prevented cognitive decline and neuron loss but did not reduce inflammation. Therefore, neuronal loss rather than inflammation was critical for AD progression in this mouse model, and that disease progression could be ameliorated by inhibition of PTP1B (Ricke et al. J Neurosci 2020, PMID: 31915254). Similarly, Trodusquemine not only prevented cognitive decline but also restored proper emotional response in PS19 mice. In summary, our preclinical studies suggests that targeting PTP1B may be a new strategy to intervene in the progression of AD. Significance: Trodusquemine is a non-competitive selective inhibitor of PTP1B. It is a natural compound isolated from dogfish liver and can pass through the blood-brain-barrier. Trodusquemine has undergone phase II clinical trials for obesity treatment, hence can be repurposed for Alzheimer's disease therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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