Cystamine metabolism and brain transport properties: clinical implications for neurodegenerative diseases
Why this work is in the frame
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Bibliographic record
Abstract
Cystamine has shown significant neuroprotective properties in preclinical studies of Parkinson's disease (PD) and Huntington's disease (HD). Cysteamine, its FDA-approved reduced form, is scheduled to be tested for clinical efficacy in HD patients. Here, we studied the key cystamine metabolites, namely cysteamine, hypotaurine and taurine, as well as cysteine, in order to identify which one is more distinctively responsible for the neuroprotective action of cystamine. After a single administration of cystamine (10, 50 or 200 mg/kg), naïve mice were perfused with phosphate-buffered saline (PBS) at 1, 3, 12, 24 or 48 h post-injection and brain and plasma samples were analyzed by two distinct HPLC methods. Although plasma levels remained under the detection threshold, significant increases in cysteamine brain levels were detected with the 50 and 200 mg/kg doses in mice perfused 1 and 3 h following cystamine injection. To further assess cysteamine as the candidate molecule for pre-clinical and clinical trials in PD, we evaluated its capacity to cross the blood brain barrier. Using an in situ cerebral perfusion technique, we determined that the brain transport coefficient (Clup) of cysteamine (259 μM) was 0.15 ± 0.02 μL/g/s and was increased up to 0.34 ± 0.07 μL/g/s when co-perfused in the presence of cysteine. Taken together, these results strongly suggest that cysteamine is the neuroactive metabolite of cystamine and may further support its therapeutic use in neurodegenerative diseases, particularly in HD and PD.
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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 | 0.004 |
| 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 | 0.000 |
| 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