Fusion of diphtheria toxin and urotensin II produces a neurotoxin selective for cholinergic neurons in the rat mesopontine tegmentum
Bibliographic record
Abstract
Urotensin II is a neuropeptide first isolated from fish and later found in mammals: where it has potent cardiovascular, endocrine and behavioral effects. In rat brain the urotensin II receptor (UII-R) is predominately expressed in the cholinergic neurons of the pedunculopontine (PPTg) and laterodorsal tegmental nuclei. Typically, the function of the PPTg has been examined using excitotoxins, destroying both cholinergic and non-cholinergic neurons, which confounds interpretation. We took advantage of UII-R's unique expression profile, by combining UII with diphtheria toxin, to engineer a toxin specific for cholinergic neurons of the PPTg. In vitro, two different toxin constructs were shown to selectively activate UII-R (average EC50 approximately 30 nmol/L; calcium mobility assay) and to be 10,000-fold more toxic to UII-R expressing CHO cells, than wildtype cells (average LD50 approximately 2 nmol/L; cell viability). In vivo, pressure injection into the PPTg of rats, resulted in specific loss of choline transporter and NADPH diaphorase positive neurons known to express the UII-R. The lesions developed over time, resulting in the loss of over 80% of cholinergic neurons at 21 days, with little damage to surrounding neurons. This is the first highly selective molecular tool for the depletion of mesopontine cholinergic neurons. The toxin will help to functionally dissect the pedunculopontine and laterodorsal tegmental nuclei, and advance the understanding of the functions of these structures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".