Evaluation and Validation of Commercially Available Dopamine Transporter Antibodies
Bibliographic record
Abstract
With a wide variety of dopamine transporter (DAT) antibodies available commercially, it is important to validate which antibodies provide sufficient immunodetection for reproducibility purpose and for accurate analysis of DAT levels and/or location. Commercially available DAT antibodies that are commonly used were tested in western blotting (WB) on wild-type (WT) and DAT-knock-out (DAT-KO) brain tissue and with immunohistology (IH) techniques against coronal slices of unilaterally lesioned 6-OHDA rats, in addition to wild-type and DAT-knock-out mice. DAT-KO mice and unilateral 6-OHDA lesions in rats were used as a negative control for DAT antibody specificity. Antibodies were tested at various concentrations and rated based on signal detection varying from no signal to optimal signal detection. Commonly used antibodies, including AB2231 and PT-22 524-1-AP, did not provide specific DAT signals in WB and IH. Although certain antibodies provided a good DAT signal, such as SC-32258, D6944, and MA5-24796, they also presented nonspecific bands in WB. Many DAT antibodies did not detect the DAT as advertised, and this characterization of DAT antibodies may provide a guide for immunodetection of DAT for molecular studies.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".