Dopamine Receptors Gene Expression Pattern and Locomotor Improvement Differ Between Female and Male Zebrafish During Spinal Cord Auto Repair
Bibliographic record
Abstract
The dopaminergic system, a spinal cord (SC) motor circuit regulator, is administrated by sexual hormones and evolutionary conserved in all vertebrates. Accordingly, we hypothesized that the dopamine receptor (DAR) expression pattern may be dissimilar in female and male zebrafish SC auto repair. We implemented an uncomplicated method to induce spinal cord injury (SCI) on fully reproductive adult zebrafish, in both genders. SCI was induced using a 28-gauge needle at 9th–10th vertebra without skin incision. Thereupon, lesioned SC was harvested for DAR gene expression analysis; zebrafish were tracked routinely for any improvement in swim distance, speed, and their roaming capabilities/preference. Our findings revealed discrepancies between drd2a , drd2b , drd3 , drd4a , and drd4b expression patterns at 1, 7, and 14 days postinjury (DPI) between female and male zebrafish. The receptors were mostly upregulated at 7 DPI in both genders, whereas drd2a and drd2b were mostly maximized in females. Surprisingly, drd3 was measured greater even in intact SC in males. In addition, female zebrafish were able to swim farther distances more accelerated, in multiple directions, by engaging more caudal muscles compared with males, of course with no statistical significance. Indeed, females were able to generate whole-body rotation and move forward using the muscles downstream to the lesion site, whereas the coordinated movement in males was accomplished by rostral muscles. In conclusion, there are differences in DAR gene expression pattern throughout SC autonomous recovery between adult female and male zebrafish, and also, female locomotion seems to ameliorate more rapidly.
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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".