Loss of Panx1 Function in Zebrafish Alters Motor Behavior in a Lab-on-Chip Model of Parkinson's Disease
Bibliographic record
Abstract
Pannexin 1 (Panx1) forms ATP-permeable membrane channels that play essential roles in purinergic signaling in the nervous system. Several studies suggest a link between Panx1-based channels activity and neurodegenerative disorders including Parkinson’s disease (PD), but experimental evidence is limited. Here, we applied behavioral and molecular screening of zebrafish larvae to examine the role of Panx1 in both pathological and normal conditions, using electrical stimulation in a microfluidic chip and RT-qPCR. A zebrafish model of PD was produced by exposing wildtype (panx1a+/+) and Panx1a knock-out (panx1a-/-) zebrafish larvae to 250µM 6-hydroxydopamine (6-OHDA). After 72hrs treatment with 6-OHDA a reduced electric-induced locomotor activity was observed in 5 days post fertilization (dpf) panx1a+/+ larvae. The 5dpf panx1a-/- larvae were not different from affected. The RT-qPCR data showed a reduction in tyrosine hydroxylase (TH) expression level in both panx1a+/+ and panx1a-/- groups. However, TH expression of 6-OHDA exposed panx1a-/- larvae was not decreased when compared to untreated mutants. Extending 6-OHDA treatment duration to 120hrs caused a significant reduction in the locomotor response of 7dpf panx1a-/- larvae when compared to the untreated panx1a-/- group. The RT-qPCR data also confirmed a significant decrease in TH expression levels after 120hrs treatments with 6-OHDA for both genotypes. Our results suggest that the absence of Panx1a channels compromised dopaminergic signaling in 6-OHDA-treated zebrafish larvae. We here propose that zebrafish Panx1a models offer great opportunities to shed light on the physiological and molecular basis of PD. Panx1a might play a preventive role on PD progression, and therefore deserves further investigation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".