A Novel Biological Activity of Praziquantel Requiring Voltage-Operated Ca2+ Channel β Subunits: Subversion of Flatworm Regenerative Polarity
Bibliographic record
Abstract
BACKGROUND: Approximately 200 million people worldwide harbour parasitic flatworm infections that cause schistosomiasis. A single drug-praziquantel (PZQ)-has served as the mainstay pharmacotherapy for schistosome infections since the 1980s. However, the relevant in vivo target(s) of praziquantel remain undefined. METHODS AND FINDINGS: Here, we provide fresh perspective on the molecular basis of praziquantel efficacy in vivo consequent to the discovery of a remarkable action of PZQ on regeneration in a species of free-living flatworm (Dugesia japonica). Specifically, PZQ caused a robust (100% penetrance) and complete duplication of the entire anterior-posterior axis during flatworm regeneration to yield two-headed organisms with duplicated, integrated central nervous and organ systems. Exploiting this phenotype as a readout for proteins impacting praziquantel efficacy, we demonstrate that PZQ-evoked bipolarity was selectively ablated by in vivo RNAi of voltage-operated calcium channel (VOCC) beta subunits, but not by knockdown of a VOCC alpha subunit. At higher doses of PZQ, knockdown of VOCC beta subunits also conferred resistance to PZQ in lethality assays. CONCLUSIONS: This study identifies a new biological activity of the antischistosomal drug praziquantel on regenerative polarity in a species of free-living flatworm. Ablation of the bipolar regenerative phenotype evoked by PZQ via in vivo RNAi of VOCC beta subunits provides the first genetic evidence implicating a molecular target crucial for in vivo PZQ activity and supports the 'VOCC hypothesis' of PZQ efficacy. Further, in terms of regenerative biology and Ca(2+) signaling, these data highlight a novel role for voltage-operated Ca(2+) entry in regulating in vivo stem cell differentiation and regenerative patterning.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".