Differential functions of phosphatidylinositol 4‐kinases in neurotransmission and synaptic development
Bibliographic record
Abstract
Abstract Phosphoinositides, such as PI(4,5)P 2 , are known to function as structural components of membranes, signalling molecules, markers of membrane identity, mediators of protein recruitment and regulators of neurotransmission and synaptic development. Phosphatidylinositol 4‐kinases (PI4Ks) synthesize PI4P, which are precursors for PI(4,5)P 2 , but may also have independent functions. The roles of PI4Ks in neurotransmission and synaptic development have not been studied in detail. Previous studies on PI4KII and PI4KIIIβ at the Drosophila larval neuromuscular junction have suggested that PI4KII and PI4KIIIβ enzymes may serve redundant roles, where single PI4K mutants yielded mild or no synaptic phenotypes. However, the precise synaptic functions (neurotransmission and synaptic growth) of these PI4Ks have not been thoroughly studied. Here, we used PI4KII and PI4KIIIβ null mutants and presynaptic‐specific knockdowns of these PI4Ks to investigate their roles in neurotransmission and synaptic growth. We found that PI4KII and PI4KIIIβ appear to have non‐overlapping functions. Specifically, glial PI4KII functions to restrain synaptic growth, whereas presynaptic PI4KIIIβ promotes synaptic growth. Furthermore, loss of PI4KIIIβ or presynaptic PI4KII impairs neurotransmission. The data presented in this study uncover new roles for PI4K enzymes in neurotransmission and synaptic growth.
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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".