LKB1 regulates polarity remodeling and adherens junction formation in the <i>Drosophila</i> eye
Bibliographic record
Abstract
The serine-threonine kinase LKB1 regulates cell polarity from Caenorhabditis elegans to man. Loss of lkb1 leads to a cancer predisposition, known as Peutz-Jeghers Syndrome. Biochemical analysis indicates that LKB1 can phosphorylate and activate a family of AMPK- like kinases, however, the precise contribution of these kinases to the establishment and maintenance of cell polarity is still unclear. Recent studies propose that LKB1 acts primarily through the AMP kinase to establish and/or maintain cell polarity. To determine whether this simple model of how LKB1 regulates cell polarity has relevance to complex tissues, we examined lkb1 mutants in the Drosophila eye. We show that adherens junctions expand and apical, junctional, and basolateral domains mix in lkb1 mutants. Surprisingly, we find LKB1 does not act primarily through AMPK to regulate cell polarity in the retina. Unlike lkb1 mutants, ampk retinas do not show elongated rhabdomeres or expansion of apical and junctional markers into the basolateral domain. In addition, nutrient deprivation does not reveal a more dramatic polarity phenotype in lkb1 photoreceptors. These data suggest that AMPK is not the primary target of LKB1 during eye development. Instead, we find that a number of other AMPK-like kinase, such as SIK, NUAK, Par-1, KP78a, and KP78b show phenotypes similar to weak lkb1 loss of function in the eye. These data suggest that in complex tissues, LKB1 acts on an array of targets to regulate cell polarity.
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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) | 0.001 | 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".