Aberrant adhesion impacts early development in a<i>Dictyostelium</i>model for juvenile neuronal ceroid lipofuscinosis
Bibliographic record
Abstract
Neuronal ceroid lipofuscinosis (NCL), also known as Batten disease, refers to a group of severe neurodegenerative disorders that primarily affect children. The most common subtype of the disease is caused by loss-of-function mutations in CLN3, which is conserved across model species from yeast to human. The precise function of the CLN3 protein is not known, which has made targeted therapy development challenging. In the social amoeba Dictyostelium discoideum, loss of Cln3 causes aberrant mid-to-late stage multicellular development. In this study, we show that Cln3-deficiency causes aberrant adhesion and aggregation during the early stages of Dictyostelium development. cln3− cells form ∼30% more multicellular aggregates that are comparatively smaller than those formed by wild-type cells. Loss of Cln3 delays aggregation, but has no significant effect on cell speed or cAMP-mediated chemotaxis. The aberrant aggregation of cln3− cells cannot be corrected by manually pulsing cells with cAMP. Moreover, there are no significant differences between wild-type and cln3− cells in the expression of genes linked to cAMP chemotaxis (e.g., adenylyl cyclase, acaA; the cAMP receptor, carA; cAMP phosphodiesterase, pdsA; g-protein α 9 subunit, gpaI). However, during this time in development, cln3− cells show reduced cell-substrate and cell-cell adhesion, which correlate with changes in the levels of the cell adhesion proteins CadA and CsaA. Specifically, loss of Cln3 decreases the intracellular level of CsaA and increases the amount of soluble CadA in conditioned media. Together, these results suggest that the aberrant aggregation of cln3− cells is due to reduced adhesion during the early stages of development. Revealing the molecular basis underlying this phenotype may provide fresh new insight into CLN3 function.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".