Astrocyte-like glia-specific gene deathstar is crucial for normal development, adult locomotion and lifespan of male Drosophila
Bibliographic record
Abstract
Abstract Background: Drosophila melanogaster is a proper model organism for studying the development and function of the nervous system. The Drosophila nervous system consists of distinct cell types with significant homologies to various cell types of more advanced organisms, including human. Among all cell types of the nervous system, astrocyte-like glia (ALG) have conserved functions to mammals and are essential for normal physiology and behaviours of the fly.Results: In this study, we exploited the gene expression profile of single cells in Drosophila optic lobe to identify the genes with specific expression pattern in each cell type. Through a bioinformatical analysis of the data, a novel ALG-specific gene (here assigned as deathstar) was identified. Immunostaining of deathstar in the central nervous system (CNS) showed its presence in specific regions of Drosophila ventral nerve cord, which previously has been characterized as ALG cells. Consistent with the bioinformatical analysis, deathstar-related signals were overlapped with the signals of the previously-reported ALG marker, Eaat1, supporting its specific expression in ALG cells. At the physiological level, RNAi-mediated suppression of deathstar gene impeded the normal development of male flies without any effects on females. Cell type-specific expression of deathstar RNAi showed that deathstar gene affects locomotion behaviour and lifespan of D. melanogaster, in an ALG-specific manner.Conclusions: Taken together, we showed that bioinformatical analysis of a previously reported expression data of Drosophila optic lobe successfully predicted the ALG-specific expression pattern of deathstar gene. Moreover, it was consistent with the ALG-specific effects of this gene on locomotion and lifespan of D. melanogaster, in vivo.
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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".