Various dictyostelids from the environment can produce multilamellar bodies
Bibliographic record
Abstract
Multilamellar bodies (MLBs), structures composed of concentric membrane layers, are known to be produced by different protozoa, including species of ciliates, free-living amoebae, and Dictyostelium discoideum social amoebae. Initially believed to be metabolic waste, potential roles like cell communication and food storage have been suggested for D. discoideum MLBs, which could be useful for the multicellular development of social amoebae and as a food source. However, among dictyostelids, this phenomenon has only been observed with D. discoideum, and mainly with laboratory strains grown in axenic conditions. It was thought that other social amoebae may also produce MLBs. Four environmental social amoeba isolates were characterized. All strains belong to the Dictyostelium genus, including some likely to be Dictyostelium giganteum. They have distinctive phenotypes comprising their growth rate on Klebsiella aerogenes lawns and the morphology of their fruiting bodies. They all produce MLBs like those produced by a D. discoideum laboratory strain when grown on K. aerogenes lawns, as revealed by analysis using the H36 antibody in epifluorescence microscopy as well as by transmission electron microscopy. Consequently, this study shows that MLBs are produced by various dictyostelid species, which further supports a role for MLBs in the lifestyle of amoebae.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".