Delineating cellular interactions between ciliates and fish by co‐culturing <i>Tetrahymena thermophila</i> with fish cells
Bibliographic record
Abstract
Although several species of Tetrahymena are often described as histophagous and opportunistic pathogens of fish, little is known about ciliate/fish cell interactions, but one approach for studying these is in vitro with cell lines. In this study, T. thermophila, B1975 (wild type) and NP1 (temperature sensitive mutant for phagocytosis) were cultured on monolayers of 3 fish epithelial cell lines, CHSE-214, RTgill-W1, and ZEB2J, and the rabbit kidney epithelial cell line, RK-13. Generally the ciliates flourished, whereas the monolayers died, being completely consumed over several days. The destruction of monolayers required that the ciliates could make contact with the animal cells through swimming, which appeared to dislodge or loosen cells so that they could be phagocytosed. The ciliates internalized into food vacuoles ZEB2J from cell monolayers as well as from cell suspensions. Phagocytosis was essential for monolayer destruction as monolayers remained intact under conditions where phagocytosis was impeded, such as 37°C for NP1 and 4°C for B1975. Monolayers of fish cells supported the proliferation of ciliates. Thus T. thermophila can 'eat' animal cells or be histophagous in vitro, with the potential to be histophagous in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".