Extracellular excystation and development of Cryptosporidium: tracing the fate of oocysts within Pseudomonas aquatic biofilm systems
Bibliographic record
Abstract
BACKGROUND: Aquatic biofilms often serve as environmental reservoirs for microorganisms and provide them with a nutrient-rich growth environment under harsh conditions. With regard to Cryptosporidium, biofilms can serve as environmental reservoirs for oocysts, but may also support the growth of additional Cryptosporidium stages. RESULTS: Here we used confocal laser scanning microscopy, scanning electron microscopy (SEM), and flow cytometry to identify and describe various Cryptosporidium developmental stages present within aquatic biofilm systems, and to directly compare these to stages produced in cell culture. We also show that Cryptosporidium has the ability to form a parasitophorous vacuole independently, in a host-free biofilm environment, potentially allowing them to complete an extracellular life cycle. Correlative data from confocal and SEM imaging of the same cells confirmed that the observed developmental stages (including trophozoites, meronts, and merozoites) were Cryptosporidium. These microscopy observations were further supported by flow cytometric analyses, where excysted oocyst populations were detected in 1, 3 and 6 day-old Cryptosporidium-exposed biofilms, but not in biofilm-free controls. CONCLUSIONS: These observations not only highlight the risk that aquatic biofilms pose in regards to Cryptosporidium outbreaks from water distribution systems, but further indicate that even simple biofilms are able to stimulate oocyst excystation and support the extracellular multiplication and development of Cryptosporidium within aquatic environments.
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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".