Caractérisation et rôle dans l'interaction tripartite du microbiote d'hôtes intermédiaires Planorbidae des parasites trématodes Schistosoma spp. agent responsable de la bilharziose
Bibliographic record
Abstract
Every living organism is faced, eventually, to microorganisms, whether they are bacteria, viruses, fungi or protists. Microbiota largo sensu represent all these microorganisms, living in a host a T time. It is considered, since years, as an integral compartment of its host. It can affect several host functions, like nutrition, development or immunity. Thus, it can play a key role in interactions between organisms, notably hosts/parasites and hosts/pathogens interactions, improving the immune system of its host or directly affecting the invader. The case of Biomphalaria glabrata and other Planorbidae, intermediate hosts of Schistosoma sp. parasites, responsible agent for bilharzia, is a perfect model to study the role of microbiota in host/parasite interactions. Indeed, understanding the interaction between the worm and its intermediate host could open the way for new measure to fight it, as blocking its lifecycle. The characterization of mollusks' microbiota and its role in the interaction is, thus, an interesting way to explore. During my PhD, I (i) characterized the bacterial and protist microbiota of several Planorbidae species in order to compare it according to host phylogeny; (ii) studied the dynamic of microbiota bacterial communities during an infection kinetic in different B. glabrata strains and; (iii) disturbed the bacterial microbiota and observed the consequences on the mollusks resistance to parasite, in order to highlight a potential role of these bacteria in their host immunity. One of the main results of this work is the high specificity of bacterial communities to their host phylogeny, displaying a phylosymbiosis pattern. Moreover, a variation in infection intensity or prevalence has been highlighted, depending on host/parasite combination, after a microbiota disturbance, suggesting a link between the latter and the antiparasitic immunity of mollusks. Thus, this PhD work is a first step in the understanding of the tripartite interaction between a parasite, its intermediate host and the microbiota of the latter, that could, in time, open new perspectives in the fight against the responsible agent of bilharzia.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".