Autophagy in protists and their hosts: When, how and why?
Bibliographic record
Abstract
Pathogenic protists are a group of organisms responsible for causing a variety of human diseases including malaria, sleeping sickness, Chagas disease, leishmaniasis, and toxoplasmosis, among others. These diseases, which affect more than one billion people globally, mainly the poorest populations, are characterized by severe chronic stages and the lack of effective antiparasitic treatment. Parasitic protists display complex life-cycles and go through different cellular transformations in order to adapt to the different hosts they live in. Autophagy, a highly conserved cellular degradation process, has emerged as a key mechanism required for these differentiation processes, as well as other functions that are crucial to parasite fitness. In contrast to yeasts and mammals, protist autophagy is characterized by a modest number of conserved autophagy-related proteins (ATGs) that, even though, can drive the autophagosome formation and degradation. In addition, during their intracellular cycle, the interaction of these pathogens with the host autophagy system plays a crucial role resulting in a beneficial or harmful effect that is important for the outcome of the infection. In this review, we summarize the current state of knowledge on autophagy and other related mechanisms in pathogenic protists and their hosts. We sought to emphasize when, how, and why this process takes place, and the effects it may have on the parasitic cycle. A better understanding of the significance of autophagy for the protist life-cycle will potentially be helpful to design novel anti-parasitic strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".