Hydra’s Lasting Partnership with Microbes: The Key for Escaping Senescence?
Bibliographic record
Abstract
Aging results from a complex interplay between genetic endowment and environmental exposures during lifetime. As our understanding of the aging process progresses, so does the need for experimental animal models that allow a mechanistic understanding of the genetic and environmental factors involved. One such well-studied animal model is the freshwater polyp Hydra. Hydra are remarkable because they are non-senescent. Much of this non-senescence can be ascribed to a tissue consisting of stem cells with continuous self-renewal capacity. Another important fact is that Hydra’s ectodermal epithelial surface is densely colonized by a stable multispecies bacterial community. The symbiotic partnership is driven by interactions among the microbiota and the host. Here, we review key advances over the last decade that are deepening our understanding of the genetic and environmental factors contributing to Hydra’s non-senescent lifestyle. We conclude that the microbiome prevents pathobiont invasion (colonization resistance) and stabilizes the patterning mechanisms, and that microbiome malfunction negatively affects Hydra’s continuous self-renewal capacity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.005 | 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 teacher head, 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".