Huddling together to survive: Population density as a survival strategy of non-spore forming bacteria under nutrient starvation and desiccation at solid-air interfaces
Bibliographic record
Abstract
Acclimation and flexible response mechanisms are survival adaptations allowing prokaryotic cells to colonize diverse habitats and maintain viability in nature. Lack of water significantly impacts cellular response, which can be partially compensated for through community interactions and accessing survival means beyond the cell's boundaries. In the present study, higher numbers of cultivable Gram-positive Arthrobacter sp. and Gram-negative Pseudomonas stutzeri cells were found on surfaces when high population density was used after prolonged periods of desiccation and nutrient starvation. Total cell counts during desiccation periods decreased slower than culturable cell counts independently from initial population density. The presence of homogenate, prepared by filtering homogenized cultures through a 0.2 µm filter, extended culturability of Arthrobacter sp. cells, while intact heat-killed cells extended the culturability of Arthrobacter sp. and P. stutzeri. Our results suggest very slow cell membrane breakdown for desiccated bacterial cells at solid-air interfaces over extended time spans, which may serve as reservoirs of nutrients, and may potentially provide trace amounts of water for surviving cells. Higher initial population density and recycling of resources from "zombie"-like cells, may support growth in a similar fashion as access to cell lysates or the contents of heat-killed cells analogous to dead-phase cultures where some cells experience cryptic growth.
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) | 0.000 | 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".