A Submersible, Off-Axis Holographic Microscope for Detection of Microbial Motility and Morphology in Aqueous and Icy Environments
Bibliographic record
Abstract
Sea ice is an analog environment for several of astrobiology's near-term targets: Mars, Europa, Enceladus, and perhaps other Jovian or Saturnian moons. Microorganisms, both eukaryotic and prokaryotic, remain active within brine channels inside the ice, making it unnecessary to penetrate through to liquid water below in order to detect life. We have developed a submersible digital holographic microscope (DHM) that is capable of resolving individual bacterial cells, and demonstrated its utility for immediately imaging samples taken directly from sea ice at several locations near Nuuk, Greenland. In all samples, the appearance and motility of eukaryotes were conclusive signs of life. The appearance of prokaryotic cells alone was not sufficient to confirm life, but when prokaryotic motility occurred, it was rapid and conclusive. Warming the samples to above-freezing temperatures or supplementing with serine increased the number of motile cells and the speed of motility; supplementing with serine also stimulated chemotaxis. These results show that DHM is a useful technique for detection of active organisms in extreme environments, and that motility may be used as a biosignature in the liquid brines that persist in ice. These findings have important implications for the design of missions to icy environments and suggest ways in which DHM imaging may be integrated with chemical life-detection suites in order to create more conclusive life detection packages.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".