Fungal diversity differences in the indoor dust microbiome from built environments on earth and in space
Bibliographic record
Abstract
Abstract Human occupied built environments are no longer confined to Earth. In fact, there have been humans living and working in low-Earth orbit on the International Space Station (ISS) since November 2000. With NASA’s Artemis missions and the age of commercial space stations set to begin, more human-occupied spacecraft than ever will be in Earth’s orbit and beyond. On Earth and in the ISS, microbes, especially fungi, can be found in dust and grow when unexpected, elevated moisture conditions occur. However, we do not yet know how indoor microbiomes in Earth-based homes and in the ISS differ due to their unique set of environmental conditions. Here we show that bacterial and fungal communities are different in dust collected from vacuum bags on Earth and the ISS, with Earth-based homes being more diverse (465 fungal OTUs and 237 bacterial ASVs) compared to the ISS (102 fungal OTUs and 102 bacterial ASVs). When dust from these locations were exposed to varying equilibrium relative humidity conditions (ERH), there were also significant fungal community composition changes as ERH and time elevated increased (Bray Curtis: R2 = 0.35, P = 0.001). These findings can inform future spacecraft design to promote healthy indoor microbiomes that support crew health, spacecraft integrity, and planetary protection.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".