Microgravity-induced immune dysregulation: phase-specific profiles of differential gene expression.
Bibliographic record
Abstract
Astronauts experience the reactivation of latent viruses in spaceflight, an indicator of reduced immunity. It is unclear how the immune system responds to pathogens in a microgravity environment. A longitudinal profile of leukocytes' transcriptome changes from participants to an Earth model of microgravity and from astronauts sojourning aboard the International Space Station revealed a reduced expression of immune-related genes while in microgravity. In the current study, we identified transcriptomic changes specific to the transition to and from bed/space, as well as the adaptation, and the recovery from microgravity/space exposure. The expression of immune-related gene shifted in opposite direction at phase transition compared to within the bed rest and reambulation phases. Differential expression of cytokine genes supported a reduced immune-response during the head down tilt bed rest phase and return to baseline levels at reambulation. Immunoglobulin gene expression increased after participants left the facility. The enrichment analysis of the differentially expressed genes identified the gene ontology terms virus/viral and genes previously involved in the modulation of the response to latent reactivation, including IFNL1, TNFSF14, IL10, and ISG15. Leukocytes' transcriptomic analysis revealed dynamic changes of immune-related gene expression timed with phases of spaceflight. The current analysis combined with previous evidence of herpesvirus reactivation during space mission represent a valuable model for the study of viral latency in vivo.
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".