Simulated Microgravity Influences Immunity-Related Biomarkers in Lung Cancer
Bibliographic record
Abstract
Microgravity is a novel strategy that may serve as a complementary tool to develop future cancer therapies. In lung cancer, the influence of microgravity on cellular processes and the migratory capacity of cells is well addressed. However, its effect on the mechanisms that drive lung cancer progression remains in their infancy. In this study, 13 differentially expressed genes were shown to be associated with the prognosis of lung cancer under simulated microgravity (SMG). Using gene set enrichment analysis, these genes are enriched in humoral immunity pathways. In lieu, alveolar basal-epithelial (A549) cells were exposed to SMG via a 2D clinostat system in vitro. In addition to morphology change and decrease in proliferation rate, SMG reverted the epithelial-to-mesenchymal transition (EMT) phenotype of A549, a key mechanism in cancer progression. This was evidenced by increased epithelial E-cadherin expression and decreased mesenchymal N-cadherin expression, hence exhibiting a less metastatic state. Interestingly, we observed increased expression of FCGBP, BPIFB, F5, CST1, and CFB and their correlation to EMT under SMG, rendering them potential tumor suppressor biomarkers. Together, these findings reveal new opportunities to establish novel therapeutic strategies for lung cancer treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".