Simulated Microgravity Reduces Focal Adhesions and Alters Cytoskeleton and Nuclear Positioning Leading to Enhanced Apoptosis via Suppressing FAK/RhoA-Mediated mTORC1/NF-κB and ERK1/2 Pathways
Bibliographic record
Abstract
Simulated-microgravity (SMG) promotes cell-apoptosis. We demonstrated that SMG inhibited cell proliferation/metastasis via FAK/RhoA-regulated mTORC1 pathway. Since mTORC1, NF-κB, and ERK1/2 signaling are important in cell apoptosis, we examined whether SMG-enhanced apoptosis is regulated via these signals controlled by FAK/RhoA in BL6-10 melanoma cells under clinostat-modelled SMG-condition. We show that SMG promotes cell-apoptosis, alters cytoskeleton, reduces focal adhesions (FAs), and suppresses FAK/RhoA signaling. SMG down-regulates expression of mTORC1-related Raptor, pS6K, pEIF4E, pNF-κB, and pNF-κB-regulated Bcl2, and induces relocalization of pNF-κB from the nucleus to the cytoplasm. In addition, SMG also inhibits expression of nuclear envelope proteins (NEPs) lamin-A, emerin, sun1, and nesprin-3, which control nuclear positioning, and suppresses nuclear positioning-regulated pERK1/2 signaling. Moreover, rapamycin, the mTORC1 inhibitor, also enhances apoptosis in cells under 1 g condition via suppressing the mTORC1/NF-κB pathway. Furthermore, the FAK/RhoA activator, toxin cytotoxic necrotizing factor-1 (CNF1), reduces cell apoptosis, restores the cytoskeleton, FAs, NEPs, and nuclear positioning, and converts all of the above SMG-induced changes in molecular signaling in cells under SMG. Therefore, our data demonstrate that SMG reduces FAs and alters the cytoskeleton and nuclear positioning, leading to enhanced cell apoptosis via suppressing the FAK/RhoA-regulated mTORC1/NF-κB and ERK1/2 pathways. The FAK/RhoA regulatory network may, thus, become a new target for the development of novel therapeutics for humans under spaceflight conditions with stressed physiological challenges, and for other human diseases.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".