Transcriptomic response of bioengineered human cartilage to parabolic flight microgravity is sex-dependent
Bibliographic record
Abstract
Spaceflight and simulated spaceflight microgravity induced osteoarthritic-like alterations at the transcriptomic and proteomic levels in the articular and meniscal cartilages of rodents. But little is known about the effect of spaceflight or simulated spaceflight microgravity on the transcriptome of tissue-engineered cartilage developed from human cells. In this study, we investigate the effect of simulated spaceflight microgravity facilitated by parabolic flights on tissue-engineered cartilage developed from in vitro chondrogenesis of human bone marrow mesenchymal stem cells obtained from age-matched female and male donors. The successful induction of cartilage-like tissue was confirmed by the expression of well-demonstrated chondrogenic markers. Our bulk transcriptome data via RNA sequencing demonstrated that parabolic flight altered mostly fundamental biological processes, and the modulation of the transcriptome profile showed sex-dependent differences. The secretome profile analysis revealed that two genes (WNT7B and WNT9A) from the Wnt-signaling pathway, which is implicated in osteoarthritis development, were only up-regulated for female donors. The results of this study showed that the engineered cartilage tissues responded to microgravity in a sex-dependent manner, and the reported data offers a strong foundation to further explore the underlying mechanisms.
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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 | 0.000 | 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".