Effects of Sphingosine-1-Phosphate on Cell Viability, Differentiation, and Gene Expression of Adipocytes
Bibliographic record
Abstract
Sphingosine-1-phosphate (S1P) is a highly potent sphingolipid metabolite, which controls numerous physiological and pathological process via its extracellular and intracellular functions. The breast is mainly composed of epithelial cells (mammary gland) and adipocytes (stroma). Adipocytes play an important role in regulating the normal functions of the breast. Compared to the vast amount studies on breast epithelial cells, the functions of S1P in breast adipocytes are much less known. Thus, in the current study, we used human preadipocyte cell lines SGBS and mouse preadipocyte cell line 3T3-L1 as in vitro models to evaluate the effects of S1P on cell viability, differentiation, and gene expression in adipocytes. Our results showed that S1P increased cell viability in SGBS and 3T3-L1 preadipocytes but moderately reduced cell viability in differentiated SGBS and 3T3-L1 adipocytes. S1P was also shown to inhibit adipogenic differentiation of SGBS and 3T3-L1 at concentration higher than 1000 nM. Transcriptome analyses showed that S1P was more influential on gene expression in differentiated adipocytes. Furthermore, our network analysis in mature adipocytes showed that the upregulated DEGs (differentially expressed genes) were related to regulation of lipolysis, PPAR (peroxisome proliferator-activated receptor) signaling, alcoholism, and toll-like receptor signaling, whereas the downregulated DEGs were overrepresented in cytokine-cytokine receptor interaction, focal adhesion, starch and sucrose metabolism, and nuclear receptors pathways. Together previous studies on the functions of S1P in breast epithelial cells, the current study implicated that S1P may play a critical role in modulating the bidirectional regulation of adipocyte-extracellular matrix-epithelial cell axis and maintaining the normal physiological functions of the breast.
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 | 0.001 |
| 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".