St. John's wort and its constituent hyperforin concordantly regulate expression of genes encoding enzymes involved in basic cellular pathways
Bibliographic record
Abstract
OBJECTIVES AND METHODS: The effects of St. John's wort and hyperforin on gene expression were analysed in HepG2 cells by Affymetrix microarray hybridization and real time reverse transcription-PCR. RESULTS: Both compounds increased mRNAs of the drug metabolizing enzymes CYP3A4, CYP1A1, CYP1A2 and the flavin containing monooxygenase FMO5, and of the multidrug resistance protein MRP2. CYP4F2 and the reduced nicotinamide adenine dinucleotide dehydrogenase NQO1 were downregulated. Expression of genes mediating cholesterol biosynthesis was decreased, while facilitated glucose transporters and glycolysis genes were induced, indicating increased glucose metabolism. Changes of a considerable number of additional transcripts corresponded to reports on gene regulation by hypoxia. Endoplasmic reticulum stress-regulated genes involved in unfolded protein response and in protection of cells from apoptosis were downregulated. Other calcium binding proteins were affected by both treatments, suggesting an increase in intracellular calcium. CONCLUSIONS: St. John's wort and hyperforin concordantly affected expression of genes not only mediating metabolism and transport of exogenous and endogenous compounds, but also involved in energy metabolism, intracellular calcium regulation, cell proliferation and apoptosis.
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) | 0.002 | 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".