Tetracycline Derivative Minocycline Inhibits Autophagy and Inflammation in Concanavalin-A-Activated Human Hepatoma Cells
Bibliographic record
Abstract
Inhibition of soluble matrix metalloproteinase (MMP) activity is among the non-antibiotic cellular effects exerted by the anti-inflammatory tetracycline derivative minocycline. The impact of minocycline on the signal transduction functions of membrane-bound MMPs is however unknown. We assessed minocycline in a concanavalin-A (ConA)-activated human HepG2 hepatoma cell model, a condition known to increase the expression of membrane type-1 MMP (MT-MMP) and to trigger inflammatory and autophagy processes. We found that minocycline inhibited ConA-induced formation of autophagic acidic vacuoles, green fluorescent microtubule-associated protein 1 light chain 3 (GFP-LC3) puncta formation, gene and protein expression of autophagy biomarker BCL2/adenovirus E1B 19 kDa interacting protein 3 (BNIP3), invasion biomarker MT1-MMP, and inflammation biomarker cyclooxygenase (COX)-2. Gene silencing of MT1-MMP abrogated ConA-induced formation of autophagic acidic vacuoles and ConA-induced expressions of BNIP3 and COX-2. Minocycline was also shown to inhibit ConA-induced signal transducer and activator of transcription 3 (STAT3) phosphorylation as well as gene expression of NANOS1, a biomarker believed to colocalize with MT1-MMP and the specific silencing of which further inhibited ConA-induced STAT3 phosphorylation. Collectively, our data demonstrate that part of minocycline's effects on autophagy could be exerted through the inhibition of MT1-MMP signaling functions, which contribute to the autophagy and inflammatory phenotype of ConA-activated HepG2 cells.
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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 | 0.000 | 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) | 0.000 | 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".