Inhibitory effects of AptaminC320 targeting vitamin C on LPS-induced inflammation in RAW264.7 cells
Bibliographic record
Abstract
Inflammation, a vital immune response, is regulated by macrophages. Key regulators of this response in macrophages are the nuclear factor-kappa B (NF-kB) and mitogen-activated protein kinase (MAPK) pathways. This study explored the anti-inflammatory effects of vitamin C and AptaminC320 in macrophages. We found that nitric oxide, produced by lipopolysaccharide (LPS), was reduced by vitamin C and AptaminC320 in RAW264.7 cells, which are murine macrophages. Furthermore, these substances reduced the production of inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-6, and interleukin-1β. We also demonstrated that protein expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), increased by LPS in macrophages, as well as the phosphorylation of c-Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK), and p38, were reduced by vitamin C and AptaminC320. These findings suggest that vitamin C and AptaminC320 exhibit anti-inflammatory activity by modulating NF-κB and MAPK signaling, suggesting that they offer significant therapeutic potential as safe and effective treatments for inflammatory diseases with minimal side effects in comparison with the commonly used steroidal anti-inflammatory drug dexamethasone.
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) | 0.001 | 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".