Novel Treatment of Neuroinflammation Against Low Back Pain by Soluble Fullerol Nanoparticles
Bibliographic record
Abstract
STUDY DESIGN: An in vitro study to investigate the anti-inflammatory effects of fullerol on mouse dorsal root ganglia (DRG) under tumor necrosis factor (TNF)-α induction. OBJECTIVE: To evaluate the potential of a free radical scavenger, fullerol nanoparticles, to prevent DRG tissue and neuron inflammatory responses under TNF-α induction in vitro. SUMMARY OF BACKGROUND DATA: Low back pain is one of the most common reasons for clinician visits in Western societies. Symptomatic intervertebral disc degeneration is strongly implicated as a cause of low back pain, as it results in DRG inflammation. Increased production of reactive oxygen species (ROS) is associated with DRG inflammation. METHODS: With or without fullerol treatment, DRG tissue and DRG neurons isolated from wild-type C3H/HeNCrl (Charles River Laboratories, Wilmington, MA) mice were cultured under TNF-α induction. The amount of intracellular ROS was measured with H2DCFDA (Life Technologies Corporation, Grand Island, NY) fluorescence staining. Cellular apoptosis was detected via terminal deoxynucleotidyl transferase dUTP nick-end labeling assay. The expression of inflammatory as well as antioxidative enzyme genes in neurons was analyzed by real-time polymerase chain reaction. In addition, inflammatory cytokine expression in DRG tissue was determined by immunofluorescence staining and enzyme-linked immunosorbent assay. RESULTS: Fluorescence staining results indicated that TNF-α markedly increased the production of intracellular ROS and the number of apoptotic cells. Under fullerol treatment, cellular apoptosis was reduced along with concomitant suppression of ROS. The expression of inflammatory cytokines interleukin 1 β, interleukin 6, cyclooxygenase-2, and prostaglandin E2, was also inhibited by fullerol in a dose-dependent manner. Furthermore, fullerol-treated cells exhibited upregulation of antioxidative enzyme genes superoxide dismutase 2 and catalase. CONCLUSION: The results obtained from this study clearly suggest that fullerol treatment suppresses the inflammatory responses of DRG and neurons, as well as cellular apoptosis by decreasing the level of ROS and potentially enhancing antioxidative enzyme gene expression. Therefore, fullerol has potential to serve as a novel therapeutic agent for low back pain treatment. LEVEL OF EVIDENCE: N/A.
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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 | 0.001 | 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".