<i>Curcuma longa</i> and Its Bioactive Curcuminoids: Molecular Mechanisms in Anti-inflammatory and Immunomodulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Curcuma longa and its major bioactive compound, curcumin, have been used widely in traditional medicine and have attracted wide research attention worldwide for their prominent anti-inflammation and immunomodulatory effects in recent years.This study summarizes the chemical properties of C. longa and curcumin, their major bioactive constituents, and the mechanism of their synergistic actions, focusing on inhibiting inflammatory responses through the modulation of the NF-B, MAPK, JAK/STAT, and PI3K/Akt/mTOR signaling pathways to regulate innate and adaptive immunity, inflammasomes, and the activity of immune-related cells.It integrates the progress in the in vitro, animal, and clinical research, discussing bioavailability, metabolism, and gut microbiota interactions on their physiological activities.Safety, dosage, possible risks, and challenges in translation into pharmaceutical applications are analyzed.Being natural products, C. longa and curcumin possess huge potential in the prevention and treatment of chronic inflammation-related diseases.More studies in mechanistic elucidation and clinical validation would be required to promote the clinical application of C. longa and curcumin.In addition, this study has helped gain further insight into the molecular mechanisms of the therapeutic properties of C. longa and curcumin, which provides the scientific basis necessary for developing and applying C. longa and curcumin as natural anti-inflammatory and immunomodulatory agents in the management of chronic diseases.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it