<i>In vivo</i> and <i>in vitro</i> effects of curcumin on head and neck carcinoma: a systematic review
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
BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) contributes globally to a great number of deaths and morbidity, in spite of new therapeutic strategies. There is a great need of new drugs that are significantly effective and less deleterious to the patients' general health. In this sense, phytotherapy is a tendency, with results pointing to its use as a chemo-preventive and adjuvant therapy. Therefore, the objective of this systematic review was to investigate the effects of curcumin on proliferation and survival of HNSCC. MATERIALS AND METHODS: The search was conducted on six databases: Cochrane, LILACS, EMBASE, MEDLINE, PubMed, and Web of Science. In vitro and in vivo studies that evaluated the effects of curcumin on cell viability, tumor growth, cell cycle and/or cell death pattern in HNSCC cell lines or animal models were selected. RESULTS: /M phase in HSNCC cell lines. It also reduces tumor measurements in animal models. These events were mostly studied through MTT assay, flow cytometry, and cell cycle- and apoptosis-related proteins expression. CONCLUSION: This systematic review demonstrated that curcumin is effective on HNSCC cell proliferation and survival, reinforcing the currently available evidence that curcumin could be an adjuvant drug in HNSCC treatment.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 it