Enhancing the efficacy of photodynamic therapy by a chinese herbal medicine for hepatocellular carcinoma
Bibliographic record
Abstract
Commentary to:Pheophorbide a, An Active Compound Isolated from Scutellaria barbata, Possesses Photodynamic Activities by Inducing Apoptosis in Human Hepatocellular CarcinomaPatrick Ming-Kuen Tang, Judy Yuet-Wa Chan, Shannon Wing-Ngor Au, Siu-Kai Kong, Stephen Kwok-Wing Tsui, Mary Mui-Yee Waye, Thomas Chung-Wai Mak, Wing-Ping Fong and Kwok-Pui FungHepatocellular carcinoma (HCC) ranks the sixth among the most common malignancies, with chronic HBV infection being the most common cause. HCC is more common in Africa, China and south-east Asia, but its incidence in the USA, Canada and Australia is rising. Current treatment modalities for HCC are not effective, and only a small percentage of patients are suitable for surgical resection and liver transplantation. Thus other treatment options and improvement of available modalities are badly in need. Photodynamic therapy (PDT) may have some therapeutic benefit for patients with HCC. The study by Tang et al has implicated that coupled with Pheophorbide a (Pa), PDT may offer therapeutic benefit for patients with HCC. Inhibition of cell proliferation and induction of apoptosis by Pa may be mechanistically responsible for Pa-PDT. As Pa is an extract from a Chinese herbal medicine Scutellaria Barbata, which is widely available, less toxic and less expensive, such a combination may find a better clinical usage in the treatment of HCC patients. More studies are mandatory to fully elucidate the efficacy and mechanisms of Pa-mediated PDT.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".