Correlation of trace elemental content in selected anticancer medicinal plants with their curative ability using particle induced x-ray emission (PIXE
Bibliographic record
Abstract
Trace elemental analysis employing particle induced x-ray emission (PIXE) technique was carried out in some selected medicinal plants used in the preparation of anti-cancer drugs. The 3MV Pelletron Accelerator at Institute of Physics, Bhubaneswar, India was used for the present PIXE measurements. A beam of 3 MeV protons, collimated to a diameter of 2 mm, bombarded the samples placed at an angle of 45° to the beam direction. The characteristic X-rays emitted by the elements present in the sample were recorded by a high resolution Si(Li) detector. The elements Cl, K, Ca, Ti, V, Mn, Fe, Cu, Zn, Br, and Sr were identified and their concentrations were estimated by using Guelph PIXE (GUPIX) software. These elements were found to be in widely varying concentrations in the specific parts of the analyzed anti-cancer medicinal plants. These medicinal plants can be considered as potential sources for providing a reasonable amount of the required elements other than diet to the cancer patients. The quantity of trace elements administered through these medicinal plants was found to be less than the recommended dietary allowance. The present data on elemental concentration in these medicinal plants will be useful to set new standards for prescribing the dosage and duration of administration of these herbal medicines to the cancer patients. Key words: Trace elements, particle induced x-ray emission (PIXE), anticancer, medicinal plants.
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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 | 0.001 | 0.001 |
| 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".