Combination of Anti α-Gal-PpIX Conjugate and Photodynamic Therapy for the Diagnosis and Elimination of HeLa and CaSki Cells
Bibliographic record
Abstract
The photodynamic therapy (PDT) is a specific and alternative treatment for premalignant and malignant diseases. The -Gal epitope is expressed in red blood cells and nucleated cells of placental mammals not primates, but absent in old world monkeys, apes and humans. -Gal epitope has been found in cervical biopsies HPV positive, in biopsies at different stages of cervical intraepithelial neoplasia and in cell lines such as HeLa and CaSki. The aim of this work was to obtain IgG anti a-Gal monoclonal antibody (mAb) and evaluate its usefulness in the photodynamic therapy in order to diagnosis and eliminate infected cells by HPV, types 16 and 18. From the 4C1F6D5G7B8 hybridoma line was obtained a producer hybridoma of IgG3, the mAb was conjugated with PpIX (IgG-PpIX). The IgG-PpIX conjugated was capable of identify the -Gal epitope present at the membrane of HeLa and CaSki cell lines by immunocitochemistry. The cell lines were exposed to IgG-PpIX and irradiated with a LED system at 635 nm at an energy dose of 64.3 J/cm2. The PDT using IgG anti Gal monoclonal antibody has effect on the viability of cervical carcinoma cells; the mortality results obtained were, in descendent order, HeLa (66.9 %) and CaSki (50.8 %). It was possible to conclude that PDT using the immunoconjugate IgG anti -Gal-PpIX is effective to diagnosis and eliminate cervical carcinoma cells.
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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 | 0.000 | 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".