Preliminary Results of Nanopharmaceuticals Used in the Radioimmunotherapy of Ovarian Cancer
Bibliographic record
Abstract
PURPOSE: The treatment of late stage ovarian cancer presents an unmet clinical need for women around the world. A multistep radioimmunotherapeutic (RIT) approach, exploiting the combination of a bispecific monoclonal antibody (BsMAb) with 90Y labelled biotinylated long-circulating liposomes was tested as a potential adjuvant treatment for epithelial ovarian carcinomatosis in an attempt to meet this need. This approach was used to overcome some of the major obstacles associated with conventional strategies, in particular, to increase the amount of radioactivity delivered to the tumor site compared with conventional monoclonal antibody (MAb) radionuclide delivery. We hypothesize that sequential intraperitoneal administration of the targeting and therapeutic moieties provides the basis for an enhanced therapeutic ratio. METHODS: A BsMAb, with anti-CA 125 and anti-biotin epitopes was engineered for use with PEGylated liposomes coated with biotin to deliver the cytotoxic radionuclide 90Y to tumor sites. An in vivo therapy trial was used to test this RIT protocol with Balb/c nude mice (n=29) xenografted with the NIH:OVCAR-3 (CA 125+) human ovarian cancer cell line. RESULTS: A median tumor growth delay of 91 days for the combined treatment group versus 77.7 days for the control group was observed. CONCLUSION: An ongoing tumor growth delay/control study using this model has indicated an appreciable delay in progress of tumor and ascites development in treated vs. control populations.
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.
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".