Bibliographic record
Abstract
Bcl-2 functions as a key survival factor for lymphocytes and is highly expressed in a majority of non-Hodgkin's lymphomas. The ability of oblimersen sodium (Genasense, previously known as G3139) to target bcl-2 messenger RNA and decrease Bcl-2 protein levels has the potential to enhance the activity of cytotoxic chemotherapy. Pretreatment with oblimersen followed by cyclophosphamide (Cytoxan, Neosar) markedly improved survival relative to single-agent cyclophosphamide in a murine xenograft model. Oblimersen has also enhanced the cytotoxicity of a variety of other agents against non-Hodgkin's lymphoma, including etoposide, rituximab (Rituxan), and alemtuzumab (Campath). An initial phase I study of oblimersen in non-Hodgkin's lymphoma demonstrated modest single-agent activity. Recent reports suggest that oblimersen may add to the activity of R-CHOP (rituximab-cyclophosphamide/doxorubicin/vincristine/prednisone) in previously untreated mantle cell lymphoma and to rituximab alone in a variety of subtypes of relapsed non-Hodgkin's lymphoma. Additional studies in both treatment-naive and relapsed patients will define the role of oblimersen in the treatment of non-Hodgkin's lymphoma.
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 | 0.001 |
| 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".