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Development of target‐specific treatments in multiple myeloma

2010· review· en· W1616213856 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBritish Journal of Haematology · 2010
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Institutes of HealthNational Cancer InstituteCelgeneBristol-Myers Squibb
KeywordsThalidomideBortezomibMultiple myelomaArsenic trioxideCancer researchLenalidomideMedicineHistone deacetylaseProtein kinase BPharmacologyPanobinostatMonoclonal antibodyImmunologyBiologyApoptosisHistoneSignal transductionAntibodyCell biology

Abstract

fetched live from OpenAlex

In the last decade, the novel agents lenalidomide, bortezomib, and thalidomide have dramatically improved outcomes for patients with multiple myeloma (MM). A number of new therapies with precise targets involved in MM cell growth and replication are now in development and have the potential for further improvements. Second-generation proteasome inhibitors and thalidomide derivatives may offer increased efficacy and safety. Investigational therapies with rationally selected targets in MM include inhibitors of histone deacetylase, heat shock protein 90, mammalian target of rapamycin, BCL2, Akt, mitogen-activated protein kinase, and telomerase. In addition, monoclonal antibodies directed against several targets have been developed and many are showing promise in initial clinical trials in MM. Interest in the ancient remedy of arsenic trioxide has been revived because of its proapoptotic effects on mitochondria, despite its established toxicities. In general, combination regimens are proving the most efficacious, which is to be expected given the multiple overlapping pathways responsible for MM growth and progression.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.907
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.357
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it