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Record W1997358378 · doi:10.1080/10428190701713655

The role of TRAIL death receptors in the treatment of hematological malignancies

2008· review· en· W1997358378 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

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsApoptosisReceptorTumor necrosis factor alphaCancer researchLymphomaLeukemiaMonoclonal antibodyProgrammed cell deathImmunologySignal transductionMedicineBiologyAntibodyCell biologyInternal medicine

Abstract

fetched live from OpenAlex

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a promising new treatment for the hematological malignancies. TRAIL induces apoptosis by binding to its two death receptors DR4 (TRAIL-R1) and DR5 (TRAIL-R2). The extent of apoptosis by TRAIL is tightly regulated by the expression of these receptors and by downstream signaling. Chemotherapeutic agents increase the expressions of DR4 and DR5 on tumor cells through the activation of various transcription factors and there is enhanced killing on combining these agents with TRAIL. In this review, we will discuss the mechanism of TRAIL death receptor-induced apoptosis and the regulation of DR4 and DR5 expression. In particular, we will focus on the regulation of TRAIL death receptor signaling in hematological malignancies and the mechanisms responsible for the sensitization of leukemia and lymphoma cells to TRAIL-induced apoptosis by chemotherapy. Finally, we shall review the clinical data regarding the use of recombinant TRAIL and activating monoclonal antibodies against the TRAIL death receptors in the hematological malignancies.

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)0.000
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 score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.254
Teacher spread0.237 · 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