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Record W2588589218 · doi:10.1111/phpp.12302

Psoralen with ultraviolet A‐induced apoptosis of cutaneous lymphoma cell lines is augmented by type I interferons via the JAK1–STAT1 pathway

2017· article· en· W2588589218 on OpenAlexaff
Walter Liszewski, David Gram Naym, Edyta Biskup, Robert Gniadecki

Bibliographic record

VenuePhotodermatology Photoimmunology & Photomedicine · 2017
Typearticle
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsUniversity of Alberta
FundersBispebjerg Hospital
KeywordsPsoralenSTAT1ApoptosisCancer researchLymphomaCell cultureChemistryVirologyInterferonMedicineBiologyImmunologyDNAGeneticsBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Photochemotherapy with psoralen and ultraviolet A (PUVA), with or without adjuvant interferon-α (IFN-α), is a first-line therapy for early-stage mycosis fungoides and other forms of cutaneous T-cell lymphoma (CTCL). However, the mechanism by which PUVA with IFN-α work in CTCL is poorly understood. PURPOSE: To develop a model to investigate the mechanisms of PUVA and PUVA with IFN-α in CTCL cells. METHODS: An in vitro model to study the molecular mechanisms of PUVA was created using two different CTCL cell lines, MyLa, which has functional p53, and HuT-78, in which p53 is inactivated due to a homozygous nonsense mutation. RESULTS: PUVA caused G2/M cell cycle block and apoptosis of MyLa and HuT-78 accompanied by increase in the expression of the mitochondrial pro-apoptotic genes Bax, BAK, and PUMA and a downregulation in anti-apoptotic Bcl-2. p53 was induced and c-Myc was repressed by PUVA, but neither were essential for PUVA-induced apoptosis. IFN-α augmented PUVA-induced apoptosis via the JAK1 pathway, and this activity could be inhibited by ruxolitinib. CONCLUSION: PUVA induces p53-independent apoptosis in CTCL cell lines, and this process is augmented by type I interferons via the JAK1 pathway.

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 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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.290
Teacher spread0.272 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2017
Admission routes1
Has abstractyes

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