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Record W2346395064 · doi:10.1002/ijc.30171

Interaction of acid ceramidase inhibitor LCL521 with tumor response to photodynamic therapy and photodynamic therapy‐generated vaccine

2016· article· en· W2346395064 on OpenAlexafffund
Mladen Korbelik, Judit P. Banáth, Wei Zhang, Kyi Min Saw, Zdzisław M. Szulc, Alicja Bielawska, Duška Šeparović

Bibliographic record

VenueInternational Journal of Cancer · 2016
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsBC Cancer Agency
FundersUniversiteit StellenboschCanadian Cancer Society
KeywordsPhotodynamic therapyAdjuvantImmunologyCancer researchCancerAdjuvant therapyMedicineInternal medicineChemistry

Abstract

fetched live from OpenAlex

Acid ceramidase has been identified as a promising target for cancer therapy. One of its most effective inhibitors, LCL521, was examined as adjuvant to photodynamic therapy (PDT) using mouse squamous cell carcinoma SCCVII model of head and neck cancer. Lethal effects of PDT, assessed by colony forming ability of in vitro treated SCCVII cells, were greatly enhanced when combined with 10 µM LCL521 treatment particularly when preceding PDT. When PDT-treated SCCVII cells are used to vaccinate SCCVII tumor-bearing mice (PDT vaccine protocol), adjuvant LCL521 treatment (75 mg/kg) resulted in a marked retardation of tumor growth. This effect can be attributed to the capacity of LCL521 to effectively restrict the activity of two main immunoregulatory cell populations (Tregs and myeloid-derived suppressor cells, MDSCs) that are known to hinder the efficacy of PDT vaccines. The therapeutic benefit with adjuvant LCL521 was also achieved with SCCVII tumors treated with standard PDT when using immunocompetent mice but not with immunodeficient hosts. The interaction of LCL521 with PDT-based antitumor mechanisms is dominated by immune system contribution that includes overriding the effects of immunoregulatory cells, but could also include a tacit contribution from boosting direct tumor cell kill.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.094
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.341
Teacher spread0.326 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations27
Published2016
Admission routes2
Has abstractyes

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