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Immunomodulatory effects of piperine on dendritic cell function (50.36)

2009· article· en· W159693214 on OpenAlexaff
Gemma Rodgers, Carolyn D. Doucette, David R. Spurrell, David W. Hoskin, Kenneth A. West, Robert Liwski

Bibliographic record

VenueThe Journal of Immunology · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPiperaceae Chemical and Biological Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPiperineCD86Dendritic cellChemistryT cellChemokineImmune systemC-C chemokine receptor type 7PharmacologyImmunologyBiologyChemokine receptor

Abstract

fetched live from OpenAlex

Abstract Piperine is a major alkaloid in black and long pepper and has been shown to have potent anti-inflammatory properties. In this study we investigated the immunomodulatory effects of piperine on dendritic cells (DC), key initiators and modulators of T cell mediated immune responses. C57BL/6 bone marrow derived DC were matured in the presence of 100 µM of piperine or vehicle control. DC maturation marker and chemokine receptor expression was assessed by flow cytometry. T cell proliferation was measured by CFSE dilution. Cytokine secretion was assessed by cytometric bead array assay. In vitro DC migration was assessed using CCL21 as the chemotactic stimulus. Piperine treated DC showed decreased expression of CD40, CD86, class II MHC and CCR7 and increased expression of CCR5, consistent with an immature phenotype. DC production of IL-6, TNF and MCP-1 was significantly reduced following piperine treatment. Treatment with piperine also reduced DC migration and DC induced T cell proliferation. In addition, naïve T cells activated with piperine-treated DC secreted lower levels IFN-γ, IL-4, IL-17, and IL-2. This study demonstrates that piperine inhibits DC maturation, migration and T cell stimulatory capacity. Further investigation of piperine mediated DC immunomodulation could lead to the development of novel therapies for the treatment of autoimmune disorders or allograft rejection. This research is supported by CIHR.

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 score0.086
Threshold uncertainty score0.426

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 integrity0.0000.001
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 head0.040
GPT teacher head0.340
Teacher spread0.300 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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