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Record W2029080479 · doi:10.1155/2007/71921

Impact of Lactic Acid Bacteria on Dendritic Cells from Allergic Patients in an Experimental Model of Intestinal Epithelium

2007· article· en· W2029080479 on OpenAlexaff
Céline Ratajczak, Catherine Duez, Corinne Grangette, Pierre Pochard, André‐Bernard Tonnel, Joël Pestel

Bibliographic record

VenueJournal of Biomedicine and Biotechnology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of Manitoba
FundersInstituto DanoneInstitut National de la Santé et de la Recherche MédicaleDanone
KeywordsLactobacillus caseiEpitheliumIntestinal epitheliumImmune systemDendritic cellMicrobiologyEx vivoImmunologyInterleukin 13AntigenBiologyChemistryBacteriaInterleukin 4In vitroBiochemistry

Abstract

fetched live from OpenAlex

Lactic acid bacteria (LAB) are Gram positive nonpathogenic commensal organisms present in human gastrointestinal tract. In vivo, LAB are separated from antigen-presenting cells such as dendritic cells (DC) by the intestinal epithelial barrier. In this study, the impact of one LAB strain (Lactobacillus casei ATCC393) on human monocyte-derived DC from allergic and healthy donors was assessed by using a polarized epithelium model. Confocal and flow cytometer analyses showed that immature DC efficiently captured FITC-labelled L. casei through the epithelial layer. After interaction with L. casei, DC acquired a partial maturation status (i.e., CD86 and CD54 increase) and increased their interleukin (IL)-10 and IL-12 production. Interestingly, after activation by L. casei in the presence of experimental epithelium, DC from allergic patients instructed autologous naïve CD4(+) T cells to produce more interferon-gamma than without the epithelium. Thus by modulating human DC reactivity, LAB and intestinal epithelium might modify T cell immune response and regulate the development of allergic reaction.

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 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 score0.167
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.262
Teacher spread0.244 · 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

Citations22
Published2007
Admission routes1
Has abstractyes

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