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Record W2277439873 · doi:10.1038/srep17723

Differential effect of DJ-1/PARK7 on development of natural and induced regulatory T cells

2015· article· en· W2277439873 on OpenAlexaff
Yogesh Singh, Hong Chen, Yuetao Zhou, Michael Föller, Tak W. Mak, Madhuri S. Salker, Florian Läng

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicMorinda citrifolia extract uses
Canadian institutionsOntario Institute for Cancer Research
FundersDeutsche Forschungsgemeinschaft
KeywordsDifferential (mechanical device)Computer scienceComputational biologyBiologyPhysics

Abstract

fetched live from OpenAlex

Regulatory T cells (Tregs) are essential for maintaining an effective immune tolerance and a homeostatic balance of various other immune cells. To manipulate the immune response during infections and autoimmune disorders, it is essential to know which genes or key molecules are involved in the development of Tregs. Transcription factor Foxp3 is required for the development of Tregs and governs most of the suppressive functions of these cells. Inhibited PI3K/AKT/mTOR signalling is critical for Foxp3 stability. Previous studies have suggested that DJ-1 or PARK7 protein is a positive regulator of the PI3K/AKT/mTOR pathway by negatively regulating the activity of PTEN. Thus, we hypothesised that a lack of DJ-1 could promote the development of Tregs. As a result, loss of DJ-1 decreased the total CD4(+) T cell numbers but increased the fraction of thymic and peripheral nTregs. In contrast, Foxp3 generation was not augmented following differentiation of DJ-1-deficient naïve CD4(+) T cells. DJ-1-deficient-iTregs were imperfect in replication, proliferation and more prone to cell death. Furthermore, DJ-1 deficient iTregs were less sensitive to pSmad2 and pStat5 signalling but had activated AKT/mTOR signalling. These observations reveal an unexpected differential role of DJ-1 in the development of nTregs and iTregs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations45
Published2015
Admission routes1
Has abstractyes

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