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Record W2286538882 · doi:10.1371/journal.pone.0146770

MiR-1303 Regulates Mycobacteria Induced Autophagy by Targeting Atg2B

2016· article· en· W2286538882 on OpenAlexfundno aff
Kin Yi Au, John C. H. Pong, Wai Lim Ling, J. Li

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsnot available
FundersUniversity of British ColumbiaHealth and Medical Research FundUniversity of Hong Kong
KeywordsAutophagyInnate immune systemBiologyCell biologyImmunityDownregulation and upregulationmicroRNATranslation (biology)PI3K/AKT/mTOR pathwayFunction (biology)Acquired immune systemMicrobiologyGeneImmune systemImmunologySignal transductionGeneticsMessenger RNAApoptosis

Abstract

fetched live from OpenAlex

MicroRNAs are emerging post-transcriptional regulators of gene expressions in both innate immunity and adaptive immunity. In mycobacteria infection, autophagy plays an important role in innate defense mechanism and is tightly regulated by the autophagy-related proteins. Here, we show that Atg2B is involved in the regulation of mycobacteria-induced autophagy. MiR-1303, which function is not defined yet, is found to negatively regulate mycobacteria-induced Atg2B protein production, ultimately down-regulate mycobacteria-induced autophagy. MiR-1303 production is shown to be upregulated during BCG infection and its production is regulated by PI3K and NFκB. It is also demonstrated that miR-1303 targets putative target sites on Atg2B and possibly represses its translation.

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 score0.004

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.031
GPT teacher head0.242
Teacher spread0.212 · 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

Citations27
Published2016
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicAutophagy in Disease and TherapyFrench-language works237,207