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Additional file 1 of MicroRNA miR-223 modulates NLRP3 and Keap1, mitigating lipopolysaccharide-induced inflammation and oxidative stress in bovine mammary epithelial cells and murine mammary glands

2023· other· en· W6902172086 on OpenAlexaff

Bibliographic record

VenueFigshare · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInflammationmicroRNAOxidative stressCell cultureTransfectionEpitheliumGene expressionDownregulation and upregulation

Abstract

fetched live from OpenAlex

Additional file 1. Establishment of bta-miR-223 mimics and bta-miR-223 inhibitor on immortalized bMECs. Effects of 20 nmol/L or 50 nmol/L bta-miR-223 mimic (A, B), 20 nmol/L or 50 nmol/L bta-miR-223 inhibitor (A, B) of protein expression of NLRP3 or Keap1. *p < 0.05 and **p < 0.01, differences compared to control group (mimics or inhibitor siRNA NC); &p < 0.05, differences between 20 nmol/L and 50 nmol/L bta-miR-223 mimics samples; aap < 0.01, differences between 20 nmol/L and 50 nmol/L bta-miR-223 inhibitor samples.

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)0.002
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9080.275

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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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