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Record W2796132488 · doi:10.1371/journal.pone.0195212

PPAR-gamma activation is associated with reduced liver ischemia-reperfusion injury and altered tissue-resident macrophages polarization in a mouse model

2018· article· en· W2796132488 on OpenAlexafffund
Ivan Linares, Kaveh Farrokhi, Juan Echeverri, Johan Moritz Kaths, Dagmar Kollmann, Mátyás Hamar, Peter Urbanellis, Sujani Ganesh, Oyedele Adeyi, Paul S. F. Yip, Markus Selzner, Nazia Selzner

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersUniversity of Toronto
KeywordsAgonistReperfusion injuryTUNEL assayLiver injuryApoptosisEndocrinologyInternal medicineIschemiaNecrosisMedicineNitric oxidePeroxisome proliferator-activated receptorChemistryPharmacologyReceptorBiochemistry

Abstract

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BACKGROUND: PPAR-gamma (γ) is highly expressed in macrophages and its activation affects their polarization. The effect of PPAR-γ activation on Kupffer cells (KCs) and liver ischemia-reperfusion injury (IRI) has not yet been evaluated. We investigated the effect of PPAR-γ activation on KC-polarization and IRI. MATERIALS AND METHODS: Seventy percent (70%) liver ischemia was induced for 60mins. PPAR-γ-agonist or vehicle was administrated before reperfusion. PPAR-γ-antagonist was used to block PPAR-γ activation. Liver injury, necrosis, and apoptosis were assessed post-reperfusion. Flow-cytometry determined KC-phenotypes (pro-inflammatory Nitric Oxide +, anti-inflammatory CD206+ and anti-inflammatory IL-10+). RESULTS: Liver injury assessed by serum AST was significantly decreased in PPAR-γ-agonist versus control group at all time points post reperfusion (1hr: 3092±105 vs 4469±551; p = 0.042; 6hr: 7041±1160 vs 12193±1143; p = 0.015; 12hr: 5746±328 vs 8608±1259; p = 0.049). Furthermore, liver apoptosis measured by TUNEL-staining was significantly reduced in PPAR-γ-agonist versus control group post reperfusion (1hr:2.46±0.49 vs 6.90±0.85%;p = 0.001; 6hr:26.40±2.93 vs 50.13±8.29%; p = 0.048). H&E staining demonstrated less necrosis in PPAR-γ-agonist versus control group (24hr:26.66±4.78 vs 45.62±4.57%; p = 0.032). The percentage of pro-inflammatory NO+ KCs was significantly lower at all post reperfusion time points in the PPAR-γ-agonist versus control group (1hr:28.49±4.99 vs 53.54±9.15%; p = 0.040; 6hr:5.51±0.54 vs 31.12±9.58%; p = 0.009; 24hr:4.15±1.50 vs 17.10±4.77%; p = 0.043). In contrast, percentage of anti-inflammatory CD206+ KCs was significantly higher in PPAR-γ-agonist versus control group prior to IRI (8.62±0.96 vs 4.88 ±0.50%; p = 0.04). Administration of PPAR-γ-antagonist reversed the beneficial effects on AST, apoptosis, and pro-inflammatory NO+ KCs. CONCLUSION: PPAR-γ activation reduces IRI and decreases the pro-inflammatory NO+ Kupffer cells. PPAR-γ activation can become an important tool to improve outcomes in liver surgery through decreasing the pro-inflammatory phenotype of KCs and IRI.

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)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.235
Teacher spread0.216 · 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

Citations40
Published2018
Admission routes2
Has abstractyes

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