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L‐Citrulline Decreases LPS‐Induced Inflammation and Oxidative Stress in Newborn Rat Lungs

2021· article· en· W3170629567 on OpenAlexaff
Nikola Ivanovski, Huanhuan Wang, Jingyi Pan, Julijana Ivanovska, Nades Palaniyar, Harvard Tran, Jaques Belik, Estelle B. Gauda

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsEndocrinologyOxidative stressBronchopulmonary dysplasiaInternal medicineInflammationMitochondrial biogenesisAdiponectinCoactivatorLipopolysaccharideTFAMSuperoxide dismutaseChemistryMedicineBiologyMitochondrionBiochemistryTranscription factor

Abstract

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Introduction Extremely low birth weight infants have immature lungs at birth as well as low levels of anti‐inflammatory and antioxidative defences, placing them at high risk of developing bronchopulmonary dysplasia (BPD). Adiponectin (APN) is produced by adipocytes and has potent anti‐inflammatory and antioxidative properties, and anti‐proliferative effects; APN levels are quite low in premature infants. We showed that exogenous APN markedly attenuated lipopolysaccharide (LPS)‐induced lung injury (Ivanovska et al. 2020) in newborn rats. Recombinant APN is not available for human use; however, L‐citrulline (L‐CIT) increases APN gene expression in adult rats (Joffin et al., 2015) and upregulates expression of peroxisome proliferator‐activated receptor‐gamma coactivator alpha (PGC‐1α). PGC‐1α is a master coactivator of genes involved in mitochondrial biogenesis, inflammation and oxidative stress. L‐CIT levels are also low in premature infants. Thus, we sought to determine the effect of exogenous L‐CIT on LPS‐induced changes in protein expression of PGC‐1α, APN, APN receptors (AdipoR1/2), cytokines, and superoxide dismutase (SOD) in lung and pulmonary artery smooth muscle cells (PASMC) homogenates, and on LPS‐induced changes of intracellular ROS levels in PASMC. Methods in‐vivo: Sprague Dawley rat pups were treated with L‐CIT (2.5 g/kg) or saline intraperitoneally from postnatal day (PND) 1‐5. On PND 5, intra‐pharyngeal LPS (5mg/kg) or saline was given to L‐CIT (n=4‐6) or saline (n=4‐6) treated animals; pups were euthanized 24 h after LPS treatment and lungs were removed and processed for western blot. In‐vitro: PASMCisolated from PND 4 rats were treated with L‐CIT (4 mM/ml), LPS (5μg/ml) and a combination of the two, for 3 h; cells were harvested and processed for protein expression (n=4 replicate experiments). PASMC were assayed for the level of LPS‐induced intracellular ROS with fluorescence dye in the presence and absence of blocker for PGC‐1α (SR 18292) Results In vivo , L‐CIT, in the presence of LPS, increased lung protein expression of APN (1.36‐fold), AdipoR1/2 (2‐fold), PGC‐1α (1.8‐fold), phosphorylated AMP‐kinase (2.1‐fold), SOD1 (2.3‐fold), SOD2 (1.7‐fold), SOD3 (1.43‐fold), and decreased tumor necrosis factor α (1.2‐fold), and interleukin‐8 (1.28‐fold) compared to saline and LPS treated animals (p<0.05 L‐CIT+LPS vs saline+LPS for all proteins). In vitro , in the presence of LPS, L‐CIT increased PASMC protein expression of PGC‐1α (1.55‐fold), SOD1 (2‐fold), SOD2 (1.57‐fold), and SOD3 (2.2‐fold) compared to cells only exposed to LPS (p<0.05; L‐CIT+LPS vs medium+LPS). L‐CIT decreased LPS‐induced ROS production in PASMC, an effect that was inhibited in the presence of PGC‐1α blocker. Conclusion L‐CIT upregulates APN signaling in presence of LPS and decreases LPS‐induced lung inflammation and oxidative stress in newborn rats through activation of PGC1‐α. The translational significance of these findings warrants further clinical studies of the L‐CIT potential preventative/curative benefit in BPD.

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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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.354
Teacher spread0.307 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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