DEVELOPMENTAL PROFILE OF ADIPONECTIN AND ADIPONECTIN RECEPTOR EXPRESSION IN NEWBORN RAT LUNG DURING ALVEOLARIZATION
Bibliographic record
Abstract
Adiponectin (APN) is a pleotropic adipokine mainly produced by adipocyte. It modulates many biological functions including metabolism, immunity, vascular integrity, tissue remodeling and inflammation. In genetically modified mice, APN protects the lung from oxidative and inflammatory injury (Sliman SM et al., Cell Biochem Biophys 2013, Konter JM et al. J Immunol 2012). Premature infants and infants who are small for gestational age have minimal fat mass, very low levels of circulating APN and are at increased risk for developing bronchopulmonary dysplasia (BPD) from oxidative stress and inflammation. To begin to understand the potential role that APN may play in protecting the lung from injury during lung development, we characterized the developmental profile of circulating APN levels, and protein and gene expression for APN and its receptors in the lung during development in newborn rats. METHODS APN, adiponectin receptors (AdipoR1 and AdipoR2) gene and protein expression were measured in lung homogenates from fetal day (FD)19 and postnatal day (PD) 1,4,7,10,14,21 and 28 (n= 8/each age). Relative mRNA expression was detected by quantitative PCR and serum APN was measured using ELISA. Protein levels of APN and AdipoR1 and AdipoR2 in lung homogenates were measured by western blot. RESULTS Lung APN protein levels significantly changed with development (ANOVA, p<0.05). Total lung APN levels were lowest at FD19 and PD1, increased by 4 fold by PD 7 followed by a 2 fold drop from PD 7 to 10. AdipoR1 protein expression in the lung peaked at PD1; increased by 1.8 fold from FD19 to PD1 followed by a 3 fold drop by PD4 and remained low until PD 14 when levels again increased and were comparable to levels measured at PD1. Similar to AdipoR1, AdipoR2 protein expression in the lung was highest at PD1, but in contrast, AdipoR2 did not significantly change until PD7‐10 at which time levels decreased by 2‐fold and then subsequently increased at PD14, reaching levels similar to those measured at PD1. The pattern of mRNA relative expression for lung APN, AdipoR1 and AdipoR2 mirrored the protein expression. Serum APN levels ELISA did not differ between animals PD 4–28. CONCLUSIONS These data are the first to characterize the developmental profile of APN and its receptors in the lung of a newborn model. At birth, similar to lung of the premature infant, rat lungs are in the saccular stage of lung development. At PD4, alveolarization starts, peaks at P10 and ends at PD21. In APN knock out mice, alveolarization is abnormal. Here we show that APN and its receptors are undergoing significant changes in expression associated with alveolar development. AdipoR1 on alveolar epithelial cells decreases the cytotoxic effects of inflammatory cytokines (TNF‐α and IL‐1β), and induces the expression of pro‐inflammatory cytokine (IL‐10) (Nigro et al, Int J Biochem Cell Biol 2013). We found that AdipoR1 receptor expression is lowest from D4‐D10. We speculate the drop in the AdipoR1 receptors during the stage of lung alveolarization may be a critical period of increased vulnerability to inflammatory and oxidative stress that may contribute to development of bronchopulmonary dysplasia in human infants. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".