A Lipidomic Approach to Assess the Impact of One-lung Ventilation on Lipid-mediated Inflammation During Lung Surgery in a Porcine Model
Bibliographic record
Abstract
Abstract RATIONALE: Lung surgery is curative treatment for early-stage lung cancer. To facilitate the surgery, the operated lung is deflated while all the mechanical ventilation is delivered through the contralateral single-lung; this is called one-lung ventilation (OLV). To maintain adequate oxygenation while avoiding injurious high volumes and pressures, higher fraction of inspired oxygen (hyperoxia) is often used during OLV. However, the trade-offs of using hyperoxia during OLV have not yet been fully elucidated. Therefore, we hypothesized that hyperoxia during OLV increases lipid-inflammatory mediators, eliciting inflammatory response post-OLV. METHODS: We developed an OLV-surgery porcine model (n=15) exposed to lung-protective ventilation[asterisk] (LPV), injurious mechanical ventilation[asterisk][asterisk] (IMV), and hyperoxia[asterisk][asterisk][asterisk], in context of a left upper lobectomy surgery. Bronchoalveolar lavage fluid (BALF) from the ventilated lung and arterial plasma samples were collected before and after OLV to assess its local and systemic impact, respectively. Plasma samples underwent untargeted liquid chromatography-tandem mass spectrometry to measure lipids at the systemic level. Top significant lipids were enriched in a pathway analysis to predict major signalling cascades. To validate the lipidomic results, BALF and plasma samples were analyzed with a multiplex cytokine assay to compare local and systemic inflammatory cytokine levels. (Significant results: p-value ≤ 0.05, fold change ≥ 2). RESULTS: At the systemic level, differential abundance analysis of plasma lipids revealed significant increase of lysophosphatidylcholine, lysophosphatidylethanolamine, linoleoyl carnitine, phosphatidylserine and free-fatty acids in hyperoxia group post-versus pre-OLV. Conversely, diacylglycerides, triacylglycerides, and linoleoyl carnitine were upregulated in IMV group. Pathway analysis of these lipids revealed inflammatory mediator regulation of transient receptor potential channels as a major pathway upregulated in hyperoxia and IMV groups (false discovery rates 6.52E-06 and 8.48E-11, respectively). Consistent with our hypothesis, localized cytokine analysis in BALF revealed an upregulation of interleukin (IL)-8 and IL-1RA in hyperoxia group, and IL-8, IL-6, IL-1α, and IL-1β in IMV group. However, systemically, no significant cytokine changes were observed in the hyperoxia group, while IL-6 was upregulated in IMV group. There were no significant changes in lipidomics or cytokines within the LPV group. CONCLUSION: Collectively, plasma lipidomic findings showed upregulation of inflammatory-mediator lipids post-OLV in both hyperoxia and IMV groups. Next, the inflammatory mediation of these lipids was validated by cytokine analysis both locally in the lung and systemically. This result confirms our hypothesis that hyperoxia impacts lipid metabolism and elicits inflammatory response post-OLV. This study presents a promising direction in targeting lipids that trigger inflammation to mitigate hyperoxia-induced lung injury.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".