ArticleAnnals of translational medicine2020
Lipidomic signatures of post-hepatectomy liver failure using porcine hepatectomy models.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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9 authors at 3 institutions in 1 country.
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Abstract
backgroundClinical diagnosis of post-hepatectomy liver failure (PHLF) can only be made on or after the 5th postoperative day. Biomarker for early diagnosis is considered as a critical unmet need.
methodsTwenty domestic female crossbreed (Yorkshire-landrace and duroc) pigs underwent sham operation (n=6), 70% (n=7) and 90% (n=7) partial hepatectomy (PH). A comprehensive lipidomic analysis was conducted using sera collected at pre-operation (PO), 14, 30, and 48 h after PH using nanoflow ultrahigh performance liquid chromatography-electrospray ionization-tandem mass spectrometry.
resultsOf the 184 quantified lipids, 14 lipids showed significant differences between the two resection groups starting at 30 h after surgery. Four phosphatidylcholine (PC) plasmalogen species (P-16:0/16:0, P-18:0/18:2, P-18:0/20:4, and P-18:0/22:6) and PC 32:2 significantly increased in the 90% PH group while these returned to PO level after 30 h in the 70% PH group, presumably implying the failure markers. In contrast, eight triacylglycerol (TG) species (40:0, 42:1, 42:0, 44:1, 44:2, 46:1, 46:2, and 48:3) and sphingomyelin d18:1/20:0 showed an opposite trend, wherein they significantly decreased in the 90% PH group while these in the 70% PH group were abruptly increased until 30 h but returned to near PO levels at 48 h, implying the recovery markers. Same trends could also be observed in the level of whole lipid classes of PC plasmalogens and TGs, in addition to selected individual lipid species.
conclusionsCharacteristic lipidomic signatures of PHLF could be identified using large animal models. These candidates have a potential to serve as a tool for early diagnosis and may open new paths to the study to overcome PHLF.
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