Simca 13

Principal component analysis (PCA) was performed using SIMCA 13.0.3 software (Umetrics) following mean centering and unit variance scaling of LM amounts. PCA is an unbiased, multivariate projection designed to identify the systematic variation in a data matrix (the overall bioactive LM profile of each sample) with lower dimensional plane using score plots and loading plots. The score plot shows the systematic clusters among the observations (closer plots presenting higher similarity in the data matrix). Loading plots describe the magnitude and the manner (positive or negative correlation) in which the measured LM/SPM contribute to the cluster separation in the score plot ^{39 (link)}.

Male C57B6 mice (4–5wks; Jackson Labs, Bar Harbor, ME) were injected once with rhPTH 1–34 (50 μg/kg) (Bachem, Torrance, CA) or vehicle (saline) 2h prior to sacrifice. Spleens and long bones were frozen in liquid nitrogen then placed in ice cold methanol containing dueterated internal standards (d₈-5S-hydroxyeicosatetraenoic acid (HETE), d₄-leukotriene (LT) B₄, d₄-prostaglandin (PG)E₂ and d₅-lipoxin (LX) A₄; 500pg each) and homogenized using a PTFE dounce (Kimble Chase). Proteins were precipitated (4°C), solid-phase extracted using Biotage RapidTrace_®⁺(5 (link)), and analyzed using liquid chromatography-ultraviolet-tandem mass spectrometry, QTrap 5500 (ABSciex, Framingham, MA) equipped with an Agilent HP1100 binary pump (Santa Clara, CA). An Agilent Eclipse Plus C18 column (100mm × 4.6 mm × 1.8 μm) maintained at 50°C was used with a gradient of methanol/water/acetic acid of 55:45:0.01 (v/v/v) to 100:0:0.01 at 0.4 ml/min flow rate. Multiple reaction monitoring (MRM) with signature ion fragments for each molecule was used with six diagnostic ions employed for identification, and quantification achieved using calibration curves (5 (link)). Principal component analysis (PCA) was performed using SIMCA 13.0.3 software (Umetrics, Umea, Sweden) following mean centering and unit variance scaling of lipid mediators (LM).