Analytical Chemistry · 2019 · 21 citations · 24 references
EngineeringAdvanced ImagingImmunologyPathologyBiomedical EngineeringTissue ImagingSepsisSepsis PhenotypingTexture Feature ExtractionMouse ModelMolecular ImagingNovel Imaging MethodRadiologyMedical ImagingLiver PhysiologyDimension ReductionHistopathologyAbdominal ImagingBiomedical AnalysisMedical Image ComputingAbdominal SepsisHepatologyBiomedical ImagingMedicine
Sepsis constitutes a life-threatening organ failure caused by a deregulated host response to infection. Identifying early biomolecular indicators of organ dysfunction may improve clinical decision-making and outcome of patients. Herein we utilized label-free nonlinear multimodal imaging, combining coherent anti-Stokes Raman scattering (CARS), two-photon excited autofluorescence (TPEF), and second-harmonic generation (SHG) to investigate the consequences of early septic liver injury in a murine model of polymicrobial abdominal infection. Liver tissue sections from mice with and without abdominal sepsis were analyzed using multimodal nonlinear microscopy, immunofluorescence, immunohistochemistry, and quantitative reverse transcription polymerase chain reaction (qRT-PCR). Twenty-four hours after the induction of sepsis, hepatic mRNA of inflammatory cytokines and acute phase proteins was upregulated, and liver-infiltrating myeloid cells could be visualized alongside hepatocellular cytoplasmic translocation of high mobility group box 1. According to the statistical analysis based on texture feature extraction followed by the combination of dimension reduction and linear discriminant analysis, CARS (AUC = 0.93) and TPEF (AUC = 0.83) showed an excellent discrimination between liver sections from septic mice and sham-treated mice in contrast to SHG (AUC = 0.49). Spatial analysis revealed no major differences in the distribution of sepsis-associated changes between periportal and pericentral zones. These data suggest early alterations in hepatic lipid distribution and metabolism during liver injury and confirm nonlinear multimodal imaging as a promising complementary method for the real-time, label-free study of septic liver damage.
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Scikit-learn: Machine Learning in Python
Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.3K citations · Full text
The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)
Mervyn Singer, Clifford S. Deutschman, Christopher W. Seymour et al. · JAMA · 2016 · 26.3K citations · Full text