Prediction of six macrophage phenotypes and their IL-10 content based on single-cell morphology using artificial intelligence.

Introduction: The last decade has led to rapid developments and increased usage of computational tools at the single-cell level. However, our knowledge remains limited in how extracellular cues alter quantitative macrophage morphology and how such morphological changes can be used to predict macrophage phenotype as well as cytokine content at the single-cell level. Methods: Using an artificial intelligence (AI) based approach, this study determined whether (i) accurate macrophage classification and (ii) prediction of intracellular IL-10 at the single-cell level was possible, using only morphological features as predictors for AI. Using a quantitative panel of shape descriptors, our study assessed image-based original and synthetic single-cell data in two different datasets in which CD14+ monocyte-derived macrophages generated from human peripheral blood monocytes were initially primed with GM-CSF or M-CSF followed by polarization with specific stimuli in the presence/absence of continuous GM-CSF or M-CSF. Specifically, M0, M1 (GM-CSF-M1, TNFα/IFNγ-M1, GM-CSF/TNFα/IFNγ-M1) and M2 (M-CSF-M2, IL-4-M2a, M-CSF/IL-4-M2a, IL-10-M2c, M-CSF/IL-10-M2c) macrophages were examined. Results: Phenotypes were confirmed by ELISA and immunostaining of CD markers. Variations of polarization techniques significantly changed multiple macrophage morphological features, demonstrating that macrophage morphology is a highly sensitive, dynamic marker of phenotype. Using original and synthetic single-cell data, cell morphology alone yielded an accuracy of 93% for the classification of 6 different human macrophage phenotypes (with continuous GM-CSF or M-CSF). A similarly high phenotype classification accuracy of 95% was reached with data generated with different stimuli (discontinuous GM-CSF or M-CSF) and measured at a different time point. These comparably high accuracies clearly validated the here chosen AI-based approach. Quantitative morphology also allowed prediction of intracellular IL-10 with 95% accuracy using only original data. Discussion: Thus, image-based machine learning using morphology-based features not only (i) classified M0, M1 and M2 macrophages but also (ii) classified M2a and M2c subtypes and (iii) predicted intracellular IL-10 at the single-cell level among six phenotypes. This simple approach can be used as a general strategy not only for macrophage phenotyping but also for prediction of IL-10 content of any IL-10 producing cell, which can help improve our understanding of cytokine biology at the single-cell level.

Which factors influence the need for inpatient rehabilitation after severe trauma?

INTRODUCTION: Despite the importance of rehabilitation in the treatment of patients with severe trauma or even of severely injured patients, the cooperation between acute and rehabilitation hospitals is often inadequate. The present study aims to identify factors that make it probable that a severely injured patient requires inpatient rehabilitation following the acute treatment. MATERIAL AND METHODS: A retrospective analysis of 75.357 cases from the TraumaRegister DGU® (TR-DGU) was performed. All cases from 2002 until 2013 with an ISS≥9, who were taken to the ICU were included. Regarding the discharge destination the subgroups "at home" and "rehabilitation hospital" were analyzed in detail. Finally, we performed a multivariate regression analysis based on the parameters previously collected. RESULTS: 24.208 patients (32.1%) were transferred to a rehabilitation clinic. In the multivariate regression analysis the most relevant independent parameters for discharge in a rehabilitation hospital were age (18-54: OR 1.65; 55-74: OR 2.86 and 75 and older: OR 5.07, all p≤0.001), AIS pelvis≥2 (OD 1.94), AIS legs (OR 2.02), AIS spine (AIS 4: OR 5.78 and AIS 5-6: OR 6.36) and the AIS head (AIS 3: OR 1.88; AIS 4: OR 3.11 and AIS 5-6: OR 7.55) (all p≤0.001). The length of stay in the ICU (3-7 days: OR 1.88; 8-28 Days: OR 5.42 and 29 and more days: OR 14.7, all p≤0.001) was also a relevant parameter. The overall ISS presented no relevant influence with an OR of 1.02 (p=0.03). DISCUSSION AND CONCLUSION: Knowing independent factors for a required inpatient rehabilitation helps the treating physicians to identify the patients at an early stage in acute hospitals. So the transfer to a rehabilitation clinic can be organized faster and more selective in future.