Human immune system (HIS) mouse models can be valuable when cross-reactivity of drug candidates to mouse systems is missing. However, no HIS mouse models of psoriasis have been established. In this study, it was investigated if imiquimod (IMQ) induced psoriasis-like skin inflammation was driven by human immune cells in human FMS-related tyrosine kinase 3 ligand (hFlt3L) boosted (BRGSF-HIS mice). BRGSF-HIS mice were boosted with hFlt3L prior to two or three topical applications of IMQ. Despite clinical skin inflammation, increased epidermal thickness and influx of human immune cells, a human derived response was not pronounced in IMQ treated mice. However, the number of murine neutrophils and murine cytokines and chemokines were increased in the skin and systemically after IMQ application. In conclusion, IMQ did induce skin inflammation in hFlt3L boosted BRGSF-HIS mice, although, a limited human immune response suggest that the main driving cellular mechanisms were of murine origin.
Copyright: © 2023 Christensen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Highly heterogeneous cell populations require multiple flow cytometric markers for appropriate phenotypic characterization. This exponentially increases the complexity of 2D scatter plot analyses and exacerbates human errors due to variations in manual gating of flow data. We describe a semi-automated workflow, based entirely on the Flowjo Graphical User Interface (GUI), that involves the stepwise integration of several, newly available machine learning tools for the analysis of myeloid-derived suppressor cells (MDSCs) in septic and non-septic critical illness. Supervised clustering of flow cytometric data showed correlation with, but significantly different numbers of, MDSCs as compared with the cell numbers obtained by manual gating. Neither quantification method predicted 30-day clinical outcomes in a cohort of 16 critically ill and septic patients and 5 critically ill and non-septic patients. Machine learning identified a significant decrease in the proportion of PMN-MDSC in critically ill and septic patients as compared with healthy controls. There was no difference between the proportion of these MDSCs in septic and non-septic critical illness.
Copyright © 2022 Bonavia, Samuelsen, Luthy and Halstead.

Highly heterogeneous cell populations require multiple flow cytometric markers for appropriate phenotypic characterization. This exponentially increases the complexity of 2D scatter plot analysis and exacerbates human errors due to variations in manual gating of flow data. We describe a workflow involving the stepwise integration of several, newly available machine learning tools for the analysis of myeloid-derived suppressor cells (MDSCs) in septic and non-septic critical illness. Unsupervised clustering of flow cytometric data showed good correlation with, but significantly different numbers of, MDSCs as compared with the cell numbers obtained by manual gating. However, both quantification methods revealed a significant difference between numbers of PMN-MDSC at day 1 in healthy volunteers and critically ill patients having septic or non-septic illness. Numbers of PMN-MDSC obtained by machine learning positively correlated with 30 days hospital readmission following critical illness, whereas manual gating of this cell population distinguished between septic and non-septic critical illness. Neither gating strategy found a correlation between number of MDSCs and 30-day mortality or hospital length of stay.

Despite the introduction of vaccines, COVID-19 still affects millions of people worldwide. A better understanding of pathophysiology and the discovery of novel therapies are needed. One of the cells of interest in COVID-19 is the neutrophil. This cell type is being recruited to a site of inflammation as one of the first immune cells. In this project, we investigated a variety of neutrophils phenotypes during COVID-19 by measuring the expression of markers for migration, maturity, activation, gelatinase granules and secondary granules using flow cytometry. We show that neutrophils during COVID-19 exhibit altered phenotypes compared to healthy individuals. The activation level including NETs production and maturity of neutrophils seem to last longer during COVID-19 than expected for innate immunity. Neutrophils as one of the drivers of severe cases of COVID-19 are considered as potential treatment targets. However, for a successful implementation of treatment, there is a need for a better understanding of neutrophil functions and phenotypes in COVID-19. Our study answers some of those questions.
© 2022. The Author(s).

Monocytic myeloid-derived suppressor cells (M-MDSCs), granulocytic MDSC (G-MDSCs) and regulatory T cells (Tregs) inhibit adaptive anti-tumor immunity and undermine the efficacy of anti-PD-1 therapy. However, the impact of anti-PD-1 treatment on these immunosuppressive cells has not been clearly defined in non-small cell lung cancer (NSCLC). In this retrospective study, 27 advanced NSCLC patients were divided into partial response (PR), stable disease (SD), and progressive disease (PD) groups. The impact of anti-PD-1 therapy on circulating Tregs, G-MDSCs, and M-MDSCs was assessed by flow cytometer. Here, we found that anti-PD-1 treatment boosted circulating Tregs levels, which presented the most remarkable augment during the first two therapeutic cycles, in NSCLC patients. In contrast, anti-PD-1 therapy did not overall change G-MDSCs and M-MDSCs levels. However, the PR group had a higher baseline level of M-MDSCs, which exhibited a significant decrease after the first cycle of anti-PD-1 treatment. Besides, M-MDSCs levels in the PR group were maintained at a low level in the following therapeutic cycles. Consistently, Tregs levels robustly increased in the syngeneic tumor model after anti-mouse PD-1 Ab treatment. Accordingly, M-MDSCs neutralization by anti-mouse ly6c Ab enhanced the anti-tumor efficacy of anti-PD-1 therapy in mice. Finally, the decreased M-MDSCs levels were associated with the enhanced effector CD8+ T cells expansion in the PR group and mice. In conclusion, anti-PD-1 therapy upregulates Tregs levels in NSCLC patients, and the M-MDSC levels are associated with the anti-tumor efficacy of anti-PD-1 treatment. Neutralization of M-MDSCs may be a promising option to augment anti-PD-1 therapy efficacy in NSCLC.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.