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Innate immune memory, the ability of innate cells to react in a more protective way to secondary challenges, is induced by exposure to infectious and other exogeous and endogenous agents. Engineered nanoparticles are particulate exogenous agents that, as such, could trigger an inflammatory reaction in monocytes and macrophages and could therefore be also able to induce innate memory. Here, we have evaluated the capacity of engineered gold nanoparticles (AuNPs) to induce a memory response or to modulate the memory responses induced by microbial agents. Microbial agents used were in soluble vs. particulate form (MDP and the gram-positive bacteria Staphylococcus aureus; ?-glucan and the ?-glucan-producing fungi C. albicans), and as whole microrganisms that were either killed (S. aureus, C. albicans) or viable (the gram-negative bacteria Helicobacter pylori). The memory response was assessed in vitro, by exposing human primary monocytes from 2-7 individual donors to microbial agents with or without AuNPs (primary response), then resting them for 6 days to allow return to baseline, and eventually challenging them with LPS (secondary memory response). Primary and memory responses were tested as production of the innate/inflammatory cytokine TNF? and other inflammatory and anti-inflammatory factors. While inactive on the response induced by soluble microbial stimuli (muramyl dipeptide -MDP-, ?-glucan), AuNPs partially reduced the primary response induced by whole microorganisms. AuNPs were also unable to directly induce a memory response but could modulate stimulus-induced memory in a circumscribed fashion, limited to some agents and some cytokines. Thus, the MDP-induced tolerance in terms of TNF? production was further exacerbated by co-priming with AuNPs, resulting in a less inflammatory memory response. Conversely, the H. pylori-induced tolerance was downregulated by AuNPs only relative to the anti-inflammatory cytokine IL-10, which would lead to an overall more inflammatory memory response. These effects of AuNPs may depend on a differential interaction/association between the reactive particle surfaces and the microbial components and agents, which may lead to a change in the exposure profiles. As a general observation, however, the donor-to-donor variability in memory response profiles and reactivity to AuNPs was substantial, suggesting that innate memory depends on the individual history of exposures.

Frailty is a common syndrome in older individuals that is associated with poor cognitive outcome. The underlying brain correlates of frailty are unclear. The aim of this study was to investigate the association between frailty and MRI features of cerebral small vessel disease in a group of non-demented older individuals. We included 170 participants who were classified as frail (n = 30), pre-frail (n = 85) or non-frail (n = 55). The association of frailty and white matter hyperintensity volume and shape features, lacunar infarcts and cerebral perfusion was investigated by regression analyses adjusted for age and sex. Frail and pre-frail participants were older, more often female and showed higher white matter hyperintensity volume (0.69 [95%-CI 0.08 to 1.31], p = 0.03 respectively 0.43 [95%-CI: 0.04 to 0.82], p = 0.03) compared to non-frail participants. Frail participants showed a non-significant trend, and pre-frail participants showed a more complex shape of white matter hyperintensities (concavity index: 0.04 [95%-CI: 0.03 to 0.08], p = 0.03; fractal dimensions: 0.07 [95%-CI: 0.00 to 0.15], p = 0.05) compared to non-frail participants. No between group differences were found in gray matter perfusion or in the presence of lacunar infarcts. In conclusion, increased white matter hyperintensity volume and a more complex white matter hyperintensity shape may be structural brain correlates of the frailty phenotype.

BackgroundCerebral microbleeds (CMB) occur in the context of cerebral small vessel disease. Other brain MRI markers of cerebral small vessel disease are associated with the occurrence of postoperative delirium (POD) and postoperative cognitive dysfunction (POCD), but for CMB this is unknown. We aimed to study the association between CMB and the occurrence of POD and POCD in older individuals.MethodsThe current study consists of 65 patients (72±5 years) from the BIOCOG study, which is a prospective, observational study of patients who underwent an elective surgery of at least 60 minutes. Patients in the current study received a preoperative cerebral MRI scan including a 3D susceptibility-weighted imaging sequence to detect CMB. The occurrence of POD was screened for twice a day until postoperative day 7 by using the DSM-5, NuDesc, CAM, and CAM-ICU. The occurrence of POCD was determined by the reliable change index model at 7 days after surgery or discharge, respectively, and 3 months after surgery. Statistical analyses consisted of logistic regression adjusted for age and gender.ResultsA total of 39 CMB were detected in 17 patients (26%) prior to surgery. POD occurred in 14 out of 65 patients (22%). POCD at 7 days after surgery occurred in 11 out of 54 patients (20%) and in 3 out of 40 patients at the 3 month follow-up (8%). Preoperative CMB were not associated with the occurrence of POD (OR (95%-CI): 0.28 (0.05, 1.57); p = 0.147) or POCD at 7 days after surgery (0.76 (0.16, 3.54); p = 0.727) or at 3 months follow-up (0.61 (0.03, 11.64); p = 0.740).ConclusionWe did not find an association between preoperative CMB and the occurrence of POD or POCD.Trial registrationclinicaltrials.gov (NCT02265263) on 23 September 2014.

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions – particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost–benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation.

IL-1 receptor family

The immune system recognizes non-self-entities and decides whether they present a danger that requires defensive action. This is, for practical purposes, an assessment of nanosafety. The intense interaction between immune system components and nanoparticles also suggests a fruitful perspective for medical exploitation.

Interaction of nanoparticles with the immune system

Engineered nanoparticles (NP) are generally contaminated by bacterial endotoxin, a ubiquitous bacterial molecule with significant toxic and inflammatory effects. The presence of endotoxin, if not recognised, can be responsible for many of the in vitro and in vivo effects attributed to NPs. The Limulus Amoebocyte Lysate (LAL) assay, the test requested by regulatory authorities for assessing endotoxin contamination in products for human use, is not immediately applicable for testing endotoxin in NP preparations, mainly due to the possible interference of NPs with the assay readouts and components. In this study, we have compared different commercially available LAL assays for detecting endotoxin in gold, silver and iron oxide NPs. Different NP chemistry, concentrations and surface coatings could differently interfere with the LAL assays' results. After accurate testing of the possible interaction/interference of NPs with the various assay components, the modified chromogenic LAL assay proved the most suitable assay for measuring endotoxin in NP samples, provided the appropriate controls are performed. Thus, endotoxin determination can be performed in NP preparation with commercial LAL assays only after assay validation, i.e. once possible interference of NPs with the assay components and readouts has been excluded.

Monocytes/macrophages are key players in all phases of physiological and pathological inflammation. To understanding the regulation of macrophage functional differentiation during inflammation, we designed an in vitro model that recapitulates the different phases of the reaction (recruitment, initiation, development, and resolution), based on human primary blood monocytes exposed to sequential changes in microenvironmental conditions. All reaction phases were profiled by transcriptomic microarray analysis. Distinct clusters of genes were identified that are differentially regulated through the different phases of inflammation. The gene sets defined by GSEA analysis revealed that the inflammatory phase was enriched in inflammatory pathways, while the resolution phase comprised pathways related to metabolism and gene rearrangement. By comparing gene clusters differentially expressed in monocytes vs. M1 and vs. M2 macrophages extracted from an in-house created meta-database, it was shown that cells in the model resemble M1 during the inflammatory phase and M2 during resolution. The validation of inflammatory and transcriptional factors by qPCR and ELISA confirmed the transcriptomic profiles in the different phases of inflammation. The accurate description of the development of the human inflammatory reaction provided by this in vitro kinetic model can help in identifying regulatory mechanisms in physiological conditions and during pathological derangements. © 2014 Italiani et al.

IL-18 is an immunomodulatory/inflammatory protein belonging to the IL-1 family of innate cytokines. IL-18 activates target cells following interaction with IL-18RRα, an Ig-like protein belonging to the IL-1R family. As for IL-11β, after interaction of IL-18 with IL-18RRα, a second accessory receptor chain (IL-18RRβ, another member of the IL-1R family) is recruited to the complex and allows signal transduction. The complex of IL-11β with its receptor IL-1RI has been crystallised and its structure resolved. A subsequent modelling study has allowed to describe the interaction of the accessory chain IL-1RAcP with the IL-11β/IL-1RI complex. Nothing is known about the interaction between IL-18, IL-18RRα, and IL-18RRβ. In this study, the interaction of IL-18 with IL-18RRα and the subsequent interaction of the complex with IL-18RRβ has been studied in silico by molecular modelling, on the basis of the structural data of the IL-11β/IL-1RI/IL-1RAcP complex. First, IL-18RRα and IL-18RRβ have been modelled on the crystal structure of IL-1RI, PDB code 1ITB. The alignment was generated with ClustalW, the 3D structure prediction was made with MODELLER9 and validated with PROSA/PROCHECK. Then, the IL-18 NMR structure (PDB code 1J0S) has been docked to IL-18RRα using AutoDock 3.05 on the basis of mutagenesis data. At last, IL-18RRβ has been docked to the predicted IL-18/IL-18RRα model. Another IL-1-like molecule, IL-1F7, can bind to IL-18RRα, but allegedly does not recruit IL-18RRβ into an activating complex. Modelling and docking of IL-1F7 to the IL-18RRα model and subsequent docking of the IL-18RRβ model to the modelled IL-1F7/IL-18RRα complex is in progress.

Nanoparticles and the Immune System provides a reference text for toxicologists, materials scientists and regulators and covers the key issues of interaction of nanomaterials with the immune system. The book discusses several issues that toxicologists and regulators need to know: identification of endpoints that are relevant for assessing hazard, evaluating impact on immunologically frail populations, and how to evaluate chronic/cumulative effects. In addition, the book addresses the possibility of turning the immunomodulating properties of certain nanomaterials to our advantage for amplifying immune responses in certain diseases or preventive strategies (e.g. vaccination). © 2014 Elsevier Inc. All rights reserved.