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Neutrophils, the most abundant white blood cells in the human circulation, play crucial roles in various diseases, including kidney disease. Traditionally viewed as short-lived pro-inflammatory phagocytes that release reactive oxygen species, cytokines and neutrophil extracellular traps, recent studies have revealed their complexity and heterogeneity, thereby challenging this perception. Neutrophils are now recognized as transcriptionally active cells capable of proliferation and reverse migration, displaying phenotypic and functional heterogeneity. They respond to a wide range of signals and deploy various cargo to influence the activity of other cells in the circulation and in tissues. They can regulate the behavior of multiple immune cell types, exhibit innate immune memory, and contribute to both acute and chronic inflammatory responses while also promoting inflammation resolution in a context-dependent manner. Here, we explore the origin and heterogeneity of neutrophils, their functional diversity, and the cues that regulate their effector functions. We also examine their emerging role in infectious and non-infectious diseases with a particular emphasis on kidney disease. Understanding the complex behavior of neutrophils during tissue injury and inflammation may provide novel insights, thereby paving the way for potential therapeutic strategies to manage acute and chronic conditions. By deciphering their multifaceted role, targeted interventions can be developed to address the intricacies of neutrophil-mediated immune responses and improve disease outcomes., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Innate myeloid cells especially neutrophils and their extracellular traps are known to promote intravascular coagulation and thrombosis formation in infections and various other conditions. Innate myeloid cell-dependent fibrin formation can support systemic immunity while its dysregulation enhances the severity of infectious diseases. Less is known about the immune mechanisms preventing dysregulation of fibrin homeostasis in infection. During experimental systemic infections local fibrin deposits in the liver microcirculation cause rapid arrest of CD4+ T cells. Arrested T-helper cells mostly represent Th17 cells that partially originate from the small intestine. Intravascular fibrin deposits activate mouse and human CD4+ T cells which can be mediated by direct fibrin-CD4+ T-cell interactions. Activated CD4+ T cells suppress fibrin deposition and microvascular thrombosis by directly counteracting coagulation activation by neutrophils and classical monocytes. T-cell activation, which is initially triggered by IL-12p40- and MHC-II-dependent mechanisms, enhances intravascular fibrinolysis via LFA-1. Moreover, CD4+ T cells disfavor the association of the thrombin-activatable fibrinolysis inhibitor (TAFI) with fibrin whereby fibrin deposition is increased by TAFI in the absence but not in the presence of T cells. In human infections thrombosis development is inversely related to microvascular levels of CD4+ T cells. Thus, fibrin promotes LFA-1-dependent T-helper cell activation in infections which drives a negative feedback cycle that rapidly restricts intravascular fibrin and thrombosis development.

Neutrophils rapidly respond to inflammation and infection, but to which degree their functional trajectories after mobilization from the bone marrow are shaped within the circulation remains vague. Experimental limitations have so far hampered neutrophil research in human disease. Here, using innovative fixation and single-cell-based toolsets, we profile human and murine neutrophil transcriptomes and proteomes during steady state and bacterial infection. We find that peripheral priming of circulating neutrophils leads to dynamic shifts dominated by conserved up-regulation of antimicrobial genes across neutrophil substates, facilitating pathogen containment. We show the TLR4/NF-κB signaling-dependent up-regulation of canonical neutrophil activation markers like CD177/NB-1 during acute inflammation, resulting in functional shifts in vivo. Blocking de novo RNA synthesis in circulating neutrophils abrogates these plastic shifts and prevents the adaptation of antibacterial neutrophil programs by up-regulation of distinct effector molecules upon infection. These data underline transcriptional plasticity as a relevant mechanism of functional neutrophil reprogramming during acute infection to foster bacterial containment within the circulation.

The pandemic caused by SARS-CoV-2 impacted health systems globally, creating increased workload and mental stress upon health care workers (HCW). During the first pandemic wave (March to May 2020) in southern Germany, we investigated the impact of stress and the resilience to stress in HCW by measuring changes in hair concentrations of endocannabinoids, endocannabinoid-like compounds and cortisone. HCW (n = 178) recruited from multiple occupation and worksites in the LMU-University-Hospital in Munich were interviewed at four interval visits to evaluate mental stress associated with the COVID-19 pandemic. A strand of hair of up to 6 cm in length was sampled once in May 2020, which enabled retrospective individual stress hormone quantifications during that aforementioned time period. Perceived anxiety and impact on mental health were demonstrated to be higher at the beginning of the COVID-19 pandemic and decreased significantly thereafter. Resilience was stable over time, but noted to be lower in women than in men. The concentrations of the endocannabinoid anandamide (AEA) and the structural congeners N-palmitoylethanolamide (PEA), N-oleoylethanolamide (OEA) and N-stearoylethanolamide (SEA) were noted to have decreased significantly over the course of the pandemic. In contrast, the endocannabinoid 2-arachidonoylglycerol (2-AG) levels increased significantly and were found to be higher in nurses, laboratory staff and hospital administration than in physicians. PEA was significantly higher in subjects with a higher resilience but lower in subjects with anxiety. SEA was also noted to be reduced in subjects with anxiety. Nurses had significantly higher cortisone levels than physicians, while female subjects had significant lower cortisone levels than males. Hair samples provided temporal and measurable objective psychophysiological-hormonal information. The hair endocannabinoids/endocannabinoid-like compounds and cortisone correlated to each other and to professions, age and sex quite differentially, relative to specific periods of the COVID-19 pandemic., (© 2024. The Author(s).)

Graph Neural Networks (GNNs) have established themselves as state-of-the-art for many machine learning applications such as the analysis of social and medical networks. Several among these datasets contain privacy-sensitive data. Machine learning with differential privacy is a promising technique to allow deriving insight from sensitive data while offering formal guarantees of privacy protection. However, the differentially private training of GNNs has so far remained under-explored due to the challenges presented by the intrinsic structural connectivity of graphs. In this work, we introduce a framework for differential private graph-level classification. Our method is applicable to graph deep learning on multi-graph datasets and relies on differentially private stochastic gradient descent (DP-SGD). We show results on a variety of datasets and evaluate the impact of different GNN architectures and training hyperparameters on model performance for differentially private graph classification, as well as the scalability of the method on a large medical dataset. Our experiments show that DP-SGD can be applied to graph classification tasks with reasonable utility losses. Furthermore, we apply explainability techniques to assess whether similar representations are learned in the private and non-private settings. Our results can also function as robust baselines for future work in this area.

To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry., Competing Interests: Declaration of Competing Interest Bernhard T Baune has consulting roles with the National Health and Medical Research Council, Australia. He has received honoraria from AstraZeneca, Bristol-Myers Squibb, Lundbeck, Pfizer, Servier, Wyeth, Otsuka, Biogen; Research grants from private industries from AstraZeneca, Sanofi-Synthélabo; and research grants from the National Health and Medical Research Council (Australia), DFG (Germany), BMBF (Germany), Horizon Europe (EU); ERAPerMed (EU). He has served on advisory boards for Janssen-Cilag, Lundbeck, Biogen, Otsuka and received research funds from the Fay Fuller Foundation, and James & Diana Ramsay Foundation, Adelaide. Alessandro Serretti is or has been a consultant to or has received honoraria or grants unrelated to the present work from: Abbott, Abbvie, Angelini, Astra Zeneca, Clinical Data, Boheringer, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Innovapharma, Italfarmaco, Janssen, Lundbeck, Naurex, Pfizer, Polifarma, Sanofi, Servier, Taliaz. Chiara Fabbri was a speaker for Janssen. Roos van Westrhenen received research funding from the Royal Dutch medical Association, the Erasmus MC (Koers 2018), the Dutch Kidney Foundation, Baxter and she is the Principal Investigator of PSY-PGx funded by Horizon2020 (www.psy-pgx.nl). She was a consultant for Cipsoft and teaches at PsyFar and Schola Medica. She has served on advisory boards of the EU (Horizon2021) and the British Medical Research Council., (Copyright © 2023 Elsevier B.V. and ECNP. All rights reserved.)

The increasing prevalence of large-scale data collection in modern society represents a potential threat to individual privacy. Addressing this threat, for example through privacy-enhancing technologies (PETs), requires a rigorous definition of what exactly is being protected, that is, of privacy itself. In this work, we formulate an axiomatic definition of privacy based on quantifiable and irreducible information flows. Our definition synthesizes prior work from the domain of social science with a contemporary understanding of PETs such as differential privacy (DP). Our work highlights the fact that the inevitable difficulties of protecting privacy in practice are fundamentally information-theoretic. Moreover, it enables quantitative reasoning about PETs based on what they are protecting, thus fostering objective policy discourse about their societal implementation.

Purpose: To determine risk factors for coronavirus disease 2019 (COVID-19) in healthcare workers (HCWs), characterize symptoms, and evaluate preventive measures against SARS-CoV-2 spread in hospitals., Methods: In a cross-sectional study conducted between May 27 and August 12, 2020, after the first wave of the COVID-19 pandemic, we obtained serological, epidemiological, occupational as well as COVID-19-related data at a quaternary care, multicenter hospital in Munich, Germany., Results: 7554 HCWs participated, 2.2% of whom tested positive for anti-SARS-CoV-2 antibodies. Multivariate analysis revealed increased COVID-19 risk for nurses (3.1% seropositivity, 95% CI 2.5-3.9%, p = 0.012), staff working on COVID-19 units (4.6% seropositivity, 95% CI 3.2-6.5%, p = 0.032), males (2.4% seropositivity, 95% CI 1.8-3.2%, p = 0.019), and HCWs reporting high-risk exposures to infected patients (5.5% seropositivity, 95% CI 4.0-7.5%, p = 0.0022) or outside of work (12.0% seropositivity, 95% CI 8.0-17.4%, p < 0.0001). Smoking was a protective factor (1.1% seropositivity, 95% CI 0.7-1.8% p = 0.00018) and the symptom taste disorder was strongly associated with COVID-19 (29.8% seropositivity, 95% CI 24.3-35.8%, p < 0.0001). An unbiased decision tree identified subgroups with different risk profiles. Working from home as a preventive measure did not protect against SARS-CoV-2 infection. A PCR-testing strategy focused on symptoms and high-risk exposures detected all larger COVID-19 outbreaks., Conclusion: Awareness of the identified COVID-19 risk factors and successful surveillance strategies are key to protecting HCWs against SARS-CoV-2, especially in settings with limited vaccination capacities or reduced vaccine efficacy., (© 2021. The Author(s).)

Background: High infection rates among healthcare personnel in an uncontained pandemic can paralyze health systems due to staff shortages. Risk constellations and rates of seroconversion for healthcare workers (HCWs) during the first wave of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic are still largely unclear., Methods: Healthcare personnel (n = 300) on different organizational units in the LMU Munich University Hospital were included and followed in this prospective longitudinal study from 24 March until 7 July 2020. Participants were monitored in intervals of 2 to 6 weeks using different antibody assays for serological testing and questionnaires to evaluate risk contacts. In a subgroup of infected participants, we obtained nasopharyngeal swabs to perform whole-genome sequencing for outbreak characterization., Results: HCWs involved in patient care on dedicated coronavirus disease 2019 (COVID-19) wards or on regular non-COVID-19 wards showed a higher rate of SARS-CoV-2 seroconversion than staff in the emergency department and non-frontline personnel. The landscape of risk contacts in these units was dynamic, with a decrease in unprotected risk contacts in the emergency department and an increase on non-COVID-19 wards. Both intensity and number of risk contacts were associated with higher rates of seroconversion. On regular wards, staff infections tended to occur in clusters, while infections on COVID-19 wards were less frequent and apparently independent of each other., Conclusions: Risk of SARS-CoV-2 infection for frontline HCWs was increased during the first pandemic wave in southern Germany. Stringent measures for infection control are essential to protect all patient-facing staff during the ongoing pandemic., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)