Memory-Like NK Cells: Remembering a Previous Activation by Cytokines and NK Cell Receptors

Natural Killer (NK) cells are cytotoxic innate lymphoid cells serving at the front line against infection and cancer. In inflammatory microenvironments, multiple soluble and contact-dependent signals modulate NK cell responsiveness. Besides their innate cytotoxic and immunostimulatory activity, it has been uncovered in recent years that NK cells constitute a heterogeneous and versatile cell subset. Persistent memory-like NK populations that mount a robust recall response were reported during viral infection, contact hypersensitivity reactions, and after stimulation by pro-inflammatory cytokines or activating receptor pathways. In this review, we highlight recent findings on the generation, functionality, and clinical applicability of memory-like NK cells and describe common features in comparison to other recent concepts of memory NK cells. Understanding of these features will facilitate the conception and design of novel NK cell-based immunotherapies

Human innate immune cell crosstalk induces melanoma cell senescence

Mononuclear phagocytes and NK cells constitute the first line of innate immune defense. How these cells interact and join forces against cancer is incompletely understood. Here, we observed an early accumulation of slan$^{+}$ (6-sulfo LacNAc) non-classical monocytes (slanMo) in stage I melanoma, which was followed by an increase in NK cell numbers in stage III. Accordingly, culture supernatants of slanMo induced migration of primary human NK cells in vitro via the chemotactic cytokine IL-8 (CXCL8), suggesting a role for slanMo in NK cell recruitment into cancer tissues. High levels of TNF-α and IFN-γ were produced in co-cultures of TLR-ligand stimulated slanMo and NK cells, whereas much lower levels were contained in cultures of slanMo and NK cells alone. Moreover, TNF-α and IFN-γ concentrations in slanMo/NK cell co-cultures exceeded those in CD14$^{+}$ monocyte/NK cell and slanMo/T cell co-cultures. Importantly, TNF-α and IFN-γ that was produced in TLR-ligand stimulated slanMo/NK cell co-cultures induced senescence in different melanoma cell lines, as indicated by reduced melanoma cell proliferation, increased senescence-associated β-galactosidase expression, p21 upregulation, and induction of a senescence-associated secretory phenotype (SASP). Taken together, we identified a role for slanMo and NK cells in a collaborative innate immune defense against melanoma by generating a tumor senescence-inducing microenvironment. We conclude that enhancing the synergistic innate immune crosstalk of slanMo and NK cells could improve current immunotherapeutic approaches in melanoma

Macrophages inhibit human osteosarcoma cell growth after activation with the bacterial cell wall derivative liposomal muramyl tripeptide in combination with interferon-γ

Drug Delivery Technolog

Evaluation of the preventive capacities of a topically applied azithromycin formulation against Lyme borreliosis in a murine model

Objectives: Systemic antibiotic treatment of Lyme borreliosis is effective during the early stages of the infection, while chronic manifestations of the disease may remain refractory and difficult to treat. This study was carried out in order to evaluate the potential of topically applied azithromycin to eliminate the spirochaetal organisms in the skin of the freshly bitten host and thereby prevent Lyme borreliosis. Methods: Laboratory mice were challenged with Borrelia burgdorferi sensu stricto by needle inoculation or via infected ticks as vectors. Then, an azithromycin-containing formulation was applied once daily to the sites of exposure for three consecutive days. In the case of needle inoculation, a 5% azithromycin formulation was applied starting 1 h, 3 days and 5 days after infection. In the case of tick exposure, 4%, 10% and 20% azithromycin formulations were applied, starting directly after the detachment of the engorged ticks. Subsequently, the infection status of the mice was determined. Results: Concentrations of azithromycin in murine skin were >3800-fold higher than the published minimal inhibitory concentration for B. burgdorferi as soon as 3 h after the first application. After needle inoculation, spirochaetes were not detectable in all infected mice after treatment, if the first application started 1 h or even after 3 days post-infection. Furthermore, no borrelial organisms were detected after topical treatment when ticks were used for spirochaete inoculation. Conclusions: Our data indicate that topical treatment with a formulation containing azithromycin is a promising approach to prevent Lyme borreliosis shortly after a tick bite

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Synapses in the Network: Learning in Governance Networks in the Context of Environmental Management

In the face of apparent failures to govern complex environmental problems by the central state, new modes of governance have been proposed in recent years. Network governance is an emerging concept that has not yet been consolidated. In network governance, processes of (collective) learning become an essential feature. The key issue approached here is the mutual relations between network structure and learning, with the aim of improving environmental management. Up to now, there have been few attempts to apply social network analysis (SNA) to learning and governance issues. Moreover, little research exists that draws on structural characteristics of networks as a whole, as opposed to actor-related network measures. Given the ambiguities of the concepts at stake, we begin by explicating our understanding of both networks and learning. In doing so, we identify the pertinent challenge of individual as opposed to collective actors that make up a governance network. We introduce three learning-related functions that networks can perform to different degrees: information transmission, deliberation, and resilience. We address two main research questions: (1) What are the characteristics of networks that foster collective learning in each of the three dimensions? To this end, we consider SNA-based network measures such as network size, density, cohesion, centralization, or the occurrence of weak as opposed to strong ties. (2) How does collective learning alter network structures? We conclude by outlining a number of open issues for further research