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Jil Sander is known for designing well sculptured, high quality clothes in subdued colors. This comprehensive book presents her work from the late 1960s to 2014. Challenging the styles of flamboyant femininity, her collections delighted the fashion world with their purity. She proposed a modernity which did away with senseless ornaments, while dynamizing the individual. This book will showcase the ingenuity and creative power of a designer who aimed at underlining a person's personality. More than 150 illustrations present the Jil Sander vision which had a huge impact not only on fashion, but on product design, advertising campaigns, and store architecture as well. Exhibition: Museum Angewandte Kunst, Frankfurt am Main, Germany (04.11.2017-06.05.2018).

Background In concert with other digital technologies, artificial intelligence (AI) is shaping the vision of smart hospitals. The transformation into smart hospitals, however, is all but trivial due to the lack of financial and human resources, digital skills, and supporting policies. Thus, the extent to which the vision of smart hospitals will eventually become reality is uncertain. In this context, our study provides a multidimensional conceptualization of the immediate future of smart hospitals to 2042. Methods This study employs an iterative mixed-methods approach, including expert workshops and a Delphi study. We conducted a real-time Delphi study to forecast the evolution of smart hospitals in 5-year steps from 2027 to 2042. A total of 39 experts in healthcare, artificial intelligence, and management participated. Results Our understanding of a technology-enabled smart hospital in this study includes four dimensions: artificial intelligence (AI), sustainability, ecosystems, and human-centeredness. Our findings underscore the critical need to address the shortage of hospital staff and general practitioners that models predict will peak by 2032. Additionally, our results show a significant shift to individualized medicine and home care. This shift indicates that smart hospitals are expected to leverage AI and digital technologies to tailor care to each patient. Furthermore, the roles and responsibilities of hospital staff will undergo significant changes. Healthcare personnel will have to adapt to new technologies that facilitate more efficient workflows and improve patient engagement in evolving healthcare environments. The results of our study suggest a shift in care to individualized medicine and home care, with corresponding changes in the roles and responsibilities of hospital staff who will employ new technologies. Conclusions The findings from our real-time Delphi study suggest that the vision of smart hospitals is gradually becoming reality over the next 20 years. Advancements in artificial intelligence should enhance operational efficiency and patient-centric care, while facilitating the integration of sustainability practices and fostering collaborative ecosystems. However, addressing challenges such as staff shortages, ethical considerations, and the need for robust digital skills will be essential. A deep pool of expert healthcare practitioners, clear ethical guidelines, and robust digital skills are essential to fully realize this vision and ensure that smart hospitals can meet the evolving needs of healthcare delivery.

Macrophages are dynamic cells integrating signals from their microenvironment to develop specific functional responses. Although, microarray-based transcriptional profiling has established transcriptional reprogramming as an important mechanism for signal integration and cell function of macrophages, current knowledge on transcriptional regulation of human macrophages is far from complete. To discover novel marker genes, an area of great need particularly in human macrophage biology but also to generate a much more thorough transcriptome of human M1- and M1-like macrophages, we performed RNA sequencing (RNA-seq) of human macrophages. Using this approach we can now provide a high-resolution transcriptome profile of human macrophages under classical (M1-like) and alternative (M2-like) polarization conditions and demonstrate a dynamic range exceeding observations obtained by previous technologies, resulting in a more comprehensive understanding of the transcriptome of human macrophages. Using this approach, we identify important gene clusters so far not appreciated by standard microarray techniques. In addition, we were able to detect differential promoter usage, alternative transcription start sites, and different coding sequences for 57 gene loci in human macrophages. Moreover, this approach led to the identification of novel M1-associated (CD120b, TLR2, SLAMF7) as well as M2-associated (CD1a, CD1b, CD93, CD226) cell surface markers. Taken together, these data support that high-resolution transcriptome profiling of human macrophages by RNA-seq leads to a better understanding of macrophage function and will form the basis for a better characterization of macrophages in human health and disease.

Differentiation of inflammatory macrophages from monocytes is characterized by an orderly integration of epi- genetic and transcriptional regulatory mechanisms guided by lineage-determining transcription factors such as PU.1. Further activation of macrophages leads to a stimulus- or microenvironment-specific signal integration with subse- quent transcriptional control established by the action of tissue- or signal-associated transcription factors. Here, we assess four histone modifications during human macrophage activation and integrate this information with the gene expression data from 28 different macrophage activation conditions in combination with GM-CSF. Bioinformatically, for inflammatory macrophages we define a unique network of transcriptional and epigenetic regulators （TRs）, which was characterized by accessible promoters independent of the activation signal. In contrast to the general accessibil- ity of promoters of TRs, mRNA expression of central TRs belonging to the TR network displayed stimulus-specific expression patterns, indicating a second level of transcriptional regulation beyond epigenetic chromatin changes. In contrast, stringent integration of epigenetic and transcriptional regulation was observed in networks of TRs estab- lished from somatic tissues and tissue macrophages. In these networks, clusters of TRs with permissive bistone marks were associated with high gene expression whereas clusters with repressive chromatin marks were associated with absent gene expression. Collectively, these results support that macrophage activation during inflammation in con- trast to lineage determination is mainly regulated transcriptionally by a pre-defined TR network.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Lipolysis declines with age because NLRP3 inflammasome-activated adipose tissue macrophages reduce levels of noradrenaline by upregulating genes that control its degradation, such as GDF3 and MAOA . The age old problem of fat breakdown With increasing age, lipolysis (the breakdown of fats in the body) induced by catecholamines declines and fewer free fatty acids are mobilized. This is associated with increased fat around the abdomen, a lower exercise capacity, and a reduced ability to maintain core body temperature and to survive starvation. Vishwa Deep Dixit and colleagues now show that lipolysis declines because fatty tissue macrophages activated by NLRP3 inflammasome reduce the levels of catecholamine by upregulating genes that control its degradation, such as growth differentiation factor-3 (GDF3) and monoamine oxidase A (MAOA). Deletion of NLRP3 or GDF3, or inhibition of MAOA restores lipolysis to more youthful levels. Catecholamine-induced lipolysis, the first step in the generation of energy substrates by the hydrolysis of triglycerides 1 , declines with age 2 , 3 . The defect in the mobilization of free fatty acids in the elderly is accompanied by increased visceral adiposity, lower exercise capacity, failure to maintain core body temperature during cold stress, and reduced ability to survive starvation. Although catecholamine signalling in adipocytes is normal in the elderly, how lipolysis is impaired in ageing remains unknown 2 , 4 . Here we show that adipose tissue macrophages regulate the age-related reduction in adipocyte lipolysis in mice by lowering the bioavailability of noradrenaline. Unexpectedly, unbiased whole-transcriptome analyses of adipose macrophages revealed that ageing upregulates genes that control catecholamine degradation in an NLRP3 inflammasome-dependent manner. Deletion of NLRP3 in ageing restored catecholamine-induced lipolysis by downregulating growth differentiation factor-3 (GDF3) and monoamine oxidase A (MAOA) that is known to degrade noradrenaline. Consistent with this, deletion of GDF3 in inflammasome-activated macrophages improved lipolysis by decreasing levels of MAOA and caspase-1. Furthermore, inhibition of MAOA reversed the age-related reduction in noradrenaline concentration in adipose tissue, and restored lipolysis with increased levels of the key lipolytic enzymes adipose triglyceride lipase (ATGL) and hormone sensitive lipase (HSL). Our study reveals that targeting neuro-immunometabolic signalling between the sympathetic nervous system and macrophages may offer new approaches to mitigate chronic inflammation-induced metabolic impairment and functional decline.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Functional T cell exhaustion occurs during chronic viral infection or in tumor settings. Beyer et al . report that chronic inflammation mediated by the cytokine TNF is responsible for this dysfunction and that blockade of this pathway restores immune system–mediated control of viral infection. Persistent viral infections are characterized by the simultaneous presence of chronic inflammation and T cell dysfunction. In prototypic models of chronicity—infection with human immunodeficiency virus (HIV) or lymphocytic choriomeningitis virus (LCMV)—we used transcriptome-based modeling to reveal that CD4 + T cells were co-exposed not only to multiple inhibitory signals but also to tumor-necrosis factor (TNF). Blockade of TNF during chronic infection with LCMV abrogated the inhibitory gene-expression signature in CD4 + T cells, including reduced expression of the inhibitory receptor PD-1, and reconstituted virus-specific immunity, which led to control of infection. Preventing signaling via the TNF receptor selectively in T cells sufficed to induce these effects. Targeted immunological interventions to disrupt the TNF-mediated link between chronic inflammation and T cell dysfunction might therefore lead to therapies to overcome persistent viral infection.

Functional T cell exhaustion occurs during chronic viral infection or in tumor settings. Beyer et al. report that chronic inflammation mediated by the cytokine TNF is responsible for this dysfunction and that blockade of this pathway restores immune system-mediated control of viral infection.

Rapid advances in digital technology and the promising potential of artificial intelligence (AI) are changing our everyday lives and have already impacted on hospital procedures. The use of AI applications, in particular, enables a wide range of possible uses and has considerable potential for improving medical and nursing care. In radiological diagnostics, for example, there are already many well-researched applications for AI-based image evaluation. In this article further AI developments are presented, which can help to relieve medical staff in order to create more time for direct patient care. In addition, essential aspects regarding the development and transfer of AI-based applications are highlighted. It is crucial that the integration of AI into medical practice is carried out with the utmost care and prudence. Data protection and ethical aspects need to be considered and respected at all times. Ensuring the reliability and integrity of AI systems is essential to earn the trust of both patients and healthcare professionals. A comprehensive inspection for possible bias within the underlying data and algorithms is indispensable. In this field of tension between promising possibilities and ethical challenges, the digital transformation in medicine and care can be designed to increase patient safety and to relieve staff.Rapid advances in digital technology and the promising potential of artificial intelligence (AI) are changing our everyday lives and have already impacted on hospital procedures. The use of AI applications, in particular, enables a wide range of possible uses and has considerable potential for improving medical and nursing care. In radiological diagnostics, for example, there are already many well-researched applications for AI-based image evaluation. In this article further AI developments are presented, which can help to relieve medical staff in order to create more time for direct patient care. In addition, essential aspects regarding the development and transfer of AI-based applications are highlighted. It is crucial that the integration of AI into medical practice is carried out with the utmost care and prudence. Data protection and ethical aspects need to be considered and respected at all times. Ensuring the reliability and integrity of AI systems is essential to earn the trust of both patients and healthcare professionals. A comprehensive inspection for possible bias within the underlying data and algorithms is indispensable. In this field of tension between promising possibilities and ethical challenges, the digital transformation in medicine and care can be designed to increase patient safety and to relieve staff.