Epidermal ADAM17 maintains the skin barrier by regulating EGFR ligand-dependent terminal keratinocyte differentiation

ADAM17 (a disintegrin and metalloproteinase 17) is ubiquitously expressed and cleaves membrane proteins, such as epidermal growth factor receptor (EGFR) ligands, l-selectin, and TNF, from the cell surface, thus regulating responses to tissue injury and inflammation. However, little is currently known about its role in skin homeostasis. We show that mice lacking ADAM17 in keratinocytes (A17(ΔKC)) have a normal epidermal barrier and skin architecture at birth but develop pronounced defects in epidermal barrier integrity soon after birth and develop chronic dermatitis as adults. The dysregulated expression of epidermal differentiation proteins becomes evident 2 d after birth, followed by reduced transglutaminase (TGM) activity, transepidermal water loss, up-regulation of the proinflammatory cytokine IL-36α, and inflammatory immune cell infiltration. Activation of the EGFR was strongly reduced in A17(ΔKC) skin, and topical treatment of A17(ΔKC) mice with recombinant TGF-α significantly improved TGM activity and decreased skin inflammation. Finally, we show that mice lacking the EGFR in keratinocytes (Egfr(ΔKC)) closely resembled A17(ΔKC) mice. Collectively, these results identify a previously unappreciated critical role of the ADAM17–EGFR signaling axis in maintaining the homeostasis of the postnatal epidermal barrier and suggest that this pathway could represent a good target for treatment of epidermal barrier defects

A survey of distributed learning in cloud, mobile, and edge settings

In the era of deep learning (DL), convolutional neural networks (CNNs), and large language models (LLMs), machine learning (ML) models are becoming increasingly complex, demanding significant computational resources for both inference and training stages. To address this challenge, distributed learning has emerged as a crucial approach, employing parallelization across various devices and environments. This survey explores the landscape of distributed learning, encompassing cloud and edge settings. We delve into the core concepts of data and model parallelism, examining how models are partitioned across different dimensions and layers to optimize resource utilization and performance. We analyze various partitioning schemes for different layer types, including fully connected, convolutional, and recurrent layers, highlighting the trade-offs between computational efficiency, communication overhead, and memory constraints. This survey provides valuable insights for future research and development in this rapidly evolving field by comparing and contrasting distributed learning approaches across diverse contexts.Electrical and Computer Engineerin

Beyond prejudice: Are negative evaluations the problem and is getting us to like one another more the solution?

This is a post print version of an article published in Behavioral and Brain Sciences, 2012, 35 (6), pp 438-439 DOI: http://dx.doi.org/10.1017/S0140525X12001252 Copyright © Cambridge University Press 2012For most of the history of prejudice research, negativity has been treated as its emotional and cognitive signature, a conception that continues to dominate work on the topic. By this definition, prejudice occurs when we dislike or derogate members of other groups. Recent research, however, has highlighted the need for a more nuanced and ‘inclusive’ (Eagly 2004) perspective on the role of intergroup emotions and beliefs in sustaining discrimination. On the one hand, several independent lines of research have shown that unequal intergroup relations are often marked by attitudinal complexity, with positive responses such as affection and admiration mingling with negative responses such as contempt and resentment. Simple antipathy is the exception rather than the rule. On the other hand, there is mounting evidence that nurturing bonds of affection between the advantaged and the disadvantaged sometimes entrenches rather than disrupts wider patterns of discrimination. Notably, prejudice reduction interventions may have ironic effects on the political attitudes of the historically disadvantaged, decreasing their perceptions of injustice and willingness to engage in collective action to transform social inequalities. These developments raise a number of important questions. Has the time come to challenge the assumption that negative evaluations are inevitably the cognitive and affective hallmarks of discrimination? Is the orthodox concept of prejudice in danger of side-tracking, if not obstructing, progress towards social justice in a fuller sense? What are the prospects for reconciling a prejudice reduction model of change, designed to get people to like one another more, with a collective action model of change, designed to ignite struggles to achieve intergroup equality

A review of friction stir welding of aluminium matrix composites

As a solid state joining process, friction stir welding (FSW) has proven to be a promising approach for joining aluminium matrix composites (AMCs). However, challenges still remain in using FSW to join AMCs even with considerable progress having been made in recent years. This review paper provides an overview of the state of-the-art of FSW of AMC materials. Specific attention and critical assessment have been given to: (a) the macrostructure and microstructure of AMC joints, (b) the evaluation of mechanical properties of joints, and (c) the wear of FSW tools due to the presence of reinforcement materials in aluminium matrices. This review concludes with recommendations for future research directions