SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids

Kidney failure is frequently observed during and after COVID-19, but it remains elusive whether this is a direct effect of the virus. Here, we report that SARS-CoV-2 directly infects kidney cells and is associated with increased tubule-interstitial kidney fibrosis in patient autopsy samples. To study direct effects of the virus on the kidney independent of systemic effects of COVID-19, we infected human-induced pluripotent stem-cell-derived kidney organoids with SARS-CoV-2. Single-cell RNA sequencing indicated injury and dedifferentiation of infected cells with activation of profibrotic signaling pathways. Importantly, SARS-CoV-2 infection also led to increased collagen 1 protein expression in organoids. A SARS-CoV-2 protease inhibitor was able to ameliorate the infection of kidney cells by SARS-CoV-2. Our results suggest that SARS-CoV-2 can directly infect kidney cells and induce cell injury with subsequent fibrosis. These data could explain both acute kidney injury in COVID-19 patients and the development of chronic kidney disease in long COVID

Declarative versus imperative process modeling languages : the issue of understandability

Advantages and shortcomings of different process modeling languages are heavily debated, both in academia and industry, but little evidence is presented to support judgements. With this paper we aim to contribute to a more rigorous, theoretical discussion of the topic by drawing a link to well-established research on program comprehension. In particular, we focus on imperative and declarative techniques of modeling a process. Cognitive research has demonstrated that imperative programs deliver sequential information much better while declarative programs offer clear insight into circumstantial information. In this paper we show that in principle this argument can be transferred to respective features of process modeling languages. Our contribution is a pair of propositions that are routed in the cognitive dimensions framework. In future research, we aim to challenge these propositions by an experiment

AGILE Interface for ‘No-Learning Nor Experience Required’ Interaction

The wide variety of technological devices is a barrier to satisfactory usage and learning over all. Different types of interface element distribution and dissimilarities of their functionalities, even in the same category of products under the same brand, can steepen the learning curve to effective device operation. Interface design can be understood as a mechanism for the adequacy of the technological environment to substantially improve performance, satisfaction and life of the user with special requirements. Based on an inclusive paradigm, we aim to improve the usability, accessibility and satisfiability of the interface for a specific group of users, such as novice elderly, to benefit all types of users in their daily lives. The requirements derived from a holistic analysis of user, goals and context lead to the introduction of the AGILE Interface (Assisted Guided Interaction with no Learning nor Experience required). This interface is the pillar of a new interaction style designed to assist and guide users with specific needs owing to age and non-Information and Technology experience. In the context of present-day technology interactions, the ultimate goal of this work is to move beyond out of date user stereotypes to tailor appropriate interface design adapted to realistic and specific user demands