Global Engineering Research and Technologies (United States)

Gremlin-1 has been implicated in liver fibrosis in metabolic dysfunction-associated steatohepatitis (MASH) via inhibition of bone morphogenetic protein (BMP) signalling and has thereby been identified as a potential therapeutic target. Using rat in vivo and human in vitro and ex vivo model systems of MASH fibrosis, we show that neutralisation of Gremlin-1 activity with monoclonal therapeutic antibodies does not reduce liver inflammation or liver fibrosis. Still, Gremlin-1 was upregulated in human and rat MASH fibrosis, but expression was restricted to a small subpopulation of COL3A1/THY1+ myofibroblasts. Lentiviral overexpression of Gremlin-1 in LX-2 cells and primary hepatic stellate cells led to changes in BMP-related gene expression, which did not translate to increased fibrogenesis. Furthermore, we show that Gremlin-1 binds to heparin with high affinity, which prevents Gremlin-1 from entering systemic circulation, prohibiting Gremlin-1-mediated organ crosstalk. Overall, our findings suggest a redundant role for Gremlin-1 in the pathogenesis of liver fibrosis, which is unamenable to therapeutic targeting.

COVID-19 has infected millions of people and caused hundreds of thousands of deaths worldwide. One of the most serious complications of COVID-19 is acute respiratory distress syndrome (ARDS), which can be fatal. People who are at least 60 years old or have underlying health conditions are at higher risk of developing ARDS. Medical imaging, such as computed tomography (CT) scans and chest x-rays, can be used to diagnose ARDS. However, these tests can be time-consuming and require specialised equipment. Artificial intelligence (AI) is being developed to automate the diagnosis of ARDS from medical images. AI-based systems can be used to quickly and accurately identify patients who are at risk of developing ARDS. They can also be used to monitor patients who have already developed ARDS and to assess the severity of their condition. AI-based systems are still under development, but they have the potential to improve the diagnosis and treatment of ARDS. By automating the diagnosis of ARDS, AI can help to reduce the time it takes to get patients the treatment they need. AI can also help to improve the accuracy of diagnosis and to identify patients who are at risk of developing ARDS. The use of AI in the diagnosis and treatment of ARDS is still in its early stages, but it has the potential to revolutionise the way this serious condition is managed.

The chapter is organized as follows: section 1.2 examines the physiological mechanisms underlying the four pathways that result in heart and brain injuries. Section 1.3 presents an overview of the justification for utilizing imaging in the context of the COVID-19 pandemic. Section 1.4 provides an in-depth exploration of utilizing AI-based tissue characterization for risk assessment. Ultimately, the paper concludes with a thorough critical analysis.

Supplementary Data and figures belonging to the manuscript titled "Tracing timing of growth in cultured mollusks using strontium spiking", in review with Frontiers in Marine Science. v2.0: Updated Supplementary File SI7 to include calculations of percentages of trace element peaks cooccurring with peaks in Sr. v2.1: Add latest versions of manuscript figures

The purpose of this study is to explore the direction of the association between work values and networking behavior by treating quality of work life as a mediator in contrast to how it is used in majority of previous studies. Analytical type of research design was used, and the data were collected from 304 participants. Three measurement devices were employed: Schwartz’s Portrait Values Questionnaire, Quality of Work Life questionnaire by Sirgy, and Aizen’s Networking Behavior Questionnaire. Four important outcomes are: 1. Intrinsic and social work values are effective in shaping networking behavior; 2. Quality of work life is mediated the relationship between work values and networking behavior; 3. The perceived quality of work life by the employees is not satisfactory and 4. The prioritized needs for male employees are aesthetics and self-actualization, while for female employees, these are knowledge and economics-family. The current study provides empirical evidence for demonstrating the direction of the association between work value orientations, quality of work life and networking behaviors of employees in organizations as well as the mediator effect of the quality of work life in the association between work values and networking behaviors of the members of organizations.

A form of ranked-order filters is introduced as the local maximum filter. The construction of the local maximum filter is described, followed by a discussion of its function and some of its more important properties, and an example application of a two-dimensional local maximum filter is provided to illustrate the detection of single-pixel targets against a cloud clutter background. The closing discussion provides a mathematical development of the filter.