A graph-traversal approach to identify influential nodes in a network

Evolutionary characteristics of global offshore carbon emissions network and responsibility allocation of emissions reduction

Offshore carbon emissions from the international shipping trade are significant contributors to climate change. Based on the complex shipping trade networks, offshore carbon emissions are correlated rather than independent, and allocating responsibility for reducing emissions does not depend solely on the amount but on linkages. We use the global container shipping data covering more than 98% of routes from 2015 to 2020 to calculate the offshore carbon emissions from shipping. Subsequently, we construct an offshore carbon emissions network based on the shipping routes and emissions to identify the evolutionary tendency of network and clarify emissions reduction responsibilities by considering equity and efficiency. We discover that global offshore carbon emissions present a complicated network structure dominated by developed countries and large economies. Countries on the same continent or within the same economic organizations have closer and more frequent carbon correlations. Greater responsibilities should be allocated to countries who are at the center of the network.

In silico investigation of molecular networks linking gastrointestinal diseases, malnutrition, and sarcopenia

Malnutrition (MN) is a common primary or secondary complication in gastrointestinal diseases. The patient’s nutritional status also influences muscle mass and function, which can be impaired up to the degree of sarcopenia. The molecular interactions in diseases leading to sarcopenia are complex and multifaceted, affecting muscle physiology, the intestine (nutrition), and the liver at different levels. Although extensive knowledge of individual molecular factors is available, their regulatory interplay is not yet fully understood. A comprehensive overall picture of pathological mechanisms and resulting phenotypes is lacking. In silico approaches that convert existing knowledge into computationally readable formats can help unravel mechanisms, underlying such complex molecular processes. From public literature, we manually compiled experimental evidence for molecular interactions involved in the development of sarcopenia into a knowledge base, referred to as the Sarcopenia Map. We integrated two diseases, namely liver cirrhosis (LC), and intestinal dysfunction, by considering their effects on nutrition and blood secretome. We demonstrate the performance of our model by successfully simulating the impact of changing dietary frequency, glycogen storage capacity, and disease severity on the carbohydrate and muscle systems. We present the Sarcopenia Map as a publicly available, open-source, and interactive online resource, that links gastrointestinal diseases, MN, and sarcopenia. The map provides tools that allow users to explore the information on the map and perform in silico simulations.