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Fasting hyperglycemia in diabetes mellitus is caused by un-regulated glucagon secretion that activates gluconeogenesis (GNG) and increases the use of pyruvate, lactate, amino acids, and glycerol. Studies of GNG in hepatocytes, however, tend to test a limited number of substrates at nonphysiologic concentrations. Therefore, we treated cultured primary hepatocytes with three identical substrate mixtures of pyruvate/lactate, glutamine, and glycerol at serum fasting concentrations, where a different U-13C- or 2-13C-labeled substrate was substituted in each mix. In the absence of glucagon stimulation, 80% of the glucose produced in primary hepatocytes incorporated either one or two 13C-labeled glycerol molecules in a 1:1 ratio, reflecting the high overall activity of this pathway. In contrast, glucose produced from 13C-labeled pyruvate/lactate or glutamine rarely incorporated two labeled molecules. While glucagon increased the glycerol and pyruvate/lactate contributions to glucose carbon by 1.6- and 1.8-fold, respectively, the glutamine contribution to glucose carbon was increased 6.4-fold in primary hepatocytes. To account for substrate 13C carbon loss during metabolism, we also performed a metabolic flux analysis, which confirmed that the majority of glucose carbon produced by primary hepatocytes was from glycerol. In vivo studies using a PKA-activation mouse model that represents elevated glucagon activity confirmed that most circulating lactate carbons originated from glycerol, but very little glycerol was derived from lactate carbons, reflecting glycerol's importance as a carbon donor to GNG. Given the diverse entry points for GNG substrates, hepatic glucagon action is unlikely to be due to a single mechanism. [ABSTRACT FROM AUTHOR]

The article discusses a research conducted on practical synthesis of lycopene.

Gluconeogenesis (GNG) is de novo production of glucose from endogenous carbon sources. Although it is a commonly studied pathway, particularly in disease, there is a lack of consensus about substrate preference. Moreover, primary hepatocytes are the current gold standard for in vitro liver studies, but no direct comparison of substrate preference at physiological fasting concentrations has been performed. We show that mouse primary hepatocytes prefer glycerol to pyruvate/lactate in glucose production assays and 13C isotope tracing studies at the high concentrations commonly used in the literature, as well as at more relevant fasting, physiological concentrations. In addition, when glycerol, pyruvate/lactate, and glutamine are all present, glycerol is responsible for over 75% of all glucose carbons labeled. We also found that glycerol can induce a ratelimiting enzyme of GNG, glucose-6-phosphatase. Lastly, we suggest that glycerol is a better substrate than pyruvate to test in vivo production of glucose in fasting mice. In conclusion, glycerol is the major carbon source for GNG in vitro and in vivo and should be compared with other substrates when studying GNG in the context of metabolic disease states. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality). In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones. [ABSTRACT FROM AUTHOR]

Recently, energy harvesting has been emerging as a promising technique to prolong the lifetime for wireless sensor nodes. Most existing efforts address the design of energy harvesting and sensor node subsystem separately or ignore some real-world constraints. In this paper, we study how to codesign the two subsystems and how to jointly manage energy harvesting, storage, and usage. We first propose a novel system architecture for energy harvesting which employs several supercapacitors to eliminate the conflicts on charging and discharging among different system components. Then, we present a method to schedule their charging and discharging, which is proved to be able to guarantee zero waste of the harvested energy if the battery is not full. Third, we propose an optimal algorithm to minimize different components' capacity and two heuristic algorithms to maximize the system reward. We conduct extensive experiments based on real-life data traces. Results show that the proposed system architecture can harvest more energy compared to the state of the art, and the capacity optimization algorithm can choose the most suitable size for each system component. [ABSTRACT FROM AUTHOR]