Integrated transcriptomic and metabolomic analysis reveals the metabolic programming of GM-CSF- and M-CSF- differentiated mouse macrophages

Macrophages play a critical role in the inflammatory response and tumor development. Macrophages are primarily divided into pro-inflammatory M1-like and anti-inflammatory M2-like macrophages based on their activation status and functions. In vitro macrophage models could be derived from mouse bone marrow cells stimulated with two types of differentiation factors: GM-CSF (GM-BMDMs) and M-CSF (M-BMDMs), to represent M1- and M2-like macrophages, respectively. Since macrophage differentiation requires coordinated metabolic reprogramming and transcriptional rewiring in order to fulfill their distinct roles, we combined both transcriptome and metabolome analysis, coupled with experimental validation, to gain insight into the metabolic status of GM- and M-BMDMs. The data revealed higher levels of the tricarboxylic acid cycle (TCA cycle), oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO), and urea and ornithine production from arginine in GM-BMDMs, and a preference for glycolysis, fatty acid storage, bile acid metabolism, and citrulline and nitric oxide (NO) production from arginine in M-BMDMs. Correlation analysis with the proteomic data showed high consistency in the mRNA and protein levels of metabolic genes. Similar results were also obtained when compared to RNA-seq data of human monocyte derived macrophages from the GEO database. Furthermore, canonical macrophage functions such as inflammatory response and phagocytosis were tightly associated with the representative metabolic pathways. In the current study, we identified the core metabolites, metabolic genes, and functional terms of the two distinct mouse macrophage populations. We also distinguished the metabolic influences of the differentiation factors GM-CSF and M-CSF, and wish to provide valuable information for in vitro macrophage studies

Cloud-based Geophysical Inversion Modeling Using GNU Octave and MatlabMPI on Amazon EC2

Computer modeling and simulation can be very demanding in terms of computational resources. Cloud computing has opened up new avenues for the scientific researchers with limited resources to do complicated simulation. In order to investigate whether cloud computing is suitable for modeling and simulation, we first describe how to build a cloud-based modeling and simulation platform using GNU Octave and MatlabMPI on the Amazon Elastic Compute Cloud (EC2). Then, we evaluation its performance taking the geophysical inversion modeling as an example. The results show that the cloud-based modeling and simulation platform is suitable for basic modeling for free. It can provide much more higher performance with acceptable price. Furthermore, we can cut down the cost by  employing the Spot instance without losing the computation performance

Cloud-based Geophysical Inversion Modeling Using GNU Octave and MatlabMPI on Amazon EC2

Computer modeling and simulation can be very demanding in terms of computational resources. Cloud computing has opened up new avenues for the scientific researchers with limited resources to do complicated simulation. In order to investigate whether cloud computing is suitable for modeling and simulation, we first describe how to build a cloud-based modeling and simulation platform using GNU Octave and MatlabMPI on the Amazon Elastic Compute Cloud (EC2). Then, we evaluation its performance taking the geophysical inversion modeling as an example. The results show that the cloud-based modeling and simulation platform is suitable for basic modeling for free. It can provide much more higher performance with acceptable price. Furthermore, we can cut down the cost by  employing the Spot instance without losing the computation performance

Nitrogen analogues of Thiele\u27s hydrocarbon

A series of bis[N,N-di-(4-methoxylphenyl)amino]arene dications 12+-32+ have been synthesized and characterized. Their electronic structures were investigated by various experiments assisted by theoretical calculations. It was found that they are singlets in the ground state and that their diradical character is dependent on the bridging moiety. 32+ has a smaller singlet-triplet energy gap and its excited triplet state is thermally readily accessible. The work provides a nitrogen analogue of Thiele\u27s hydrocarbon with considerable diradical character

Association among Household Wealth, Maternal Employment, and Undernutrition in Children under Three Years of Age in Pakistan

Background: There is an abundance of studies explaining the separate impact of female employment and household wealth status in reducing malnutrition. However, our study has unraveled the combined impact of maternal employment and household wealth on undernutrition among children under three in Pakistan. Methods: Using a sample of 1093 children under three years of age from the Pakistan Demographic and Health Survey 2017–2018, a binary logistic model was employed to gauge factors influencing the children’s undernutrition. Results: Our results indicated that children up to a certain age (three years old) with residence in certain regions (Pakistan) and recent episodes of diarrhea had an increased risk of undernutrition. Conversely, secondary and higher maternal education, access to improved water sources, and sanitation facilities lowered the chances of undernutrition in children under three in Pakistan. The interaction between maternal employment and household wealth showed that maternal employment significantly lowered the risk of stunting, being underweight, and wasting among the average, rich, and richest households; however, it did not contribute to child nutrition among the poorer and poor households. Notably, regardless of whether the mother was employed, the wealth status of being rich and richest reduced the risk of stunting, being underweight, and wasting. Conclusions: In overcoming undernutrition, maternal employment significantly contributed to middle-income households. However, in the richer and richest households, the wealth status played a more crucial role compared to the maternal employment. This indicates that while employment plays a supportive role in household resources, the wealth status is overall more influential in reducing undernutrition

Molecular Link between Leaf Coloration and Gene Expression of Flavonoid and Carotenoid Biosynthesis in Camellia sinensis Cultivar ‘Huangjinya’

‘Huangjinya’ is an excellent albino tea germplasm cultivated in China because of its bright color and high amino acid content. It is light sensitive, with yellow leaves under intense light while green leaves under weak light. As well, the flavonoid and carotenoid levels increased after moderate shading treatment. However, the mechanism underlying this interesting phenomenon remains unclear. In this study, the transcriptome of ‘Huangjinya’ plants exposed to sunlight and shade were analyzed by high-throughput sequencing followed by de novo assembly. Shading ‘Huangjinya’ made its leaf color turn green. De novo assembly showed that the transcriptome of ‘Huangjinya’ leaves comprises of 127,253 unigenes, with an average length of 914 nt. Among the 81,128 functionally annotated unigenes, 207 differentially expressed genes were identified, including 110 up-regulated and 97 down-regulated genes under moderate shading compared to full light. Gene ontology (GO) indicated that the differentially expressed genes are mainly involved in protein and ion binding and oxidoreductase activity. Antioxidation-related pathways, including flavonoid and carotenoid biosynthesis, were highly enriched in these functions. Shading inhibited the expression of flavonoid biosynthesis-associated genes and induced carotenoid biosynthesis-related genes. This would suggest that decreased flavonoid biosynthetic gene expression coincides with increased flavonoids (e.g., catechin) content upon moderate shading, while carotenoid levels and biosynthetic gene expression are positively correlated in ‘Huangjinya.’ In conclusion, the leaf color changes in ‘Huangjinya’ are largely determined by the combined effects of flavonoid and carotenoid biosynthesis

Lower hybrid current drive experiments in support of high confinement long pulse operation in EAST

The lower hybrid current drive (LHCD) system plays a crucial role in the mission of the Experimental Advanced Superconducting Tokamak (EAST) and is a prerequisite for reaching long pulse, high confinement plasmas on EAST [1, 2]. LHCD experiments and modelling [3] have been carried out on EAST in 2015-2016, with the aim to optimising EAST long pulse scenarios, and at the same time gain experience for the exploitation of WEST [4]. Experiments have been carried out to study the LH current drive efficiency in different plasma configurations (Upper Single Null and Lower Single Null). The effect of the gas feed location on the LH wave coupling was investigated by comparing gas fuelling from high field side, low field side and upper divertor. In view of long pulse H-mode scenarios, a series of H-mode experiments were conducted where all the heating power was provided by RF heating methods only, i.e. LHCD, ECRH and ICRH. H-modes were sustained in both Upper Single Null (W divertor) and Lower Single Null (carbon divertor) configurations, with loop voltage maintained as low as 50 mV

Overview of Multi-Scale Simulation Techniques for Three Typical Steel Manufacturing Processes

Steel products typically undergo intricate manufacturing processes, commencing from the liquid phase, with casting, hot rolling, and laminar cooling being among the most crucial processes. In the background of carbon neutrality, thin-slab casting and direct rolling (TSCR) technology has attracted significant attention, which integrates the above three processes into a simpler and more energy-efficient sequence compared to conventional methods. Multi-scale computational modeling and simulation play a crucial role in steel design and optimization, enabling the prediction of properties and microstructure in final steel products. This approach significantly reduces the time and cost of production compared to traditional trial-and-error methodologies. This study provides a review of cross-scale simulations focusing on the casting, hot-rolling, and laminar cooling processes, aiming at presenting the key techniques for realizing cross-scale simulation of the TSCR process

DataSheet_1_Integrated transcriptomic and metabolomic analysis reveals the metabolic programming of GM-CSF- and M-CSF- differentiated mouse macrophages.docx

Macrophages play a critical role in the inflammatory response and tumor development. Macrophages are primarily divided into pro-inflammatory M1-like and anti-inflammatory M2-like macrophages based on their activation status and functions. In vitro macrophage models could be derived from mouse bone marrow cells stimulated with two types of differentiation factors: GM-CSF (GM-BMDMs) and M-CSF (M-BMDMs), to represent M1- and M2-like macrophages, respectively. Since macrophage differentiation requires coordinated metabolic reprogramming and transcriptional rewiring in order to fulfill their distinct roles, we combined both transcriptome and metabolome analysis, coupled with experimental validation, to gain insight into the metabolic status of GM- and M-BMDMs. The data revealed higher levels of the tricarboxylic acid cycle (TCA cycle), oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO), and urea and ornithine production from arginine in GM-BMDMs, and a preference for glycolysis, fatty acid storage, bile acid metabolism, and citrulline and nitric oxide (NO) production from arginine in M-BMDMs. Correlation analysis with the proteomic data showed high consistency in the mRNA and protein levels of metabolic genes. Similar results were also obtained when compared to RNA-seq data of human monocyte derived macrophages from the GEO database. Furthermore, canonical macrophage functions such as inflammatory response and phagocytosis were tightly associated with the representative metabolic pathways. In the current study, we identified the core metabolites, metabolic genes, and functional terms of the two distinct mouse macrophage populations. We also distinguished the metabolic influences of the differentiation factors GM-CSF and M-CSF, and wish to provide valuable information for in vitro macrophage studies.</p