The Intertwined Renewable Energy–Water–Environment (REWE) Nexus Challenges and Opportunities: A Case Study of California

In our built environment, societal production of energy and clean water is inextricably linked to the natural resources from which they are derived. Acknowledgement and consideration of the coupling of energy, water, and the environment (the energy–water–environment nexus) will be critical to a sustainable future. This is particularly true as we transition away from historical energy sources (e.g., coal, petroleum, natural gas) and into the widespread adaptation of renewable energy (RE) sources (e.g., solar, wind, geothermal, hydro, bioenergy) as a strategy to decrease greenhouse gas emissions and consequently slow global climate change. This transition is fraught with both challenges and opportunities at the county, state, national, and international levels, as addressing future societal needs with respect to energy and water, and the environment requires recognition of their interdependence and development of new technologies and societal practices. In this study, the focus is on the RE–water–environment (REWE) nexus. In California, the REWE nexus is becoming increasingly important in achieving 100% clean electricity from eligible RE and zero-carbon resources by 2045 and in the face of climate change and population and economic growth. In this context, California’s RE deployment and renewable electrical generation, its RE legislative information, REWE nexus, and intertwined REWE nexus challenges and opportunities in California (e.g., administrative–legal, technology development, digitalization, and end-of-life RE waste) are comprehensively discussed to identify the knowledge gaps in this nexus and solutions

Comparison of reaction networks of Wnt signaling

Wnt signaling is a vital biological mechanism that regulates crucial development processes and maintenance of tissue homeostasis. Here, we extended the parameter-free analysis of four mathematical models of the beta-catenin-dependent Wnt signaling pathway performed by MacLean et al. (PNAS USA 2015) using chemical reaction network theory. We showed that the reaction networks of the four models considered (Lee, Schmitz, MacLean, and Feinberg) coincide in basic structural and kinetic properties except in their mono-stationarity/multi-stationarity, and their capacity for admitting a degenerate equilibrium. Moreover, we showed that the embedded networks of the Lee and Feinberg models are very similar, and the discordance of the Lee network limits its mono-stationarity to mass action kinetics, which challenge the absoluteness of model discrimination into mono-stationarity versus multi-stationarity alone. Focusing, henceforth, on the three multi-stationary networks, we showed that their finest independent decompositions are very different and can be used to study further similarities and differences among them. We also determined equilibria parametrizations of the networks and inferred the presence of species with absolute concentration robustness. Finally, direct comparison of the Schmitz and Feinberg networks with the MacLean network yielded new results in three aspects: structural/kinetic relationships between embedded networks relative to their set of common species, connections between the positive equilibria of the subnetwork of common reactions and the positive equilibria of the whole networks, and construction of maximal concordant subnetwork containing the common reactions of the networks under comparison. Thus, this work can provide general insights in comparing mathematical models of the same or closely-related systems

A Computational Approach to Multistationarity of Power-Law Kinetic Systems

This paper presents a computational solution to determine if a chemical reaction network endowed with power-law kinetics (PLK system) has the capacity for multistationarity, i.e., whether there exist positive rate constants such that the corresponding differential equations admit multiple positive steady states within a stoichiometric class. The approach, which is called the "Multistationarity Algorithm for PLK systems" (MSA), combines (i) the extension of the "higher deficiency algorithm" of Ji and Feinberg for mass action to PLK systems with reactant-determined interactions, and (ii) a method that transforms any PLK system to a dynamically equivalent one with reactant-determined interactions. Using this algorithm, we obtain two new results: the monostationarity of a popular model of anaerobic yeast fermentation pathway, and the multistationarity of a global carbon cycle model with climate engineering, both in the generalized mass action format of biochemical systems theory. We also provide examples of the broader scope of our approach for deficiency one PLK systems in comparison to the extension of Feinberg's "deficiency one algorithm" to such systems

Numerical simulations of the Warm-Hot Intergalactic Medium

In this paper we review the current predictions of numerical simulations for the origin and observability of the warm hot intergalactic medium (WHIM), the diffuse gas that contains up to 50 per cent of the baryons at z~0. During structure formation, gravitational accretion shocks emerging from collapsing regions gradually heat the intergalactic medium (IGM) to temperatures in the range T~10^5-10^7 K. The WHIM is predicted to radiate most of its energy in the ultraviolet (UV) and X-ray bands and to contribute a significant fraction of the soft X-ray background emission. While O VI and C IV absorption systems arising in the cooler fraction of the WHIM with T~10^5-10^5.5 K are seen in FUSE and HST observations, models agree that current X-ray telescopes such as Chandra and XMM-Newton do not have enough sensitivity to detect the hotter WHIM. However, future missions such as Constellation-X and XEUS might be able to detect both emission lines and absorption systems from highly ionised atoms such as O VII, O VIII and Fe XVII.Comment: 18 pages, 5 figures, accepted for publication in Space Science Reviews, special issue "Clusters of galaxies: beyond the thermal view", Editor J.S. Kaastra, Chapter 14; work done by an international team at the International Space Science Institute (ISSI), Bern, organised by J.S. Kaastra, A.M. Bykov, S. Schindler & J.A.M. Bleeke

Food insecurity, school absenteeism and educational attainment of adolescents in Jimma Zone Southwest Ethiopia: a longitudinal study

<p>Abstract</p> <p>Background</p> <p>Food insecurity not only affects physical growth and health of children but also their intellectual development, school attendance and academic performance. However, most evidences are based on studies in high income countries. Although food insecurity is common in Ethiopia, to what extent it affects school attendance and educational attainment of adolescents is not explored. We hypothesized that food insecure adolescents would be more likely to be absent from school and have lower grades attained after 1 year compared to their food secure peers.</p> <p>Methods</p> <p>We used data from 2009 adolescents in the age group of 13-17 years from two consecutive surveys of a five year longitudinal family study in Southwest Ethiopia. A stratified random sampling was used to select participants. Regression analyses were used to compare school absenteeism and the highest grade attained after 1 year of follow-up in food secure and insecure adolescents. The analysis was adjusted for demographic factors, reported illness and workload.</p> <p>Results</p> <p>Significantly more (33.0%) food insecure adolescents were absent from school compared with their food secure peers (17.8%, P < 0.001). Multivariable logistic regression analyses showed that after adjusting for gender, place of residence and gender of the household head, adolescent food insecurity [OR 1.77 (1.34-2.33)], severe household food insecurity [OR 1.62 (1.27-2.06)], illness during the past one month before the survey [OR 2.26 (1.68-3.06)], the highest grade aspired to be completed by the adolescent [OR 0.92 (0.88-0.96)], and the number of days that the adolescent had to work per week [OR 1.16 (1.07-1.26)] were independent predictors of school absenteeism. Similarly after controlling for household income and gender of the household head, adolescent food insecurity(P < 0.001), severe household food insecurity(P < 0.001), illness during the last month(P < 0.001) and rural residence(P < 0.001) were inversely associated with highest grade attained, while age of the adolescent(P < 0.001), the highest grade intended to be completed(P < 0.001) and residence in semi urban area(P < 0.001) were positively associated with the highest grade attained.</p> <p>Conclusions</p> <p>Adolescent and household food insecurity are positively associated with school absenteeism and a lower educational attainment. Programs aiming to achieve universal access to primary education in food insecure environments should integrate interventions to ensure food security of adolescents.</p

Mutational heterogeneity in cancer and the search for new cancer genes

Major international projects are now underway aimed at creating a comprehensive catalog of all genes responsible for the initiation and progression of cancer. These studies involve sequencing of matched tumor–normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here, we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false positive findings that overshadow true driver events. Here, we show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumor-normal pairs and discover extraordinary variation in (i) mutation frequency and spectrum within cancer types, which shed light on mutational processes and disease etiology, and (ii) mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and allow true cancer genes to rise to attention

Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain

A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We present a set of integrated experiments that investigate the effects of common genetic variability on DNA methylation and mRNA expression in four human brain regions each from 150 individuals (600 samples total). We find an abundance of genetic cis regulation of mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation across the genome. We show peak enrichment for cis expression QTLs to be approximately 68,000 bp away from individual transcription start sites; however, the peak enrichment for cis CpG methylation QTLs is located much closer, only 45 bp from the CpG site in question. We observe that the largest magnitude quantitative trait loci occur across distinct brain tissues. Our analyses reveal that CpG methylation quantitative trait loci are more likely to occur for CpG sites outside of islands. Lastly, we show that while we can observe individual QTLs that appear to affect both the level of a transcript and a physically close CpG methylation site, these are quite rare. We believe these data, which we have made publicly available, will provide a critical step toward understanding the biological effects of genetic variation