Volatile-consuming reactions fracture rocks and self-accelerate fluid flow in the lithosphere

Hydration and carbonation reactions within the Earth cause an increase in solid volume by up to several tens of vol%, which can induce stress and rock fracture. Observations of naturally hydrated and carbonated peridotite suggest that permeability and fluid flow are enhanced by reaction-induced fracturing. However, permeability enhancement during solid-volume–increasing reactions has not been achieved in the laboratory, and the mechanisms of reaction-accelerated fluid flow remain largely unknown. Here, we present experimental evidence of significant permeability enhancement by volume-increasing reactions under confining pressure. The hydromechanical behavior of hydration of sintered periclase [MgO + H2O → Mg(OH)2] depends mainly on the initial pore-fluid connectivity. Permeability increased by three orders of magnitude for low-connectivity samples, whereas it decreased by two orders of magnitude for high-connectivity samples. Permeability enhancement was caused by hierarchical fracturing of the reacting materials, whereas a decrease was associated with homogeneous pore clogging by the reaction products. These behaviors suggest that the fluid flow rate, relative to reaction rate, is the main control on hydromechanical evolution during volume-increasing reactions. We suggest that an extremely high reaction rate and low pore-fluid connectivity lead to local stress perturbations and are essential for reaction-induced fracturing and accelerated fluid flow during hydration/carbonation.

Education shapes the structure of semantic memory and impacts creative thinking

Education is central to the acquisition of knowledge, such as when children learn new concepts. It is unknown, however, whether educational differences impact not only what concepts children learn, but how those concepts come to be represented in semantic memory—a system that supports higher cognitive functions, such as creative thinking. Here we leverage computational network science tools to study hidden knowledge structures of 67 Swiss schoolchildren from two distinct educational backgrounds—Montessori and traditional, matched on socioeconomic factors and nonverbal intelligence—to examine how educational experience shape semantic memory and creative thinking. We find that children experiencing Montessori education show a more flexible semantic network structure (high connectivity/short paths between concepts, less modularity) alongside higher scores on creative thinking tests. The findings indicate that education impacts how children represent concepts in semantic memory and suggest that different educational experiences can affect higher cognitive functions, including creative thinking.

Comprehensive analysis of the ceRNA network in coronary artery disease

With the rapid aging of the population, coronary artery disease (CAD) has become one of the most fatal chronic diseases. However, the genetic mechanism of CAD is still unclear. The purpose of this study is to construct the lncRNA-miRNA-mRNA regulatory network for CAD diseases and systematically identify differentially expressed genes in patients with coronary heart disease. In this study, two lncRNA datasets (GSE69587 and GSE113079) and a microRNA dataset (GSE105449) which contained 393 and 38 CAD samples were selected. In addition, two mRNA datasets which named GSE113079 (98 CAD samples) and GSE9820 (8 CAD samples) were selected to search the differentially expressed genes (DEGs). By comparing the expression data between CAD and control samples, a total of 1111 lncRNAs, 2595 mRNAs and 22 miRNAs were identified. Based on the DEGs, a lncRNA-miRNA-mRNA ceRNA network was constructed to explore the hub nodes in CAD. In the ceRNA network, the lncRNAs KCNQ1OT1 and H19 showed high connectivity with the nine miRNAs. GO and KEGG results showed that genes in ceRNA networks were mainly involved in nitrogen compound metabolic process, PI3K-Akt signaling pathway and retrograde endocannabinoid signaling. These findings will improve the understanding of the occurrence and development mechanism of CAD.

A Continental-Scale Connectivity Analysis to Predict Current and Future Colonization Trends of Biofuel Plant’s Pests for Sub-Saharan African Countries

Biofuel production in Sub-Saharan Africa is an important part of local low-income countries. Among many plant species, Jatropha curcas gained popularity in this area, as it can be grown even where crops of agricultural interest cannot. A natural African pest of J. curcas is the Aphthona cookei species group, for which future climatic suitability is predicted to favor areas of co-occurrence. In this research, we identify the possible climatic corridors in which the colonization of J. curcas crops may occur through a circuit theory-based landscape connectivity software at a country scale. Additionally, we use the standardized connectivity change index to predict possible variations in future scenarios. Starting from ecological niche models calibrated on current and 2050 conditions (two different RCP scenarios), we found several countries currently showing high connectivity. Ghana, Zambia and Ivory Coast host both high connectivity and a high number of J. curcas cultivations, which is also predicted to increase in the future. On the other side, Burundi and Rwanda reported a future increase of connectivity, possibly acting as “connectivity bridges” among neighboring countries. Considering the economic relevance of the topic analyzed, our spatially explicit predictions can support stakeholders and policymakers at a country scale in informed territorial management.

Identification of Key Ischemic Stroke Genes by Computational Systems Biology

Stroke is one of the leading causes of death in humans. Even if patients survive from stroke, they may suffer sequelae such as disability. Treatment for strokes remains unsatisfactory due to an incomplete understanding of its mechanisms. This study investigates Ischemic Stroke (IS), a primary subtype of stroke, through analyses based on microarray data. Limma (in R)derives differentially expressed genes, and the protein-protein interaction (PPI) network is mapped from the database. Gene co-expression patterns are obtained for clustering gene modules by the Weighted Correlation Network Analysis (WGCNA), and genes with high connectivity in the significantly co-expressed modules are selected as key regulators. Common hubs are identified as Cdkn1a, Nes and Anxa2. Based on our analyses, we hypothesize that these hubs might play a key role in the onset and progression of IS. Result suggests the potential of identifying unexplored key regulators by the systemic method used in this work. Further analyses aim at expanding candidate genes for screening biomarkers for IS, and experimental validation is required on identified potential hubs.

A connectivity signature for glioblastoma

Tumor cell extensions called tumor microtubes (TMs) in glioma resemble neurites during neurodevelopment and connect glioma cells to a network that has considerable relevance for tumor progression and therapy resistance. The determination of interconnectivity in individual tumors has been challenging and the impact of tumor cell connectivity on patient survival remained unresolved so far. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells was established and clinically validated. Thirty-four of 40 connectivity genes were related to neurogenesis, neural tube development or glioma progression, including the TM-network-relevant GAP43 gene. Astrocytic-like and mesenchymal-like GB cells had the highest connectivity signature scores in scRNA-Seq data of patient-derived xenografts and patient samples. In 230 human GBs, high connectivity correlated with the mesenchymal expression subtype, TP53 wildtype, and with dismal patient survival. CHI3L1 was identified as a robust molecular marker of connectivity. Thus, the connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell connectivity is relevant for patients prognosis, and serves as a robust biomarker that can be used for future clinical trials.

KMT5C encodes robust heterochromatin retention and liquid-like behavior using limited sequence features

Cells use multiple strategies to compartmentalize functions through a combination of membrane-bound and membraneless organelles. The latter represent complex assemblies of biomolecules that coalesce into a dense phase through low affinity, multivalent interactions and undergo rapid exchange with the surrounding dilute phase. We describe a liquid-like state for the lysine methyltransferase KMT5C characterized by diffusion within heterochromatin condensates but lacking appreciable nucleoplasmic exchange. Retention was strongly correlated with reduction of condensate surface area, suggesting formation of a liquid droplet with high connectivity. This behavior mapped to a discrete domain whose activity was dependent on multiple short linear motifs. Moreover, it was strikingly resilient to marked phylogenetic differences or targeted changes in intrinsic disorder, charge, sequence, and architecture. Collectively, these findings show that a limited number of sequence features can dominantly encode multivalency, localization, and dynamic behavior within heterochromatin condensates to confer protein retention without progression to a gel or solid.

Urban Green Infrastructure and Sustainable Development: A Review

Urban green infrastructure (UGI) can alleviate many of the problems that the growing urban population is facing. This study performed a literature review about UGI and sustainable development (SD) using the Web of Science (WoS) and the software VOSviewer. Of 195 papers selected, 89 are qualitative, focusing on theoretical approaches and design; equally, 89 are quantitative, dealing with metrics and spatial analysis and 17 combined both approaches. A high connectivity between “green infrastructure”, “ecosystem services”, “urban planning” and “sustainable development” was observed. Only 39 of the documents embrace environmental, social and economic aspects. Most of the papers are related to Sustainable Development Goal (SDG) 11, “to make cities inclusive, safe, resilient and sustainable” and SDG 15, “protect, restore and promote sustainable use of terrestrial ecosystems”. Further research integrating the three pillars of sustainability and relating UGI to all the SDGs is recommended.

Identification of Key Ischemic Stroke Genes by Computational Systems Biology

Stroke is one of the leading causes of death in humans. Even if patients survive from stroke, they may suffer sequelae such as disability. Treatment for strokes remains unsatisfactory due to an incomplete understanding of its mechanisms. This study investigates Ischemic Stroke (IS), a primary subtype of stroke, through analyses based on microarray data. Limma (in R)derives differentially expressed genes, and the protein-protein interaction (PPI) network is mapped from the database. Gene co-expression patterns are obtained for clustering gene modules by the Weighted Correlation Network Analysis (WGCNA), and genes with high connectivity in the significantly co-expressed modules are selected as key regulators. Common hubs are identified as Cdkn1a, Nes and Anxa2. Based on our analyses, we hypothesize that these hubs might play a key role in the onset and progression of IS. Result suggests the potential of identifying unexplored key regulators by the systemic method used in this work. Further analyses aim at expanding candidate genes for screening biomarkers for IS, and experimental validation is required on identified potential hubs.