Reactions of Molten LiI with I₂, H₂O, and O₂ Relevant to Halogen-Mediated Oxidative Dehydrogenation of Alkanes

Constant-temperature ab initio molecular dynamics is used to study reactions between molten LiI and gas phase molecules (O₂, H₂O, and I₂) in an attempt to elucidate some aspects of the alkane oxidative dehydrogenation activity performed in the presence of molten LiI. We investigate the energy of reactions that produce LiIO, LiIO₃, LiIO₄, Li₂O₂, Li₂O, LiOH, and I₂. We find that the most favorable process is the formation of gaseous I₂, coproduced with LiOH or Li₂O (depending on the availability of water). If water is absent, then some LiIO₄ will also be formed. However, this is unlikely to happen during oxidative dehydrogenation, because LiI is very hydroscopic and the oxidative dehydrogenation reaction produces water

Mapping and evaluating global urban entities (2000–2020): A novel perspective to delineate urban entities based on consistent nighttime light data

The differences in the definition of urban areas lead to our contrasting or inconsistent understanding of global urban development and their corresponding socioeconomic and environmental impacts. The existing urban areas were widely identified by the boundaries of built-environment or social-connections, rather than urban entities that are essentially the spatial extents of human activity agglomerations. Thus, this study has attempted to map and evaluate global urban entities (2000–2020) from a perspective of an updated urban concept of urban entities based on the consistent remotely sensed nighttime light data. First, a K-means algorithm was developed to cluster urban and non-urban pixels automatically in consideration of global region division. Then, a post-processing was conducted to enhance the temporal and logical consistency of urban entities during the study period. Rationality assessment indicates that urban entities derived from remotely sensed nighttime light data more effectively reflect the spatial agglomeration extents of human activities than those of physical urban areas. Global urban entities increased from 157,733 km2 in 2000 to 470,632 km2 in 2020 accompanied by a differentiated urban expansion at global, continental, and national levels. Our study provides long-time series and fine-resolution datasets (500 m) and new research avenues for spatiotemporal analysis of global urban entity expansion with the improvement of the understanding of urbanization and the emergence of effective urban mapping theories and approaches.</p

H3.3 nucleosomes with higher turnover index tend to associate with higher splitting index.

<p>(A) The distribution of splitting index for H3.3 nucleosomes within each specified turnover index range. (B) The distribution of splitting index for H3.3 nucleosomes within the highest turnover index ranges.</p

H3.3 nucleosome splitting events feature cell-type specific enhancers.

<p>(A) An example enhancer region enriched with split H3.3 nucleosomes. Profiles of single-round ChIPs, sequential ChIP, turnover index, splitting index are illustrated. Percentile ranking of turnover index and splitting index are shown in a grey scale. (B) Split H3.3 nucleosomes were specifically enriched at enhancers, whereas the non-split H3.3 nucleosomes were specifically depleted at enhancers. (C) Distribution of the H3.3 nucleosomes, split and non-split H3.3 nucleosomes, intergenic split H3.3 nucleosomes and high and low turnover H3.3 nucleosomes at the cell-type specific enhancers. (D) All H3.3 nucleosomes were sorted by their splitting index and grouped into 5000 nucleosome widows. These nucleosomes were then plotted against their overlap percentage with enhancers. The arbitrarily defined split and non-split nucleosomes with top or bottom 5% splitting index were boxed in red. (E) Similar to (D), but common enhancers were excluded. (F) The 10-kb genomic intervals sorted by their numbers of split nucleosomes were plotted against their overlap percentage with the cell-type specific enhancers. (G) Similar to (F), but common enhancers were excluded.</p

Genome-wide analysis of H3.3 nucleosome turnover.

<p>(A) Experimental scheme to determine the turnover index. (B) Two-dimensional histogram of <i>T₂₄</i> and <i>T₄₈</i> for all H3.3 nucleosomes. (C) Distribution profiles of the H3.3 nucleosome turnover index around the TSS (left panel) and TES (right panel). (D) Bimodal distribution of turnover at +1 nucleosome versus expression level. Genes were sorted by RPKM from high to low with a sliding widow of 600 genes and then plotted against their turnover index at the +1 nucleosome. (E) Genomic distribution of high turnover and low turnover H3.3 nucleosomes.</p

Moderate correlation between the H3.3 turnover index and splitting index.

<p>(A) Turnover index distribution profile for all H3.3 nucleosomes. (B) Turnover index distribution profile for the split H3.3 nucleosomes. (C) Turnover index distribution profile for the non-split H3.3 nucleosomes. (D) Box plot for the turnover index of all, split, and non-split H3.3 nucleosomes.</p

The enhancer H3.3 nucleosomes display higher splitting index than the non-enhancer H3.3 nucleosomes.

<p>(A) Box plot of the splitting index of enhancer or non-enhancer H3.3 nucleosomes within the same turnover ranges. (B) Box plot of the splitting index of H3.3 nucleosomes at the enhancers, promoters, 5-UTRs within the same turnover ranges. (C) Percentage of split nucleosomes for enhancer H3.3 or non-enhancer H3.3 at various turnover ranges. *** indicates the significant difference with P value<0.0001. (D) Dual-tagged H3.3 nucleosomes derived from the co-expression experiment did not show enrichment at cell-type specific enhancers.</p

Determine H3.3 nucleosome occupancy, turnover and splitting events at the genome-wide level.

<p>(A) Induction of Flag-H3.3 and HA-H3.3 histones. (B) Experimental scheme to determine the splitting index. (C) Distribution profiles of new H3.3 nucleosomes (Flag-tagged) around the TSS (left panel) and TES (right panel). Genes were divided into 3 groups according to their RPKM: High, the top one-third genes; Medium, the middle one-third genes and Low, the bottom one-third genes. (D) Distribution profiles of old H3.3 nucleosomes (HA-tagged).</p

H3.3 nucleosome splitting events are better markers for active transcription than H3.3 nucleosome occupancy.

<p>(A) Split H3.3 nucleosomes were enriched in the top 25% expression level genes, as compared to the total H3.3 nucleosomes or non-split H3.3 nucleosomes. Non-split H3.3 nucleosomes were enriched in the bottom 25% expression level genes. P values were calculated with chi-square test. ***P<0.001, **P<0.01, #P>0.1. (B) After normalization against the H3.3 occupancy, the split but not the non-split H3.3 nucleosomes were enriched at active genes. H3.3 nucleosomes at the entire genes were analyzed together.</p

Additional file 1: of JAK/STAT3 regulated global gene expression dynamics during late-stage reprogramming process

Schematic representation of the Dlk1-Dio3 region at mouse chromosome 12qF1. The Gtl2-Rian-Mirg lincRNAs are expressed from the maternally inherited chromosome, while the protein coding Dlk1, Rtl1, and Dio3 genes are expressed from the paternally inherited chromosome. IG-DMR is paternally methylated but demethylated in maternal chromosome to control expression of the Gtl2-Rian-Mirg lincRNAs. (PDF 61 kb