Methane and Carbon Dioxide Adsorption on Illite

The adsorption of CH₄ and CO₂ onto illitic clay was investigated at the temperatures 298, 313, 328, 358, and 423 K (25, 40, 55, 85, and 150 °C) over a range of pressures up to 50 MPa using grand canonical Monte Carlo (GCMC) simulations. Our simulation results showed spontaneous and exothermic adsorption behavior of illite for CH₄ and CO₂ with enthalpy changes of −3.50 kJ/mol and −25.09 kJ/mol, respectively. Our results indicated that the interlayer counter cations (K⁺) play an important role in CO₂ adsorption. Methane adsorption is mainly affected by the clay surface layers rather than the interlayer counter cations. The density and volume of CH₄ and CO₂ in their adsorbed phase at saturation were extrapolated from the linear portion of the excess adsorption isotherm. The resulting values were compared with available experimental data, and possible factors causing inconsistency were described. We discussed some issues associated with the Langmuir fit to experimental excess adsorption data in the case of low pressures. Our findings may provide some insights into gas adsorption behavior in illite-bearing shales

Allelic interaction effects of DNA damage and repair genes on the predisposition to age-related cataract

<div><p>Purpose</p><p>Age-related cataract (ARC) is a leading cause of visual impairment and blindness worldwide. DNA damage and malfunction of DNA repair are believed to contribute to the pathogenesis of ARC. Aside from increasing age, the risk factors for ARC appear to be rather complex, and one or more gene variations could play critical roles in the diverse processes of ARC progression. This study aimed to investigate the combined effects of different genetic variants on ARC risk.</p><p>Methods</p><p>A cohort of 789 ARC patients and 531 normal controls from the Jiangsu Eye Study was included in this study. Genotyping of 18 single-nucleotide polymorphisms (SNPs) in 4 DNA damage/repair genes was performed using TaqMan SNP assays. SNP-SNP interactions were analyzed via multifactor dimensionality reduction (MDR), classification and regression tree (CART) and genetic risk score (GRS) analyses.</p><p>Results</p><p>Based on single-locus analyses of the 18 SNPs examined, <i>WRN-rs11574311 (</i></p><p><i>T>C</i></p><i>)</i> was associated with ARC risk. However, in MDR, the gene-gene interaction among the five SNPs (<i>WRN-rs4733220 (</i><p><i>G>A</i></p><i>)</i>, <i>WRN-rs1801195 (</i><p><i>T>G</i></p><i>)</i>, <i>OGG1-rs2072668 (</i><p><i>G>C</i></p><i>)</i> and <i>OGG1-rs2304277 (</i><p><i>A>G</i></p><i>)</i>) on ARC risk was significant (OR = 5.03, 95% CI: 3.54~7.13). CART analyses also revealed that the combination of five SNPs above was the best polymorphic signature for discriminating between the cases and the controls. The overall odds ratio for CART ranged from 4.56 to 7.90 showing an incremental risk for ARC. This result indicated that these critical SNPs participate in complex interactions. The GRS results showed an increased risk for ARC among individuals with the SNPs in this polymorphic signature.<p></p><p>Conclusion</p><p>The use of multifactorial analysis (or an integrated approach) rather than a single methodology could be an improved strategy for identifying complex gene interactions. The multifactorial approach used in this study has the potential to identify complex biological relationships among ARC-related genes and processes. This approach will lead to the discovery of novel biological information, ultimately improving ARC risk management.</p></div

Association of higher-order interactions with overall ARC risk based on MDR Analysis.

<p>Association of higher-order interactions with overall ARC risk based on MDR Analysis.</p

Transcriptomic Variation during Spermiogenesis in Mouse Germ Cells

<div><p>To explore variations in the transcription activity during spermiogenesis, round and elongated spermatids were collected from ICR/CD1 model mice using laser capture microdissection (LCM) and cauda epididymal sperm samples. The transcripts were sequenced using RNA-seq, and the reads were mapped to mm9. The majority of the reads (70%) in the round and elongated spermatids were mappable to known and predicted exons, but that in sperm was only 9%. The results of the distribution of reads suggested that alternative splicing was more complicated in sperm than in round and elongated spermatids. In the 19,127 genes, we detected the expression of 5,104 de novo genes and 91,112 alternative splicing events, and 12,105 were differentially expressed. Gene ontology (GO), InterPro domains, and KEGG revealed changes in gene transcription, mitochondrial protein translation, cellular components, and energy metabolism during spermiogenesis. The results provided considerable information about alternative splicing events, differentiallly expressed genes (DEGs), and novel transcriptions during spermiogenesis in mice.</p></div

Genotype distribution of SNPs in control and ARC subjects.

<p>Genotype distribution of SNPs in control and ARC subjects.</p

Risk estimates of CART Terminal Nodes for all ARC patients.

<p>Risk estimates of CART Terminal Nodes for all ARC patients.</p

Mean GRSs according to ARC subtype and corresponding P-values.

<p>Mean GRSs according to ARC subtype and corresponding P-values.</p

Risk estimates of CART Terminal Nodes for patients with the C subtype of ARC.

<p>Risk estimates of CART Terminal Nodes for patients with the C subtype of ARC.</p

Effect of Pio on Müller cell activation in retina.

<p>Immunoreactivity for PPARγ (green) and GFAP (red) in rat retinal sections of each group at 7days after ONC. Bar = 100 µm.</p

Functional enrichment results of each subcluster using NbClust R package.

<p>Asterisks (*) indicate the differentially expressed genes that were significantly enriched in GO terms.</p