Does the position of the electron-donating nitrogen atom in the ring system influence the efficiency of a dye-sensitized solar cell? A computational study

Electronic structure of the XeOF₂ molecule and its two complexes with HX (X= F, Cl, Br, I) molecules have been studied in the gas phase using quantum chemical topology methods: topological analysis of electron localization function (ELF), electron density, ρ(r), reduced gradient of electron density |RDG(r)| in real space, and symmetry adapted perturbation theory (SAPT) in the Hilbert space. The wave function has been approximated by the MP2 and DFT methods, using APF-D, B3LYP, M062X, and B2PLYP functionals, with the dispersion correction as proposed by Grimme (GD3). For the Xe-F and Xe=O bonds in the isolated XeOF₂ molecule, the bonding ELF-localization basins have not been observed. According to the ELF results, these interactions are not of covalent nature with shared electron density. There are two stable F₂OXe^…HF complexes. The first one is stabilized by the F-H^…F and Xe^…F interactions (type I) and the second by the F-H^…O hydrogen bond (type II). The SAPT analysis confirms the electrostatic term, E_elst ⁽¹⁾ and the induction energy, E_ind ⁽²⁾ to be the major contributors to stabilizing both types of complexes.

     

Genetics of barley tiller and leaf development

In cereals, tillering and leaf development are key factors in the concept of crop ideotype, introduced in the 1960 s to enhance crop yield, via manipulation of plant architecture. In the present review, we discuss advances in genetic analysis of barley shoot architecture,focusing on tillering, leaf size and angle. We also discuss novel phenotyping techniques, such as 2 D and 3 D imaging, that have been introduced in the era of phenomics, facilitating reliable trait measurement. We discuss the identification of genes and pathways that are involved in barley tillering and leaf development,highlighting key hormones involved in the control of plant architecture in barley and rice. Knowledge on genetic control of traits related to plant architecture provides useful resources for designing ideotypes for enhanced barley yield and performance.     

A distance-type measure approach to the analysis of copy number variation in DNA sequencing data

Background

The next generation sequencing technology allows us to obtain a large amount of short DNA sequence (DNA-seq) reads at a genome-wide level. DNA-seq data have been increasingly collected during the recent years. Count-type data analysis is a widely used approach for DNA-seq data. However, the related data pre-processing is based on the moving window method, in which a window size need to be defined in order to obtain count-type data. Furthermore, useful information can be reduced after data pre-processing for count-type data.

Results

In this study, we propose to analyze DNA-seq data based on the related distance-type measure. Distances are measured in base pairs (bps) between two adjacent alignments of short reads mapped to a reference genome. Our experimental data based simulation study confirms the advantages of distance-type measure approach in both detection power and detection accuracy. Furthermore, we propose artificial censoring for the distance data so that distances larger than a given value are considered potential outliers. Our purpose is to simplify the pre-processing of DNA-seq data. Statistically, we consider a mixture of right censored geometric distributions to model the distance data. Additionally, to reduce the GC-content bias, we extend the mixture model to a mixture of generalized linear models (GLMs). The estimation of model can be achieved by the Newton-Raphson algorithm as well as the Expectation-Maximization (E-M) algorithm. We have conducted simulations to evaluate the performance of our approach. Based on the rank based inverse normal transformation of distance data, we can obtain the related z-values for a follow-up analysis. For an illustration, an application to the DNA-seq data from a pair of normal and tumor cell lines is presented with a change-point analysis of z-values to detect DNA copy number alterations.

Conclusion

Our distance-type measure approach is novel. It does not require either a fixed or a sliding window procedure for generating count-type data. Its advantages have been demonstrated by our simulation studies and its practical usefulness has been illustrated by an experimental data application.

     

Late‐onset retinal degeneration pathology due to mutations in CTRP5 is mediated through HTRA1

Late‐onset retinal degeneration (L‐ORD) is an autosomal dominant macular degeneration characterized by the formation of sub‐retinal pigment epithelium (RPE) deposits and neuroretinal atrophy. L‐ORD results from mutations in the C1q‐tumor necrosis factor‐5 protein (CTRP5), encoded by the CTRP5/C1QTNF5 gene. To understand the mechanism underlying L‐ORD pathology, we used a human cDNA library yeast two‐hybrid screen to identify interacting partners of CTRP5. Additionally, we analyzed the Bruch's membrane/choroid (BM‐Ch) from wild‐type (Wt), heterozygous S163R Ctrp5 mutation knock‐in (Ctrp5^S163R/wt), and homozygous knock‐in (Ctrp5^S163R/S163R) mice using mass spectrometry. Both approaches showed an association between CTRP5 and HTRA1 via its C‐terminal PDZ‐binding motif, stimulation of the HTRA1 protease activity by CTRP5, and CTRP5 serving as an HTRA1 substrate. The S163R‐CTRP5 protein also binds to HTRA1 but is resistant to HTRA1‐mediated cleavage. Immunohistochemistry and proteomic analysis showed significant accumulation of CTRP5 and HTRA1 in BM‐Ch of Ctrp5^S163R/S163R and Ctrp5^S163R/wt mice compared with Wt. Additional extracellular matrix (ECM) components that are HTRA1 substrates also accumulated in these mice. These results implicate HTRA1 and its interaction with CTRP5 in L‐ORD pathology.     

Noncancer risk assessment of arsenic safe and unsafe water uses: Bayesian estimation on cohort study

Cancer and noncancer risk of arsenic exposure depends on arsenic intake through drinking water and diets. The present study evaluated the probability of noncancer effects of arsenic exposure from drinking water and diets in a cohort of 82 participants in arsenic-endemic rural areas, considering arsenic-safe and arsenic-unsafe water uses for three consecutive years. The risk assessment included the collection of last 24 hours' diet replica and urine of the participants followed by total arsenic analysis of the same. Toxic dose emerging from exposure duration is a nonlinear variable. So, Bayesian estimation of the data for noncancer risk assessment of the variable arsenic consumption was performed. In spite of using arsenic-safe water, we observed arsenic consumption and release. Participants with skin lesions had more arsenic in urine than participants without skin lesions. Future risk for participants without skin lesions was twice due to less arsenic release in urine. For the first time, Bayesian simulation was used to assess noncancer risk on a cohort for a consecutive three-year study. A significant finding was the higher assessed noncancer risk of the participants without skin lesions than the participants with skin lesions.     

Effects of hydrophobic surfactant proteins on collapse of pulmonary surfactant monolayers

To determine if hydrophobic surfactant proteins affect the stability of pulmonary surfactant monolayers at an air/water interface, the studies reported here compared the kinetics of collapse for the complete set of lipids in calf surfactant with and without the proteins. Monomolecular films spread at the surface of captive bubbles were compressed at 37°C to surface pressures above 46 mN/m, at which collapse first occurred. The rate of area-compression required to maintain a constant surface pressure was measured to directly determine the rate of collapse. For films with and without the proteins, higher surface pressures initially produced faster collapse, but the rates then reached a maximum and decreased to values <0.04 min⁻¹ above 53 mN/m. The maximum rate for the lipids with the proteins (1.22 ± 0.28 min⁻¹) was almost twice the value for the lipids alone (0.71 ± 0.15 min⁻¹). Because small increments in surface pressure produced large shifts in the rate close to the fastest collapse, compressions at a series of constant speeds also established the threshold rate required to achieve high surface pressure as an indirect indication of the fastest collapse. Both samples produced a sharply defined threshold that occurred at slightly faster compression with the proteins present, supporting the conclusion of the direct measurements that the proteins produce a faster maximum rate of collapse. Our results indicate that at 47-53 mN/m, the hydrophobic surfactant proteins destabilize the compressed monolayers and tend to limit access to the higher surface pressures at which the lipid films become metastable.     

Differential recovery of membrane proteins after extraction by aqueous methanol and trifluoroethanol

Cell membrane proteome analysis is limited by inherent membrane hydrophobicity. Conventional membrane protein extraction techniques use detergents, chaotropes and organic acids that require sample clean-up or pH adjustment, and are associated with significant sample loss. We extracted membrane proteins from red blood cells (RBCs) using methanol (MeOH), trifluoroethanol (TFE) and urea, and identified membrane proteins using 2-D LC coupled with MALDI-TOF/TOF-MS. We show that organic solvents MeOH- and TFE-based methods have membrane protein analysis efficiencies comparable to urea, and are complementary for the recovery of both hydrophilic and hydrophobic peptides. The mean grand average of hydropathicity (GRAVY) value of identified peptides from the TFE-based method (-0.107) was significantly higher than that of the MeOH-based method (-0.465) (p<0.001). Sequential and adjunctive use of the organic solvents MeOH and TFE increases the number of proteins identified, and the confidence of their identification. We show that this strategy is effective for shotgun membrane proteome analysis.