Theoretical Insight into Coordination Chemistry of Am(VI) and Am(V) with Phenanthroline Ligand: Implications for High Oxidation State Based Minor Actinide Separation.

Despite continuing and burgeoning interest in americium (Am) coordination chemistry in recent years, investigations of the electronic structures and bonding chemistry of high oxidation state americium complexes and their implications for minor actinide separation remain relatively less explored to date. Here, we used density functional theory (DFT) to create high oxidation states of americium but experimentally feasible models of Am(V) and Am(VI) complexes of phenanthroline ligand (DAPhen) as [AmO2(L)]1+/2+ and [AmO3(L)]1+ (L = 2,9-bis[(N,N-dimethyl)-carbonyl]-1,10-phenanthroline (oxo-DAPhen, LO) and 2,9-bis[(N,N-dimethyl)-thio-carbonyl]-1,10-phenanthroline (thio-DAPhen, LS)), meanwhile comparing these with [UO2(L)]2+. On the basis of the calculations, the Am(V) and Am(VI) oxidation state are thermodynamically feasible and can be stabilized by DAPhen ligands. From a comparative study, the strength of thio-DAPhen in the separation of high oxidation state Am emerges better than does oxo-DAPhen, which relates to the nature, energy level, and spatial arrangement of their frontier orbitals. This study provides fundamental knowledge toward understanding the transuranic separations processes, which has implications in designing new, more selective extraction processes for the separation of Am from curium (Cm) as well as lanthanide.

Probing the Electronic Structure and Chemical Bonding of Uranium Nitride Complexes of NU-XO (X = C, N, O).

Uranium(III) compounds are very reactive and exhibit a broad range of chemical-bonding tendencies owing to the spatially diffused valence orbitals of uranium. A systematic study on the geometries, electronic structures, and chemical bonding of NU-XO (X = C, N, O) is performed using relativistic quantum chemistry approaches. The NU-CO and NU-NO complexes have an end-on structure, that is, (NU) (η1-CO) and (NU) (η1-NO), whereas NU-OO adopts a side-on ((NU) (η2-O2)) structure. The electronic structure analysis shows that UN exhibits efficient activation reactivity to molecules, especially to NO and O2, because of the significant U 7s/5f → XO 2π* electron transfer. Thus, the oxidation state of U is +V with the dianion ligand NO2- and O22- in NU-NO and NU-OO, respectively. Instead, U retains its usual +III oxidation state in NU-CO with a neutral CO ligand. The significant stability of NU-XO (X = C, N, O) is determined by the covalent U-X bonding which contains both X → U σ-, π-donation from the X lone pair and U 5f → XO 2π* back-donation contributions. The significant back-donation to the antibonding X-O 2π* orbital results in the obvious weakening of the X-O bonding.

Establishment of a graphene oxide-assisted nucleic acid chromatography strip detection technology for Prorocentrum minimum.

In recent decades, the harmful algal blooms (HABs) caused by Prorocentrum minimum have caused serious environmental damage and economic losses. The detection of P. minimum plays an important role in warning the outbreak of P. minimum-forming HABs. By utilizing the powerful absorption of graphene oxide (GO) on short-stranded DNA, a GO-assisted nucleic acid chromatography strip (GO-NACS) was proposed here to achieve a highly sensitive, specific, intuitive, and convenient detection of P. minimum. In particular, this study used our previously reported conventional-NACS (C-NACS) as a control to evaluate the improvement of detection performance with the use of GO. The performance of GO-NACS was evaluated from the perspectives of specificity, sensitivity, stability, and practicality. The specificity test demonstrated that it had a high degree of specificity and did not display cross-reacting with non-target algal species. The sensitivity test with the genomic DNA indicated that it had a detection limit of 1.30 × 10-3 ng µL-1, representing a 10-fold higher sensitivity than C-NACS and a 100-fold higher sensitivity than agarose gel electrophoresis (AGE). The interference test with non-target algal species demonstrated that it had a good detection stability, and the interfering algal species had no obvious effect on the detection of P. minimum. The practicality test with simulated natural water samples showed that the cellular detection limit of GO-NACS was 6.8 cells mL-1, which was 10-fold and 100-fold lower than that of C-NACS and AGE, respectively. In conclusion, the established GO-NACS may offer a novel alternative technique for the detection of P. minimum while guaranteeing specificity and enhancing sensitivity without requiring extensive apparatus.

Remodeling of active endothelial enhancers is associated with aberrant gene-regulatory networks in pulmonary arterial hypertension.

Environmental and epigenetic factors often play an important role in polygenic disorders. However, how such factors affect disease-specific tissues at the molecular level remains to be understood. Here, we address this in pulmonary arterial hypertension (PAH). We obtain pulmonary arterial endothelial cells (PAECs) from lungs of patients and controls (n = 19), and perform chromatin, transcriptomic and interaction profiling. Overall, we observe extensive remodeling at active enhancers in PAH PAECs and identify hundreds of differentially active TFs, yet find very little transcriptomic changes in steady-state. We devise a disease-specific enhancer-gene regulatory network and predict that primed enhancers in PAH PAECs are activated by the differentially active TFs, resulting in an aberrant response to endothelial signals, which could lead to disturbed angiogenesis and endothelial-to-mesenchymal-transition. We validate these predictions for a selection of target genes in PAECs stimulated with TGF-ß, VEGF or serotonin. Our study highlights the role of chromatin state and enhancers in disease-relevant cell types of PAH.

A study of feature extraction for Alzheimer's disease based on resting-state fMRI.

The Alzheimer's Disease (AD) has become a major threat of human health with its incidence rate ascending year by year. Early diagnosis of AD is very important for AD patients to keep life quality. The resting-state fMRI (rs-fMRI) which precisely reflects the brain changes on the resting state of individuals provides a quantitative approach, which has been introduced to distinguish AD patients from normal population. In this study, we proposed a method to find the most distinctive features identifying AD patients from rs-fMRI images. The ALFF and ReHo parameters based on pre-processed rs-fMRI data were extracted, and some key parameters of the brain functional network based on graph theory were calculated. Then we tested the recognition performance of different classifiers, and the best classification algorithm, that is, Support Vector Machine (SVM) with linear-kernel are selected. Finally through a recursive feature selection procedure, we got the most distinctive feature set. Additionally, this study also implies that there may be several changes in some particular ROIs of the brain during the AD development.