Search

Efficient trivalent actinides/lanthanides(Am3+/Ln3+) separation is one of the key components of advanced nuclear fuel cycle. Owing to their similar chemical behavior in condensed phase, it remains a challenge to adopt traditional liquid-liquid extraction techniques. The strategy of separating Am by oxidizing Am(Ⅲ) to its penta- and hexa-valent states has the benefit of high efficiency and large space of improvement and is attracting growing attention. The obstacle to adopt this strategy is the high oxidation potential, which impedes the efficient conversion of Am(Ⅲ) to Am(Ⅴ,Ⅵ) under mild conditions, and the low stability of high oxidation states of Am. This poses two questions to solve: (1) how to minimize the oxidation potential of Am? (2) how to stabilize Am in its high oxidation state? In this work, we surveyed the advances in the chemical and electrochemical oxidation of Am towards its separation from lanthanides. In its chemical oxidation, copper(Ⅲ) periodate was identified as a superior oxidants over bismuthate and persulfate in view of its high oxidizing power and high yield of Am(Ⅴ,Ⅵ). In its electrochemical oxidation, functionalization of electrode by appropriate ligands can significantly decrease the oxidation potential of Am and increase the overpotential of water, which circumvents the side reactions, e.g. oxidation of water. These results provide insights for the design and optimization of novel protocols for Am/Ln separation, and calls for improved understanding of the underlying mechanisms to stimulate extensive advances of efficient Am/Ln separation.

The deep subspace clustering algorithm utilizes deep neural networks to map the original input data to a latent space and employs the self-expression of the data as a measure of data similarity, effectively achieving clustering of high-dimensional data. However, such algorithms only focus on the self-expressive relationship in the latent space, resulting in their performance heavily relying on the quality of features extracted by the deep neural networks. Additionally, the regularization process ignores the connectivity within each subspace, affecting the performance of spectral clustering. To address these issues, a deep subspace clustering algorithm based on dual self-expression and the maximum entropy principle is proposed. This algorithm simultaneously learns the self-expressive relationships in both the latent space and the input space, guiding the deep neural network to obtain data representations suitable for subspace clustering. By maximizing the entropy of the similarity matrix, it ensures that elements within the same subspace are uniformly and densely distributed, thereby improving the performance of data clustering. Extensive experiments on five datasets verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Melatonin (MLT) protects cells by reducing reactive oxygen species (ROS) levels, which are key for inducing cellular autophagy. The aim of this study was to investigate the molecular mechanisms underlying MLT regulation of autophagy in granulosa cells (GCs) with BMPR‐1B homozygous (FecB BB) and wild type (FecB ++) mutations. GCs collected from small‐tailed Han sheep with different FecB genotypes were typed using a TaqMan probe assay, and autophagy levels were found to be significantly higher in GCs with FecB BB than the levels in those with FecB ++. Autophagy‐related 2 homolog B (ATG2B) was associated with cell autophagy and was highly expressed in GCs with the FecB BB genotype in small‐tailed Han sheep. Overexpression of ATG2B in the GCs of sheep with both FecB genotypes promoted GC autophagy, and the contrary was observed after the inhibition of ATG2B expression. Subsequently, treatment of GCs with different genotypes of FecB and MLT revealed a significant decrease in cellular autophagy and an increase in ATG2B expression. Addition of MLT to GCs with inhibited ATG2B expression revealed that MLT could protect GCs by decreasing ROS levels, especially in GCs with FecB ++ genotype. In conclusion, this study determined that autophagy levels were significantly higher in sheep GCs with FecB BB genotype than the levels in those with FecB ++ genotype, which may have contributed to the difference in lambing numbers between the two FecB genotypes. Autophagy was regulated by ATG2B and was able to protect GCs by reducing the high levels of ROS produced following inhibition of ATG2B through the addition of MLT in vitro. [ABSTRACT FROM AUTHOR]

A novel series of 1-substituted phenazines 4a-4l were designed and synthesized via Palladium-catalyzed reactions from 1-phenazine trifluoromethanesulfonate. These phenazines showed antichlamydial activity with IC50 values from 1 to 10 μM. Among them, compounds 4c and 4i exhibited the best antichlamydial activity with IC50 values from 2.06 to 2.74 μM without apparent cytotoxicity to host cells. [ABSTRACT FROM AUTHOR]

We report the discovery of superconductivity on the border of antiferromagnetic order in a quasi-one-dimensional material RbMn6Bi5 via measurements of resistivity and magnetic susceptibility under high pressures. Its phase diagram of temperature versus pressure resembles those of many magnetism-mediated superconducting systems. With increasing pressure, its antiferromagnetic ordering transition with T N = 83 K at ambient pressure is first enhanced moderately and then suppressed completely at a critical pressure of P c ≈ 13 GPa, around which bulk superconductivity emerges and exhibits a dome-like T c(P) with a maximal T c onset ≈ 9.5 K at about 15 GPa. In addition, the superconducting state around P c is characterized by a large upper critical field μ 0 H c2(0) exceeding the Pauli paramagnetic limit, implying a possible unconventional paring mechanism. The present study, together with our recent work on KMn6Bi5 (the maximum T c onset ≈ 9.3 K), makes A Mn6Bi5 (A = alkali metal) a new family of Mn-based superconductors with relatively high T c. [ABSTRACT FROM AUTHOR]