RuII(α-diimine) or RuIII(α-diimine·–)? Structural, spectroscopic, and theoretical evidence for the stabilization of a prominent metal-to-Ligand charge- transfer excited-state configuration in the ground state

The new compounds [Ru(R-DAB)(acac)2] (R-DAB = 1,4-diorganyl- 1,4-diazabuta-1,3-diene; R = tert-butyl, 4-methoxyphenyl, 2,6-dimethylphenyl; acac– = 2,4-pentanedionate) exhibit intrachelate ring bond lengths 1.297ligand to produce UV/Vis/NIR and electron paramagnetic resonance (EPR) spectroelectrochemically detectable RuIII species, whereas the reduction proceeds less reversibly and yields predominantly (R-DAB)-ligand-based spin for the 4-methoxyphenyl derivative, measured at low temperature. The results are discussed with respect to metal-to-ligand chargetransfer (MLCT) excited states of conventional (α-diimine)- ruthenium(II) complexes and in view of other (α-diimine)- metal complexes with ambiguous oxidation-state assignments.

Electrocatalytic reduction of carbon dioxide with a manganese(I)tricarbonyl complex containing a nonaromatic α‑diimine ligand

The 2e reduced anion [Mn(CO)3(iPr-DAB)]− (DAB = 1,4- diazabuta-1,3-diene, iPr = isopropyl) was shown to convert in the presence of CO2 and a small amount of water to the unstable complex [Mn(CO)3(iPr-DAB)(η1-OCO2H)] (OCO2H− = unidentate bicarbonate) that was further reductively transformed to give a stable catalytic intermediate denoted as X2, showing νs(OCO) 1672 and 1646 (sh) cm−1. The subsequent cathodic shift by ca. 650 mV in comparison to the single 2e cathodic wave of the parent [Mn(CO)3(iPr-DAB)Br] triggers the reduction of intermediate X2 and catalytic activity converting CO2 to CO. Infrared spectroelectrochemistry has revealed that the high excess of CO generated at the cathode leads to the conversion of [Mn(CO)3(iPr-DAB)]− to inactive [Mn(CO)5]−. In contrast, the five-coordinate anion [Mn(CO)3(pTol-DAB)]−(pTol = 4-tolyl) is completely inert toward both CO2 and H2O (solvolysis). This detailed spectroelectrochemical study is a further contribution to the development of sustainable electro- and photoelectrocatalysts of CO2 reduction based on abundant first-row transition metals, in particular manganese.

Quantitative single-molecule localization microscopy combined with rule-based modeling reveals ligand-induced TNF-R1 reorganization toward higher-order oligomers

We report on the assembly of tumor necrosis factor receptor 1 (TNF-R1) prior to ligand activation and its ligand-induced reorganization at the cell membrane. We apply single-molecule localization microscopy to obtain quantitative information on receptor cluster sizes and copy numbers. Our data suggest a dimeric pre-assembly of TNF-R1, as well as receptor reorganization toward higher oligomeric states with stable populations comprising three to six TNF-R1. Our experimental results directly serve as input parameters for computational modeling of the ligand-receptor interaction. Simulations corroborate the experimental finding of higher-order oligomeric states. This work is a first demonstration how quantitative, super-resolution and advanced microscopy can be used for systems biology approaches at the single-molecule and single-cell level.

Zero-Dimensional Units of Ligand-Bridged Gallium-Sulfide Supertetrahedra

The synthesis and characterization of the first anions containing two gallium-sulfide supertetrahedra linked via an organic moiety are described.

Understanding the link between single cell and population scale responses of Escherichia coli in differing ligand gradients

We formulate an agent-based population model of Escherichia coli cells which incorporates a description of the chemotaxis signalling cascade at the single cell scale. The model is used to gain insight into the link between the signalling cascade dynamics and the overall population response to differing chemoattractant gradients. Firstly, we consider how the observed variation in total (phosphorylated and unphosphorylated) signalling protein concentration affects the ability of cells to accumulate in differing chemoattractant gradients. Results reveal that a variation in total cell protein concentration between cells may be a mechanism for the survival of cell colonies across a wide range of differing environments. We then study the response of cells in the presence of two different chemoattractants.In doing so we demonstrate that the population scale response depends not on the absolute concentration of each chemoattractant but on the sensitivity of the chemoreceptors to their respective concentrations. Our results show the clear link between single cell features and the overall environment in which cells reside.

Low rank representation on Riemannian manifold of symmetric positive definite matrices

Sparse coding aims to find a more compact representation based on a set of dictionary atoms. A well-known technique looking at 2D sparsity is the low rank representation (LRR). However, in many computer vision applications, data often originate from a manifold, which is equipped with some Riemannian geometry. In this case, the existing LRR becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to applications. In this paper, we generalize the LRR over the Euclidean space to the LRR model over a specific Rimannian manifold—the manifold of symmetric positive matrices (SPD). Experiments on several computer vision datasets showcase its noise robustness and superior performance on classification and segmentation compared with state-of-the-art approaches.

Synthesis and evaluation of a novel hydrophilic 6,6′-bis(1,2,4-triazin-3-yl)-2,2′-bipyridine ligand for separating actinide(III) from lanthanide(III)

We report the synthesis and evaluation of a novel hydrophilic 6,6′-bis(1,2,4-triazin-3-yl)-2,2′-bipyridine (BTBP) ligand containing carboxylate groups as a selective aqueous complexing agent for the minor actinides over lanthanides. The novel ligand is able to complex and separate Am(III) from Eu(III) in alkaline solutions selectively.

Retinoid-Related Receptor (ROR) alpha mRNA Expression Is Altered in the Brain of Male Mice Lacking All Ligand-Binding Thyroid Hormone Receptor (TR) Isoforms

In the vertebrate brain, the thalamus serves as a relay and integration station for diverse neuronal information en route from the periphery to the cortex. Deficiency of TH during development results in severe cerebral abnormalities similar to those seen in the mouse when the retinoic acid receptor (ROR)α gene is disrupted. To investigate the effect of the thyroid hormone recep-tors (TRs) on RORalpha gene expression, we used intact male mice, in which the genes encoding the α and beta TRs have been deleted. In situ hybridization for RORalpha mRNA revealed that this gene is expressed in specific areas of the brain including the thalamus, pons, cerebellum, cortex, and hippocampus. Our quantitative data showed differences in RORalpha mRNA expression in different subthalamic nuclei between wild-type and knock-out mice. For example, the centromedial nucleus of the thalamus, which plays a role in mediating nociceptive and visceral information from the brainstem to the basal ganglia and cortical regions, has less expression of RORalpha mRNA in the knockout mice (-37%) compared to the wild-type controls. Also, in the dorsal geniculate (+72%) and lateral posterior nuclei (+58%) we found more RORalpha mRNA in dKO as compared to dWT animals. Such differences in RORalpha mRNA expression may play a role in the behavioral alterations resulting from congenital hypothyroidism.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.