Electrochemical Carbon Dioxide Capture and Concentration.

Electrochemical carbon capture and concentration (eCCC) offers a promising alternative to thermochemical processes as it circumvents the limitations of temperature-driven capture and release. This review will discuss a wide range of eCCC approaches, starting with the first examples reported in the 1960s and 1970s, then transitioning into more recent approaches and future outlooks. For each approach, the achievements in the field, current challenges, and opportunities for improvement will be described. This review is a comprehensive survey of the eCCC field and evaluates the chemical, theoretical, and electrochemical engineering aspects of different methods to aid in the development of modern economical eCCC technologies that can be utilized in large-scale carbon capture and sequestration (CCS) processes.

CO2 Activation with Manganese Tricarbonyl Complexes through an H-Atom Responsive Benzimidazole Ligand.

Herein, we report the synthesis and characterization of two manganese tricarbonyl complexes, MnI (HL)(CO)3 Br (1 a-Br) and MnI (MeL)(CO)3 Br (1 b-Br) (where HL=2-(2'-pyridyl)benzimidazole; MeL=1-methyl-2-(2'-pyridy)benzimidazole) and assayed their electrocatalytic properties for CO2 reduction. A redox-active pyridine benzimidazole ancillary ligand in complex 1 a-Br displayed unique hydrogen atom transfer ability to facilitate electrocatalytic CO2 conversion at a markedly lower reduction potential than that observed for 1 b-Br. Notably, a one-electron reduction of 1 a-Br yields a structurally characterized H-bonded binuclear Mn(I) adduct (2 a') rather than the typically observed Mn(0)-Mn(0) dimer, suggesting a novel method for CO2 activation. Combining advanced electrochemical, spectroscopic, and single crystal X-ray diffraction techniques, we demonstrate the use of an H-atom responsive ligand may reveal an alternative, low-energy pathway for CO2 activation by an earth-abundant metal complex catalyst.

Molecular design of redox carriers for electrochemical CO2 capture and concentration.

Developing improved methods for CO2 capture and concentration (CCC) is essential to mitigating the impact of our current emissions and can lead to carbon net negative technologies. Electrochemical approaches for CCC can achieve much higher theoretical efficiencies compared to the thermal methods that have been more commonly pursued. The use of redox carriers, or molecular species that can bind and release CO2 depending on their oxidation state, is an increasingly popular approach as carrier properties can be tailored for different applications. The key requirements for stable and efficient redox carriers are discussed in the context of chemical scaling relationships and operational conditions. Computational and experimental approaches towards developing redox carriers with optimal properties are also described.

Whole Exome Sequencing in 16p13.11 Microdeletion Patients Reveals New Variants Through Deductive and Systems Medicine Approaches.

The 16p13.11 microdeletion, whose prevalence in the general population is about 0.04%, is known in literature as a predisposition factor to neurodevelopmental disorders, being found in about 0.13% of patients with schizophrenia, in 0.5-0.6% of patient with epilepsy, cognitive impairment, autism spectrum disorder (ASD) and aggressiveness. The goal of this study was to identify a specific gene set pattern unique for the affected patients in comparison with other familial components. Due to the incomplete penetrance of this copy number variant (CNV), we studied by whole exome sequencing (WES), with particular regard of 850 SFARI genes, three families with an affected member carrier of inherited 16p13.11 and 16p13.11p12.3 microdeletion and one family with an affected member with a de novo 16p13.11 microdeletion. By combining a deductive approach together with personalized network models, we identified gene signatures potentially capable of explaining the clinical phenotype. Candidate variants in genes of interest were identified as possibly involved in determining the neurological phenotype of the four patients, such as compound heterozygosity in CECR2, variants in MTOR and RICTOR genes, compound heterozygous single nucleotide variants in the LRRK2 gene. Moreover, genes present in the microdeletion region were partially present as central nodes, with a focus on NDE1. No additional pathogenetic or uncertain CNVs were found in all four patients. No significant variants were detected in genes included in the microdeletion in patients 1, 2 and 3, excluding the finding of unmasked recessive variants. In conclusion, WES is a fundamental tool in the genetic investigation of patients having a predisposing variant, which is not sufficient to define the clinical phenotype. Moreover, the analysis of WES data using Systems medicine tools, such as personalized network models, led to the prioritization of genes on a high throughput scale and to discover variants in genes that were not prioritized at first.

Gene Set Enrichment Analysis of Interaction Networks Weighted by Node Centrality.

Gene set enrichment analysis (GSEA) is a powerful tool to associate a disease phenotype to a group of genes/proteins. GSEA attributes a specific weight to each gene/protein in the input list that depends on a metric of choice, which is usually represented by quantitative expression data. However, expression data are not always available. Here, GSEA based on betweenness centrality of a protein-protein interaction (PPI) network is described and applied to two cases, where an expression metric is missing. First, personalized PPI networks were generated from genes displaying alterations (assessed by array comparative genomic hybridization and whole exome sequencing) in four probands bearing a 16p13.11 microdeletion in common and several other point variants. Patients showed disease phenotypes linked to neurodevelopment. All networks were assembled around a cluster of first interactors of altered genes with high betweenness centrality. All four clusters included genes known to be involved in neurodevelopmental disorders with different centrality. Moreover, the GSEA results pointed out to the evidence of "cell cycle" among enriched pathways. Second, a large interaction network obtained by merging proteomics studies on three neurodegenerative disorders was analyzed from the topological point of view. We observed that most central proteins are often linked to Parkinson's disease. The selection of these proteins improved the specificity of GSEA, with "Metabolism of amino acids and derivatives" and "Cellular response to stress or external stimuli" as top-ranked enriched pathways. In conclusion, betweenness centrality revealed to be a suitable metric for GSEA. Thus, centrality-based GSEA represents an opportunity for precision medicine and network medicine.