The Synergistic Effect between Metal and Sulfur Vacancy to Boost CO₂ Reduction Efficiency: A Study on Descriptor Transferability and Activity Prediction

Both metal center active sites and vacancies can influence the catalytic activity of a catalyst. A quantitative model to describe the synergistic effect between the metal centers and vacancies is highly desired. Herein, we proposed a machine learning model to evaluate the synergistic index, PSyn, which is learned from the possible pathways for CH4 production from CO2 reduction reaction (CO2RR) on 26 metal-anchored MoS2 with and without sulfur vacancy. The data set consists of 1556 intermediate structures on metal-anchored MoS2, which are used for training. The 2028 structures from the literature, comprising both single active site and dual active sites, are used for external test. The XGBoost model with 3 features, including electronegativity, d-shell valence electrons of metal, and the distance between metal and vacancy, exhibited satisfactory prediction accuracy on limiting potential. Fe@Sv-MoS2 and Os@MoS2 are predicted to be promising CO2RR catalysts with high stability, low limiting potential, and high selectivity against hydrogen evolution reactions (HER). Based on some easily accessible descriptors, transferability can be achieved for both porous materials and 2D materials in predicting the energy change in the CO2RR and nitrogen reduction reaction (NRR). Such a predictive model can also be applied to predict the synergistic effect of the CO2RR in other oxygen and tungsten vacancy systems

Comprehensive Metabolic Profiling of Age-Related Mitochondrial Dysfunction in the High-Fat-Fed <i>ob</i>/<i>ob</i> Mouse Heart

The ectopic deposition of fat is thought to lead to lipotoxicity and has been associated with mitochondrial dysfunction and diabetic cardiomyopathy. We have measured mitochondrial respiratory capacities in the hearts of <i>ob</i>/<i>ob</i> and wild-type mice on either a regular chow (RCD) or high-fat (HFD) diet across four age groups to investigate the impact of diet and age on mitochondrial function alongside a comprehensive strategy for metabolic profiling of the tissue. Myocardial mitochondrial dysfunction was only evident in <i>ob</i>/<i>ob</i> mice on RCD at 14 months, but it was detectable at 3 months on the HFD. Liquid chromatography–mass spectrometry (LC–MS) was used to study the profiles of acylcarnitines and the accumulation of triglycerides, but neither class of lipid was associated with mitochondrial dysfunction. However, a targeted LC–MS/MS analysis of markers of oxidative stress demonstrated increases in GSSG/GSH and 8-oxoguanine, in addition to the accumulation of diacylglycerols, which are lipid species linked to lipotoxicity. Our results demonstrate that myocardial mitochondria in <i>ob</i>/<i>ob</i> mice on RCD maintained a similar respiratory capacity to that of wild type until a late stage in aging. However, on a HFD, unlike wild-type mice, <i>ob</i>/<i>ob</i> mice failed to increase mitochondrial respiration, which may be associated with a complex I defect following increased oxidative damage

Secondary metabolites isolated from <i>Penicillium christenseniae</i> SD.84 and their antimicrobial resistance effects

A pair of new quinolone alkaloid enantiomers, (Ra)-(-)-viridicatol (1) and (Sa)-(+)-viridicatol (4), and seven known compounds, namely, 2, 3 and 5–9, were isolated from Penicillium christenseniae SD.84. The structures of 1 and 4 were determined using NMR and HRESIMS data. Theoretical calculations through CD and ECD confirmed 1 and 4 as a pair of enantiomers. The MIC values of 4 against Staphylococcus aureus and methicillin-resistant S. aureus were 12.4 and 24.7 μM, respectively, compound 1 had no inhibitory activity. Antimicrobial assays of 2, 3, and 5–7 showed a moderate activity against S. aureus and methicillin-resistant S. aureus. This study demonstrated the remarkable potential of Penicillium sp. to produce new drug-resistant leading compounds, thereby advancing the mining for new sources of antimicrobial agents.</p

Additional file 1: of Mechanistic insights revealed by lipid profiling in monogenic insulin resistance syndromes

Supplementary Table S1 and Figures S1 and S2. (DOCX 102 kb