What Determines the Lewis Acidity of a Bismuthane? Towards Bi-Based FLPs.

Aiming at intramolecular frustrated Lewis pairs (FLPs) based on soft Lewis acidic bismuth centers, a phosphine function was combined with a dichloridobismuthane unit on a phenylene backbone utilizing a scrambling approach. The reaction between two equivalents of BiCl3 and (o-(Ph2P)C6H4)3Bi yielded (o-(Ph2P)C6H4)BiCl2(THF), the structure of which indicated Bi…P interactions and thus a pronounced Lewis acidity at the bismuth center that was confirmed by the Gutmann-Beckett method. However, the system turned out to be insufficient to be utilized for FLP reactivity. Hence, the chloride ligands were exchanged by iodide and C2F5 substituents, respectively. Despite a lower electronegativity the iodide compound exhibits a shorter Bi…P contact, while the C2F5 substituents led to a further decrease of the Lewis acidity, despite their high group electronegativity. DFT calculations rationalized this by a quenching of the Lewis acidity inherent to the σ*(Bi-C) orbital by negative hyperconjugation from occupied p-orbitals at the F atoms. Furthermore, it turned out that the strength of the covalent Bi-X σ-bond is a more important factor than the charge at Bi in determining the energetic accessibility and thus Lewis acidity of the antibonding σ*(Bi-C) orbital.

Clonal haematopoiesis of indeterminate potential-related mutations and outcome in dilated and ischaemic cardiomyopathy.

AIMS: Clonal haematopoiesis of indeterminate potential (CHIP)-associated mutation is a risk factor for the development of ischaemic cardiomyopathy (ICM), but its association with non-ischaemic dilated cardiomyopathy (DCM) remains unclear. We aimed to determine the prevalence of CHIP in patients with DCM and define its risk for disease progression. METHODS AND RESULTS: Next-generation sequencing targeting 54 common CHIP-associated genes was performed in 48 ICM and 52 DCM patients. The patients were monitored for a median of 3.1 years, and a COX proportional hazards model was used to examine the association between CHIP and adverse clinical outcome with regard to all-cause death or all-cause hospitalization. Overall, the prevalence of CHIP mutations was 19% and 13% in DCM and ICM, respectively. Seventeen per cent of ICM patients over 75 years were CHIP carriers. In DCM cohort, mutation event had already been observed in the patients who were under the age of 45 (13%). Among 54 genes analysed, DNMT3A had the highest mutation frequency, followed by TET2 and CUX1. Kaplan-Meier curve over a median of 3.1 year tracking period showed a trend towards poor clinical outcome in the DCM patients who carried DNMT3A or TET2 mutation; however, such association was not statistically significant. CONCLUSIONS: The prevalence of CHIP is detected at a young age in DCM, and accumulation of mutational frequency in DCM patients is independent of age. However, a larger patient cohort is required to validate the association between CHIP and clinical progression in the DCM patients.

72-h kinetics of high-sensitive troponin T and inflammatory markers after marathon.

INTRODUCTION: Strenuous exercise induces significant increases in cardiac biomarkers. However, it is still unclear whether this is caused by cardiomyocyte necrosis or secondary mechanisms such as ischemia, cardiac energy deficiency, increased inflammation, or renal dysfunction. METHODS: Therefore, we investigated cardiac biomarkers (high-sensitive cardiac troponin T (hs-cTnT), N-terminal pro-brain natriuretic peptide (NT-proBNP), heart-type fatty acid-binding protein (h-FABP)), inflammation markers (high-sensitive C-reactive protein (hs-CRP), interleukin-6 (IL-6), interleukin-10, tumor necrosis factor-α), and renal function (cystatin C) in 102 healthy men age 42 ± 9 yr before and 0, 24, and 72 h after a marathon. RESULTS: Kinetics of hs-cTnT revealed a peak immediately after the race (V3) that decreased rapidly to pretest values within 72 h (V5) (median (interquartile range) = 31.07 (19.25-46.86) ng·L(-1) at V3 and 3.61 (3.20-6.70) ng·L(-1) at V5, P < 0.001). NT-proBNP and h-FABP kinetics showed a similar pattern (NT-proBNP = 92.6 (56.9-149.7) ng·L(-1) at V3 and 34.9 (21.7-54.5) ng·L(-1) at V5; h-FABP = 44.99 (32.19-64.42) µg·L(-1) at V3 and 7.66 (5.64-10.60) µg·L(-1) at V5; always P < 0.001). Proinflammatory markers, such as IL-6 and hs-CRP, and renal dysfunction were significantly augmented immediately after the race (before the race compared with maximum after the race: IL-6 = 15.5-fold, hs-CRP = 28-fold, cystatin C = 1.22-fold, all P < 0.001). These increases were not related to the increase of hs-cTnT. Similarly, training history, finishing time, and exercise intensity were not associated with changes of hs-cTnT. CONCLUSIONS: Cardiac biomarkers were increased immediately after a marathon race. Interestingly, values returned to normal levels within 72 h. These kinetics with a sharp peak indicate that cardiac necrosis during marathon running seems very unlikely but may be explained by altered myocyte metabolism.