Tracking metabolites at single-cell resolution reveals metabolic dynamics during plant mitosis.

Analyzing only one cell allows the changes and characteristics of intracellular metabolites during the chromosome segregation process to be precisely captured and mitotic sub-phases to be dissected at the metabolite level.

Random forest and live single-cell metabolomics reveal metabolic profiles of human macrophages upon polarization.

Human macrophages are innate immune cells with diverse, functionally distinct phenotypes, namely, pro-inflammatory M1 and anti-inflammatory M2 macrophages. Both are involved in multiple physiological and pathological processes, including would healing, infection, and cancer. However, the metabolic differences between these phenotypes are largely unexplored at single-cell resolution. To address this knowledge gap, an untargeted live single-cell mass spectrometry-based metabolomic profiling coupled with a machine-learning data analysis approach was developed to investigate the metabolic profile of each phenotype at the single-cell level. Results show that M1 and M2 macrophages have distinct metabolic profiles, with differential levels of fatty acyls, glycerophospholipids, and sterol lipids, which are important components of plasma membrane and involved in multiple biological processes. Furthermore, we could discern several putatively annotated molecules that contribute to inflammatory response of macrophages. The combination of random forest and live single-cell metabolomics provided an in-depth profile of the metabolome of primary human M1 and M2 macrophages at the single-cell level for the first time, which will pave the way for future studies targeting the differentiation of other immune cells.

Echocardiographic predictors of presence of cardiac amyloidosis in aortic stenosis.

AIMS: Aortic stenosis (AS) and cardiac amyloidosis (CA) frequently coexist but the diagnosis of CA in AS patients remains a diagnostic challenge. We aim to evaluate the echocardiographic parameters that may aid in the detection of the presence of CA in AS patients. METHOD AND RESULTS: We performed a systematic literature search of electronic databases for peer-reviewed articles from inception until 10 January 2022. Of the 1449 patients included, 160 patients had both AS-CA whereas the remaining 1289 patients had AS-only. The result of our meta-analyses showed that interventricular septal thickness [standardized mean difference (SMD): 0.74, 95% CI: 0.36-1.12, P = 0.0001), relative wall thickness (SMD: 0.74, 95% CI: 0.17-1.30, P < 0.0001), posterior wall thickness (SMD: 0.74, 95% CI 0.51 to 0.97, P = 0.0011), LV mass index (SMD: 1.62, 95% CI: 0.63-2.62, P = 0.0014), E/A ratio (SMD: 4.18, 95% CI: 1.91-6.46, P = 0.0003), and LA dimension (SMD: 0.73, 95% CI: 0.43-1.02, P < 0.0001)] were found to be significantly higher in patients with AS-CA as compared with AS-only patients. In contrast, myocardial contraction fraction (SMD: -2.88, 95% CI: -5.70 to -0.06, P = 0.045), average mitral annular S' (SMD: -1.14, 95% CI: -1.86 to -0.43, P = 0.0017), tricuspid annular plane systolic excursion (SMD: -0.36, 95% CI: -0.62 to -0.09, P = 0.0081), and tricuspid annular S' (SMD: -0.77, 95% CI: -1.13 to -0.42, P < 0.0001) were found to be significantly lower in AS-CA patients. CONCLUSION: Parameters based on echocardiography showed great promise in detecting CA in patients with AS. Further studies should explore the optimal cut-offs for these echocardiographic variables for better diagnostic accuracy.