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The oxygenation of food-derived trimethylamine to its N-oxide is a representative reaction mediated by human flavin-containing monooxygenase 3 (FMO3). Impaired FMO3 enzymatic activity is associated with trimethylaminuria (accumulation of substrate), whereas trimethylamine N-oxide (metabolite) is associated with arteriosclerosis. We previously reported FMO3 single-nucleotide and/or haplotype variants with low FMO3 metabolic capacity using urinary phenotyping and the whole-genome sequencing of Japanese populations. Here, we further analyze Japanese volunteers with self-reported malodor and interrogate an updated Japanese database for novel FMO3 single-nucleotide and/or haplotype variants. After 3 years of follow up, seven probands were found to harbor the known impaired FMO3 variant p.(Gly191Cys) identified in the database or novel variants/haplotypes including p.(Met66Val), p.(Arg223Gln), p.(Glu158Lys;Glu308Gly;Arg492Trp), and p.(Glu158Lys;Glu308Gly;Pro496Ser). Nirmatrelvir SARS-CoV inhibitor The known severe mutation p.(Cys197Ter) (a TG deletion) and four variants including p.(Tyr269His) and p.(Pro496Ser) were first detected in the updated genome panel. Among previously unanalyzed FMO3 variants, the trimethylamine/benzydamine N-oxygenation activities of recombinant p.(Met66Val), p.(Arg223Gln), p.(Tyr269His), p.(Glu158Lys;Glu308Gly;Arg492Trp), and p.(Glu158Lys;Glu308Gly;Pro496Ser) FMO3 variant proteins were severely decreased (Vmax/Km less then 10% of wild-type). Although the present novel mutations or alleles were relatively rare, both in self-reported Japanese trimethylaminuria sufferers and in the genomic database panel, three common FMO3 missense or deletion variants severely impaired FMO3-mediated N-oxygenation of trimethylamine.

We used a dataset from a Japanese nationwide registry of patients with primary aldosteronism, to determine which of the parameters of hyperaldosteronism and blood pressure before or after treatments for primary aldosteronism (i.e., surgical adrenalectomy or a medication treatment) are important in terms of cardiovascular prognosis.

We assessed whether plasma aldosterone-to-renin ratio and pulse pressure levels before treatment and 6 months after treatment were associated with composite cardiovascular disease events during the 5-year follow-up period.

The cohort included 1987 patients (mean age was 53.2 years, 52.0% were female, 37.2% had undergone surgical treatment, and the remainder had been treated with mineralocorticoid receptor antagonists). In the Cox proportional hazard model, the covariate-adjusted hazard ratio (95% confidence interval) for the composite cardiovascular disease events risk for each one-standard-deviation increase in the aldosterone-to-renin ratio or pulse pressure before treatmen cardiovascular disease among patients with primary aldosteronism.

The coprescription of an angiotensin-converting enzyme inhibitor (ACEi) with clopidogrel reportedly increases bleeding risk. However, studies have not described such an increase in cases of dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI).

We analyzed electronic medical records of patients with discharge records of having undergone DAPT after PCI from a national health insurance claims database for January 1, 2006 to December 31, 2014. The date of PCI was the index date, and the primary outcome was major bleeding. The unit of analysis was one person-quarter. We compared patients who were prescribed with those not prescribed an ACEi in the cohort. A Poisson model with inverse probability of treatment weighting was fitted using generalized estimating equations to measure the risk of outcomes.

In total, 193,258 patients underwent DAPT after PCI; 46% had a coprescription of an ACEi. After screening, 170,775 patients (479,263 person-quarters) remained for analysis. The mean patient age was 65±13 years, and 73.43% were men. In total, 79,739 prescriptions of an ACEi were written 57%, 14.21%, 8.88%, 7.17%, and 4.68% were for captopril, ramipril, enalapril, perindopril, and imidapril, respectively. A concomitant prescription of an ACEi with clopidogrel was not associated with increased bleeding risk (adjusted rate ratio 1.08, 99% confidence interval 0.99-1.17).

The coadministration of an ACEi with clopidogrel after PCI is common. In this real-world cohort study, such coadministration was not associated with an increased risk of major bleeding in patients undergoing DAPT after PCI.

The coadministration of an ACEi with clopidogrel after PCI is common. In this real-world cohort study, such coadministration was not associated with an increased risk of major bleeding in patients undergoing DAPT after PCI.

Although plaque characterization by intravascular ultrasound (IVUS) is important for risk stratification, frame-by-frame analysis of a whole vascular segment is time-consuming. The aim was to develop IVUS-based algorithms for classifying attenuation and calcified plaques.

IVUS image sets of 598 coronary arteries from 598 patients were randomized into training and test sets with 51 ratio. Each IVUS frame at a 0.4-mm interval was circumferentially labeled as one of three classes attenuated plaque, calcified plaque, or plaque without attenuation or calcification. The model was trained on multi-class classification with 5-fold cross validation. By converting from Cartesian to polar coordinate images, the class corresponding to each array from 0 to 360° was plotted.

At the angle-level, Dice similarity coefficients for identifying calcification vs. attenuation vs. none by using ensemble model were 0.79, 0.74 and 0.99, respectively. Also, the maximal accuracy was 98% to classify those groups in the test set. At the frame-level, the model identified the presence of attenuation with 80% sensitivity, 96% specificity, and 93% overall accuracy, and the presence of calcium with 86% sensitivity, 97% specificity, and 96% overall accuracy. In the per-vessel analysis, the attenuation and calcification burden index closely correlated with human measurements (r=0.89 and r=0.95, respectively), as did the maximal attenuation and calcification burden index over 4mm (r=0.82 and r=0.91, respectively). The inference times were 0.05s per frame and 7.8s per vessel.

Our deep learning algorithms for plaque characterization may assist clinicians in recognizing high-risk coronary lesions.

Our deep learning algorithms for plaque characterization may assist clinicians in recognizing high-risk coronary lesions.