Nevin Manimala

Catheter Cardiovasc Interv. 2022 May 18. doi: 10.1002/ccd.30178. Online ahead of print.

ABSTRACT

BACKGROUND: The natural history of peridevice leak (PDL) following left atrial appendage occlusion (LAAO) is unknown. This study sought to investigate changes of PDL from 2 until 12 months after LAAO, using cardiac computed tomography (CT), and to assess the potential association between persistent PDL and clinical outcomes METHODS: Single-center observational study of Amplatzer LAAO implants between 2010 and 2017 (n = 206). Patients with 2 and 12 months cardiac CT were included in the study (n = 153). Images were blindly analyzed. PDL was characterized by frequency and size at the device disc, lobe, and left atrial appendage contrast patency. Patients were followed for the composite outcome of ischemic stroke, transient ischemic attack, systemic embolism, or all-cause death. Median follow up from LAAO was 3.1 (2.3-4.3) years.

RESULTS: Contrast patency was present in 101 (66%) and 72 (47%) (p < 0.001) at 2 and 12 months, respectively. PDL was identified at the disc in 103 (67%) patients at 2 months versus 93 (61%) at 12 months (p = 0.08), and at the lobe in 29 (19%) at both time points. PDL area at the disc did not change significantly over time, $∆$ area: -8.95 mm (95% confidence interval [CI]: -18.9; 1.01) p = 0.08. Permanent atrial fibrillation was independently associated with persistent PDL. Persistent versus no PDL was associated with a 62% worse clinical outcome, however not statistically significant, hazard ratio (HR): 1.62 (95% CI: 0.9-2.93), p = 0.11.

CONCLUSION: Persistent PDL was frequently observed following LAAO with Amplatzer devices. The PDL frequency and size appeared unchanged between 2 and 12 months. Persistent PDL was not significantly associated with worse clinical outcomes, yet this needs further delineation in future studies.

PMID:35582829 | DOI:10.1002/ccd.30178

Bioconjug Chem. 2022 May 18;33(5):948-955. doi: 10.1021/acs.bioconjchem.2c00159. Epub 2022 May 3.

ABSTRACT

d-Xylonic acid (XA), derived from pentose sugar xylose, is a multifunctional high-value chemical with a wide range of applications in the fields of medicines, food, agriculture and is a valuable chemical reagent for the synthesis of other useful commodity chemicals. In the bacterial system, xylose dehydrogenase (XDH) catalyzes the oxidation of d-xylose into d-xylonolactone, consuming NAD⁺ or NADP⁺ as a cofactor. The d-xylonolactone then undergoes auto-oxidation into d-xylonic acid. Herein, the XDH enzyme overexpressed in Escherichia coli is purified and immobilized on ferromagnetic nanoparticles, effectively converting xylose into xylonic acid. Parameters deciding the bioconversion were statistically optimized and obtained a maximum of 91% conversion rate. Kinetic parameters of immobilized xylose dehydrogenase showed a 2-fold increase in the maximum velocity of the reaction and catalytic efficiency compared to free enzyme. The operational stability test for the enzyme-nanoparticle conjugate retained 93% relative activity after 10 successive experiments, exhibiting the good recyclability of the biocatalyst for XA production.

PMID:35582818 | DOI:10.1021/acs.bioconjchem.2c00159

Stat Med. 2022 May 18. doi: 10.1002/sim.9440. Online ahead of print.

ABSTRACT

Correlated phenotypes often share common genetic determinants. Thus, a multi-trait analysis can potentially increase association power and help in understanding pleiotropic effect. When multiple traits are jointly measured over time, the correlation information between multivariate longitudinal responses can help to gain power in association analysis, and the longitudinal traits can provide insights on the dynamic gene effect over time. In this work, we propose a multivariate partially linear varying coefficients model to identify genetic variants with their effects potentially modified by environmental factors. We derive a testing framework to jointly test the association of genetic factors and illustrated with a bivariate phenotypic trait, while taking the time varying genetic effects into account. We extend the quadratic inference functions to deal with the longitudinal correlations and used penalized splines for the approximation of nonparametric coefficient functions. Theoretical results such as consistency and asymptotic normality of the estimates are established. The performance of the testing procedure is evaluated through Monte Carlo simulation studies. The utility of the method is demonstrated with a real data set from the Twin Study of Hormones and Behavior across the menstrual cycle project, in which single nucleotide polymorphisms associated with emotional eating behavior are identified.

PMID:35582816 | DOI:10.1002/sim.9440

Stat Med. 2022 May 18. doi: 10.1002/sim.9408. Online ahead of print.

ABSTRACT

To strengthen inferences meta-analyses are commonly used to summarize information from a set of independent studies. In some cases, though, the data may not satisfy the assumptions underlying the meta-analysis. Using three Bayesian methods that have a more general structure than the common meta-analytic ones, we can show the extent and nature of the pooling that is justified statistically. In this article, we reanalyze data from several reviews whose objective is to make inference about the COVID-19 asymptomatic infection rate. When it is unlikely that all of the true effect sizes come from a single source researchers should be cautious about pooling the data from all of the studies. Our findings and methodology are applicable to other COVID-19 outcome variables, and more generally.

PMID:35582808 | DOI:10.1002/sim.9408