Nevin Manimala

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

Proc Biol Sci. 2022 May 25;289(1975):20212535. doi: 10.1098/rspb.2021.2535. Epub 2022 May 18.

ABSTRACT

A clade’s evolutionary history is shaped, in part, by geographical range expansion, sweepstakes dispersal and local extinction. A rigorous understanding of historical biogeography may therefore yield insights into macroevolutionary dynamics such as adaptive radiation. Modern historical biogeographic analyses typically fit statistical models to molecular phylogenies, but it remains unclear whether extant species provide sufficient signal or if well-sampled phylogenies of extinct and extant taxa are necessary to produce meaningful estimates of past ranges. We investigated the historical biogeography of Primates and their euarchontan relatives using a novel meta-analytical phylogeny of over 900 extant (n= 419) and extinct (n = 483) species spanning their entire evolutionary history. Ancestral range estimates for young nodes were largely congruent with those derived from molecular phylogeny. However, node age exerts a significant effect on ancestral range estimate congruence, and the probability of congruent inference dropped below 0.5 for nodes older than the late Eocene, corresponding to the origins of higher-level clades. Discordance was not observed in analyses of extinct taxa alone. Fossils are essential for robust ancestral range inference and biogeographic analyses of extant clades originating in the deep past should be viewed with scepticism without them.

PMID:35582793 | DOI:10.1098/rspb.2021.2535