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Complex Patterns of Gene Duplication in the APETALA3 and PISTILLATA Lineages of the Ranunculaceae
It has been proposed that the diversification of the MADS-box gene family of transcription factors has played a major role in the radiation of land plants. This suggestion is based on the critical roles that these genes play in plant development and the apparent coincidence of key duplication events with major radiations, such as the establishment of the B and C lineages concurrent with the evolution of the seed plants. On a more recent scale, it is also possible that subsequent duplication events have contributed to later morphological diversifications. In order to investigate this possibility, we are studying the evolution of homologs of the petal and stamen identity genes APETALA3 (AP3) and PISTILLATA (PI) in the Ranunculaceae. In this family, the AP3 and PI lineages have undergone many duplication events at every phylogenetic level. Early duplications gave rise to three paralogous AP3 lineages, which are found throughout the family. In contrast, numerous duplications have occurred relatively recently in the PI lineage. We outline a hypothesis that these duplications have played a role in the evolution of the unique types of petaloid organs in the Ranunculaceae and present preliminary expression data supporting such a scenario.Organismic and Evolutionary Biolog
Renewal reward perspective on linear switching diffusion systems
In many biological systems, the movement of individual agents is commonly
characterized as having multiple qualitatively distinct behaviors that arise
from various biophysical states. This is true for vesicles in intracellular
transport, micro-organisms like bacteria, or animals moving within and
responding to their environment. For example, in cells the movement of
vesicles, organelles and other cargo are affected by their binding to and
unbinding from cytoskeletal filaments such as microtubules through molecular
motor proteins. A typical goal of theoretical or numerical analysis of models
of such systems is to investigate the effective transport properties and their
dependence on model parameters. While the effective velocity of particles
undergoing switching diffusion is often easily characterized in terms of the
long-time fraction of time that particles spend in each state, the calculation
of the effective diffusivity is more complicated because it cannot be expressed
simply in terms of a statistical average of the particle transport state at one
moment of time. However, it is common that these systems are regenerative, in
the sense that they can be decomposed into independent cycles marked by returns
to a base state. Using decompositions of this kind, we calculate effective
transport properties by computing the moments of the dynamics within each cycle
and then applying renewal-reward theory. This method provides a useful
alternative large-time analysis to direct homogenization for linear
advection-reaction-diffusion partial differential equation models. Moreover, it
applies to a general class of semi-Markov processes and certain stochastic
differential equations that arise in models of intracellular transport.
Applications of the proposed framework are illustrated for case studies such as
mRNA transport in developing oocytes and processive cargo movement by teams of
motor proteins.Comment: 35 pages, 6 figure
Oxygen reduction reaction at La<sub>x</sub>Ca<sub>1-x</sub>MnO<sub>3</sub> nanostructures: interplay between A-site segregation and B-site valency
The mean activity of surface Mn sites at LaxCa1-xMnO3 nanostructures towards the oxygen reduction reaction (ORR) in alkaline solution is assessed as a function of the oxide composition. Highly active oxide nano-particles were synthesised by an ionic liquid-based route, yielding phase-pure nanoparticles, across the entire range of compositions, with sizes between 20 and 35 nm. The bulk vs. surface composition and structure are investigated by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and X-ray absorption near edge spectroscopy (XANES). These techniques allow quantification of not only changes in the mean oxidation state of Mn as a function of x, but also the extent of A-site surface segregation. Both trends manifest themselves in the electrochemical responses associated with surface Mn sites in 0.1 M KOH solution. The characteristic redox signatures of Mn sites are used to estimate their effective surface number density. This parameter allows comparing, for the first time, the mean electrocatalytic activity of surface Mn sites as a function of the LaxCa1-xMnO3 composition. The ensemble of experimental data provides a consistent picture in which increasing electron density at the Mn sites leads to an increase in the ORR activity. We also demonstrate that normalisation of electrochemical activity by mass or specific surface area may result in inaccurate structure–activity correlations
Digitalizing nursing in the Bavarian Swabia region of Germany: presentation of the joint project CARE REGIO
KELVIN: A Software Package for Rigorous Measurement of Statistical Evidence in Human Genetics
This paper describes the software package KELVIN, which supports the PPL (posterior probability of linkage) framework for the measurement of statistical evidence in human (or more generally, diploid) genetic studies. In terms of scope, KELVIN supports two-point (trait-marker or marker-marker) and multipoint linkage analysis, based on either sex-averaged or sex-specific genetic maps, with an option to allow for imprinting; trait-marker linkage disequilibrium (LD), or association analysis, in case-control data, trio data, and/or multiplex family data, with options for joint linkage and trait-marker LD or conditional LD given linkage; dichotomous trait, quantitative trait and quantitative trait threshold models; and certain types of gene-gene interactions and covariate effects. Features and data (pedigree) structures can be freely mixed and matched within analyses. The statistical framework is specifically tailored to accumulate evidence in a mathematically rigorous way across multiple data sets or data subsets while allowing for multiple sources of heterogeneity, and KELVIN itself utilizes sophisticated software engineering to provide a powerful and robust platform for studying the genetics of complex disorders
Geometric morphometrics reveals shifts in flower shape symmetry and size following gene knockdown of CYCLOIDEA and ANTHOCYANIDIN SYNTHASE
Peer reviewe
Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA
Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis
An advanced bioinformatics approach for analyzing RNA-seq data reveals sigma H-dependent regulation of competence genes in Listeria monocytogenes
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