Exponential signaling gain at the receptor level enhances signal-to-noise ratio in bacterial chemotaxis

Peer reviewedPublisher PD

Information integration and decision making in flowering time control

In order to successfully reproduce, plants must sense changes in their environment and flower at the correct time. Many plants utilize day length and vernalization, a mechanism for verifying that winter has occurred, to determine when to flower. Our study used available temperature and day length data from different climates to provide a general understanding how this information processing of environmental signals could have evolved in plants. For climates where temperature fluctuation correlations decayed exponentially, a simple stochastic model characterizing vernalization was able to reconstruct the switch-like behavior of the core flowering regulatory genes. For these and other climates, artificial neural networks were used to predict flowering gene expression patterns. For temperate plants, long-term cold temperature and short-term day length measurements were sufficient to produce robust flowering time decisions from the neural networks. Additionally, evolutionary simulations on neural networks confirmed that the combined signal of temperature and day length achieved the highest fitness relative to neural networks with access to only one of those inputs. We suggest that winter temperature memory is a well-adapted strategy for plants' detection of seasonal changes, and absolute day length is useful for the subsequent triggering of flowering

Identifying barriers to vaccination intention at walk-in vaccination facilities in deprived neighbourhoods:A cross-sectional survey

Objectives: Low COVID-19 vaccination adherence in deprived neighbourhoods is problematic since the prevalence of chronic diseases associated with mortality rates due to COVID-19 is higher in these populations. The aim of this study is to provide an insight about beliefs and considerations relating to vaccination intention among inhabitants of deprived neighbourhoods in the Netherlands. Design: Cross-sectional survey. Setting: Easily accessible vaccination facilities at markets in deprived neighbourhoods in the Netherlands. Participants: Participants were recruited at three vaccination facilities that were set up at markets in deprived neighbourhoods in Rotterdam. A total of 124 surveys were retained for analysis. Main outcome measure: Intention to get vaccinated against COVID-19. Results: The survey was filled out by 124 respondents; 62 % had - prior to visiting the easily accessible locations - intended to get a COVID-19 vaccine and 38 % were hesitant (22.3 % had doubts and 15.7 % did not plan to get vaccinated). Many people mentioned the convenience of an easily accessible location nearby. At the bivariate level, the influence of information from the family was associated with vaccination intention (p &lt; 0.01). In a logistic regression model, both fear of vaccination and fear of side-effects were significantly associated with vaccination intention (ORs 0.56 (CI 0.35–0.89) and 0.47 (CI 0.30–0.73)). Conclusion: The accessibility of a vaccination facility, family influence and fear are relevant factors for the intention to get vaccinated against COVID-19 in people living in deprived neighbourhoods. Interventions should address these factors in order to increase vaccination uptake.</p

Systematic evaluation of agarose- and agar-based bioinks for extrusion-based bioprinting of enzymatically active hydrogels

Extrusion-based 3D bioprinting enables the production of customized hydrogel structures that can be employed in flow reactors when printing with enzyme-containing inks. The present study compares inks based on either low-melt agarose or agar at different concentrations (3–6%) and loaded with the thermostable enzyme esterase 2 from the thermophilic organism Alicyclobacillus acidocaldarius (AaEst2) with regard to their suitability for the fabrication of such enzymatically active hydrogels. A customized printer setup including a heatable nozzle and a cooled substrate was established to allow for clean and reproducible prints. The inks and printed hydrogel samples were characterized using rheological measurements and compression tests. All inks were found to be sufficiently printable to create lattices without overhangs, but printing quality was strongly enhanced at 4.5% polymer or more. The produced hydrogels were characterized regarding mechanical strength and diffusibility. For both properties, a strong correlation with polymer concentration was observed with highly concentrated hydrogels being more stable and less diffusible. Agar hydrogels were found to be more stable and show higher diffusion rates than comparable agarose hydrogels. Enzyme leaching was identified as a major drawback of agar hydrogels, while hardly any leaching from agarose hydrogels was detected. The poor ability of agar hydrogels to permanently immobilize enzymes indicates their limited suitability for their employment in perfused biocatalytic reactors. Batch-based activity assays showed that the enzymatic activity of agar hydrogels was roughly twice as high as the activity of agarose hydrogels which was mostly attributed to the increased amount of enzyme leaching. Agarose bioinks with at least 4.5% polymer were identified as the most suitable of the investigated inks for the printing of biocatalytic reactors with AaEst2. Drawbacks of these inks are limited mechanical and thermal stability, not allowing the operation of a reactor at the optimum temperature of AaEst2 which is above the melting point of the employed low-melt agarose

Correlation analysis of intracellular and secreted cytokines via the generalized integrated mean fluorescence intensity

The immune response in humans is usually assessed using immunogenicity assays to provide biomarkers as correlates of protection (CoP). Flow cytometry is the assay of choice to measure intracellular cytokine staining (ICS) of cell-mediated immune (CMI) biomarkers. For CMI analysis, the integrated mean fluorescence intensity (iMFI) was introduced as a metric to represent the total functional CMI response as a CoP. iMFI is computed by multiplying the relative frequency (percent positive) of cells expressing a particular cytokine with the MFI of that population, and correlates better with protection in challenge models than either the percentage or the MFI of the cytokine-positive population. While determination of the iMFI as a CoP can readily be accomplished in animal models that allow challenge/protection experiments, this is not feasible in humans for ethical reasons. As a first step toward extending the iMFI concept to humans, we investigated the correlation of the iMFI derived from a human innate immune response ICS assay with functional cytokine release into the culture supeRNAtant, as innate cytokines need to be released to have a functional impact. Next, we developed a quantitatively more correlative mathematical approach for calculating the functional response of cytokine-producing cells by incorporating the assignment of different weights to the magnitude (frequency of cytokine-positive cells) and the quality (the MFI) of the observed innate immune response. We refer to this model as generalized iMFI. © 2010 Interantional Society for Advancement of Cytometry

The Clustering of X-ray Luminous Quasars

The clustering of active galactic nuclei (AGN) sheds light on their typical large (Mpc-scale) environments, which can constrain the growth and evolution of supermassive black holes. Here we measure the clustering of luminous X-ray-selected AGN in the Stripe 82X and XMM-XXL-North surveys around the peak epoch of black hole growth, in order to investigate the dependence of luminosity on large-scale AGN environment. We compute the auto-correlation function of AGN in two luminosity bins, $10^{43}\leq L_X<10^{44.5}$ erg s$^{-1}$ at $z\sim 0.8$ and $L_X\geq 10^{44.5}$ erg s$^{-1}$ at $z\sim 1.8$, and calculate the AGN bias taking into account the redshift distribution of the sources using three different methods. Our results show that while the less luminous sample has an inferred typical halo mass that is smaller than for the more luminous AGN, the host halo mass may be less dependent on luminosity than suggested in previous work. Focusing on the luminous sample, we calculate a typical host halo mass of $\sim 10^{13}$ M$_{\odot}~h^{-1}$, which is similar to previous measurements of moderate-luminosity X-ray AGN and significantly larger than the values found for optical quasars of similar luminosities and redshifts. We suggest that the clustering differences between different AGN selection techniques are dominated by selection biases, and not due to a dependence on AGN luminosity. We discuss the limitations of inferring AGN triggering mechanisms from halo masses derived by large-scale bias.Comment: Accepted for publication in Ap

Energetic charged particle fluxes relevant to Ganymede's polar region

The JEDI instrument made measurements of energetic charged particles near Ganymede during a close encounter with that moon. Here we find ion flux levels are similar close to Ganymede itself but outside its magnetosphere and on near wake and open field lines. But energetic electron flux levels are more than a factor of 2 lower on polar and near-wake field lines than on nearby Jovian field lines at all energies reported here. Flux levels are relevant to the weathering of the surface, particularly processes that affect the distribution of ice, since surface brightness has been linked to the open-closed field line boundary. For this reason, we estimate the sputtering rates expected in the polar regions due to energetic heavy ions. Other rates, such as those related to radiolysis by plasma and particles that can reach the surface, need to be added to complete the picture of charged particle weathering