Stochastic modelling of wall stresses in abdominal aortic aneurysms treated by a gene therapy

A stochastic mechanical model using the membrane theory was used to simulate the in vivo mechanical behaviour of abdominal aortic aneurysms (AAAs) in order to compute the wall stresses after stabilisation by gene therapy. For that, both length and diameter of AAAs rats were measured during their expansion. Four groups of animals, control and treated by an endovascular gene therapy during 3 or 28 days were included. The mechanical problem was solved analytically using the geometric parameters and assuming the shape of aneurysms by a ‘parabolic–exponential curve’. When compared to controls, stress variations in the wall of AAAs for treated arteries during 28 days decreased, while they were nearly constant at day 3. The measured geometric parameters of AAAs were then investigated using probability density functions (pdf) attributed to every random variable. Different trials were useful to define a reliable confidence region in which the probability to have a realisation is equal to 99%. The results demonstrated that the error in the estimation of the stresses can be greater than 28% when parameters uncertainties are not considered in the modelling. The relevance of the proposed approach for the study of AAA growth may be studied further and extended to other treatments aimed at stabilisation AAAs, using biotherapies and pharmacological approaches.     

Functional and structural roles of the N-terminal extension in Methanosarcina acetivorans protoglobin

Functional and structural properties of protoglobin from Methanosarcina acetivorans, whose Cys(101)E20 residue was mutated to Ser (MaPgb*), and of mutants missing either the first 20 N-terminal amino acids (MaPgb*-ΔN20 mutant), or the first 33 N-terminal amino acids [N-terminal loop of 20 amino acids and a 13-residue Z-helix, preceding the globin fold A-helix; (MaPgb*-ΔN20Z mutant)] have been investigated. In keeping with the MaPgb*-ΔN20 mutant crystal structure, here reported at 2.0 Å resolution, which shows an increased exposure of the haem propionates to the solvent, the analysis of ligand binding kinetics highlights high accessibility of ligands to the haem pocket in ferric MaPgb*-ΔN20. CO binding to ferrous MaPgb*-ΔN20 displays a marked biphasic behavior, with a fast binding process close to that observed in MaPgb* and a slow carbonylation process, characterized by a rate-limiting step. Conversely, removal of the first 33 residues induces a substantial perturbation of the overall MaPgb* structure, with loss of α-helical content and potential partial collapse of the protein chain. As such, ligand binding kinetics are characterized by very slow rates that are independent of ligand concentration, this being indicative of a high energy barrier for ligand access to the haem, possibly due to localized misfolding. This article is part of a Special Issue entitled: Oxygen Binding and Sensing Proteins.     

Elevated cell-free fetal DNA contributes to placental inflammation and antiangiogenesis via AIM2 and IFI16 during pre-eclampsia

Accumulated evidence has shown that pre-eclampsia (PE) is related to both maternal and utero-placental antiangiogenesis and inflammation. Remarkably, an elevated cell-free fetal DNA (cffDNA) level has been found in maternal circulation; however, it remains unclear whether this DNA can induce activation of cytosolic DNA sensor signaling pathways and lead to the development of PE. In this study, we found that trophoblast cells constitutively expressed the cytosolic DNA sensors, absent in melanoma 2 (AIM2) and interferon-inducible protein 16 (IFI16). The cffDNA and pro-inflammatory and antiangiogenic factors were present at higher concentrations in PE compared with the control group and correlated with the severity of PE. DNA stimulation significantly increased the AIM2 and IFI16 levels, consistent with the elevated AIM2 and IFI16 expression in women with PE, and elicited increased production of AIM2-mediated interleukin IL-8 (IL-8), IL-6 and CC chemokine ligand 2 (CCL2) and IFI16-mediated sEndoglin, sFlt-1 and CXCL10. Furthermore, enhancement of the inflammatory response was found to be induced by DNA exposure, but DNA exposure did not induce PE-like symptoms in pregnant mice. It is possible that elevated cffDNA could reflect the degree of placental damage and trigger cytosolic DNA sensor activation, which disrupts the immunity balance and, consequently, contributes to inflammatory and antiangiogenic responses. In conclusion, the results of this study suggest that circulating cffDNA levels are increased in preeclamptic women and act through AIM2 and IFI16 activation to promote the production of pro-inflammatory and antiangiogenic factors, which correlate with the severity of the disease, and may offer insights into the etiology and pathogenesis of PE.     

Reception and learning of electric fields in bees

Honeybees, like other insects, accumulate electric charge in flight, and when their body parts are moved or rubbed together. We report that bees emit constant and modulated electric fields when flying, landing, walking and during the waggle dance. The electric fields emitted by dancing bees consist of low- and high-frequency components. Both components induce passive antennal movements in stationary bees according to Coulomb''s law. Bees learn both the constant and the modulated electric field components in the context of appetitive proboscis extension response conditioning. Using this paradigm, we identify mechanoreceptors in both joints of the antennae as sensors. Other mechanoreceptors on the bee body are potentially involved but are less sensitive. Using laser vibrometry, we show that the electrically charged flagellum is moved by constant and modulated electric fields and more strongly so if sound and electric fields interact. Recordings from axons of the Johnston organ document its sensitivity to electric field stimuli. Our analyses identify electric fields emanating from the surface charge of bees as stimuli for mechanoreceptors, and as biologically relevant stimuli, which may play a role in social communication.     

Investment risk in bioenergy crops

Perennial, cellulosic bioenergy crops represent a risky investment. The potential for adoption of these crops depends not only on mean net returns, but also on the associated probability distributions and on the risk preferences of farmers. Using 6‐year observed crop yield data from highly productive and marginally productive sites in the southern Great Lakes region and assuming risk neutrality, we calculate expected breakeven biomass yields and prices compared to corn (Zea mays L.) as a benchmark. Next we develop Monte Carlo budget simulations based on stochastic crop prices and yields. The crop yield simulations decompose yield risk into three components: crop establishment survival, time to maturity, and mature yield variability. Results reveal that corn with harvest of grain and 38% of stover (as cellulosic bioenergy feedstock) is both the most profitable and the least risky investment option. It dominates all perennial systems considered across a wide range of farmer risk preferences. Although not currently attractive for profit‐oriented farmers who are risk neutral or risk averse, perennial bioenergy crops have a higher potential to successfully compete with corn under marginal crop production conditions.     

Long‐term persistence,density dependence and effects of climate change on rosyside dace (Cyprinidae)

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Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor – a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon‐specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness.     

A population‐based temporal logic gate for timing and recording chemical events

Engineered bacterial sensors have potential applications in human health monitoring, environmental chemical detection, and materials biosynthesis. While such bacterial devices have long been engineered to differentiate between combinations of inputs, their potential to process signal timing and duration has been overlooked. In this work, we present a two‐input temporal logic gate that can sense and record the order of the inputs, the timing between inputs, and the duration of input pulses. Our temporal logic gate design relies on unidirectional DNA recombination mediated by bacteriophage integrases to detect and encode sequences of input events. For an E. coli strain engineered to contain our temporal logic gate, we compare predictions of Markov model simulations with laboratory measurements of final population distributions for both step and pulse inputs. Although single cells were engineered to have digital outputs, stochastic noise created heterogeneous single‐cell responses that translated into analog population responses. Furthermore, when single‐cell genetic states were aggregated into population‐level distributions, these distributions contained unique information not encoded in individual cells. Thus, final differentiated sub‐populations could be used to deduce order, timing, and duration of transient chemical events.     

Perspectives of surface plasmon resonance sensors for optimized biogas methanation

Biogas production is becoming significantly viable as an energy source for replacing fossil‐based fuels. The further development of the biogas production process could lead to significant improvements in its potential. Wastewater treatment currently accounts for 3% of the electrical energy load in developed countries, while it could be developed to provide a source of nitrogen and phosphorus, in addition to energy. The improvement of anaerobic digestion (AD) detection technologies is the cornerstone to reach higher methane productivities and develop fully automatized processes to decrease operational costs. New sensors are requested to automatically obtain a better interpretation of the complex and dynamical internal reactor environment. This will require detailed systematic detection in order to realize a near‐optimal production process. In this review, optical fiber‐based sensors will be discussed to assess their potential for use in AD. There is currently a disparity between the complexity of AD, and online detection. By improving the durability, sensitivity, and cost of dissolved H₂ (as well as H₂S, acetic acid, ammonia, and methane) sensor technology, further understanding of the AD process may allow the prevention of process failure. The emergence of surface plasmon resonance (SPR) sensing with optical fibers coupled with the H₂‐sensitive metal palladium, allows detection of dissolved hydrogen in liquid. By implementing these SPR sensors into AD, improvements to the biogas production process, even at small scales, may be achieved by guiding the process in the optimum direction, avoiding the collapse of the biological process. This review intends to assess the feasibility of online, cost‐effective, rapid, and efficient detection of dissolved H₂, as well as briefly assessing H₂S, acetic acid, ammonia, and methane in AD by SPR.