A predictive computational model of the kinetic mechanism of stimulus-induced transducer methylation and feedback regulation through CheY in archaeal phototaxis and chemotaxis

BACKGROUND: Photo- and chemotaxis of the archaeon Halobacterium salinarum is based on the control of flagellar motor switching through stimulus-specific methyl-accepting transducer proteins that relay the sensory input signal to a two-component system. Certain members of the transducer family function as receptor proteins by directly sensing specific chemical or physical stimuli. Others interact with specific receptor proteins like the phototaxis photoreceptors sensory rhodopsin I and II, or require specific binding proteins as for example some chemotaxis transducers. Receptor activation by light or a change in receptor occupancy by chemical stimuli results in reversible methylation of glutamate residues of the transducer proteins. Both, methylation and demethylation reactions are involved in sensory adaptation and are modulated by the response regulator CheY. RESULTS: By mathematical modeling we infer the kinetic mechanisms of stimulus-induced transducer methylation and adaptation. The model (deterministic and in the form of ordinary differential equations) correctly predicts experimentally observed transducer demethylation (as detected by released methanol) in response to attractant and repellent stimuli of wildtype cells, a cheY deletion mutant, and a mutant in which the stimulated transducer species is methylation-deficient. CONCLUSIONS: We provide a kinetic model for signal processing in photo- and chemotaxis in the archaeon H. salinarum suggesting an essential role of receptor cooperativity, antagonistic reversible methylation, and a CheY-dependent feedback on transducer demethylation

ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative–quantitative modeling

Summary: Often competing hypotheses for biochemical networks exist in the form of different mathematical models with unknown parameters. Considering available experimental data, it is then desired to reject model hypotheses that are inconsistent with the data, or to estimate the unknown parameters. However, these tasks are complicated because experimental data are typically sparse, uncertain, and are frequently only available in form of qualitative if–then observations. ADMIT (Analysis, Design and Model Invalidation Toolbox) is a MatLabTM-based tool for guaranteed model invalidation, state and parameter estimation. The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior. A constraint satisfaction problem is automatically generated and algorithms are implemented for solving the desired estimation, invalidation or analysis tasks. The implemented methods built on convex relaxation and optimization and therefore provide guaranteed estimation results and certificates for invalidity

ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative–quantitative modeling

Summary: Often competing hypotheses for biochemical networks exist in the form of different mathematical models with unknown parameters. Considering available experimental data, it is then desired to reject model hypotheses that are inconsistent with the data, or to estimate the unknown parameters. However, these tasks are complicated because experimental data are typically sparse, uncertain, and are frequently only available in form of qualitative if–then observations. ADMIT (Analysis, Design and Model Invalidation Toolbox) is a MatLabTM-based tool for guaranteed model invalidation, state and parameter estimation. The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior. A constraint satisfaction problem is automatically generated and algorithms are implemented for solving the desired estimation, invalidation or analysis tasks. The implemented methods built on convex relaxation and optimization and therefore provide guaranteed estimation results and certificates for invalidity

Model Predictive Control Tailored to Epidemic Models

We propose a model predictive control (MPC) approach for minimising the social distancing and quarantine measures during a pandemic while maintaining a hard infection cap. To this end, we study the admissible and the maximal robust positively invariant set (MRPI) of the standard SEIR compartmental model with control inputs. Exploiting the fact that in the MRPI all restrictions can be lifted without violating the infection cap, we choose a suitable subset of the MRPI to define terminal constraints in our MPC routine and show that the number of infected people decays exponentially within this set. Furthermore, under mild assumptions we prove existence of a uniform bound on the time required to reach this terminal region (without violating the infection cap) starting in the admissible set. The findings are substantiated based on a numerical case study.Comment: 14 pages, 3 figure

Novel Dual Walling Cob Building: Dynamic Thermal Performance

This paper emphasizes the experimental and numerical study of new cob mixes used for insulation and load bearing wall elements. The experimental study provides complete datasets of thermal properties of the new walling materials, using cob with density ranging from 1107 kg/m3 to 1583 kg/m3 for structural walls and less than 700 kg m−3 for insulation walls. Various mixes of French soils and fibres (reed, wheat straw, hemp shiv, hemp straw, and flax straw) with different water contents are studied. The lowest average thermal conductivity is obtained for the structural cob mix prepared of 5% wheat straw and 31% of water content. The insulation mix, prepared with 25% reed and 31% water content, has the lowest thermal conductivity. Investigation of diffusivity, density, and heat capacity shows that, when thermal conductivity is lower than 0.4 W m−1 K−1, the decrease in cob density leads to better insulation values and higher heat capacity. Little variation is noticed regarding the density and heat capacity for cob mixes with thermal conductivity higher than 0.4 W m−1 K−1. Furthermore, the non-uniformity of local thermal conductivity and heat losses through the samples is due mainly to the non-uniform distribution of fibres inside the mixes inducing an increase in heat loss up to 50% for structural walls and 25% for insulation walls. Cob thermal properties are used in a comparative simulation case study of a typical house under French and UK climatic conditions. The energy performance of the conventional building is compared to a dual walled cob building, showing remarkable reduction in energy consumption as the cob walls, whilst maintaining comfortable indoor conditions without additional heating.</jats:p

Simulating future salinity dynamics in a coastal marshland under different climate scenarios

Salinization is a well‐known problem in agricultural areas worldwide. In the last 20–30 yr, rising salinity in the upper, unconfined aquifer has been observed in the Freepsumer Meer, a grassland near the German North Sea coast. For investigating long‐term development of salinity and water balance during 1961–2099, the one‐dimensional Soil–Water–Atmosphere–Plant (SWAP) model was set up and calibrated for a soil column in the area. The model setup involves a deep aquifer as the source of salt through upward seepage. In the vertical salt transport equation, dispersion and advection are included. Six different regional outputs of statistical downscaling methods were used as climate scenarios. These comprise different rates of increasing surface temperature and different trends in seasonal rainfall. The simulation results exhibit opposing salinity trends for topsoil and deeper layers. Although projections of some scenarios entail decreasing salinities near the surface, most of them project a rise in subsoil salinity, with the strongest trends of up to +0.9 mg cm−3 100 yr−1 at −65 cm. The results suggest that topsoil salinity trends in the study area are affected by the magnitude of winter rainfall trends, whereas high subsoil salinities correspond to low winter rainfall and high summer temperature. How these projected trends affect the vegetation and thereby future land use will depend on the future management of groundwater levels in the area

Case report: mRNA-1273 COVID-19 vaccine-associated myopericarditis: Successful treatment and re-exposure with colchicine

IntroductionVaccine-induced myocarditis is a rare complication of messenger RNA (mRNA) COVID-19 vaccines.Case presentationWe report a case of acute myopericarditis in a recipient of allogeneic hematopoietic cells following the first dose of the mRNA-1273 vaccine and the successful administration of a second and third dose while on prophylactic treatment with colchicine to successfully complete the vaccination.ConclusionTreatment and prevention of mRNA-vaccine-induced myopericarditis represent a clinical challenge. The use of colchicine is feasible and safe to potentially reduce the risk of this rare but severe complication and allows re-exposure to an mRNA vaccine