Vaccination, Immunity and Breakthrough: Quantitative Effects in Individual Immune Responses Illustrated by a Simple Kinetic Model

The personal risks of infection, as well as the conditions for achieving herd immunity, are strongly dependent on an individual’s response to the infective agents on the one hand, and the individual’s reactions to vaccination on the other hand. The main goal of this work is to illustrate the importance of quantitative individual effects for disease risk in a simple way. The applied model was able to illustrate the quantitative effects, in the cases of different individual reactions, after exposition to viruses or bacteria and vaccines. The model was based on simple kinetic equations for stimulation of antibody production using different concentrations of the infective agent, vaccine and antibodies. It gave a qualitative explanation for the individual differences in breakthrough risks and different requirements concerning a second, third or further vaccinations, reconsidering different efficiencies of the stimulation of an immune reaction.

Absorbed radiation and kinetic model in photocatalysis by TiO2

The current work studies a novel and affordable methodology to estimate and quantify the photon flux absorbed and the amount of light that leaves from an illuminated photocatalytic system with TiO2 suspended in water. To achieve it, a new parameter B F S λ w a t $BF{S}_{\lambda }^{wat}$ is defined and presented. It indicates, for every wavelength, the fraction of the incoming radiation which is not absorbed by the system. B F S λ w a t $BF{S}_{\lambda }^{wat}$ was estimated by means of actinometric experiments in a jacketed reactor and a model based on Beer–Lambert law. For wavelengths below 388 nm and TiO2 concentrations between 0.05 and 2 g L−1, experimental values of B F S λ w a t $BF{S}_{\lambda }^{wat}$ were between 0.77 and 0.27. In the second part of the work, a simple kinetic model, which breaks down the effect of incident radiation and kinetic constant, is developed. For this, the photon flux absorbed by TiO2, previously determined, was included in the model. This new model was tested in the photocatalytic degradation of 2,4-dichlorophenol under different TiO2 concentrations. The kinetic model fits satisfactorily the experimental values and a new kinetic constant kʹ ap [mol·L−1 Einstein−1] was obtained, which is independent of the amount of catalyst loaded to the system. This achievement may be very useful for an easy initial comparison, design or scaling up of different photocatalytic reactors with similar geometry.

A Multisubcellular Compartment Model of AMPA Receptor Trafficking for Neuromodulation of Hebbian Synaptic Plasticity

Neuromodulation can profoundly impact the gain and polarity of postsynaptic changes in Hebbian synaptic plasticity. An emerging pattern observed in multiple central synapses is a pull–push type of control in which activation of receptors coupled to the G-protein Gs promote long-term potentiation (LTP) at the expense of long-term depression (LTD), whereas receptors coupled to Gq promote LTD at the expense of LTP. Notably, coactivation of both Gs- and Gq-coupled receptors enhances the gain of both LTP and LTD. To account for these observations, we propose a simple kinetic model in which AMPA receptors (AMPARs) are trafficked between multiple subcompartments in and around the postsynaptic spine. In the model AMPARs in the postsynaptic density compartment (PSD) are the primary contributors to synaptic conductance. During LTP induction, AMPARs are trafficked to the PSD primarily from a relatively small perisynaptic (peri-PSD) compartment. Gs-coupled receptors promote LTP by replenishing peri-PSD through increased AMPAR exocytosis from a pool of endocytic AMPAR. During LTD induction AMPARs are trafficked in the reverse direction, from the PSD to the peri-PSD compartment, and Gq-coupled receptors promote LTD by clearing the peri-PSD compartment through increased AMPAR endocytosis. We claim that the model not only captures essential features of the pull–push neuromodulation of synaptic plasticity, but it is also consistent with other actions of neuromodulators observed in slice experiments and is compatible with the current understanding of AMPAR trafficking.

Standardized excitable elements for scalable engineering of far-from-equilibrium chemical networks

Engineered far-from-equilibrium synthetic chemical networks that pulse or switch states in response to environmental signals could precisely regulate the kinetics of chemical synthesis or self-assembly pathways. Currently, such networks must be extensively tuned to compensate for the different activities of and unintended reactions between different network chemical elements. Elements with standardized performance would allow rapid construction of networks with designed functions. Here we develop standardized excitable chemical elements, termed genelets, and use them to construct complex in vitro transcriptional networks. We develop a protocol for identifying >15 interchangeable genelet regulatory elements with uniform performance and minimal crosstalk. These elements can be combined to engineer feedforward and feedback modules whose dynamics are predicted by a simple kinetic model. We show modules can be rationally integrated and reorganized into networks that produce tunable temporal pulses and act as multi-state switchable memories. Standardized genelet elements, and the workflow to identify more, should make engineering complex far-from-equilibrium chemical dynamics routine.

Dynamics of photoconversion processes: the energetic cost of lifetime gain in photosynthetic and photovoltaic systems

The energy cost of lifetime gain in solar energy conversion systems is determined from a breadth of technologies. The cost of 87 meV per order of magnitude lifetime improvement is strikingly close to the 59 meV determined from a simple kinetic model.

Revisiting Trends in the Exchange Current for Hydrogen Evolution

Nørskov and collaborators proposed a simple kinetic model to explain the volcano relation for the hydrogen evolution reaction on transition metal surfaces in such that j_0= k_0 f(ΔG_H) where j_0...

Capping Mobility to Control COVID-19: A Collision-based Infectious Disease Transmission Model

We developed a mobility-informed disease-transmission model for COVID-19, inspired by collision theory in gas-phase chemistry. This simple kinetic model leads to a closed-form infectious population as a function of time and cumulative mobility. This model uses fatality data from Johns Hopkins to infer the infectious population in the past, and mobility data from Google, without social-distancing policy, geological or demographic inputs. It was found that the model appears to be valid for twenty hardest hit counties in the United States. Based on this model, the number of infected people grows (shrinks) exponentially once the relative mobility exceeds (falls below) a critical value (~30% for New York City and ~60% for all other counties, relative to a median mobility from January 3 to February 6, 2020). A simple mobility cap can be used by government at different levels to control COVID-19 transmission in reopening or imposing another shutdown.

Simple Assay, Kinetics, and Biochemical Trends for Soil Microbial Catalases

In this report, we expand upon the enzymology and biochemical ecology of soil catalases through development and application of a simple kinetic model and assay based upon volume displacement. Through this approach, we (A) directly relate apparent Michaelis-Menten terms to the catalase reaction mechanism, (B) obtain upper estimates of the intrinsic rate constants for the catalase community and moles of catalase per 16S rRNA gene copy number, (C) utilize catalase specific activities (SAs) to obtain biomass estimates of soil and permafrost communities (LOD, ~104 copy number gdw−1), and (D) relate kinetic trends to changes in bacterial community structure. This model represents a novel approach to the kinetic treatment of soil catalases, while simultaneously incorporating barometric adjustments to afford comparisons across field measurements. As per our model, and when compared to garden soils, biological soil crusts exhibited ~2-fold lower values for , ≥105-fold higher catalase moles per biomass (250-1200 zmol copy number−1), and ~104-fold higher SAs per biomass (74-230 fkat copy number−1). However, the highest SAs were obtained from permafrost and high-elevation soil communities (5900-6700 fkat copy number−1). In sum, these total trends suggest that microbial communities which experience higher degrees of native oxidative stress possess higher basal intracellular catalase concentrations and SAs per biomass, and that differing kinetic profiles across catalase communities are indicative of phylum and/or genus-level changes in community structure. For microbial ecology, therefore, these measures effectively serve as markers for microbial activity and abundance, and additionally provide insights into the community responses to exogenous stress.ImportanceThe efficient management of oxidative stresses arising from environmental pressures are central to the homeostasis of soil microbial communities. Among the enzymes that manage oxidative stress are catalases, which degrade hydrogen peroxide into oxygen gas and water. In this report, we detail the development and application of a simple kinetic model and assay to measure catalase reaction rates and estimate soil biomass. Our assay is based upon volume displacement, and is low-cost, field-amenable, and suitable for scientists and educators from all disciplines. Our results suggest that microbial communities that experience higher degrees of native oxidative stress possess higher basal intracellular catalase concentrations and specific activities when expressed per biomass. For microbial ecology, therefore, these measures serve as biochemical markers for microbial activity and abundance, and provide insights into the community responses to exogenous stress; thereby providing a novel means to study active microbial communities in soils and permafrost.