Direct Determination of High-Affinity Binding Constants by Continuous Injection Isothermal Titration Calorimetry.

Isothermal titration calorimetry (ITC) is a method to determine thermodynamic values (Δ, Δ, and Δ) for ligand-receptor binding in biological and abiological systems. It is challenging to directly determine subnanomolar dissociation constants using a standard incremental injection approach ITC (IIA-ITC) measurement. We recently demonstrated a continuous injection approach ITC (CIA-ITC) [ 2021, 125, 8075-8087]enables the estimation of thermodynamic parameters in situ.

Using dynamic data reconciliation to improve the performance of PID feedback control systems with Gaussian/non-Gaussian distributed disturbance and measurement noise.

For a stochastic PID feedback control system, the uncertainty of the working environment often leads to the unsatisfied performance of the system, which does not meet the profit requirements. The working environment generally includes external disturbance and measurement noise, etc. Gaussian distributed measurement noise and disturbances are widely considered while non-Gaussian distributed measurement noise and disturbances are rarely considered.

Establishing an inexpensive, space efficient colony of MEAM1 utilizing modelling and feedback control principles.

A stable, synchronized colony of whitefly ( MEAM1 Gennadius) was established in a single ~30 cu.ft. reach-in incubator and supported on cabbage host plants which were grown in a 2 × 2' mesh cage without the need for a greenhouse or dedicated growth rooms.

Designing social distancing policies for the COVID-19 pandemic: A probabilistic model predictive control approach.

The effective control of the COVID-19 pandemic is one the most challenging issues of recent years. The design of optimal control policies is challenging due to a variety of social, political, economical and epidemiological factors. Here, based on epidemiological data reported in recent studies for the Italian region of Lombardy, which experienced one of the largest and most devastating outbreaks in Europe during the first wave of the pandemic, we present a probabilistic model predictive control (PMPC) approach for the systematic study of what if scenarios of social distancing in a retrospective analysis for the first wave of the pandemic in Lombardy.

Continuous Injection Isothermal Titration Calorimetry for In Situ Evaluation of Thermodynamic Binding Properties of Ligand-Receptor Binding Models.

We utilize a continuous injection approach (CIA) rather than the traditional incremental injection approach (IIA) to deliver ligand (or receptor) to the calorimeter cell to evaluate thermodynamic binding parameters for three common ligand-receptor binding models-single independent, competitive, and two independent binding sites-using isothermal titration calorimetry (ITC). A general mathematical expression for the binding isotherm for any binding stoichiometry under continuous delivery of ligand (or receptor) resulting in an analytical solution for the thermodynamic binding parameters is presented. The advantages of CIA include reduction in experimental time, estimation of thermodynamic binding parameter values, and automation of the experiment since thermodynamic parameters are estimated in situ.

Dynamic data reconciliation to improve the result of controller performance assessment based on GMVC.

Due to the complexity of the industrial working environment, controllers are susceptible to various disturbance signals, resulting in unsatisfactory control performance. Therefore, it is especially important to assess the controller performance. Considering the harmful effect of measurement noise on controller performance assessment (CPA) based on generalized minimum variance control (GMVC), this paper proposes dynamic data reconciliation (DDR) to improve the accuracy of CPA based on GMVC.

Colocalization and Sequential Enzyme Activity in Aqueous Biphasic Systems: Experiments and Modeling.

Subcellular compartmentalization of biomolecules and their reactions is common in biology and provides a general strategy for improving and/or controlling kinetics in metabolic pathways that contain multiple sequential enzymes. Enzymes can be colocalized in multiprotein complexes, on scaffolds or inside subcellular organelles. Liquid organelles formed by intracellular phase coexistence could provide an additional means of sequential enzyme colocalization.

Coupled enzyme reactions performed in heterogeneous reaction media: experiments and modeling for glucose oxidase and horseradish peroxidase in a PEG/citrate aqueous two-phase system.

The intracellular environment in which biological reactions occur is crowded with macromolecules and subdivided into microenvironments that differ in both physical properties and chemical composition. The work described here combines experimental and computational model systems to help understand the consequences of this heterogeneous reaction media on the outcome of coupled enzyme reactions. Our experimental model system for solution heterogeneity is a biphasic polyethylene glycol (PEG)/sodium citrate aqueous mixture that provides coexisting PEG-rich and citrate-rich phases.

Development of a stochastic model for the efficacy of NRTIs using known mechanisms of action.

We analyze the mechanisms by which nucleoside-analogue reverse transcriptase inhibitors, the most common class of drugs used in the treatment of HIV-1, exert their antiviral effects. We then seek to identify ways in which those known mechanisms can be employed to generate mathematical models for drug efficacy in terms of measurable physical values. We demonstrate that the probability a NRTI instead of a natural nucleotide is included can be expressed in terms of intracellular drug concentrations, natural nucleotide concentrations, and relevant rate constants derived from reverse transcriptase's mechanism of nucleotide addition.

A computational procedure for optimal engineering interventions using kinetic models of metabolism.

The identification of optimal intervention strategies is a key step in designing microbial strains with enhanced capabilities. In this paper, we propose a general computational procedure to determine which genes/enzymes should be eliminated, repressed or overexpressed to maximize the flux through a product of interest for general kinetic models. The procedure relies on the generalized linearization of a kinetic description of the investigated metabolic system and the iterative application of mixed-integer linear programming (MILP) optimization to hierarchically identify all engineering interventions allowing for reaction eliminations and/or enzyme level modulations.