Strong Base Anion Exchange Selectivity of Nine Perfluoroalkyl Chemicals Relevant to Drinking Water

Selectivity with respect to chloride (K PFAS ∕ C ) was determined for nine drinking water relevant perfluoroalkyl and polyfluoroalkyl substances (PFAS): perfluoro-2-propoxypropanoic acid (GenX), five perfluoroalkyl carboxylic acids (PFCAs), and three perfluoroalkyl sulfonic acids (PFSAs). Three single-use strong base anion exchange gel resins were investigated, targeting drinking water relevant equilibrium PFAS liquid concentrations (≤500 ng/L). Except for the longest carbon chain PFCA (perfluorodecanoic acid) and PFSA (perfluorooctanesulfonic acid) studied, PFAS followed traditional ion exchange theory (law of mass action), including increasing equilibrium PFAS liquid concentrations with increasing equilibrium chloride liquid concentrations. Overall, K PFAS ∕ C values were (i) similar among resins for a given PFAS, (ii) 1-5 orders of magnitude greater than the selectivity of inorganic anions (e.g., nitrate) previously studied, (iii) 2 orders of magnitude greater for the same carbon chain length PFSA versus PFCA, (iv) found to proportionally increase with carbon chain length for both PFSAs and PFCAs, and (v) similar for GenX and perfluorohexanoic acid (six-carbon PFCA). A multisolute competition experiment demonstrated binary isotherm-determined K PFAS ∕ C values could be applied to simulate a multisolute system, extending work previously done with only inorganic anions to PFAS. Ultimately, estimated K PFAS ∕ C values allow future extension and validation of an open-source anion exchange column model to PFAS.

Modeling of Reactive Sputtering-History and Development

This work critically reviews the evolution of reactive sputtering modeling that has taken place over the last 50 years. The review summarizes the main features of the deposition of simple metal compound films (nitrides, oxides, oxynitrides, carbides, etc.) that were experimentally found by different researchers. The above features include significant non-linearity and hysteresis. At the beginning of the 1970s, specific chemisorption models were proposed. These models were based on the assumption that a compound film was formed on the target due to chemisorption. Their development led to the appearance of the general isothermal chemisorption model, which was supplemented by the processes on the surfaces of the vacuum chamber wall and the substrate. The model has undergone numerous transformations for application to various problems of reactive sputtering. At the next step in the development of modeling, the reactive sputtering deposition (RSD) model was proposed, which was based on the implantation of reactive gas molecules into the target, bulk chemical reaction, chemisorption, and the "knock-on effect". Another direction of the modeling development is represented by the nonisothermal physicochemical model, in which the Langmuir isotherm and the law of mass action are used. Various modifications of this model allowed describing reactive sputtering processes in more complex cases when the sputtering unit included a hot target or a sandwich one.

The Alchemist, Metal-Divider and Transmuter Carl F. Wenzel and his 1776 Award from the Royal Danish Academy of Sciences through Professor C. G. Kratzenstein

C. F. Wenzel was a chemist and an alchemist. He had deep knowledge of acids, bases and salts, and he was credited with the first formulation of the Law of Mass Action. Yet he was also an alchemist, who on the eve of the Chemical Revolution published his beliefs in transmutation and in the division of metals into their constituents, for which he was rewarded with the gold medal of the Royal Danish Academy of the Sciences. His promoter, Professor C. G. Kratzenstein, was himself a believer in transmutation, even if he voiced some reservations.

Systems analysis shows that thermodynamic physiological and pharmacological fundamentals drive COVID-19 and response to treatment

Why a systems analysis view of this pandemic? The current pandemic has inflicted almost unimaginable grief, sorrow, loss, and terror at a global scale. One of the great ironies with the COVID‐19 pandemic, particularly early on, is counter intuitive. The speed at which specialized basic and clinical sciences described the details of the damage to humans in COVID‐19 disease has been impressive. Equally, the development of vaccines in an amazingly short time interval has been extraordinary. However, what has been less well understood has been the fundamental elements that underpin the progression of COVID‐19 in an individual and in populations. We have used systems analysis approaches with human physiology and pharmacology to explore the fundamental underpinnings of COVID‐19 disease. Pharmacology powerfully captures the thermodynamic characteristics of molecular binding with an exogenous entity such as a virus and its consequences on the living processes well described by human physiology. Thus, we have documented the passage of SARS‐CoV‐2 from infection of a single cell to species jump, to tropism, variant emergence and widespread population infection. During the course of this review, the recurrent observation was the efficiency and simplicity of one critical function of this virus. The lethality of SARS‐CoV‐2 is due primarily to its ability to possess and use a variable surface for binding to a specific human target with high affinity. This binding liberates Gibbs free energy (GFE) such that it satisfies the criteria for thermodynamic spontaneity. Its binding is the prelude to human host cellular entry and replication by the appropriation of host cell constituent molecules that have been produced with a prior energy investment by the host cell. It is also a binding that permits viral tropism to lead to high levels of distribution across populations with newly formed virions. This thermodynamic spontaneity is repeated endlessly as infection of a single host cell spreads to bystander cells, to tissues, to humans in close proximity and then to global populations. The principal antagonism of this process comes from SARS‐CoV‐2 itself, with its relentless changing of its viral surface configuration, associated with the inevitable emergence of variants better configured to resist immune sequestration and importantly with a greater affinity for the host target and higher infectivity. The great value of this physiological and pharmacological perspective is that it reveals the fundamental thermodynamic underpinnings of SARS‐CoV‐2 infection.

Free Drug Theory - No Longer Just a Hypothesis?

The Free Drug Hypothesis is a well-established concept within the scientific lexicon pervading many areas of Drug Discovery and Development, and yet it is poorly defined by virtue of many variations appearing in the literature. Clearly, unbound drug is in dynamic equilibrium with respect to absorption, distribution, metabolism, elimination, and indeed, interaction with the desired pharmacological target. Binding interactions be they specific (e.g. high affinity) or nonspecific (e.g. lower affinity/higher capacity) are governed by the same fundamental physicochemical tenets including Hill-Langmuir Isotherms, the Law of Mass Action and Drug Receptor Theory. With this in mind, it is time to recognise a more coherent version and consider it the Free Drug Theory and a hypothesis no longer. Today, we have the experimental and modelling capabilities, pharmacological knowledge, and an improved understanding of unbound drug distribution (e.g. Kp_uu) to raise the bar on our understanding and analysis of experimental data. The burden of proof should be to rule out mechanistic possibilities and/or experimental error before jumping to the conclusion that any observations contradict these fundamentals.

Finding Liebig's law of the minimum

Liebig's law of the minimum (LLM) is often used to interpret empirical biological growth data and model multiple substrates co-limited growth. However, its mechanistic foundation is rarely discussed, even though its validity has been questioned since its introduction in the 1820s. Here we first show that LLM is a crude approximation of the law of mass action, the state of art theory of biochemical reactions, and the LLM model is less accurate than two other approximations of the law of mass action: the synthesizing unit model and the additive model. We corroborate this conclusion using empirical data sets of algae and plants grown under two co-limiting substrates. Based on our analysis, we show that when growth is modeled directly as a function of substrate uptake, the LLM model improperly restricts the organism to be of fixed elemental stoichiometry, making it incapable of consistently resolving biological adaptation, ecological evolution, and community assembly. When growth is modeled as a function of the cellular nutrient quota, the LLM model may obtain good results at the risk of incorrect model parameters as compared to those inferred from the more accurate synthesizing unit model. However, biogeochemical models that implement these three formulations are needed to evaluate which formulation is acceptably accurate and their impacts on predicted long-term ecosystem dynamics. In particular, studies are needed that explore the extent to which parameter calibration can rescue model performance when the mechanistic representation of a biogeochemical process is known to be deficient.

How and why to build a mathematical model: A case study using prion aggregation

Biological systems are inherently complex, and the increasing level of detail with which we are able to experimentally probe such systems continually reveals new complexity. Fortunately, mathematical models are uniquely positioned to provide a tool suitable for rigorous analysis, hypothesis generation, and connecting results from isolated in vitro experiments with results from in vivo and whole-organism studies. However, developing useful mathematical models is challenging because of the often different domains of knowledge required in both math and biology. In this work, we endeavor to provide a useful guide for researchers interested in incorporating mathematical modeling into their scientific process. We advocate for the use of conceptual diagrams as a starting place to anchor researchers from both domains. These diagrams are useful for simplifying the biological process in question and distinguishing the essential components. Not only do they serve as the basis for developing a variety of mathematical models, but they ensure that any mathematical formulation of the biological system is led primarily by scientific questions. We provide a specific example of this process from our own work in studying prion aggregation to show the power of mathematical models to synergistically interact with experiments and push forward biological understanding. Choosing the most suitable model also depends on many different factors, and we consider how to make these choices based on different scales of biological organization and available data. We close by discussing the many opportunities that abound for both experimentalists and modelers to take advantage of collaborative work in this field.

Biological Pathway Specificity in the Cell-Does Molecular Diversity Matter?

Biology arises from the crowded molecular environment of the cell, rendering it a challenge to understand biological pathways based on the reductionist, low-concentration in vitro conditions generally employed for mechanistic studies. Recent evidence suggests that low-affinity interactions between cellular biopolymers abound, with still poorly defined effects on the complex interaction networks that lead to the emergent properties and plasticity of life. Mass-action considerations are used here to underscore that the sheer number of weak interactions expected from the complex mixture of cellular components significantly shapes biological pathway specificity. In particular, on-pathway-i.e., "functional"-become those interactions thermodynamically and kinetically stable enough to survive the incessant onslaught of the many off-pathway ("nonfunctional") interactions. Consequently, to better understand the molecular biology of the cell a further paradigm shift is needed toward mechanistic experimental and computational approaches that probe intracellular diversity and complexity more directly. Also see the video abstract here https://youtu.be/T19X_zYaBzg.

[Anomalous Kinetics of Amyloidogenesis Suggest a Competition between Oligomers and Fibrils]

Meisl et al. have recently observed an anomalous dependence of the amyloid formation rate on the protein concentration. A novel mechanism of fibril growth has been proposed by Meisl et al. to explain the abnormality; it consists in the fibril-catalyzed initiation of fibril formation with saturation of catalytic sites at high concentrations of substrates. Our article describes an alternative explanation of the anomalous kinetics, assuming that the formation of metastable oligomers competes with fibril formation by decreasing the concentration of free monomers. Oligomers are indeed observed in the course of amyloid formation, but are usually considered as seeds of amyloid fibrils rather as their competitors. However, the oligomers visually detectable by electron microscopy were shown to be close in size to those that can be derived from the anomalous dependence of the amyloid growth rate on the protein concentration, given that the anomaly results from competition between oligomer formation and amyloidogenesis.

Characterization of Kinetic Binding Properties of Unlabeled Ligands via a Preincubation Endpoint Binding Approach

The dissociation rates of unlabeled drugs have been well studied by kinetic binding analyses. Since kinetic assays are laborious, we developed a simple method to determine the kinetic binding parameters of unlabeled competitors by a preincubation endpoint assay. The probe binding after preincubation of a competitor can be described by a single equation as a function of time. Simulations using the equation revealed the degree of IC50 change induced by preincubation of a competitor depended on the dissociation rate koff of the competitor but not on the association rate kon To validate the model, an in vitro binding assay was performed using a smoothened receptor (SMO) and [(3)H]TAK-441, a SMO antagonist. The equilibrium dissociation constants (KI) and koff of SMO antagonists determined by globally fitting the model to the concentration-response curves obtained with and without 24 h preincubation correlated well with those determined by other methods. This approach could be useful for early-stage optimization of drug candidates by enabling determination of binding kinetics in a high-throughput manner because it does not require kinetic measurements, an intermediate washout step during the reaction, or prior determination of competitors' KI values.

The law of mass action and the pharmacological concentration-effect curve: resolving the paradox of apparently non-dose-related adverse drug reactions

BACKGROUND

Adverse drug reactions are sometimes described as being 'non-dose-related' because no relationship has been found between increasing doses and either the intensity of the response or the proportion of individuals in whom the response occurs; furthermore, hypersensitivity reactions are often regarded as being non-dose-related, even if different doses have not been studied. However, the law of mass action implies that all pharmacological effects are concentration related and should increase in intensity with increasing dose. We set out to explain this paradox.

METHODS

We searched for published adverse drug reactions that have been described as non-dose-related and analysed them.

RESULTS

We identified four categories of explanations that resolve the paradox: (i) the reaction is not real; it may have occurred by chance or there may be methodological problems, such as bias or confounding factors; (ii) the dose-response curve for the adverse effect reaches a maximum at doses lower than were studied (i.e. a hypersusceptibility reaction); this underpins the use of test doses to predict the possibility of an adverse reaction at therapeutic doses; (iii) susceptibility to the adverse reaction differs widely among individuals; and (iv) imprecision or inaccuracy in the measurement of either dose or effect obscures dose responsiveness. This last explanation encompasses: (a) reactions related to cumulative dose; (b) dissociation between dose and concentration through saturable pharmacokinetics; and (c) variability in the measurement of the effect.

CONCLUSIONS AND IMPLICATIONS

If an adverse drug reaction appears to be non-dose-related, the reasons should be sought, having these mechanisms in mind.

Bioenergetic medicine

Here we discuss a specific therapeutic strategy we call 'bioenergetic medicine'. Bioenergetic medicine refers to the manipulation of bioenergetic fluxes to positively affect health. Bioenergetic medicine approaches rely heavily on the law of mass action, and impact systems that monitor and respond to the manipulated flux. Since classically defined energy metabolism pathways intersect and intertwine, targeting one flux also tends to change other fluxes, which complicates treatment design. Such indirect effects, fortunately, are to some extent predictable, and from a therapeutic perspective may also be desirable. Bioenergetic medicine-based interventions already exist for some diseases, and because bioenergetic medicine interventions are presently feasible, new approaches to treat certain conditions, including some neurodegenerative conditions and cancers, are beginning to transition from the laboratory to the clinic.

Propagation of large concentration changes in reversible protein-binding networks

We study how the dynamic equilibrium of the reversible protein-protein-binding network in yeast Saccharomyces cerevisiae responds to large changes in abundances of individual proteins. The magnitude of shifts between free and bound concentrations of their immediate and more distant neighbors in the network is influenced by such factors as the network topology, the distribution of protein concentrations among its nodes, and the average binding strength. Our primary conclusion is that, on average, the effects of a perturbation are strongly localized and exponentially decay with the network distance away from the perturbed node, which explains why, despite globally connected topology, individual functional modules in such networks are able to operate fairly independently. We also found that under specific favorable conditions, realized in a significant number of paths in the yeast network, concentration perturbations can selectively propagate over considerable network distances (up to four steps). Such "action-at-a-distance" requires high concentrations of heterodimers along the path as well as low free (unbound) concentration of intermediate proteins.

Point mutation increases a form of the NK1 receptor with high affinity for neurokinin A and B and septide

1. The binding modalities of substance P and neurokinin A on the wild type and Gly166 to-Cys mutant NK1 receptors expressed on CHO cells were investigated in homologous and heterologous binding experiments using both radiolabelled substance P and neurokinin A. 2. On the wild type NK1 receptor NKA displaces radiolabelled substance P with very low apparent affinity, despite its high-affinity binding constant (determined in homologous binding experiments). The Gly166 to-Cys substitution in the NK1 tachykinin receptor greatly enhances the apparent affinity of neurokinin A in competition for radiolabelled substance P, but it does not change the binding constant of neurokinin A. The mutation, thereby, eliminates the discrepancy between the low apparent affinity and the high binding constant of neurokinin A. 3. On the wild type receptor the binding capacity of neurokinin A is significantly smaller than that of substance P. In contrast, the two tachykinins bind to approximately the same number of sites on the mutant receptor. 4. Simultaneous mass action law analysis of binding data in which multiple radioligands were employed in parallel demonstrated that a one-site model was unable to accommodate all the experimental data, whereas a two-site model provided a dramatically better description. 5. These two receptor-sites display equally high affinity for substance P, while neurokinin A strongly discriminates between a high and a low affinity component. The binding affinities of neurokinin A are not affected by the mutation, which instead specifically alters the distribution between receptor sites in favour of a high affinity neurokinin A binding form. 6. The low apparent affinity and binding capacity of neurokinin A on the wild type receptor results from neurokinin A binding with high affinity only to a fraction of the sites labelled by substance P. The mutation increases the proportion of this site, and consequently enhances the apparent affinity and binding capacity of neurokinin A. 7. The binding modalities of septide-like ligands (i.e. neurokinin B, SP(6-11), SP-methyl ester) are affected similarly to neurokinin A and are better resolved into two sites. The mutation leaves the affinity of these ligands for the two receptor forms unchanged, but increases the fraction of high-affinity sites. On the other hand, the binding of non-peptide and peptide antagonists (SR140.333 and FK888) behaved similarly to substance P with a single high affinity site that is unaffected by the mutation. 8. These findings may suggest that the NK1 receptor exists in two different forms with similar affinity for substance P and NK1 antagonists, but with a high and a low affinity for neurokinin A and septide-like ligands. Hence, the Gly166 in the NK1 receptor would seem to control the distribution between a pan-reactive form and a substance P-selective form of the receptor.