A new paradigm for pandemic preparedness

PURPOSE OF REVIEW: Preparing for pandemics requires a degree of interdisciplinary work that is challenging under the current paradigm. This review summarizes the challenges faced by the field of pandemic science and proposes how to address them. RECENT FINDINGS: The structure of current siloed systems of research organizations hinders effective interdisciplinary pandemic research. Moreover, effective pandemic preparedness requires stakeholders in public policy and health to interact and integrate new findings rapidly, relying on a robust, responsive, and productive research domain. Neither of these requirements are well supported under the current system. SUMMARY: We propose a new paradigm for pandemic preparedness wherein interdisciplinary research and close collaboration with public policy and health practitioners can improve our ability to prevent, detect, and treat pandemics through tighter integration among domains, rapid and accurate integration, and translation of science to public policy, outreach and education, and improved venues and incentives for sustainable and robust interdisciplinary work.CCF-2200052 - National Science FoundationPublished versio

Validity of the lipid sink as a mechanism for the reversal of local anesthetic systemic toxicity: A physiologically based pharmacokinetic model study

Background: In vitro observations support the lipid sink theory of therapeutic action by confirming the capacity of lipid emulsions to successfully uptake bupivacaine from aqueous media. However, competing hypotheses and some in/ex vivo small animal studies suggest a metabolic or positive inotropic effect underlies the dramatic effects of lipid therapy. Controlled clinical tests to establish causality and mechanism of action are an impossibility. In an effort to quantitatively probe the merits of a ‘sink’ mechanism, a physiologically-based pharmacokinetic (PBPK) model has been developed that considers the binding action of plasma lipid. Methods: The model includes no fitting parameters and accounts for concentration dependence of plasma protein and lipid:anesthetic binding as well as the metabolism of the lipid scavenger. Predicted pharmacokinetics were validated by comparison with data from healthy volunteers administered a non-toxic dose of bupivacaine. The model was augmented to simulate lipid therapy and extended to the case of accidental intravenous infusion of bupivacaine at levels known to cause systemic toxicity. Results: The model yielded quantitative agreement with available pharmacokinetic data. Simulated lipid infusion following an IV overdose was predicted to yield (i) an increase in total plasma concentration, (ii) a decrease in unbound concentration, and (iii) a decrease in tissue content of bupivacaine. Conclusions: 3 Results suggest that the timescale on which tissue content is reduced varies from organ to organ, with the concentration in the heart falling by 11% within 3 minutes. This initial study suggests that, in isolation, the lipid sink is insufficient to guarantee a reversal of systemic toxicit

Adaptive Language Model Training for Molecular Design

The vast size of chemical space necessitates computational approaches to automate and accelerate the design of molecular sequences to guide experimental efforts for drug discovery. Genetic algorithms provide a useful framework to incrementally generate molecules by applying mutations to known chemical structures. Recently, masked language models have been applied to automate the mutation process by leveraging large compound libraries to learn commonly occurring chemical sequences (i.e., using tokenization) and predict rearrangements (i.e., using mask prediction). Here, we consider how language models can be adapted to improve molecule generation for different optimization tasks. We use two different generation strategies for comparison, fixed and adaptive. The fixed strategy uses a pre-trained model to generate mutations; the adaptive strategy trains the language model on each new generation of molecules selected for target properties during optimization. Our results show that the adaptive strategy allows the language model to more closely fit the distribution of molecules in the population. Therefore, for enhanced fitness optimization, we suggest the use of the fixed strategy during an initial phase followed by the use of the adaptive strategy. We demonstrate the impact of adaptive training by searching for molecules that optimize both heuristic metrics, drug-likeness and synthesizability, as well as predicted protein binding affinity from a surrogate model. Our results show that the adaptive strategy provides a significant improvement in fitness optimization compared to the fixed pre-trained model, empowering the application of language models to molecular design task

Fractional order analysis of Sephadex gel structures: NMR measurements reflecting anomalous diffusion

We report the appearance of anomalous water diffusion in hydrophilic Sephadex gels observed using pulse field gradient (PFG) nuclear magnetic resonance (NMR). The NMR diffusion data was collected using a Varian 14.1 Tesla imaging system with a home-built RF saddle coil. A fractional order analysis of the data was used to characterize heterogeneity in the gels for the dynamics of water diffusion in this restricted environment. Several recent studies of anomalous diffusion have used the stretched exponential function to model the decay of the NMR signal, i.e., exp[−(bD)(α)], where D is the apparent diffusion constant, b is determined the experimental conditions (gradient pulse separation, durations and strength), and α is a measure of structural complexity. In this work, we consider a different case where the spatial Laplacian in the Bloch-Torrey equation is generalized to a fractional order model of diffusivity via a complexity parameter, β, a space constant, μ, and a diffusion coefficient, D. This treatment reverts to the classical result for the integer order case. The fractional order decay model was fit to the diffusion-weighted signal attenuation for a range of b-values (0 < b < 4,000 s-mm(−2)). Throughout this range of b values, the parameters β, μ and D, were found to correlate with the porosity and tortuosity of the gel structure

Vesicle Formation and Endocytosis: Function, Machinery, Mechanisms, and Modeling

Vesicle formation provides a means of cellular entry for extracellular substances and for recycling of membrane constituents. Mechanisms governing the two primary endocytic pathways (i.e., caveolae- and clathrin-mediated endocytosis, as well as newly emerging vesicular pathways) have become the focus of intense investigation to improve our understanding of nutrient, hormone, and drug delivery, as well as opportunistic invasion of pathogens. In this review of endocytosis, we broadly discuss the structural and signaling proteins that compose the molecular machinery governing endocytic vesicle formation (budding, invagination, and fission from the membrane), with some regard for the specificity observed in certain cell types and species. Important biochemical functions of endocytosis and diseases caused by their disruption also are discussed, along with the structures of key components of endocytic pathways and their known mechanistic contributions. The mechanisms by which principal components of the endocytic machinery are recruited to the plasma membrane, where they interact to induce vesicle formation, are discussed, together with computational approaches used to simulate simplified versions of endocytosis with the hope of clarifying aspects of vesicle formation that may be difficult to determine experimentally. Finally, we pose several unanswered questions intended to stimulate further research interest in the cell biology and modeling of endocytosis. Antioxid. Redox Signal. 11, 1301–1312

A New Paradigm for Pandemic Preparedness

Abstract Purpose of Review Preparing for pandemics requires a degree of interdisciplinary work that is challenging under the current paradigm. This review summarizes the challenges faced by the field of pandemic science and proposes how to address them. Recent Findings The structure of current siloed systems of research organizations hinders effective interdisciplinary pandemic research. Moreover, effective pandemic preparedness requires stakeholders in public policy and health to interact and integrate new findings rapidly, relying on a robust, responsive, and productive research domain. Neither of these requirements are well supported under the current system. Summary We propose a new paradigm for pandemic preparedness wherein interdisciplinary research and close collaboration with public policy and health practitioners can improve our ability to prevent, detect, and treat pandemics through tighter integration among domains, rapid and accurate integration, and translation of science to public policy, outreach and education, and improved venues and incentives for sustainable and robust interdisciplinary work