Emergence of size-structured dominance hierarchies through size-dependent feedback

Size-based dominance hierarchies influence fitness, group size and population dynamics and link dominance structure to evolutionary and ecological outcomes. While larger individuals often gain dominance, social status may influence growth and size in return, resulting in feedbacks among status, growth and size. Here, we present two models evaluating how these feedbacks influence the emergence of size structure in a dominance hierarchy. In the first, size influences competition for food and investment in suppressing growth of groupmates. Stable size differences emerged when suppression was greatest for similarly sized individuals and size had little effect on competition for food. The model predicted size divergence when size strongly affected competition for food. In the second model, we used a dynamic game to solve for optimal investment in growth suppression as a function of size structure. Investment in growth suppression was favoured only when dominants and subordinates were similar in size, generating size ratios different than those expected by chance. Variation in the feedbacks among growth, size and status can explain variation in emergent size structure of dominance hierarchies and its consequences for conflict within groups. This article is part of the theme issue ‘The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies’.

Normal and Neoplastic Growth Suppression by The Extended Myc Network

Among the first discovered and most prominent cellular oncogenes is MYC, which encodes a bHLH-ZIP transcription factor (Myc) that both activates and suppresses numerous genes involved in proliferation, energy production, metabolism and translation. Myc belongs to a small group of bHLH-ZIP transcriptional regulators (the Myc Network) that includes its obligate heterodimerization partner Max and six “Mxd proteins” (Mxd1-4, Mnt and Mga) each of which heterodimerizes with Max and largely oppose Myc’s functions. More recently, a second group of bHLH-ZIP proteins (the Mlx Network) has emerged. It is comprised of the Myc-like factors ChREBP and MondoA, which, in association with the Max-like member Mlx, regulate smaller and more functionally restricted sets of target genes, some of which are shared with Myc. Opposing ChREBP and MondoA are heterodimers comprised of Mlx and Mxd1, Mxd4 and Mnt, which also structurally and operationally link the two Networks. We discuss here the functions of these “Extended Myc Network” members with particular emphasis on the roles played by Max, Mlx and Mxd proteins in suppressing normal and neoplastic growth. These roles are complex due to the temporally- and tissue-restricted expression of Extended Myc Network proteins in normal cells, their regulation of both common and unique target genes and, in some cases, their functional redundancy.

1088. A Whole-Body Quantitative System Pharmacology Physiologically-Based Pharmacokinetic (QSP/PBPK) Model to Support Dose Selection of ADG20: an Extended Half-Life Monoclonal Antibody Being Developed for the Treatment of Coronavirus Disease (COVID-19)

Background ADG20 is a fully human IgG1 monoclonal antibody engineered to have potent and broad neutralization against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other SARS-like CoVs with pandemic potential and an extended half-life. ADG20 is administered intramuscularly (IM). A QSP/PBPK model was constructed to support dose selection for a Phase 2/3 trial of ambulatory patients with mild to moderate COVID-19 (STAMP: NCT04805671). Methods A QSP/PBPK model was used to simulate receptor occupancy (RO) and drug exposure in the upper airway (nasopharyngeal/oropharyngeal epithelial lining fluid [ELF] compartment). RO was linked to an existing viral dynamic model to enable the prediction of the natural time course of viral load and the effect of ADG20 on viral clearance and infectivity rate. RO was calculated using: 1) in vitro ADG20–SARS-CoV-2 binding kinetics (association rate constant (kon) of 1.52E+06 M-1•s1 and dissociation rate constant (koff) of 2.81E-04 s-1 from a Biacore assay; 2) time course of ADG20 concentrations in ELF; and 3) time course of viral load following ADG20 administration. Molar SARS-CoV-2 viral binding site capacity was calculated assuming 40 spike proteins per virion, 3 binding sites per spike, and an initial viral load of log 107 copies/mL for all patients. The QSP/PBPK model and a 2018 CDC reference body weight distribution (45–150 kg) were used to simulate 1000 concentration-time profiles for a range of candidate ADG20 regimens. ADG20 regimens were evaluated against 2 criteria: 1) ability to attain near complete ( >90%), and durable (28-day) SARS-CoV-2 RO in the ELF; and 2) ability to maintain ELF ADG20 concentrations relative to a concentration (0.5 mg/L) associated with 100% viral growth suppression in an in vitro post-infection assay. Results A single 300 mg IM ADG20 dose met the dose selection criteria in terms of RO (Figure A) and viral growth suppression (Figure B). Conclusion These data support the evaluation of an ADG20 300 mg IM dose for the treatment of mild to moderate COVID-19. ADG20 is forecasted to attain near complete ( >90%) SARS-CoV-2 RO in the ELF and maintain ELF ADG20 concentrations above that associated with 100% viral growth suppression in vitro. Figure. QSP/PBPK model forecast of ADG20 300 mg IM in adults (A) Predicted RO expressed as percent occupancy with the dotted line representing the threshold for 90% RO. (B) Predicted median concentration of ADG20 relative to a concentration (0.5 mg/L) associated with 100% viral growth suppression as indicated by the dotted line; the shaded area represents the 90% prediction interval. Disclosures Evan D. Tarbell, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Scott A. Van Wart, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Laura M. Walker, PhD, Adagio Therapeutics, Inc. (Other Financial or Material Support, Laura M. Walker is an inventor on a patent application submitted by Adagio Therapeutics, Inc., describing the engineered SARS-CoV-2 antibody.) Andrew Santulli, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Lynn E. Connolly, MD, PhD, Adagio Therapeutics, Inc. (Employee) Donald E Mager, PharmD, PhD, Adagio Therapeutics, Inc. (Independent Contractor) Paul G. Ambrose, PharmD, Adagio Therapeutics, Inc. (Employee)

PSI-B-24 Assessment of the combined use of antibacterial substances on the in vitro model in the development of veterinary drugs

The wide use of antibacterial drugs in the agricultural and veterinary industries as growth stimulants and antimicrobial therapies has led to increased resistance of pathogens and opportunistic pathogens to many chemotherapy drugs. The purpose of our study is to assess the additive effect of these compounds to enhance the inhibitory action of antibiotics. Antibacterial drugs of various chemical groups, extracts from medicinal plants with microbicide and anti-quorum effects, inorganic copper and zinc salts, as well as probiotic strains of the genus Bacillus of veterinary purpose, were used to achieve the goal. The main methodical approach to assessing the additive effect of complex compounds in the work was the method of diffusion into agar, combined with the method of serial dilution. The selection of antibacterial drugs was carried out using the disk diffusion method. S. enteritidis, S. typhimurium, and P. aeruginosa were used as the test organisms in studies. The main criterion for the selection of antibacterial drugs was the resistance of probiotic strains and the moderate sensitivity of the test organisms in relation to their action. Cefixime was experimentally selected for the study against S. enteritidis and S. typhimurium and Fosfomycin against P. aeruginosa. Of all the studied phytobiotics, the most promising for further study was the oak bark extract. Against P. aeruginosa, the most significant chemical compound is CuSO4 at a concentration of 40 mg/ml, which does not affect the growth of probiotic strains. The pronounced additive effect of the combined compound based on cefixime, oak bark, and B. subtilis 534 was observed against S. enteritidis and S. typhimurium by 23% and 25%, respectively. The combined use of fosfomycin, B. subtilis 534, CuSO4, and the oak bark extract increases P. aeruginosa growth suppression by 19 % compared to the control of the growth suppression of this antibiotic.