Multiple models for outbreak decision support in the face of uncertainty.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

A Quantitative Evaluation of COVID-19 Epidemiological Models.

Quantifying how accurate epidemiological models of COVID-19 forecast the number of future cases and deaths can help frame how to incorporate mathematical models to inform public health decisions. Here we analyze and score the predictive ability of publicly available COVID-19 epidemiological models on the COVID-19 Forecast Hub. Our score uses the posted forecast cumulative distributions to compute the log-likelihood for held-out COVID-19 positive cases and deaths. Scores are updated continuously as new data become available, and model performance is tracked over time. We use model scores to construct ensemble models based on past performance. Our publicly available quantitative framework may aid in improving modeling frameworks, and assist policy makers in selecting modeling paradigms to balance the delicate trade-offs between the economy and public health.

A solid-phase PEGylation strategy for protein therapeutics using a potent FGF21 analog.

Fibroblast growth factor 21 (FGF21) is an endocrine-acting hormone that has the potential to treat metabolic diseases, such as type 2 diabetes and obesity. Development of FGF21 into a therapeutic has been hindered due to its low intrinsic bio-stability, propensity towards aggregation and its susceptibility to in vivo proteolytic degradation. In order to address these shortcomings, we've developed recombinant human FGF21 variants by strategically introducing cysteine residues via site-directed mutagenesis, and have also developed a solid-phase nickel affinity PEGylation strategy, whereby engineered, surface-exposed cysteine residues of immobilized proteins were used as a platform to efficiently and site-selectively conjugate with PEG-maleimide. The engineered PEGylated FGF21 conjugates retained its biological functions, as well as demonstrated an increase in half-life by over 211.3 min. By demonstrating the biological activity of the FGF21 analog as a prototype, we have also provided a "generalized" solid-phase approach to effectively increase serum half-life of protein therapeutics.

Molecular mechanisms of fibroblast growth factor signaling in physiology and pathology.

Fibroblast growth factors (FGFs) signal in a paracrine or endocrine fashion to mediate a myriad of biological activities, ranging from issuing developmental cues, maintaining tissue homeostasis, and regulating metabolic processes. FGFs carry out their diverse functions by binding and dimerizing FGF receptors (FGFRs) in a heparan sulfate (HS) cofactor- or Klotho coreceptor-assisted manner. The accumulated wealth of structural and biophysical data in the past decade has transformed our understanding of the mechanism of FGF signaling in human health and development, and has provided novel concepts in receptor tyrosine kinase (RTK) signaling. Among these contributions are the elucidation of HS-assisted receptor dimerization, delineation of the molecular determinants of ligand-receptor specificity, tyrosine kinase regulation, receptor cis-autoinhibition, and tyrosine trans-autophosphorylation. These structural studies have also revealed how disease-associated mutations highjack the physiological mechanisms of FGFR regulation to contribute to human diseases. In this paper, we will discuss the structurally and biophysically derived mechanisms of FGF signaling, and how the insights gained may guide the development of therapies for treatment of a diverse array of human diseases.

Grb2, a double-edged sword of receptor tyrosine kinase signaling.

Receptor tyrosine kinases (RTKs) exhibit basal tyrosine phosphorylation and activity in the absence of ligand stimulation, which has been attributed to the "leaky" nature of tyrosine kinase autoinhibition and stochastic collisions of receptors in the membrane bilayer. This basal phosphorylation does not produce a signal of sufficient amplitude and intensity to manifest in a biological response and hence is considered to be a passive, futile process that does not have any biological function. This paradigm has now been challenged by a study showing that the basal phosphorylation of RTKs is a physiologically relevant process that is actively inhibited by the intracellular adaptor protein growth factor receptor-bound 2 (Grb2) and serves to "prime" receptors for a rapid response to ligand stimulation. Grb2 is conventionally known for playing positive roles in RTK signaling. The discovery of a negative regulatory role for Grb2 reveals that this adaptor acts as a double-edged sword in the regulation of RTK signaling.