COVID-19 infection data encode a dynamic reproduction number in response to policy decisions with secondary wave implications.

The SARS-CoV-2 virus is responsible for the novel coronavirus disease 2019 (COVID-19), which has spread to populations throughout the continental United States. Most state and local governments have adopted some level of "social distancing" policy, but infections have continued to spread despite these efforts. Absent a vaccine, authorities have few other tools by which to mitigate further spread of the virus. This begs the question of how effective social policy really is at reducing new infections that, left alone, could potentially overwhelm the existing hospitalization capacity of many states. We developed a mathematical model that captures correlations between some state-level "social distancing" policies and infection kinetics for all U.S. states, and use it to illustrate the link between social policy decisions, disease dynamics, and an effective reproduction number that changes over time, for case studies of Massachusetts, New Jersey, and Washington states. In general, our findings indicate that the potential for second waves of infection, which result after reopening states without an increase to immunity, can be mitigated by a return of social distancing policies as soon as possible after the waves are detected.

Devil in the details: Mechanistic variations impact information transfer across models of transcriptional cascades.

The transcriptional network determines a cell's internal state by regulating protein expression in response to changes in the local environment. Due to the interconnected nature of this network, information encoded in the abundance of various proteins will often propagate across chains of noisy intermediate signaling events. The data-processing inequality (DPI) leads us to expect that this intracellular game of "telephone" should degrade this type of signal, with longer chains losing successively more information to noise. However, a previous modeling effort predicted that because the steps of these signaling cascades do not truly represent independent stages of data processing, the limits of the DPI could seemingly be surpassed, and the amount of transmitted information could actually increase with chain length. What that work did not examine was whether this regime of growing information transmission was attainable by a signaling system constrained by the mechanistic details of more complex protein-binding kinetics. Here we address this knowledge gap through the lens of information theory by examining a model that explicitly accounts for the binding of each transcription factor to DNA. We analyze this model by comparing stochastic simulations of the fully nonlinear kinetics to simulations constrained by the linear response approximations that displayed a regime of growing information. Our simulations show that even when molecular binding is considered, there remains a regime wherein the transmitted information can grow with cascade length, but ends after a critical number of links determined by the kinetic parameter values. This inflection point marks where correlations decay in response to an oversaturation of binding sites, screening informative transcription factor fluctuations from further propagation down the chain where they eventually become indistinguishable from the surrounding levels of noise.

Stochastically modeling multiscale stationary biological processes.

Large scale biological responses are inherently uncertain, in part as a consequence of noisy systems that do not respond deterministically to perturbations and measurement errors inherent to technological limitations. As a result, they are computationally difficult to model and current approaches are notoriously slow and computationally intensive (multiscale stochastic models), fail to capture the effects of noise across a system (chemical kinetic models), or fail to provide sufficient biological fidelity because of broad simplifying assumptions (stochastic differential equations). We use a new approach to modeling multiscale stationary biological processes that embraces the noise found in experimental data to provide estimates of the parameter uncertainties and the potential mis-specification of models. Our approach models the mean stationary response at each biological level given a particular expected response relationship, capturing variation around this mean using conditional Monte Carlo sampling that is statistically consistent with training data. A conditional probability distribution associated with a biological response can be reconstructed using this method for a subset of input values, which overcomes the parameter identification problem. Our approach could be applied in addition to dynamical modeling methods (see above) to predict uncertain biological responses over experimental time scales. To illustrate this point, we apply the approach to a test case in which we model the variation associated with measurements at multiple scales of organization across a reproduction-related Adverse Outcome Pathway described for teleosts.

Statistical relationship between metabolic decomposition and chemical uptake predicts bioconcentration factor data for diverse chemical exposures.

BACKGROUND: A challenge of in vitro to in vivo extrapolation (IVIVE) is to predict the physical state of organisms exposed to chemicals in the environment from in vitro exposure assay data. Although toxicokinetic modeling approaches promise to bridge in vitro screening data with in vivo effects, they are often encumbered by a need for redesign or re-parameterization when applied to different tissues or chemicals. RESULTS: We demonstrate a parameterization of reverse toxicokinetic (rTK) models developed for the adult zebrafish (Danio rerio) based upon particle swarm optimizations (PSO) of the chemical uptake and degradation rates that predict bioconcentration factors (BCF) for a broad range of chemicals. PSO reveals a relationship between chemical uptake and decomposition parameter values that predicts chemical-specific BCF values with moderate statistical agreement to a limited yet diverse chemical dataset, and all without a need to retrain the model to new data. CONCLUSIONS: The presented model requires only the octanol-water partitioning ratio to predict BCFs to a fidelity consistent with existing QSAR models. This success begs re-evaluation of the modeling assumptions; specifically, it suggests that chemical uptake into arterial blood may be limited by transport across gill membranes (diffusion) rather than by counter-current flow between gill lamellae (convection). Therefore, more detailed molecular modeling of aquatic respiration may further improve predictive accuracy of the rTK approach.

Crosstalk and the evolvability of intracellular communication.

Metazoan signalling networks are complex, with extensive crosstalk between pathways. It is unclear what pressures drove the evolution of this architecture. We explore the hypothesis that crosstalk allows different cell types, each expressing a specific subset of signalling proteins, to activate different outputs when faced with the same inputs, responding differently to the same environment. We find that the pressure to generate diversity leads to the evolution of networks with extensive crosstalk. Using available data, we find that human tissues exhibit higher levels of diversity between cell types than networks with random expression patterns or networks with no crosstalk. We also find that crosstalk and differential expression can influence drug activity: no protein has the same impact on two tissues when inhibited. In addition to providing a possible explanation for the evolution of crosstalk, our work indicates that consideration of cellular context will likely be crucial for targeting signalling networks.

Crosstalk and the Dynamical Modularity of Feed-Forward Loops in Transcriptional Regulatory Networks.

Network motifs, such as the feed-forward loop (FFL), introduce a range of complex behaviors to transcriptional regulatory networks, yet such properties are typically determined from their isolated study. We characterize the effects of crosstalk on FFL dynamics by modeling the cross regulation between two different FFLs and evaluate the extent to which these patterns occur in vivo. Analytical modeling suggests that crosstalk should overwhelmingly affect individual protein-expression dynamics. Counter to this expectation we find that entire FFLs are more likely than expected to resist the effects of crosstalk (≈20% for one crosstalk interaction) and remain dynamically modular. The likelihood that cross-linked FFLs are dynamically correlated increases monotonically with additional crosstalk, but is independent of the specific regulation type or connectivity of the interactions. Just one additional regulatory interaction is sufficient to drive the FFL dynamics to a statistically different state. Despite the potential for modularity between sparsely connected network motifs, Escherichia coli (E. coli) appears to favor crosstalk wherein at least one of the cross-linked FFLs remains modular. A gene ontology analysis reveals that stress response processes are significantly overrepresented in the cross-linked motifs found within E. coli. Although the daunting complexity of biological networks affects the dynamical properties of individual network motifs, some resist and remain modular, seemingly insulated from extrinsic perturbations-an intriguing possibility for nature to consistently and reliably provide certain network functionalities wherever the need arise.

Physiological fidelity or model parsimony? The relative performance of reverse-toxicokinetic modeling approaches.

BACKGROUND: Physiologically-based toxicokinetic (PBTK) models are often developed to facilitate in vitro to in vivo extrapolation (IVIVE) using a top-down, compartmental approach, favoring architectural simplicity over physiological fidelity despite the lack of general guidelines relating model design to dynamical predictions. Here we explore the impact of design choice (high vs. low fidelity) on chemical distribution throughout an animal's organ system. RESULTS: We contrast transient dynamics and steady states of three previously proposed PBTK models of varying complexity in response to chemical exposure. The steady states for each model were determined analytically to predict exposure conditions from tissue measurements. Steady state whole-body concentrations differ between models, despite identical environmental conditions, which originates from varying levels of physiological fidelity captured by the models. These differences affect the relative predictive accuracy of the inverted models used in exposure reconstruction to link effects-based exposure data with whole-organism response thresholds obtained from in vitro assay measurements. CONCLUSIONS: Our results demonstrate how disregarding physiological fideltiy in favor of simpler models affects the internal dynamics and steady state estimates for chemical accumulation within tissues, which, in turn, poses significant challenges for the exposure reconstruction efforts that underlie many IVIVE methods. Developing standardized systems-level models for ecological organisms would not only ensure predictive consistency among future modeling studies, but also ensure pragmatic extrapolation of in vivo effects from in vitro data or modeling exposure-response relationships.

Maturation of the proteasome core particle induces an affinity switch that controls regulatory particle association.

Proteasome assembly is a complex process, requiring 66 subunits distributed over several subcomplexes to associate in a coordinated fashion. Ten proteasome-specific chaperones have been identified that assist in this process. For two of these, the Pba1-Pba2 dimer, it is well established that they only bind immature core particles (CPs) in vivo. In contrast, the regulatory particle (RP) utilizes the same binding surface but only interacts with the mature CP in vivo. It is unclear how these binding events are regulated. Here, we show that Pba1-Pba2 binds tightly to the immature CP, preventing RP binding. Changes in the CP that occur on maturation significantly reduce its affinity for Pba1-Pba2, enabling the RP to displace the chaperone. Mathematical modelling indicates that this 'affinity switch' mechanism has likely evolved to improve assembly efficiency by preventing the accumulation of stable, non-productive intermediates. Our work thus provides mechanistic insights into a crucial step in proteasome biogenesis.

Phosphatase specificity and pathway insulation in signaling networks.

Phosphatases play an important role in cellular signaling networks by regulating the phosphorylation state of proteins. Phosphatases are classically considered to be promiscuous, acting on tens to hundreds of different substrates. We recently demonstrated that a shared phosphatase can couple the responses of two proteins to incoming signals, even if those two substrates are from otherwise isolated areas of the network. This finding raises a potential paradox: if phosphatases are indeed highly promiscuous, how do cells insulate themselves against unwanted crosstalk? Here, we use mathematical models to explore three possible insulation mechanisms. One approach involves evolving phosphatase KM values that are large enough to prevent saturation by the phosphatase's substrates. Although this is an effective method for generating isolation, the phosphatase becomes a highly inefficient enzyme, which prevents the system from achieving switch-like responses and can result in slow response kinetics. We also explore the idea that substrate degradation can serve as an effective phosphatase. Assuming that degradation is unsaturatable, this mechanism could insulate substrates from crosstalk, but it would also preclude ultrasensitive responses and would require very high substrate turnover to achieve rapid dephosphorylation kinetics. Finally, we show that adaptor subunits, such as those found on phosphatases like PP2A, can provide effective insulation against phosphatase crosstalk, but only if their binding to substrates is uncoupled from their binding to the catalytic core. Analysis of the interaction network of PP2A's adaptor domains reveals that although its adaptors may isolate subsets of targets from one another, there is still a strong potential for phosphatase crosstalk within those subsets. Understanding how phosphatase crosstalk and the insulation mechanisms described here impact the function and evolution of signaling networks represents a major challenge for experimental and computational systems biology.

Crosstalk and the evolution of specificity in two-component signaling.

Two-component signaling (TCS) serves as the dominant signaling modality in bacteria. A typical pathway includes a sensor histidine kinase (HK) that phosphorylates a response regulator (RR), modulating its activity in response to an incoming signal. Most HKs are bifunctional, acting as both kinase and phosphatase for their substrates. Unlike eukaryotic signaling networks, there is very little crosstalk between bacterial TCS pathways; indeed, adding crosstalk to a pathway can have disastrous consequences for cell fitness. It is currently unclear exactly what feature of TCS necessitates this degree of pathway isolation. In this work we used mathematical models to show that, in the case of bifunctional HKs, adding a competing substrate to a TCS pathway will always reduce response of that pathway to incoming signals. We found that the pressure to maintain cognate signaling is sufficient to explain the experimentally observed "kinetic preference" of HKs for their cognate RRs. These findings imply a barrier to the evolution of new HK-RR pairs, because crosstalk is unavoidable immediately after the duplication of an existing pathway. We characterized a set of "near-neutral" evolutionary trajectories that minimize the impact of crosstalk on the function of the parental pathway. These trajectories predicted that crosstalk interactions should be removed before new input/output functionalities evolve. Analysis of HK sequences in bacterial genomes provided evidence that the selective pressures on the HK-RR interface are different from those experienced by the input domain immediately after duplication. This work thus provides a unifying explanation for the evolution of specificity in TCS networks.

Crosstalk and competition in signaling networks.

Signaling networks have evolved to transduce external and internal information into critical cellular decisions such as growth, differentiation, and apoptosis. These networks form highly interconnected systems within cells due to network crosstalk, where an enzyme from one canonical pathway acts on targets from other pathways. It is currently unclear what types of effects these interconnections can have on the response of networks to incoming signals. In this work, we employ mathematical models to characterize the influence that multiple substrates have on one another. These models build off of the atomistic motif of a kinase/phosphatase pair acting on a single substrate. We find that the ultrasensitive, switch-like response these motifs can exhibit becomes transitive: if one substrate saturates the enzymes and responds ultrasensitively, then all substrates will do so regardless of their degree of saturation. We also demonstrate that the phosphatases themselves can induce crosstalk even when the kinases are independent. These findings have strong implications for how we understand and classify crosstalk, as well as for the rational development of kinase inhibitors aimed at pharmaceutically modulating network behavior.

Skeletonized internal thoracic artery harvesting reduces chest wall dysesthesia after coronary bypass surgery.

OBJECTIVE: A pain syndrome related to intercostal nerve injury during internal thoracic artery harvesting causes significant morbidity after coronary bypass surgery. We hypothesized that its incidence and severity might be reduced by using skeletonized internal thoracic artery harvesting rather than pedicled harvesting. METHODS: In a prospective double-blind clinical trial, 41 patients undergoing coronary bypass were randomized to receive either unilateral pedicled or skeletonized internal thoracic artery harvesting. Patients were assessed 7 (early) and 21 (late) weeks postoperatively with reproducible sensory stimuli used to detect chest wall sensory deficits (dysesthesia) and with a pain questionnaire used to assess neuropathic pain. RESULTS: At 7 weeks postoperatively, the area of harvest dysesthesia (percentage of the chest) in the skeletonized group (n = 21) was less (median, 0%; interquartile range, 0-0) than in the pedicled group (n = 20) (2.8% [0-13], P = .005). The incidence of harvest dysesthesia at 7 weeks was 14% in the skeletonized group versus 50% in the pedicled group (P = .02). These differences were not sustained at 21 weeks, as the median area of harvest dysesthesia in both groups was 0% (P = .89) and the incidence was 24% and 25% in the skeletonized and pedicled groups, respectively (P = 1.0). The incidence of neuropathic pain in the skeletonized group compared with the pedicled group was 5% versus 10% (P = .6) at 7 weeks and 0% versus 0% (P = 1.0) at 21 weeks. CONCLUSIONS: Compared with pedicled harvesting, skeletonized harvesting of the internal thoracic artery provides a short-term reduction in the extent and incidence of chest wall dysesthesia after coronary bypass, consistent with reduced intercostal nerve injury and therefore the reduced potential for neuropathic chest pain.

Aortic valve replacement for aortic stenosis during orthotopic cardiac transplant.

Although concomitant coronary bypass, and mitral and tricuspid valve surgery have been used to expand the donor pool for cardiac transplantation, aortic valve disease is considered an absolute contraindication for use of an offered organ. A case is presented with the successful use of an organ requiring concomitant aortic valve replacement for calcific aortic stenosis on a congenitally bicuspid valve. Eighteen-month follow-up documented excellent allograft function with a normally functioning mechanical aortic prosthesis. Aortic valve disease in offered organs can be successfully treated with aortic valve replacement at the time of transplantation and should not preclude the use of the organ in the setting of a recipient who is a candidate for a marginal allograft.

Validation of the EuroSCORE model in Australia.

OBJECTIVE: There is an important role for accurate risk prediction models in current cardiac surgical practice. Such models enable benchmarking and allow surgeons and institutions to compare outcomes in a meaningful way. They can also be useful in the areas of surgical decision-making, preoperative informed consent, quality assurance and healthcare management. The aim of this study was to assess the performance of the European System for Cardiac Operative Risk Evaluation (EuroSCORE) model on the Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) patient database. METHODS: The additive and logistic EuroSCORE models were applied to all patients undergoing cardiac surgery at six institutions in the state of Victoria between 1st July 2001 and 4th July 2005 within the ASCTS database who have complete data. The entire cohort and a subgroup of patients undergoing coronary artery bypass grafting (CABG) only were analysed. Observed and predicted mortalities were compared. Model discrimination was tested by determining the area under the receiver operating characteristic (ROC) curve. Model calibration was tested by the Hosmer-Lemeshow chi-square test. RESULTS: Eight thousand three hundred and thirty-one patients with complete data were analysed. There were significant differences in the prevalence of risk factors between the ASCTS and European cardiac surgical populations. Observed mortality was 3.20% overall and 2.00% for the CABG only group. The EuroSCORE models over estimated mortality (entire cohort: additive predicted 5.31%, logistic predicted 8.76%; CABG only: additive predicted 4.25%, logistic predicted 6.19%). Discriminative power of both models was very good. Area under ROC curve was 0.83 overall and 0.82 for the CABG only group. Calibration of both models was poor as mortality was over predicted at nearly all risk deciles. Hosmer-Lemeshow chi-square test returned P-values less than 0.05. CONCLUSIONS: The additive and logistic EuroSCORE does not accurately predict outcomes in this group of cardiac surgery patients from six Australian institutions. Hence, the use of the EuroSCORE models for risk prediction may not be appropriate in Australia. A model, which accurately predicts outcomes in Australian cardiac surgical patients, is required.

Nontraumatic localized dehiscence of the proximal ascending aorta through an aortic valve commissure.

Acute dissection of the ascending aorta is a life-threatening condition that requires timely recognition and management. Here we describe an unusual variant of acute dissection involving a localized tear in the proximal ascending aorta through the commissure of the left and noncoronary cusps of the aortic valve causing aortic regurgitation.

The radial artery in coronary surgery: a 5-year experience--clinical and angiographic results.

BACKGROUND: The radial artery (RA) has been used extensively by us as a way of reducing the use of the saphenous vein. It has been hoped that the RA will maintain greater late patency than the saphenous vein. We evaluated our initial 5-year experience with the RA in coronary surgery. METHODS: We studied 6,646 consecutive patients who had a single RA (4,872), or bilateral RA (1,774), as coronary grafts, from June 1995 to June 2000. Angiograms were performed mostly in symptomatic patients, or as part of a research project in asymptomatic patients. RESULTS: The patients' mean age was 65.1 years; 23% had diabetes, 14% had unstable angina, and 42% had prior myocardial infarction. An average of 3.3 grafts per patient were performed, 87% from arterial conduit. Conduits used were RA (8,420), left internal thoracic artery (6,296), and right internal thoracic artery (1,076). Operative mortality occurred in 58 (0.9%) patients, stroke in 92 (1.4%), deep sternal infection in 97 (1.4%), reoperation for hemorrhage in 56 (0.9%), and myocardial infarction in 52 (0.8%). Peak mean postoperative creatine kinase MB (CKMB) was 16.5 IU/L. Two patients developed fingertip ischemia. Postoperative angiographic RA patency was 90.2% (333 of 369 distal anastomoses). CONCLUSIONS: Good early clinical and angiographic results can be achieved by using the RA in coronary surgery.